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2015ApJ...799..138S__Yuan_&_Kewley_2009_Instance_1 | We present these results with one very important caveat. Accurately determining metallicities at different redshifts is of key importance to studying the evolution of the MZR. In the local universe, relationships between strong emission line ratios and metallicity can be calibrated to âdirectâ electron temperature-determined metallicities from measuring auroral lines such as [Oâiii] λ4363 (Pettini & Pagel 2004; Pilyugin & Thuan 2005) or photoionization models of star-forming regions (Zaritsky et al. 1994; Kewley & Dopita 2002; Kobulnicky & Kewley 2004; Tremonti et al. 2004). At redshifts above z â¼ 1, it is nearly impossible to detect weak auroral lines for directly determining metallicity (but see Yuan & Kewley 2009; Rigby et al. 2011; Brammer et al. 2012a; Christensen et al. 2012; Maseda et al. 2014). Creating photoionization models that suitably represent high-redshift star-forming regions requires knowledge of physical parameters which have been poorly constrained up to this point. Thus, it is unknown if local metallicity calibrations hold at high redshifts. Figure 6 shows a comparison between metallicities determined using the O3N2 indicator and the N2 indicator for both local SDSS galaxies (grey points) and MOSDEF z â¼ 2.3 galaxies (black points). The black dashed line indicates a one-to-one relationship. If local calibrations do indeed hold at high redshifts, then the relationship between metallicities determined from different indicators should not evolve with redshift. It is clear that the z â¼ 2.3 galaxies are offset below the local galaxies. The dotted line is the best-fit line of slope unity to the individual z â¼ 2.3 galaxies, yielding an offset of â0.1 dex from a one-to-one correspondence, over twice that displayed by the SDSS sample. Steidel et al. (2014) found an offset slightly larger than this at z â¼ 2.3. This offset demonstrates that the two metallicity indicators are not evolving in the same way with redshift, and shows the need of metallicity calibrations appropriate for high-redshift galaxies. | [
"Yuan & Kewley 2009"
] | [
"At redshifts above z â¼ 1, it is nearly impossible to detect weak auroral lines for directly determining metallicity (but see"
] | [
"Compare/Contrast"
] | [
[
717,
735
]
] | [
[
590,
716
]
] |
2016ApJ...817..152X__Schady_et_al._2007_Instance_1 | The connection between long-duration GRBs (LGRBs) and SNe was predicted theoretically (Colgate 1974; Woosley 1993) and has been verified observationally (e.g., Galama et al. 1998; Hjorth et al. 2003; see a review in Woosley & Bloom 2006). They usually happen in the star formation regions of the galaxies (e.g., Paczyński 1998; see the reviews in Woosley & Bloom 2006 and Kumar & Zhang 2015). The immensely bright afterglows illuminate the gas and dust within the star-forming regions of the host galaxy and intervening intergalactic medium along the GRB line of sight. Their spectra are usually featureless power-laws or broken power-laws, which can be well described by the synchrotron radiations of relativistic electrons. Therefore, GRB afterglows are good probes of burst environment and the interstellar dust and gas in distant, star-forming galaxies (Metzger et al. 1997; Jensen et al. 2001; Savaglio et al. 2003; Vreeswijk et al. 2004; Chen et al. 2005; Prochaska et al. 2007a; Schady et al. 2007, 2010; Watson et al. 2007; Fox et al. 2008; Starling et al. 2008; Jang et al. 2011; Xin et al. 2011). GRB afterglow spectra with Lyα absorption features indicate the presence of large column densities of cold neutral gas within GRB host galaxies, and their hydrogen column densities (
) are usually larger than
cm−2 (e.g., Prochaska et al. 2007b; Schady 2012). The damped Lyα systems (DLA) may represent the ISM near the GRBs in a few kiloparsecs (Kpc), but not gas directly local to the GRB (Prochaska et al. 2007b). Thus GRB optical afterglows may be used as probes of the ISM in their host galaxies, as the ISM observed is less affected by the GRB or its progenitor (Watson et al. 2007). The visual dust extinctions (
) along the GRB lines of sight of many GRBs are low. As shown in Greiner et al. (2011), about 50% of GRBs observed with GROND after the launch of Swift mission have
. In addition, the early optical light curves of about one-third of GRBs show a smooth onset bump (Li et al. 2012). It may be due to the deceleration of the GRB fireball by the ambient medium (Sari & Piran 1999; Kobayashi & Zhang 2007). In this scenario, the rising slope of the bump is determined by the medium density profile (
) and the spectrum index of the accelerated electrons
], says,
(Liang et al. 2013). Hence, The afterglow onset bumps would be also an ideal probe to study the properties of the fireball and the profile of the circumburst medium. Liang et al. (2013) found that
(see also Watson et al. 2007; Jin et al. 2012). | [
"Schady et al. 2007"
] | [
"Therefore, GRB afterglows are good probes of burst environment and the interstellar dust and gas in distant, star-forming galaxies"
] | [
"Motivation"
] | [
[
986,
1004
]
] | [
[
726,
856
]
] |
2020ApJ...902...98G__Tacconi_et_al._2020_Instance_1 | On balance, a large abundance of baryon-dominated, dark matter cored galaxies at z ∼ 2, most strongly correlated with baryonic surface density, angular momentum, and central bulge mass, may be most naturally accounted for by the interaction of baryons and dark matter during the formation epoch of massive halos. Massive halos (log(Mhalo/M⊙) > 12) formed for the first time in large abundances in the redshift range z ∼ 1–3 (Press & Schechter 1974; Sheth & Tormen 1999; Mo & White 2002; Springel et al. 2005). At the same time, gas accretion rates were maximal (Tacconi et al. 2020). This resulted in high merger rates (Genel et al. 2008, 2009; Fakhouri & Ma 2009), very efficient baryonic angular momentum transport (Dekel et al. 2009; Zolotov et al. 2015), formation of globally unstable disks, and radial gas transport by dynamical friction (Noguchi 1999; Immeli et al. 2004; Genzel et al. 2008; Bournaud & Elmegreen 2009; Bournaud et al. 2014; Dekel & Burkert 2014). These processes enabled galaxy mass doubling on a timescale 0.4 Gyr at z ∼ 2–3, and massive bulge formation by disk instabilities and compaction events on 1 Gyr timescales. However, central baryonic concentrations would naturally also increase central dark matter densities through adiabatic contraction (Barnes & White 1984; Blumenthal et al. 1986; Jesseit et al. 2002). For adiabatic contraction to be ineffective requires the combination of kinetic heating of the central dark matter cusp by dynamical friction from in-streaming baryonic clumps (El-Zant et al. 2001; Goerdt et al. 2010; Cole et al. 2011), with feedback from winds, supernovae, and AGNs driving baryons and dark matter out again (Dekel & Silk 1986; Pontzen & Governato 2012, 2014; Martizzi et al. 2013; Freundlich et al. 2020; K. Dolag et al. 2020, in preparation). Using idealized Monte Carlo simulations, El-Zant et al. (2001) demonstrated that dynamical friction acting on in-spiraling gas clumps can provide enough energy to heat up the central dark matter component and create a finite dark matter core (see also A. Burkert et al. 2020, in preparation). They argue that dark matter core formation in massive galaxies would require that clumps be compact, such that they avoid tidal and ram-pressure disruption, and have masses of >108 M⊙. Other idealized simulations (e.g., Tonini et al. 2006) confirm these results. | [
"Tacconi et al. 2020"
] | [
"At the same time, gas accretion rates were maximal"
] | [
"Background"
] | [
[
562,
581
]
] | [
[
510,
560
]
] |
2017ApJ...850..197P__Popham_&_Narayan_1991_Instance_1 | It is worth noting that more ECSNe are predicted for systems with a mass ratio close to unity, as the development of contact happens at longer periods for higher-q systems (see Figure 12). As the primary star starts transferring mass to the secondary, the orbit shrinks, until the mass ratio is reversed. This reversal happens earlier for mass ratios close to 1 and later for lower mass ratios, increasing the chance for contact (de Mink et al. 2013). This primarily affects the numbers of ECSNe, not so much the initial mass range (except for Case A systems). This is also true for the value of β, which controls the amount of matter that is lost from the system (i.e.,
is conservative mass transfer, no mass that is transferred from the primary to the secondary is lost from the system;
is completely nonconservative mass transfer, all mass that is transferred from the primary is lost from the system, no accretion onto the secondary). For the sake of our parameter study we chose various fixed values of β, while the mass transfer efficiency in real systems varies in time and will depend on the evolutionary phase of both stars, the amount of matter already accreted onto the secondary, and how that has affected its spin rate. Several mechanisms have been suggested that control the efficiency of mass transfer, mass accretion, and mass loss, including the existence of an accretion disk that regulates the amount of mass and angular momentum that can be accreted (Paczyński 1991; Popham & Narayan 1991; Deschamps et al. 2013), the necessity of the secondary to stay below critical rotation (Packet 1981), and the effects of tides on the stellar spins and the stellar orbit (Zahn 1977; Hurley et al. 2002). Work by Deschamps et al. (2013) and van Rensbergen et al. (2008) for systems with slightly lower masses suggests periods with values of β close to 1 (i.e., very inefficient mass transfer), while simulations with a strong tidal interaction (i.e., a short spin–orbit synchronization timescale) suggest shorter periods of moderately inefficient mass transfer (Paxton et al. 2015). Although our models suggest that the efficiency of mass transfer does not really affect the mass range for ECSNe, it does, however, strongly affect the range of initial periods that can lead to an ECSN. In addition, the evolution of the secondary will be affected. It will most likely rapidly spin up after the onset of mass transfer and maintain near-critical rotation for possibly extended periods of time. This will induce strong rotational mixing (de Mink et al. 2008a, 2013; Langer 2012), causing possibly quasi-chemically homogeneous evolution (Maeder 1987; Langer 2012), and alter the evolution of the star beyond just the simple fact of mass accretion (Hirschi et al. 2004; de Mink & Mandel 2016; Marchant et al. 2016). Although it is not clear to what extent this will affect the incidence of ECSNe, the effects of tides, mass and angular momentum transfer and loss, and near-critical rotation of the secondary are possibly important and will be discussed in a forthcoming paper, in addition to the effects of additional mixing and convection criteria. | [
"Popham & Narayan 1991"
] | [
"Several mechanisms have been suggested that control the efficiency of mass transfer, mass accretion, and mass loss, including the existence of an accretion disk that regulates the amount of mass and angular momentum that can be accreted"
] | [
"Motivation"
] | [
[
1501,
1522
]
] | [
[
1247,
1483
]
] |
2022MNRAS.509.3488I__Siana_et_al._2008_Instance_1 | In Fig. 11, we present the evolution of the quasar bolometric luminosity function (LF) from $z \sim 3$ down $z \sim 0$. Even though these functions give the number density of accreting black holes in different luminosity bins, they have been a powerful tool to extract information on how MBHs grow with cosmic time, on the geometry of the accretion discs and other fundamental quantities such as the black hole spins and radiative efficiencies. In this work, we only focus on the very bright objects, i.e. ${\gt}10^{45}\, \rm erg\,s^{-1}$, avoiding the comparison with lower luminosity given the current limitations on observational and theoretical models. In particular, from an observational standpoint, the covered area and depth of current surveys pose serious challenges when extracting statistical properties of the LF at the faint end (Siana et al. 2008; Masters et al. 2012; McGreer et al. 2013; Niida et al. 2016; Akiyama et al. 2018). Even more, dust attenuation effects might play an important role in shaping current measurements. On the other hand, current theoretical works show a large excesses at luminosity ${\lt}10^{45}\, \rm erg\,s^{-1}$. In order to reconcile observations with predictions, these works have played with empirical relations for obscuring accreting black holes or with the efficiency of the seeding process (see e.g Degraf, Di Matteo & Springel 2010; Fanidakis et al. 2012; DeGraf & Sijacki 2020). Even though these works provide interesting results shedding light on the nature of low-luminous quasars, the treatment of seeding or dust obscuration is beyond the scope of this paper. As shown in Fig. 11, the fiducial model is compatible with current observations of the quasar LF, showing a sharp cut-off at larger luminosity (Shen et al. 2020). On the other hand, the models with higher gas accretion display a completely different behaviour. Boosting the gas accretion during DI leads to a larger excess of bright quasars at $z \gt 1.0$. For instance, at $z \sim 2$ and for luminosities ${\gt}10^{46}\, \rm erg\,s^{-1}$, the models with $A_{\rm yr^{-1}} \sim 1.92 \times 10^{-15}$ and $A_{\rm yr^{-1}} \sim 2.67 \times 10^{-15}$ are systematically overpredicting the number density by a factor of ${\sim }1$ and ${\sim }2\, \rm dex$, respectively. A similar behaviour is seen at $z \sim 3$. At lower redshifts ($z \lt 1.0$), the model follows both the fiducial results and the observed trends. This is principally caused by the decrease of important DIs events at these redshifts. Regarding the IM models, we can see similar trends at $z \gt 2$, where the bright end of the LF is systematically larger than the observed one. We highlight that the difference is larger with $A_{\rm yr^{-1}} \sim 2.67 \times 10^{-15}$. Interestingly, the excess with respect to the observations is smaller than with the IDI model. This is principally caused by the fact that DI events are more important than mergers at these redshifts (Izquierdo-Villalba et al. 2020). At lower redshifts, we can see larger differences with respect to the fiducial and the IDI models: IM model is systematically overprotecting the bright end of the LF (${\gt}10^{46}\, \rm erg\,s^{-1}$). Such differences can be a factor of 3 (1.5) by $z \sim 0$ up to a factor of 5 (2) at $z \sim 0.5$ for $A_{\rm yr^{-1}} \sim 1.92 \times 10^{-15}$ ($A_{\rm yr^{-1}} \sim 2.67 \times 10^{-15}$). | [
"Siana et al. 2008"
] | [
"In this work, we only focus on the very bright objects, i.e. ${\\gt}10^{45}\\, \\rm erg\\,s^{-1}$, avoiding the comparison with lower luminosity given the current limitations on observational and theoretical models. In particular, from an observational standpoint, the covered area and depth of current surveys pose serious challenges when extracting statistical properties of the LF at the faint end"
] | [
"Compare/Contrast"
] | [
[
843,
860
]
] | [
[
445,
841
]
] |
2021MNRAS.508.2743A__Shakura_&_Sunyaev_1973_Instance_1 | The gas particles are distributed such that the initial surface density profile has the power law:
(7)$$\begin{eqnarray*}
\Sigma _\mathrm{g}=\Sigma _{\mathrm{g},0}\left(\frac{R}{R_{\rm in}}\right)^{-p},
\end{eqnarray*}$$where Σg, 0 is a normalization constant. We choose a locally isothermal equation of state with a sound speed cs such that
(8)$$\begin{eqnarray*}
c_\mathrm{s} = c_\mathrm{s,in} \left(\frac{R}{R_{\rm in}} \right)^{-q}.
\end{eqnarray*}$$where cs, in is the sound speed at the inner radius. We choose power law indices p = 1 and q = 0.5. We use a constant SPH artificial viscosity coefficient αSPH ≈ 0.55 such that the corresponding disc viscosity coefficient (Shakura & Sunyaev 1973) is αd = 0.01 at the inner radius. We note, however, that our choice of the indices p and q impact the radial dependence of the viscosity coefficient αd. The mapping between the SPH and disc viscosity coefficient is (e.g. Artymowicz & Lubow 1994, Murray 1996, Lodato & Pringle 2007)
(9)$$\begin{eqnarray*}
\alpha _\mathrm{d} \propto \alpha _{\rm SPH} \frac{\langle h \rangle }{H}
,
\end{eqnarray*}$$where 〈h〉 is the vertically averaged smoothing length and H is the disc thickness, which depends on disc radius:
(10)$$\begin{eqnarray*}
H = \frac{c_\mathrm{s}}{\Omega _\mathrm{k}} \propto R^{3/2-q}
.
\end{eqnarray*}$$The average smoothing length in 3D has the radial dependence:
(11)$$\begin{eqnarray*}
\langle h \rangle \propto \rho ^{-1/3} \propto \left(\frac{\Sigma }{H}\right)^{-1/3} \propto R^{1/2+(p-q)/3}
.
\end{eqnarray*}$$Hence, the choice of p and q determines the radial dependence of the disc viscosity coefficient. A common choice is to use p = 3/2 and q = 3/4, which results in a radially constant αd (e.g. Lodato & Price 2010). In this paper, we decide to use a physically motivated choice of indices (e.g. Aly et al. 2018), even though it results in a non-constant disc viscosity coefficient. For our choice of p = 1 and q = 0.5, the resulting radial dependence of the disc viscosity coefficient is αd ∝ R−1/3. To prevent particle interpenetration, we employ the recommended value βSPH = 2 for the quadratic viscosity coefficient (Price & Federrath 2010; Meru & Bate 2012). | [
"Shakura & Sunyaev 1973"
] | [
"We use a constant SPH artificial viscosity coefficient αSPH ≈ 0.55 such that the corresponding disc viscosity coefficient",
"is αd = 0.01 at the inner radius."
] | [
"Uses",
"Uses"
] | [
[
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]
] | [
[
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],
[
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]
] |
2022ApJ...926...85S__Brogi_et_al._2016_Instance_1 | A prime example of the unique benefits of the intersection of the 3D nature of (ultra)hot exoplanet atmospheres and high-resolution spectroscopy lies in the ultrahot Jupiter WASP-76b, a gas giant orbiting an F7 star (West et al. 2016) that is well studied at lower resolution (Fu et al. 2017, 2021; Fisher & Heng 2018; Tsiaras et al. 2018; Edwards et al. 2020; von Essen et al. 2020). Using the high-resolution (R ≈ 138,000) ESPRESSO spectrograph on the Very Large Telescope (Pepe et al. 2010, 2013), the Ehrenreich et al. (2020) team was able to produce novel, high signal-to-noise ratio (S/N), phase-resolved transmission spectra of this target across two separate transits. Curiously, an anomalous Doppler signature in the planet’s transmission spectrum was detected: between 0 and −5 km s−1 at ingress, but roughly −11 km s−1 by egress. These speeds far exceed the few km s−1 planet-frame velocities detected on other planets (Snellen et al. 2010; Brogi et al. 2016). The detection team attributes this variable and strong blueshift to an asymmetric distribution of atomic iron in the planet’s atmosphere, with a considerable amount of iron existing in the gas phase east of the substellar point, but cooling and condensing out as it makes its way to the much colder nightside. This asymmetry would cause a progressively blueshifted signal as the gas-phase iron region rotates into view over the course of the planet’s transit. Ehrenreich et al. (2020) posit that their signal is composed of two independent Doppler components: solid-body rotation of ±5.3 km s−1 (the tidally locked equatorial velocity of the planet), and a uniform day–night wind contributing an additional −5.3 km s−1 across both limbs, with gas-phase iron only present on the evening limb of the planet (Figure 1). Hence, the approaching limb would exhibit a blueshift from both rotation and winds totaling –10.6 km s−1, and the receding limb would produce no Doppler signal, as it would contain no gas-phase iron to absorb starlight. | [
"Brogi et al. 2016"
] | [
"These speeds far exceed the few km s−1 planet-frame velocities detected on other planets"
] | [
"Compare/Contrast"
] | [
[
952,
969
]
] | [
[
841,
929
]
] |
2018AandA...615A.148D__Sung_et_al._2013_Instance_2 | We study here the Sco OB1 association (Figs. 1 and 2), using this and other techniques. The general properties of this large OB association, which spans almost 5° on the sky, and is surrounded by a ring-shaped HII region called Gum 55, are reviewed by Reipurth (2008). Its central cluster NGC 6231 contains several tens of OB stars, which have been extensively studied. On the other hand, many fewer studies, all recent, were devoted to the full mass spectrum, using optical photometry (Sung et al. 1998, 2013) and X-rays (Sana et al. 2006, 2007; Damiani et al. 2016; Kuhn et al. 2017a,b). The currently accepted distance of NGC 6231 is approximately 1580 pc, and its age is between 2and 8 Myr, with a significant intrinsic spread (Sung et al. 2013; Damiani et al. 2016). No ongoing star formation is known to occur therein, however. Approximately one degree North of the cluster, the loose cluster Trumpler 24 (Tr 24) also belongs to the association. There is little literature on this cluster (Seggewiss 1968; Heske & Wendker 1984, 1985; Fu et al. 2003, 2005) which unlike NGC 6231 lacks a well-defined center and covers about one square degree on the sky. Its age is 10 Myr according toHeske & Wendker (1984, 1985), who find several PMS stars, and its distance is 1570–1630 pc according to Seggewiss (1968). Other studies of the entire Sco OB1 association include MacConnell & Perry (1969 – Hα-emission stars), Schild et al. (1969 – spectroscopy), Crawford et al. (1971 – photometry), Laval (Laval 1972a,b – gas and star kinematics, respectively), van Genderen et al. (1984 – Walraven photometry), and Perry et al.(1991 – photometry). At the northern extreme of Sco OB1, the partially obscured HII region G345.45+1.50 and its less obscured neighbor IC4628 were studied by Laval (1972a), Caswell & Haynes (1987), López et al. (2011), and López-Calderón et al. (2016). They contain massive young stellar objects (YSOs; Mottram et al. 2007), maser sources (Avison et al. 2016), and the IRAS source 16562-3959 with its radio jet (Guzmán et al. 2010), outflow (Guzmán et al. 2011), and ionized wind (Guzmán et al. 2014), and are therefore extremely young (1 Myr or less). The distance of G345.45+1.50 was estimated as 1.9 kpc by Caswell & Haynes (1987), and 1.7 kpc by López et al. (2011), in fair agreement with distances of Sco OB1 stars. In Fig. 1 of Reipurth (2008) a strip of blue stars is visible, connecting NGC 6231 to the region of IC4628. | [
"Sung et al. 2013"
] | [
"The currently accepted distance of NGC 6231 is approximately 1580 pc, and its age is between 2and 8 Myr, with a significant intrinsic spread"
] | [
"Background"
] | [
[
732,
748
]
] | [
[
590,
730
]
] |
2018MNRAS.473.1512A__Eichler_et_al._1989_Instance_1 | In an attempt to understand the radio properties of GRBs, Chandra & Frail (2012) conducted a complete investigation of all historical events observed in the radio domain. These included both of the main GRB populations (Kouveliotou et al. 1993): long-duration GRBs (likely produced by massive stellar collapse where the gamma-ray emission lasts for more than 2 s; Woosley 1993; Kulkarni et al. 1998; Woosley & Bloom 2006) and short-duration GRBs (likely caused by the coalescence of two neutron stars or a neutron star and black hole, which lasts for less than 2 s; Lattimer & Schramm 1976; Eichler et al. 1989; Narayan, Paczynski & Piran 1992). Only 30 per cent of their sample had a detectable radio afterglow, with the radio emission peaking within a very narrow flux range. This led them to conclude that the low percentage of detections was likely due to the sensitivity of radio telescopes rather than there being two distinct GRB populations: radio-bright and radio-faint. Ghirlanda et al. (2013) and Burlon et al. (2015) then conducted simulations to demonstrate that potentially all Swift GRBs will be detectable at radio frequencies with phase 1 of the Square Kilometre Array (SKA), specifically SKA1-MID in Band 5 (∼9 GHz)1 between 2 and 10 d post-burst, as well as with the recently upgraded Karl G. Jansky Very Large Array (VLA)2 and MeerKAT (the South African SKA precursor telescope; Jonas 2009). In fact, SKA1-MID will be so sensitive it could detect the radio counterparts from GRBs with gamma-ray emission up to five times fainter than those currently detected with Swift-BAT (note that these simulations do not account for radio emission produced by the reverse-shock, only considering contributions from the forward-shock; Burlon et al. 2015). However, a study conducted by Hancock, Gaensler & Murphy (2013), which involved visibility stacking of VLA GRB radio observations, suggested the low radio detection rate may be due to there being separate radio-bright and radio-faint GRB populations, and that ≤70 per cent are likely to be truly radio bright. | [
"Eichler et al. 1989"
] | [
"These included",
"and short-duration GRBs (likely caused by the coalescence of two neutron stars or a neutron star and black hole, which lasts for less than 2 s;"
] | [
"Background",
"Background"
] | [
[
591,
610
]
] | [
[
171,
185
],
[
422,
565
]
] |
2018AandA...609A.131G__Heithausen_2012_Instance_2 | Moreover, there could also be some contribution to the detected temperature asymmetry from high-latitude gas clouds in our Galaxy along the line of sight toward M 81. In this respect we note that M 81 is at about 40.9° north of the Galactic disk, where contamination from the Milky Way is expected to be low. However, interpretation of astronomical observations is often hampered by the lack of direct distance information. Indeed, it is often not easy to judge whether objects on the same line of sight are physically related or not. Since the discovery of the Arp’s Loop (Arp 1965) the nature of the interstellar clouds in this region has been debated; in particular whether they are related to the tidal arms around the galaxy triplet (Sun et al. 2005; de Mello et al. 2008) or to Galactic foreground cirrus (Sollima et al. 2010; Davies et al. 2010). Already Sandage et al. (1976) presented evidence showing that we are observing the M 81 triplet through widespread Galactic foreground cirrus clouds and de Vries et al. 1987 built large-scale HI, CO, and dust maps that showed Galactic cirrus emission toward the M 81 region with NH ≃ 1−2 × 1020 cm-2. The technique used to distinguish between the emission from extragalactic or Galactic gas and dust relies on spectral measurements and on the identification of the line of sight velocities, which are expected to be different in each case. Unfortunately, in the case of the M 81 Group, this technique appears hardly applicable since the radial velocities of extragalactic and Galactic clouds share a similar LSR (local standard of rest) velocity range (Heithausen 2012). Several small-area molecular clouds (SAMS), that is, tiny molecular clouds in a region where the shielding of the interstellar radiation field is too low (so that these clouds cannot survive for a long time), have been detected by Heithausen (2002) toward the M 81 Group. More recently, data from the Spectral and Photometric Imaging Receiver (SPIRE) instrument onboard Herschel ESA space observatory and Multiband Imaging Photometer for Spitzer (MIPS) onboard Spitzer allowed the identification of several dust clouds north of the M 81 galaxy with a total hydrogen column density in the range 1.5–5 × 1020 cm-2 and dust temperatures between 13 and 17 K (Heithausen 2012). However, since there is no obvious difference among the individual clouds, there was no way to distinguish between Galactic or extragalactic origin although it is likely that some of the IR emission both toward M 81 and NGC 3077 is of Galactic origin. Temperature asymmetry studies in Planck data may be indicative of the bulk dynamics in the observed region provided that other Local (Galactic) contamination in the data is identified and subtracted. This is not always possible, as in the case of the M 81 Group, and therefore it would be important to identify and study other examples of dust clouds where their origin, either Galactic or extragalactic, is not clear. One such example might be provided by the interacting system toward NGC 4435/4438 (Cortese et al. 2010) where the SAMS found appear more consistent with Galactic cirrus clouds than with extragalactic molecular complexes. Incidentally, the region A1 within R0.50 has been studied by Barker et al. (2009), who found evidence for the presence of an extended structural component beyond the M 81 optical disk, with a much flatter surface brightness profile, which might contain ≃10–15% of the M 81 total V-band luminosity. However, the lack of both a similar analysis in the other quadrants (and at larger distances from the M 81 center) and the study of the gas and dust component associated to this evolved stellar population, hamper our understanding of whether this component may explain the observed temperature asymmetry toward the M 81 halo. | [
"Heithausen 2012"
] | [
"More recently, data from the Spectral and Photometric Imaging Receiver (SPIRE) instrument onboard Herschel ESA space observatory and Multiband Imaging Photometer for Spitzer (MIPS) onboard Spitzer allowed the identification of several dust clouds north of the M 81 galaxy with a total hydrogen column density in the range 1.5–5 × 1020 cm-2 and dust temperatures between 13 and 17 K",
"However, since there is no obvious difference among the individual clouds, there was no way to distinguish between Galactic or extragalactic origin although it is likely that some of the IR emission both toward M 81 and NGC 3077 is of Galactic origin."
] | [
"Background",
"Compare/Contrast"
] | [
[
2282,
2297
]
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[
1899,
2280
],
[
2300,
2551
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2021ApJ...919L..23F__Tendulkar_et_al._2021_Instance_1 | Alongside studies of their emission properties, examining the environments of FRBs on subparcsec to kiloparsec scales can be equally informative. Thus far, only a fraction of known extragalactic repeating FRBs have been localized to host galaxies (Chatterjee et al. 2017; Tendulkar et al. 2017; Marcote et al. 2020; Macquart et al. 2020; Heintz et al. 2020; Bhandari et al. 2021; Bhardwaj et al. 2021a, 2021b; Li et al. 2021).17
17
FRB 20201124A is the fifth announced repeating FRB with a host galaxy. In total, there are eight such FRB sources known as of 2021 August.
Much closer by, FRB-like emission has been detected from a Milky Way magnetar, SGR 1935 + 2154 (CHIME/FRB Collaboration et al. 2020; Bochenek et al. 2020). All identified repeating FRB hosts have evidence for low to modest ongoing star formation rates of ∼0.06−2 M⊙ yr−1 (Gordon et al. 2004; Bhandari et al. 2020a; Heintz et al. 2020), several exhibit spiral arm morphologies (Bhardwaj et al. 2021a; Mannings et al. 2021; Tendulkar et al. 2021), and their stellar populations span a range of stellar masses, ∼108−1010.5 M⊙ (de Blok et al. 2008; Bhandari et al. 2020a; Heintz et al. 2020; Mannings et al. 2021). At face value, these characteristics, coupled with the absence of any quiescent host galaxy identifications for repeating FRBs, may indicate that FRBs are connected to host galaxies with ongoing star formation. However, studies of their more local environments reveal a rich diversity. For instance, the discovery of the repeating FRB 20200120E in an old (9.1 Gyr) globular cluster on the outskirts of the grand design spiral galaxy M81 (Bhardwaj et al. 2021a; Kirsten et al. 2021a) and the detection of the repeating FRB 20121102A embedded in a star-forming knot in its dwarf host galaxy (Bassa et al. 2017) seemingly represent polar opposite local environments. If all repeaters discovered to date originate from the same type of progenitor, then the progenitor model must accommodate the observed diversity of both local and galactic environments. Additionally, any connection in progenitors to the population of apparent nonrepeaters remains opaque. | [
"Tendulkar et al. 2021"
] | [
"several exhibit spiral arm morphologies"
] | [
"Background"
] | [
[
995,
1016
]
] | [
[
909,
948
]
] |
2020AandA...634A..81B__Bleem_et_al._2015_Instance_1 | After checking the results of the U-net in the test area, we applied the same detection method to the full-sky SZ prediction map, with a detection threshold of pmax = 0.1 in order to recover the maximum number of Planck_z clusters. We detected 20 204 sources in the full-sky map with the U-net with pmax = 0.1. We compared the detections with the three catalogues of known galaxy clusters, Planck_z, Planck_no-z, and MCXCwP. Among the 20 204 detected sources, 98.5% of the Planck_z clusters are recovered, together with 76.4% of Planck_no-z clusters, and 20.8% of MCXCwP clusters. Moreover, 11 cluster are identified by ACT (Hasselfield et al. 2013) and 98 clusters are identified by the South Pole Telescope (SPT; Bleem et al. 2015), but are not included in the Planck PSZ2 catalogue. This means that 18 415 sources do not belong to any of the catalogues. We investigated the nature of the sources detected with the U-net. First, we cross-matched the sample of 18 415 sources with Planck point sources. Only 6.1% are matched within a cross-match radius of 5 arcmin with the positions of the Planck catalogue of galactic cold cores, and only 0.2% are matched with the positions of the Planck sources identified at 353 GHz. Second, we stacked at their positions 16 maps in different wavelengths, each of them potentially probing different galaxy cluster counterparts. Some of the 16 maps are also based on Planck data and thus are not independent, but some of the maps are independent and may show indications of galaxy cluster counterparts in other wavelengths, that is, in near-infra-red (where galaxies emit) and in X-rays (where the same gas emits as is detected with the SZ). The 16 maps are the Planck SZ MILCA map, the 6 Planck HFI frequency maps, the IRIS map at 100 μm (Miville-Deschênes & Lagache 2005), the CMB lensing map (based on Planck; Planck Collaboration VIII 2020), 4 galaxy over-density maps of all galaxies (called GAL ALL), passive galaxies (called GAL P), transitioning galaxies (called GAL T), and active galaxies (called GAL A) following Bonjean et al. (2019), star formation rate density maps (called SFR), a stellar mass density maps (called Mstar) constructed with the method from Bonjean et al. (2019), and finally, the ROSAT X-ray map (ByoPiC4 product). The Planck maps were masked from the Planck Catalogue of Compact Sources (PCCS, Planck Collaboration XXVI 2016), and the ROSAT map was masked from the point sources detected in ROSAT, Chandra, and XMM-Newton (Boller et al. 2016; Evans et al. 2010; Rosen et al. 2016, respectively). The result of the 16 stacks are shown in Fig. 5. | [
"Bleem et al. 2015"
] | [
"98 clusters are identified by the South Pole Telescope (SPT;",
"but are not included in the Planck PSZ2 catalogue."
] | [
"Uses",
"Differences"
] | [
[
715,
732
]
] | [
[
654,
714
],
[
735,
785
]
] |
2022MNRAS.513.3458B__Robertson,_Massey_&_Eke_2017_Instance_1 | Among the most viable mechanisms of cusp-core transformation that require changes to the assumed cosmogony is one that was proposed specifically as a possible solution to the cusp-core problem. It proposes that the DM is in fact not collisionless but self-interacting (SIDM; Spergel & Steinhardt 2000; Yoshida et al. 2000; Davé et al. 2001; Colín et al. 2002; Vogelsberger, Zavala & Loeb 2012; Rocha et al. 2013; see Tulin & Yu 2018 for a review). In SIDM, particles can exchange energy and momentum through elastic scattering, causing an outside-in energy redistribution within the centre of DM haloes, resulting in the formation of an isothermal core. The time-scale on which an initially cuspy SIDM halo forms a flat and isothermal core is roughly given by the time it takes for each DM particle in the inner halo to scatter at least once (Vogelsberger et al. 2012; Rocha et al. 2013). The strength of the self-interaction in SIDM models is parametrized in terms of the momentum transfer cross-section per unit mass, σT/mχ. Depending on the specific SIDM model, σT/mχ can either be constant or dependent on the relative velocity between the two scattering DM particles. SIDM is an efficient mechanism of cusp-core transformation in dwarf-size haloes for $\sigma _T/m_\chi \gtrsim 1\, {\rm cm^2g^{-1}}$, whereas SIDM haloes are virtually indistinguishable from CDM haloes if $\sigma _T/m_\chi \lesssim 0.1\, {\rm cm^2g^{-1}}$ (Zavala, Vogelsberger & Walker 2013). The most stringent and precise constraints on the self-interaction cross-section have been put on the scales of galaxy clusters (e.g. Robertson, Massey & Eke 2017; Robertson et al. 2019) and large elliptical galaxies (Peter et al. 2013), where observations require that $\sigma _T/m_chi \lesssim 1\, {\rm cm^2g^{-1}}$. On smaller scales, Read, Walker & Steger (2018) concluded that $\sigma _T/m_\chi \lesssim 0.6\, {\rm cm^2g^{-1}}$, based on their findings that the central density profile of the MW dwarf spheroidal galaxy Draco is cuspy (see also the SIDM results of Valli & Yu 2018). Moreover, based on a DM only analysis of the updated too-big-to-fail problem, Zavala et al. (2019) concluded that SIDM models with a constant cross-section of $\sigma _T/m_\chi \sim 1\, {\rm cm^2g^{-1}}$ fail to explain the apparently large central densities of the host haloes of the ultra-faint satellites of the MW (Errani, Peñarrubia & Walker 2018). It should be pointed out that the constraints on σT/mχ on the scale of dwarf galaxies are affected by significantly larger systematic uncertainties than on the scales of galaxy clusters or elliptical galaxies. Moreover, Zavala et al. (2019) demonstrate that SIDM with a strongly velocity-dependent self-interaction cross-section may provide a natural explanation for the observed diversity in the rotation curves of the MW dwarf spheroidals (see also Correa 2021). The strong dependence of the self-interaction cross-section on the typical DM velocities would create a bimodal distribution of rotation curves in the MW satellites in which the heavier haloes have constant density cores while the lighter haloes have undergone gravothermal collapse and have very steep central cusps as a consequence. The same mechanism of gravothermal collapse might be accelerated by tidal interactions in the environment of the MW leading to an agreement between constant cross-section SIDM models with $\sigma _T/m_\chi \sim 3\, {\rm cm^2g^{-1}}$ and the internal kinematics of MW satellites (e.g. Kahlhoefer et al. 2019; Sameie et al. 2020). | [
"Robertson, Massey & Eke 2017"
] | [
"The most stringent and precise constraints on the self-interaction cross-section have been put on the scales of galaxy clusters (e.g.",
"where observations require that $\\sigma _T/m_chi \\lesssim 1\\, {\\rm cm^2g^{-1}}$."
] | [
"Background",
"Background"
] | [
[
1600,
1628
]
] | [
[
1466,
1599
],
[
1704,
1784
]
] |
2017MNRAS.465..383R__Archibald_et_al._2016_Instance_1 | In previous work (Rogers & Safi-Harb 2016, hereafter RSH16), we studied a parametrized phenomenological model for describing magnetic field growth in neutron star (NS) evolution. Assuming that the external dipole field is buried by an intense process of fall-back accretion after the formation of the NS (Muslimov & Page 1995, 1996), the slow diffusion from the stellar surface exerts a time-dependent torque on the NS (Geppert, Page & Zannias 1999). This process may provide an explanation for the observed braking indices of young pulsars with n ≠ 3 (Espinoza 2012; Archibald et al. 2016), in contrast to the prediction of a rotating magnetic dipole in vacuum (n = 3; Ostriker & Gunn 1969). Magnetic field growth provides an evolutionary link between apparently disparate classes of NS, such as the extremely weak field1 subset of NSs known as central compact objects (CCOs), high magnetic field pulsars (HBPs) and the X-ray dim isolated NSs (XDINSs). On the other hand, magnetic field decay has been invoked to describe the evolution of the anomalous X-ray pulsars (AXPs) and soft gamma repeaters (SGRs). These objects are conventionally described by the magnetar model that posits the development of large magnetic fields via dynamo action from rapid rotation early in the life of the NS, necessary to support the core of the massive progenitor from collapse (Duncan & Thompson 1992; Akiyama et al. 2003; Thompson, Quataert & Burrows 2005). However, the distinction between the apparently rotation-powered HBPs, with dipole fields just above the quantum critical limit, BQED = 4.4 × 1013 G, and the magnetically powered AXPs and SGRs (B ≥ BQED) is significantly blurred after the HBPs were observed displaying magnetar-like activity (Gavriil et al. 2008; Kumar & Safi-Harb 2008; Göğüs et al. 2016), and radio emission was observed from magnetars (Camilo et al. 2007). Moreover, the SNRs associated with the AXPs and SGRs show evidence of ‘typical’ explosion energies (≤1051 erg) and not superenergetic as one would expect from a rapidly rotating proto-NS (Vink & Kuiper 2006; Kumar, Safi-Harb & Gonzalez 2012; Safi-Harb & Kumar 2013; Kumar et al. 2014). These complications are difficult to reconcile with the standard magnetar picture. | [
"Archibald et al. 2016"
] | [
"This process may provide an explanation for the observed braking indices of young pulsars with n ≠ 3",
"in contrast to the prediction of a rotating magnetic dipole in vacuum"
] | [
"Compare/Contrast",
"Compare/Contrast"
] | [
[
568,
589
]
] | [
[
451,
551
],
[
592,
661
]
] |
2018ApJ...869...12S__Duc_et_al._2015_Instance_1 | To verify the predictions of CDM, there have been recent attempts to compare the amount of stellar mass observed in the outskirts of galaxies with the mass fraction in accreted stars predicted by simulations (e.g., Font et al. 2008; Pillepich et al. 2014; Merritt et al. 2016; D’Souza & Bell 2018; Elias et al. 2018; Huang et al. 2018). For the purposes of this paper, we will use the term “stellar halo” in an observational sense, referring to the faint structure in the outskirts of galaxies beyond the central concentration of stellar mass. In practice, there are many observational definitions of this term that can include radial profile, surface brightness, or metallicity characteristics. Most recent observational attempts to characterize the stellar halos of galaxies, including the MW (e.g., Carollo et al. 2010) and the Andromeda galaxy (M31; e.g., Courteau et al. 2011), have used analysis of resolved stellar populations to identify the accreted component, usually by searching for an old, metal-poor population extending far from the central galaxy (e.g., Seth et al. 2007; Cockcroft et al. 2013). However, this method requires extremely deep images, mainly obtained using the Hubble Space Telescope (with the exception of Greggio et al. 2014), and has therefore been limited to a small handful of galaxies so far. Observing stellar halos in integrated light is, in principle, more easily scalable to the sample sizes needed to explore the wide variation in the accreted component that is predicted by simulations (e.g., Bakos & Trujillo 2012; D’Souza et al. 2014; Duc et al. 2015; Merritt et al. 2016; Huang et al. 2018), presuming that it is possible to account for the contribution of scattered light (de Jong 2008; Slater et al. 2009; Sandin 2014). However, the lack of resolved stellar population information makes it far more challenging to identify the regions of an image dominated by accreted material. So far, no work has attempted to account for how the method used to select the stellar halo from a galaxy observed in integrated light may bias the comparison to simulations, where the provenance of material is perfectly known and a variety of definitions of “stellar halo” are imposed. Despite efforts such as that in Rodriguez-Gomez et al. (2016) to understand whether the mass in the stellar halo comes primarily from accreted material or from stars formed in the central galaxy (which in this work we call “formed in situ”) and expelled to the halo, and its dependence with separation from the central galaxy, it is not straightforward to apply these results to the spatial selections in projection that are commonly used in integrated-light images. In fact, most prior work has focused on comparisons between observed galaxies and predictions for the stellar halo based on dark matter–only (DM-only) simulations tagged with stars, where the stellar halo is by definition 100% accreted. However, in simulations that include baryonic physics, both of these distinct channels are observed to contribute to the stellar halos of galaxies (Font et al. 2011; Cooper et al. 2013; Tissera et al. 2013; Pillepich et al. 2015; Anglés-Alcázar et al. 2017; Gómez et al. 2017a), and both are interesting for what they tell us about the process of galaxy formation, as well as the cosmology in which galaxies are formed. | [
"Duc et al. 2015"
] | [
"Observing stellar halos in integrated light is, in principle, more easily scalable to the sample sizes needed to explore the wide variation in the accreted component that is predicted by simulations (e.g.,"
] | [
"Motivation"
] | [
[
1579,
1594
]
] | [
[
1329,
1534
]
] |
2019MNRAS.484..892R__Wolf_et_al._2009_Instance_1 | In the left-hand panel of Fig. 2, we compare the morphological types assigned by the STAGES collaboration for the galaxies in the whole OMEGA sample and the jellyfish candidates sample. The sample of jellyfish galaxies (JC345) is composed mainly of late-type spirals and irregulars. In the middle panel of Fig. 2, we show the distribution of SED types for both samples. Based on the SED types of the galaxies, of the 70 jellyfish galaxy candidates analysed, 66 were found to be part of the blue cloud and 4 as being dusty reds (IDs: 11633, 17155, 19108, 30604). However, contrary to what could be expected, dusty red galaxies are only a small portion of our sample of jellyfish candidates. One reason why we may not detect many dusty reds as jellyfish galaxies might be due to the fact that these galaxies, despite having relatively high SFRs (only four times lower than that in blue spirals at fixed mass, Wolf et al. 2009), have significant levels of obscuration by dust that might hamper the identification of the jellyfish signatures. Another reason for that is that we selected jellyfish galaxy candidates within a parent sample of H α-emitting galaxies that already had a low fraction of dusty red galaxies (≈15 ${{\ \rm per\ cent}}$). As these galaxies have low star formation, it is harder to perceive the morphological features of RPS. Dusty red galaxies have been previously studied in this same system (Wolf et al. 2009), and RPS was suggested to be the main mechanism acting in these galaxies (Bösch et al. 2013). While in Bösch et al. (2013) one of the main pieces of evidence suggesting the action of enhanced RPS were the existence of disturbed kinematics without disturbed morphologies, in our study we strongly base our selection on such morphological distortions. Both our jellyfish galaxy candidates and the dusty red galaxies show different characteristics that can be correlated to the effect of RPS. Nevertheless, they might be tracing different stages of the same phenomenon, where dusty red galaxies have more regular morphologies, but disturbed kinematics. Our sample of morphologically disturbed jellyfish galaxy candidates may be showing the stage where the features of RPS are the most visible and the SFRs are enhanced. | [
"Wolf et al. 2009"
] | [
"One reason why we may not detect many dusty reds as jellyfish galaxies might be due to the fact that these galaxies, despite having relatively high SFRs (only four times lower than that in blue spirals at fixed mass,"
] | [
"Uses"
] | [
[
907,
923
]
] | [
[
690,
906
]
] |
2021AandA...655A.111K__Rojas-Arriagada_et_al._(2019)_Instance_2 | Over the last decade, the radial and vertical dependences of the metallicity-alpha-element distribution have been studied in more and more detail with increasingly larger samples (e.g., Bensby et al. 2011; Anders et al. 2014; Nidever et al. 2014; Hayden et al. 2015; Queiroz et al. 2020). Figure 6 is mostly consistent with similar plots shown in the above papers. In the inner 10 kpc, it displays two over-densities, a high alpha-element (here [Mg/Fe]), and a low one. Between Rg = 6 and 10 kpc, the two over-densities define two different sequences. In Appendix E, we note that when the sample is restricted to a ±500 pc layer around the Galactic plane, two close but separated sequences are observed in the Rg ∈ [4, 6] kpc interval. Because of their scale height (Bovy et al. 2012), kinematics (Bensby et al. 2003), and age properties (Haywood et al. 2013), these two sequences are associated with the thick disc (high-alpha) and thin disc (low-alpha), respectively. Moving inward of Rg = 4 − 6 kpc, Fig. 6 shows that the two over-densities connect through a zone of lower density to form a single sequence. This is in agreement with the observations of Hayden et al. (2015), Bensby et al. (2017), Zasowski et al. (2019), Bovy et al. (2019), and Lian et al. (2020a,b), who also report a single sequence in the inner disc and/or in the bulge/bar area. Conversely, Rojas-Arriagada et al. (2019) and Queiroz et al. (2020) observe two sequences in the inner regions. In Appendix F, we compare the distributions of different APOGEE DR16 alpha elements in the ([Fe/H], [α/Fe]) plane (restricting the sample to the stars contained in the Rg ∈ [0, 2] kpc interval). The different elements produce different patterns: the global alpha-element abundance5 and oxygen show a double sequence, while magnesium, silicon, and calcium present a single sequence. This could explain, at least partly, why Queiroz et al. (2020), who use a combined α-element abundance, observe a double sequence, while we see a single one with magnesium. However, this does not explain the discrepancy with Rojas-Arriagada et al. (2019), who also used magnesium. Beyond Rg = 10 kpc, the high-alpha sequence gradually vanishes. This is in agreement with the finding that the thick disc has a shorter scale length than the thin disc (Bensby et al. 2011; Cheng et al. 2012; Bovy et al. 2012). It should be emphasised that in this paragraph the term ‘sequence’ is used in the geometrical sense. It does not presuppose the number of chemical tracks that form the sequence or sequences. In particular, based on Fig. 6, it can not be excluded that the single geometrical sequence observed in the inner disc be made of two chemical tracks, with the low-alpha one restricted to a narrow metallicity range. We discuss and propose an interpretation of the inner disc sequence in Sect. 5. | [
"Rojas-Arriagada et al. (2019)"
] | [
"However, this does not explain the discrepancy with",
"who also used magnesium."
] | [
"Compare/Contrast",
"Compare/Contrast"
] | [
[
2073,
2102
]
] | [
[
2021,
2072
],
[
2104,
2128
]
] |
2020ApJ...898...92C__Occhiogrosso_et_al._2011_Instance_1 | The first interstellar discovery of MF took place in 1975 from the microwave emission spectrum of Sgr B2, which agrees with the rotational constants of the syn isomer (Curl 1959; Brown et al. 1975; Nummelin et al. 2000). Subsequently, it was detected in several other sources such as comet Hale–Bopp, and protostars and hot corinos (e.g., in Orion A and the protoplanetary nebula CRL 618) (Ellder et al. 1980; Ikeda et al. 2001; Cazaux et al. 2003; Bottinelli et al. 2004a, 2004b; Remijan et al. 2005, 2006; Remijan & Hollis 2006). Later, the less stable trans rotamer was detected in both the laboratory and the interstellar medium (ISM; Ruschin & Bauer 1980; Blom & Günthard 1981; Müller et al. 1983; Neill et al. 2011, 2012). The detailed mechanistic route for the interstellar synthesis of MF is a subject of considerable debate (Horn et al. 2004; Herbst 2005; Garrod & Herbst 2006; Snyder 2006; Bennett & Kaiser 2007; Occhiogrosso et al. 2011; Lawson et al. 2012). The initially assumed gas-phase model involving an ion–molecule reaction of protonated methanol (
) with formaldehyde (H2CO) fails to reproduce the large MF column density, because this pathway demands a significant activation barrier (∼128 kJ mol−1) for one of the intermediate steps (Horn et al. 2004). Instead, gas-phase radiative association between the methyl cation (
) and formic acid (HCOOH) seems energetically promising to produce H+MF and thereafter neutral MF via dissociative recombination with electrons:
1
2
However, this reaction scheme fails to reproduce the huge MF concentration observed in hot cores (Horn et al. 2004). Alternative routes suggested more recently involve ion–molecule reactions with a low barrier or no barrier between protonated methanol and formic acid (acid-catalyzed Fischer esterification) or between protonated formic acid and methanol (
transfer):
3
4
followed by reaction (2) or exothermic proton transfer of
(H+MF) to a base with a higher proton affinity than MF (Ehrenfreund & Charnley 2000; Neill et al. 2011, 2012). | [
"Occhiogrosso et al. 2011"
] | [
"The detailed mechanistic route for the interstellar synthesis of MF is a subject of considerable debate"
] | [
"Background"
] | [
[
923,
947
]
] | [
[
729,
832
]
] |
2021ApJ...923...59V__Feruglio_et_al._2015_Instance_1 | We compute the emission line luminosity using the following equation:
1
LCO′=3.25×107SCOΔvDL2(1+z)3νobs2Kkms−1pc2,
where ν
obs is the observed CO transition frequency, D
L
is the luminosity distance, and S
COΔv is the line-integrated flux in units of Jy km s−1. We convert the observed CO transition luminosity into CO (1–0) luminosity (L
CO(1−0)′
) by assuming that the low-J CO transitions are thermalized and optically thick, so
LCO4–3′=LCO3–2′=LCO1–0′
. Using the ratios (
rJ1=LCOJ→J−1′/LCO1–0′
) from Carilli & Walter (2013) with r
31=0.97 and r
41 = 0.87 did not significantly change our results. Furthermore, in 3C 298, we found that the molecular gas is consistent with being thermalized and optically thick (Vayner et al. 2017). These physical conditions are consistent with what is found for Mrk 231 (Feruglio et al. 2015). Finally, we convert the
LCO1–0′
line luminosity into molecular gas mass using the CO-to-H2 conversion factor: α
CO with units of (K km s−1pc2)−1. For sources where we do not detect any narrow CO emission at the systemic redshift, we place a limit on the molecular gas mass over an aperture equal to the beam size for an emission line with a velocity FWHM of 250 km s−1. The molecular gas mass limits can be linearly scaled with a different α
CO value. For sources with detected molecular gas at the quasar’s systemic redshift, we compute the radius of the molecular gas region, which allows us to measure the gas surface density. All radii are computed using a curve-of-growth method. Effective radii refer to a region that encloses 50% of the flux, while “maximum” extent refers to a size scale that encloses 90% of the flux. In all cases, narrow emission at the systemic redshift of the quasar is spatially resolved by our observations. We deconvolve the size of the beam from all radius measurements. For sources with no detected CO emission, we use the molecular gas mass limit and the beam of the observations as a proxy for the radius. Values associated with the molecular gas at the systemic redshift are summarized in Table 3. | [
"Feruglio et al. 2015"
] | [
"These physical conditions are consistent with what is found for Mrk 231"
] | [
"Similarities"
] | [
[
831,
851
]
] | [
[
758,
829
]
] |
2016ApJ...829...53V__Piconcelli_et_al._2005_Instance_1 | Two spectroscopically confirmed X-ray AGNs in the cluster core (#607, 661 in G13) are suitable candidates for ionizing the nebula. The depth of the new Chandra observation, coupled with an optimal on-axis alignment, allowed us to perform a basic X-ray spectral analysis despite the limited photon statistics (34 and 20 net counts in the observed 0.5–7 keV band for sources #607 and 661, respectively). Source #607 is characterized by a power-law spectrum with photon index Γ = 2.0 ± 0.6; the observed 2–10 keV flux is 1.7+1.1−0.6 × 10−15 erg cm−2 s−1, corresponding to a rest-frame 2–10 keV luminosity of
erg s−1, typical of a luminous Seyfert galaxy. The X-ray spectrum of source #661, the point-like Lyα emitter (Figure 2), is flat: fitting the data with a power-law model provides
, highly indicative of strong obscuration. We then included an absorption component and fixed the photon index to 1.8, as expected for the intrinsic AGN emission (e.g., Piconcelli et al. 2005). This model results in a column density of
cm−2, i.e., consistent with marginal Compton-thick absorption (1.5 × 1024 cm−2). The tentative detection of an iron Kα emission line at 6.4 keV (with equivalent width of ≈2.4 keV rest frame), if confirmed, would further support the heavily obscured nature of source #661. The derived 2–10 keV flux is (7.4 ± 2.2) × 10−15 erg cm−2 s−1, corresponding to a rest-frame luminosity of
erg s−1, placing source #661 in the quasar regime. We do not detect any bright counterpart in deep Jansky Very Large Array observations at 3 GHz down to 2.7 μJy (rms), and we thus classify source #661 as radio-quiet. From aperture photometry, we estimated a Lyα flux of
erg cm−2 s−1, corresponding to a luminosity of (1.9 ± 0.2) × 1042 erg s−1. The spectral energy distribution (SED) of #661 is shown in Figure 7. From SED modeling, which benefits from near-, mid-, and far-IR observations from Spitzer and Herschel, we estimated a bolometric luminosity for the AGN of (2.7 ± 1.5) × 1045 erg s−1. A similar value (3.2 ± 0.6 × 1045 erg s−1) is derived using the observed [O iii]λ5007 Å luminosity obtained from recent Subaru/MOIRCS spectroscopy of the galaxy (Valentino et al. 2015), converted into a bolometric luminosity as
(Heckman et al. 2004). Assuming the luminosity-dependent bolometric correction as in Lusso et al. (2012), we predict an intrinsic 2–10 keV luminosity for source #661 of
erg s−1. This value is consistent, within the uncertainties due to the adopted relations and measurements, with that derived from the X-ray spectral analysis reported above. | [
"Piconcelli et al. 2005"
] | [
"We then included an absorption component and fixed the photon index to 1.8, as expected for the intrinsic AGN emission (e.g.,"
] | [
"Uses"
] | [
[
966,
988
]
] | [
[
840,
965
]
] |
2018AandA...619A..13V__Saviane_et_al._2012_Instance_4 | The EWs were measured with the methods described in Vásquez et al. (2015). As in Paper I, we used the sum of the EWs of the two strongest CaT lines (λ8542, λ8662) as a metallicity estimator, following the Ca II triplet method of Armandroff & Da Costa (1991). Different functions have been tested in the literature to measure the EWs of the CaT lines, depending on the metallicity regime. For metal-poor stars ([Fe/H] ≲ −0.7 dex) a Gaussian function was used with excellent results (Armandroff & Da Costa 1991), while a more general function (such as a Moffat function or the sum of a Gaussian and Lorentzian, G + L) is needed to fit the strong wings of the CaT lines observed in metal-rich stars (Rutledge et al. 1997; Cole et al. 2004). Following our previous work (Gullieuszik et al. 2009; Saviane et al. 2012) we have adopted here a G+L profile fit. To measure the EWs, each spectrum was normalised with a low-order polynomial using the IRAF continuum task, and set to the rest frame by correcting for the observed radial velocity. The two strongest CaT lines were fitted by a G+L profile using a non-linear least squares fitting routine part of the R programming language. Five clusters from the sample of Saviane et al. (2012) covering a wide metallicity range were re-reduced and analysed with our code to ensure that our EWs measurements are on the same scale as the template clusters used to define the metallicity calibration. Figure 5 shows the comparison between our EWs measurements and the line strengths measured by Saviane et al. (2012) (in both cases the sum of the two strongest lines) for the five calibration clusters. The observed scatter is consistent with the internal errors of the EW measurements, computed as in Vásquez et al. (2015). The measurements show a small deviation from the unity relation, which is more evident at low metallicity. A linear fit to this trend gives the relation: ΣEW(S12) = 0.97 ΣEW(this work) + 0.21, with an rms about the fit of 0.13 Å. This fit is shown in Fig. 5 as a dashed black line. For internal consistency, all EWs in this work have been adjusted to the measurement scale of Saviane et al. (2012) by using this relation. In Table 3 we provide the coordinates, radial velocities, and the sum of the equivalent widths for the cluster member stars, both measured (“m”) and corrected (“c”) to the system of Saviane et al. 2012. | [
"Saviane et al. (2012)"
] | [
"For internal consistency, all EWs in this work have been adjusted to the measurement scale of"
] | [
"Uses"
] | [
[
2136,
2157
]
] | [
[
2042,
2135
]
] |
2018ApJ...856...19N__Fischer_et_al._2010_Instance_1 | Models of the ECSN progenitor cores suggest the onset of the electron-capture instability occurs at a unique ONeMg core mass in the mass range of 1.366–1.377 M⊙. (Miyaji et al. 1980; Nomoto 1984, 1987; Podsiadlowski et al. 2005; Takahashi et al. 2013). Electron captures cause the core to contract, and O and Ne burning is ignited in the central regions and propagates outwards in a deflagration front (Schwab et al. 2015), processing material to nuclear statistical equilibrium, where further electron captures and photdissociation accelerates the collapse (Miyaji et al. 1980; Nomoto 1987; Takahashi et al. 2013). Whether the core collapses or the deflagration disrupts the core depends sensitively on the ignition density (Isern et al. 1991; Jones et al. 2016). If the core does collapse, the explosion proceeds via delayed explosion on short timescales (Mayle & Wilson 1988; Kitaura et al. 2006; Fischer et al. 2010), and 2D simulations suggest the explosion occurs before significant convection has had time to develop (Wanajo et al. 2011) and hence a symmetric explosion results. This, coupled with the steep density gradient at the core surface, leads to very little mass loss from the core; estimates of mass loss include of order 10−3 M⊙ (Podsiadlowski et al. 2005), 10−2 M⊙ (Kitaura et al. 2006), and 1.39 × 10−2 M⊙ (1.14 × 10−2 M⊙) for the 1D (2D) models of Wanajo et al. (2009, 2011). Therefore the ONeMg progenitor core mass is a good estimate of the baryon mass MB of the resulting NS (Podsiadlowski et al. 2005). Indeed, PSR J0737-3039A and the companion to PSR J1756-2251 have gravitational masses consistent with baryon masses ∼1.37 M⊙ when their gravitational binding energies are taken into account (Lattimer & Yahil 1989). Population synthesis calculations incorporating the various binary evolution channels that might lead to production of NSs via ECSNe show that J0737-3039B most likely formed in an ECSN, and the companion to PSR J1756-2251 is consistent with such a formation scenario (Andrews et al. 2015). Other systems with candidates for ECSNe formation also exist (Keith et al. 2009; Chen et al. 2011). | [
"Fischer et al. 2010"
] | [
"If the core does collapse, the explosion proceeds via delayed explosion on short timescales",
"and 2D simulations suggest the explosion occurs before significant convection has had time to develop",
"and hence a symmetric explosion results."
] | [
"Compare/Contrast",
"Compare/Contrast",
"Compare/Contrast"
] | [
[
900,
919
]
] | [
[
765,
856
],
[
922,
1023
],
[
1045,
1085
]
] |
2018AandA...615A.155H__Chou_et_al._2007_Instance_1 | While the velocity field is very regular, the velocity dispersion looks more complex. Instead of one peak extended along a southeast-northwest axis (Figs. 10, and 11), we find three (Fig. 13). The central one, elongated along the main axis of the galaxy and not perpendicular to it, is accompanied by two additional regions with wider lines to the northeast and southwest, separated by a total of 5.′′ 9 ± 0.′′2. At these locations we observe the transition between rigid body rotation and steep rotation curve to a flat one (see also Chou et al. 2007). At a radius of 2.′′45 (≈45 pc) and with a rotation velocity of 140 km s−1 we obtain with Eq. (1) of Mauersberger et al. (1996; η = 1) an enclosed mass of M2.45 = 2.1 × 108 M⊙ with an estimated error of 10%, in good agreement with Cunningham & Whiteoak (2005). For comparison, Roy et al. (2010) obtain with the H92α line 3 × 107 M⊙ for the mass inside a radius of 1″ (≈19 pc). Furthermore, we note that the nuclear region is slightly lopsided: The center of the line connecting the two outer peaks of line width is located ≈1.′′4 southwest of the continuum peak (see Table 3). Systemic velocities (Vbarycentric ≈ 571 km s−1) are found about 0.′′9 (≈15–20 pc) southwest of the continuum peak and may be closer to the position of the maser disk (Greenhill et al. 1997) given in Sect. 3.1. While uncertainties with respect to the value of the systemic velocity (Sect. 2) and the relative positions of the continuum peak and the maser disk are significant, most of the star formation represented by the continuum emission (see Bendo et al. 2016) appears to originate slightly northeast of the dynamical center. The lopsidedness of the central region of NGC 4945 also explains why molecular lines with significant absorption show integrated intensity peaks slightly shifted to the southwest: With the bulk of the continuum arising from the northeast, line emission is likely more quenched by absorption at this side of the center than in the southwestern part of the inclined nuclear disk (see Sect. 4.1.2 and Fig. 7). | [
"Chou et al. 2007"
] | [
"While the velocity field is very regular, the velocity dispersion looks more complex. Instead of one peak extended along a southeast-northwest axis (Figs. 10, and 11), we find three (Fig. 13). The central one, elongated along the main axis of the galaxy and not perpendicular to it, is accompanied by two additional regions with wider lines to the northeast and southwest, separated by a total of 5.′′ 9 ± 0.′′2. At these locations we observe the transition between rigid body rotation and steep rotation curve to a flat one (see also"
] | [
"Similarities"
] | [
[
535,
551
]
] | [
[
0,
534
]
] |
2021MNRAS.507.4389G__Masters_et_al._2011_Instance_2 | Erwin (2018) showed that, in a sample drawn from the Spitzer Survey of Stellar Structure in Galaxies (S4G), the bar fraction is constant over a range of (g −r) colours and gas fractions. Their bar fraction does not increase, but rather decreases for stellar masses higher than ∼ 109.7M⊙. These results are in contrast to many SDSS-based studies cited above. Erwin (2018) argues that this apparent contradiction can be explained if SDSS-based studies miss bars in low-mass blue galaxies. In Figs 5 and 6, we showed that the newly detected bars in GZD (compared to GZ2) are weak bars in low-mass blue galaxies. Nevertheless, the ‘combined’ bar fraction in Fig. 6 is not constant over (g −r) colour and agrees well with Masters et al. (2011) for redder colours [(g −r) colour > 0.5]. Additionally, our ‘combined’ bar fraction remains roughly constant over stellar mass. As mentioned before, we conclude that strong bars drive the trends of bar fraction with (g −r) colour, stellar mass, and SFR observed in other studies (Nair & Abraham 2010b; Masters et al. 2011, 2012; Vera et al. 2016; Cervantes Sodi 2017). However, the addition of weak bars in low-mass blue galaxies is insufficient to resolve the apparent disagreement between Erwin (2018) and many SDSS-based studies (Masters et al. 2011, 2012; Vera et al. 2016; Cervantes Sodi 2017; Kruk et al. 2018), which instead seems likely to be due to the very different sample selection of the S4G and SDSS galaxy samples. For example, the median stellar mass of the sample used in Erwin (2018) is ∼109.6M⊙ (based on their Fig. 4 and the bins in the top left-hand panel of their Fig. 5). However, the median stellar mass of our sample is 1010.6M⊙. As stellar mass correlates with many parameters (including bar length), this can have major consequences. Additionally, as Erwin (2018) notes, there is also the issue of resolution to consider. With an r-band FWHM of 1.18 arcsec from DECaLS (Dey et al. 2019) and a mean redshift of 0.036, the mean linear resolution of our sample is approximately 834 pc, which is higher than the 165 pc of Erwin (2018). This explains why they observe many sub-kpc bars, while we do not. These differences in stellar mass and resolution will manifest themselves in the conclusions, so a more detailed analysis is needed for a proper comparison with Erwin (2018). | [
"Masters et al. 2011"
] | [
"As mentioned before, we conclude that strong bars drive the trends of bar fraction with (g −r) colour, stellar mass, and SFR observed in other studies"
] | [
"Extends"
] | [
[
1041,
1060
]
] | [
[
867,
1017
]
] |
2019ApJ...883..149A__Rodriguez_et_al._2015_Instance_1 | A key question that remains unanswered is how BBHs are formed. Viable formation channels include isolated binary evolution (e.g., Bethe & Brown 1998; Belczynski et al. 2002, 2014, 2016; Dominik et al. 2013; Mennekens & Vanbeveren 2014; Spera et al. 2015; Eldridge & Stanway 2016; Mandel & de Mink 2016; Marchant et al. 2016; Mapelli et al. 2017; Stevenson et al. 2017; Barrett et al. 2018; Giacobbo & Mapelli 2018; Kruckow et al. 2018; Mapelli & Giacobbo 2018) and dynamical encounters in dense stellar environments, such as globular clusters (e.g., Portegies Zwart & McMillan 2000; O’Leary et al. 2006; Sadowski et al. 2008; Downing et al. 2010, 2011; Rodriguez et al. 2015, 2016a, 2016b; Askar et al. 2017; Fragione & Kocsis 2018; Rodriguez & Loeb 2018; Samsing 2018; Samsing et al. 2018; Zevin et al. 2019), young star clusters (e.g., Banerjee et al. 2010; Ziosi et al. 2014; Mapelli 2016; Banerjee 2017, 2018; Di Carlo et al. 2019; Kumamoto et al. 2019), and galactic nuclei (e.g., O’Leary et al. 2009; Antonini & Perets 2012; Antonini & Rasio 2016; Petrovich & Antonini 2017; Stone et al. 2017a, 2017b; Rasskazov & Kocsis 2019). Moreover, the dynamical process known as Kozai–Lidov (KL) resonance (Kozai 1962; Lidov 1962) can trigger the merger of a BBH, even if the BBH has not been formed in a dense star cluster. In fact, if the BBH is orbited by a tertiary body (i.e., the BBH is the inner binary of a stable hierarchical triple system), the KL mechanism triggers oscillations of the BBH’s eccentricity, which might speed up the merger by gravitational-wave emission. Each channel is expected to produce black hole mergers with different mass and spin distributions (Mandel & O’Shaughnessy 2010; Abbott et al. 2016a; Rodriguez et al. 2016c; Farr et al. 2017; Abbott et al. 2019d). The limited statistics from the low number of systems detected through gravitational waves and model uncertainties so far do not allow strong constraints on the formation channels. | [
"Rodriguez et al. 2015"
] | [
"A key question that remains unanswered is how BBHs are formed. Viable formation channels include",
"and dynamical encounters in dense stellar environments, such as globular clusters (e.g.,"
] | [
"Background",
"Background"
] | [
[
653,
674
]
] | [
[
0,
96
],
[
461,
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]
] |
2015MNRAS.450.2749G__Brinchmann_et_al._2004_Instance_1 | Ideally, however, one would want to go beyond the description of cosmic global history, and trace galaxy evolution on a galaxy-by-galaxy basis to understand the physical processes driving it. In this respect, great progress has been made by surveys at different redshifts that have established the existence of a strong dependence of galaxy histories on galaxy stellar mass. On average, more massive galaxies have formed their stars and completed their star formation activity at higher z than less massive galaxies (the so-called downsizing effect, Cowie et al. 1996; Gavazzi et al. 2006; De Lucia et al. 2007; Sánchez-Blázquez et al. 2009). The existence of relations between SFR and galaxy stellar mass (SFR–Mass) and specific star formation rate and mass (sSFR = SFR/Mass) have been established from z = 0 out to z > 2 (Brinchmann et al. 2004; Daddi et al. 2007; Noeske et al. 2007; Salim et al. 2007; Rodighiero et al. 2011; Whitaker et al. 2012; Sobral et al. 2014; Speagle et al. 2014), and many other galaxy properties have been found to be correlated with galaxy mass. Furthermore, a number of works have pointed out that galaxy properties are even more strongly correlated with a combination of galaxy mass and galaxy ‘size’, arguing for velocity dispersion (Bernardi et al. 2003; Franx et al. 2008; Smith, Lucey & Hudson 2009; Wake, van Dokkum & Franx 2012) or galaxy surface mass density (Brinchmann et al. 2004; Kauffmann et al. 2006) as principal drivers. The exact origin of these trends is still unknown, but evidence has accumulated for a dependence of galaxy stellar population ages on galaxy sizes at fixed mass (van der Wel et al. 2009; Cappellari et al. 2012; Poggianti et al. 2013), suggesting that also galaxy structure, and not just stellar mass, is relevant. In a recent paper, Omand, Balogh & Poggianti (2014) argue that the observed correlation of the quenched fraction with M/R1.5 is related to the dominance of the bulge component with respect to the disc, suggesting it might ultimately be linked with galaxy morphology (see also Driver et al. 2013). Even the sSFR–Mass relation might be due to the increase of the bulge mass fractions with galaxy stellar mass, as the ratio of SFR and stellar mass of the galaxy disc is virtually independent of total stellar mass (Abramson et al. 2014). | [
"Brinchmann et al. 2004"
] | [
"The existence of relations between SFR and galaxy stellar mass (SFR–Mass) and specific star formation rate and mass (sSFR = SFR/Mass) have been established from z = 0 out to z > 2"
] | [
"Background"
] | [
[
824,
846
]
] | [
[
643,
822
]
] |
2015AandA...584A..75V__Essen_et_al._(2014)_Instance_8 | The data presented here comprise quasi-simultaneous observations during secondary eclipse of WASP-33 b around the V and Y bands. The predicted planet-star flux ratio in the V-band is 0.2 ppt, four times lower than the accuracy of our measurements. Therefore, we can neglect the planet imprint and use this band to measure the stellar pulsations, and most specifically to tune their current phases (see phase shifts in von Essen et al. 2014). Particularly, our model for the light contribution of the stellar pulsations consists of eight sinusoidal pulsation frequencies with corresponding amplitudes and phases. Hence, to reduce the number of 24 free parameters and the values they can take, we use prior knowledge about the pulsation spectrum of the star that was acquired during von Essen et al. (2014). As the frequency resolution is 1/ΔT (Kurtz 1983), 3.5 h of data are not sufficient to determine the pulsations frequencies. Therefore, during our fitting procedure we use the frequencies determined in von Essen et al. (2014) as starting values plus their derived errors as Gaussian priors. As pointed out in von Essen et al. (2014), we found clear evidences of pulsation phase variability with a maximum change of 2 × 10-3 c/d. In other words, as an example after one year time a phase-constant model would appear to have the correct shape with respect to the pulsation pattern of the star, but shifted several minutes in time. To account for this, the eight phases were considered as fitting parameters. The von Essen et al. (2014) photometric follow-up started in August, 2010, and ended in October, 2012, coinciding with these LBT data. We then used the phases determined in von Essen et al. (2014) during our last observing season as starting values, and we restricted them to the limiting cases derived in Sect. 3.5 of von Essen et al. (2014), rather than allowing them to take arbitrary values. The pulsation amplitudes in δ Scuti stars are expected to be wavelength-dependent (see e.g. Daszyńska-Daszkiewicz 2008). Our follow-up campaign and these data were acquired in the blue wavelength range. Therefore the amplitudes estimated in von Essen et al. (2014), listed in Table 1, are used in this work as fixed values. This approach would be incorrect if the pulsation amplitudes would be significantly variable (see e.g., Breger et al. 2005). Nonetheless, the short time span of LBT data, and the achieved photometric precision compared to the intrinsically low values of WASP-33’s amplitudes, make the detection of any amplitude variability impossible. | [
"von Essen et al. (2014)"
] | [
"Therefore the amplitudes estimated in",
"listed in Table 1, are used in this work as fixed values."
] | [
"Uses",
"Uses"
] | [
[
2148,
2171
]
] | [
[
2110,
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[
2173,
2230
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2016AandA...588A..44Y__Jones_et_al._2014_Instance_1 | The second issue concerns the fact that inside a given region, coreshine is not detected in all the dense clouds observed by Paladini (2014) and Lefèvre et al. (2014) and that the proportion of clouds exhibiting coreshine varies from one region to another. For instance, 75% of the dense clouds detected in Taurus exhibit coreshine, whereas in most other regions the proportion is closer to 50% (such as Cepheus, Chamaeleon, and Musca)5. On the contrary, there are for instance very few detections in the Orion region. In THEMIS, most of the scattering efficiency originates in the accretion of an a-C:H mantle. This leads to three possible explanations for the absence of detectable coreshine. The first explanation is related to the amount of carbon available in the gas phase. The abundance used by Köhler et al. (2015) relies on the highest C depletion measurements made by Parvathi et al. (2012) towards regions with \hbox{$N_{\rm H} \geqslant 2 \times 10^{21}$}NH⩾ 2 × 1021 H/cm2. Parvathi et al. (2012) highlighted the variability in the carbon depletion in dust depending on the line of sight. Thus, there may be clouds were the amount of carbon available for a-C:H mantle formation is smaller or even close to zero: such regions would be populated with aggregates with a thinner H-rich carbon mantle or no second mantle at all and thus exhibit very little or no coreshine emission. A second explanation is related to the stability of H-rich carbon in the ISM, which depends strongly on the radiation field intensity to local density ratio (Godard et al. 2011; Jones et al. 2014). In low-density regions (according to Jones et al. 2014, \hbox{$A_{V} \leqslant 0.7$}AV⩽ 0.7 for the standard ISRF), UV photons are responsible for causing the photo-dissociation of CH bonds, a-C:H → a-C. In transition regions from diffuse ISM to dense clouds (Jones et al. 2014, \hbox{$0.7 \leqslant A_{V} \leqslant 1.2$}0.7 ⩽ AV⩽ 1.2 for the standard ISRF), better shielded from UV photons and where the amount of hydrogen is significantly higher, H-poor carbon can be transformed into H-rich carbon through H atom incorporation, a-C → a-C:H. Similarly, carbon accreted from the gas phase in these transition regions is likely to be and stay H-rich. Then, in the dense molecular clouds, most of the hydrogen is in molecular form and thus not available to produce a-C:H mantles on the grains. However, this approximately matches the density at which ice mantles start to accrete on the grains, which would partly protect a-C:H layers that had formed earlier (Godard et al. 2011, and references therein). The stability and hydrogenation degree of a-C:H, as well as the exact values of AV thresholds, are both dependent on the timescale and UV field intensity. The resulting a-C ↔ a-C:H delicate balance could explain why in a quiet region such as Taurus most of the clouds exhibit coreshine, whereas in Orion, where on average the radiation field intensity and hardness are much higher, most clouds do not. A third explanation is related to the age and/or density of the clouds. In a young cloud, where dust growth is not advanced, or in an intermediate density cloud (ρC ~ a few 103 H/cm3), the dust population may be dominated by CMM grains instead of AMM(I) dust. Such clouds would be as bright in the IRAC 8 μm band as in the two IRAC bands at 3.6 and 4.5 μm, thus not matching the selection criteria defined by Pagani et al. (2010) and Lefèvre et al. (2014) and would be classified as “no coreshine" clouds. | [
"Jones et al. 2014"
] | [
"A second explanation is related to the stability of H-rich carbon in the ISM, which depends strongly on the radiation field intensity to local density ratio"
] | [
"Background"
] | [
[
1569,
1586
]
] | [
[
1391,
1547
]
] |
2017AandA...600A.138C__Wakeford_et_al._(2016)_Instance_1 | Gibson (2014) proposed that marginalization over many systematics is more robust than simple model selection, and that the BIC-based model selection could be the worst criterion in their experiments. To assess the impact of BIC-based model selection choices (hereafter Method 1) on our derived transmission spectrum, we also performed a separate analysis on the spectroscopic light curves employing the systematics marginalization approach (hereafter Method 2). We followed the implication of this approach described in Wakeford et al. (2016), and refer the reader to that work for more details. Instead of using the wavelet-based MCMC to account for the correlated noise (see Method 1), for simplicity, Method 2 employed the MPFIT package to fit the data and accounted for the correlated noise using the time-averaging β approach. We calculated the marginal likelihood for all the systematics models using the Akaike information criterion (AIC; Akaike 1973) as the approximation, that is, \hbox{$\ln\mathcal{P}(D|S_q)\approx-\mathrm{AIC}/2$}ln𝒫(D | Sq) ≈ −AIC/2, which provides more adequate fits and performs better than BIC as suggested by Gibson (2014). The resulting Rp/R⋆ in each spectroscopic channel was then calculated as the marginal-likelihood-weighted average of the best-fitting values from all the systematics models, whose uncertainty was propagated from both the deviation from the weighted average and the best-fitting error bar for each systematics model. The derived Rp/R⋆ values are also listed in Table 3. The middle and bottom panels of Fig. 5 show the transmission spectra derived by Method 2 and the comparison between these two methods, respectively. The great consistency confirms that the BIC-based model selection in this work does not bias the derived transmission spectrum. Since the two methods have almost the same transit-depth values in any given spectral channel, we decide to present the results from Method 2 in the following discussion, as they have smaller error bars. | [
"Wakeford et al. (2016)"
] | [
"We followed the implication of this approach described in",
"and refer the reader to that work for more details."
] | [
"Uses",
"Uses"
] | [
[
520,
542
]
] | [
[
462,
519
],
[
544,
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]
] |
2019ApJ...872...52C__Ranjan_et_al._2017_Instance_1 | Studies aiming at measuring and modeling solar radiation and its variability are strongly motivated by the impact that solar irradiance (that is, the electromagnetic energy emitted by the Sun received at the top of Earth’s atmosphere in units of area and time), especially in the UV, has on the chemistry and physical properties of Earth’s atmosphere and climate (e.g., Gray et al. 2010; Matthes et al. 2017). Studies of solar variability have been recently also driven by the necessity of improving our understanding of stellar variability (see Fabbian et al. 2017, for a recent review), which, in turn, is essential to characterize the habitable zones of stars and the atmospheres of their exoplanets. As for Earth, modeling of exoplanet atmospheres requires as fundamental input the spectral energy distribution of the hosting star, especially UV and shorter wavelengths (e.g., Tian et al. 2014; Ranjan et al. 2017; Rugheimer & Kaltenegger 2018). Unfortunately, measurements of UV radiation are strongly hampered by the interstellar medium absorption (up to 70%–90%), which is significant even for relatively close stars, so that estimates of stellar UV radiation strongly rely on modeling (see Linsky 2017, for a recent review). Moreover, because there is no mission scheduled in the near future to observe stellar spectra in the UV, after the Hubble Space Telescope ceases operations, the characterization of UV spectra of stars hosting exoplanets that will be discovered by current and future missions (e.g., TESS or James Webb Space Telescope) will necessarily rely on indirect estimates, performed, for instance, through the use of semi-empirical models (e.g., Mauas et al. 1997; Fontenla et al. 2016; Busá et al. 2017) or proxies (e.g., Stelzer et al. 2013; Shkolnik et al. 2014). Stellar irradiance variability also affects the detectability of exoplanets (see, e.g., the recent review by Oshagh 2018). The passage over the disk of spots and faculae may induce photometric variations of amplitude similar to or larger than photometric variations induced by planetary transits. Moreover, the presence of active regions may alter spectral line profiles, thus hindering exoplanet detections performed through radial velocity measurements. Similarly, spectroscopic techniques that allow us to estimate the physical properties of exoplanet atmospheres (see, e.g., Kreidberg 2017, for a recent view) require as fundamental input the spectra synthetized through models representing quiet and active regions (faculae and sunspots). Finally, stellar irradiance variability observed at different spectral ranges, especially in the UV, is a fundamental observable for the characterization of the magnetic activity of a star, and therefore for the understanding of dynamo processes in stellar objects (e.g., Reinhold et al. 2013; Basri 2016; Salabert et al. 2016). Because stellar photometric and spectral variability can be modeled using the semi-empirical approaches developed for the Sun described above (see, e.g., Shapiro et al. 2016; Witzke et al. 2018), understanding the limitations of current irradiance models is fundamental to improving our capability of modeling stellar variability. | [
"Ranjan et al. 2017"
] | [
"As for Earth, modeling of exoplanet atmospheres requires as fundamental input the spectral energy distribution of the hosting star, especially UV and shorter wavelengths (e.g.,"
] | [
"Background"
] | [
[
899,
917
]
] | [
[
704,
880
]
] |
2019ApJ...876L..28D__Lamb_et_al._2018_Instance_1 | In Figures 1 and 2 we show that the X-ray (1.7 keV5
5
This value corresponds to the geometric mean of the XRT energy band, at which the error of the estimated flux can be reasonably suppressed.
), optical (R-band), and radio (6 GHz) fluxes varied with the time of observation applied to the proper corrections if observed at a distance of 200 Mpc, motivated by the fact that the averaged sensitive range of the Advanced LIGO/Virgo detectors in their full-sensitivity run is about 210 Mpc, for the current samples. Due to the faintness of the SGRB afterglow emission, there are gaps of the data between the previous more distant events and GW170817/GRB 170817A (please note that for the latter we only consider the quick decline phase as the early part is significantly influenced by the beam effect of the off-axis outflow). Therefore we extrapolate the very late (t > 200 day) X-ray and optical afterglow data of GRB 170817A to t ∼ 2 day after the burst and then compare them to other events. The radio to X-ray spectrum of the forward shock afterglow emission of GW170817/GRB 170817A is fν ∝ ν−0.6, which yields a p = 2.2 in the slow-cooling synchrotron radiation scenario (Lamb et al. 2018; Troja et al. 2018). In the jet model, such a p can also reasonably account for the very late flux decline of
(Lamb et al. 2018). The extrapolation function of the forward shock emission of GRB 170817A to early times is thus taken as f ∝ t−2.2. Surprisingly, the forward shock afterglow emission of GW170817/GRB 170817A, the first neutron star merger event detected by Advanced LIGO/Virgo, are among the brightest ones for all SGRBs detected so far. Just a few events have X-ray afterglow emission brighter than that of GRB 170817A, as demonstrated in the right panels of Figure 1. The same conclusion holds for the optical and radio afterglow data, as shown in Figure 2, though these two samples are rather limited. We have also compared the distribution of the isotropic gamma-ray energy Eiso, calculated in the rest-frame energy band of 1–104 keV, for the SGRBs with well-measured spectra, and found no significant difference for the SGRBs with and without “long-lasting” afterglow emission (see Figure 3; where the number of events for the X-ray sample are smaller than that presented in Figure 1 because some bursts lack reliable spectral measurements). GRB170817A and GRB 150101B (Troja et al. 2018), two short events with the weakest detected prompt emission, have “bright” late-time afterglow emission because of their off-axis nature. | [
"Lamb et al. 2018"
] | [
"The radio to X-ray spectrum of the forward shock afterglow emission of GW170817/GRB 170817A is fν ∝ ν−0.6, which yields a p = 2.2 in the slow-cooling synchrotron radiation scenario"
] | [
"Uses"
] | [
[
1177,
1193
]
] | [
[
995,
1175
]
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2021MNRAS.504.2168G__Steiner_et_al._2011_Instance_2 | Finally, we attempt to characterize the reflection component using the full 2–35 keV spectra with a sophisticated model [M4: ${\tt{\rm constant}}$*${\tt{\rm TBabs}}$*(${\tt{\rm simplr}}$*${\tt {\rm kerrbb2}}$+${\tt{\rm kerrconv}}$*(${\tt{\rm ireflect}}$*${\tt{\rm simplc}}$)), to evaluate the impact on the spin measurement and understand the changes of the accretion flow and the interaction between the disc and the corona. This model features a self-consistent treatment of the thermal, Compton scattering and the reflection component: ${\tt {\rm kerrbb2}}$ describes the thermal component and supplies the seed photons for ${\tt{\rm simplr}}$ (a modified version of ${\tt{\rm simpl}}$, Steiner et al. 2011) to generate the Compton component; while a portion of the Compton component will escape to reach an observer, the remains (refer as ${\tt{\rm simplc}}$, Steiner et al. 2011) will strike back to the disc to generate the reflected component. The reflection fraction Rref in ${\tt{\rm ireflect}}$ (Magdziarz & Zdziarski 1995), defined as the ratio of the Compton photons striking back to the disc to that escaping to infinity, is restricted to negative value thereby only the reflected component is returned by ${\tt{\rm ireflect}}$. It is linked to the reflection constant parameter x in ${\tt{\rm simplr}}$ via the relation x = 1 + |Rref| (Gou et al. 2011). We set the elemental abundance to unity and the iron abundance AFe to five times the solar abundance (Bharali et al. 2019; Buisson et al. 2019; Xu et al. 2020). The disc temperature Tin is fixed at the value returned by ${\tt{\rm diskbb}}$ (M1, refer to Gou et al. 2011). The ionization parameter ξ is fixed at 1000 (i.e. log(ξ) = 3, Xu et al. 2020; Buisson et al. 2019), as it is difficult to be constrained. Finally we use ${\tt{\rm kerrconv}}$ (Brenneman & Reynolds 2006) to apply relativistic effects assuming an unbroken emissivity profile with index q = 3. The key parameters in ${\tt {\rm kerrbb2}}$ and ${\tt{\rm kerrconv}}$ are linked together. | [
"Steiner et al. 2011"
] | [
"while a portion of the Compton component will escape to reach an observer, the remains (refer as ${\\tt{\\rm simplc}}$,",
"will strike back to the disc to generate the reflected component."
] | [
"Uses",
"Uses"
] | [
[
864,
883
]
] | [
[
746,
863
],
[
885,
950
]
] |
2015ApJ...807..148G__Rees_&_Mészáros_1994_Instance_2 | The fireball model remains the most popular scenario for the gamma-ray burst (GRB) phenomenon (Cavallo & Rees 1978; Goodman 1986; Paczynski 1986; Shemi & Piran 1990; Rees & Mészáros 1992, 1994; Mészáros & Rees 1993). In this model, the GRB central engine is a stellar-mass black hole or a rapidly spinning and highly magnetized neutron star formed by either the collapse of a supermassive star (collapsar; Woosley 1993; MacFadyen & Woosley 1999; Woosley & Heger 2006) or the merger of two compact objects (Paczynski 1986; Fryer et al. 1999; Rosswog 2003). In both cases, the original explosion creates a bipolar collimated jet composed mainly of photons, electrons, positrons, and a small fraction of baryons. The relativistic explosion ejecta within the jet are not homogeneous—they form multiple high density layers, which propagate at various velocities. When the fastest layers catch up with the slowest, the charged particles contained in the layers are accelerated through mildly relativistic collisionless shocks (internal shocks; Rees & Mészáros 1994; Kobayashi et al. 1997; Daigne & Mochkovitch 1998). The particles subsequently cool via emission processes such as synchrotron, Synchrotron Self Compton (SSC), and Inverse Compton (IC). The internal shock phase is usually associated with the so-called GRB prompt emission,17
17
See Pe’er (2015) for a recent review of GRB prompt emission.
mainly observed in the keV−MeV energy range (see, e.g., the spectral catalogs by Gruber et al. 2014; von Kienlin et al. 2014) and usually lasting from a few ms up to several tens to hundreds of seconds. As the ejecta interact with the interstellar medium they slow down via relativistic collisionless shocks (external shocks; Rees & Mészáros 1992; Mészáros & Rees 1993), accelerating charged particles, which then emit non-thermal synchrotron photons. This external shock phase is usually associated with the so-called GRB afterglow emission observed at radio wavelengths up to X-rays and in some cases even up to the GeV regime hours after the prompt phase, and days and even years for the lowest frequencies. The detailed origin of the gamma-ray emission, however, is not fully understood and many theoretical difficulties remain, such as the composition of the jet, the energy dissipation mechanisms, as well as the radiation mechanisms (e.g., Zhang 2011). | [
"Rees & Mészáros 1994"
] | [
"When the fastest layers catch up with the slowest, the charged particles contained in the layers are accelerated through mildly relativistic collisionless shocks (internal shocks;"
] | [
"Background"
] | [
[
1038,
1058
]
] | [
[
858,
1037
]
] |
2021AandA...655A..12T__Tang_et_al._2017b_Instance_6 | Using the RADEX3 non local thermodynamic equilibrium (LTE) modeling program (van der Tak et al. 2007) with collisional rate coefficients from Wiesenfeld & Faure (2013), we modeled the relation between the gas kinetic temperature and the measured average of para-H2CO 0.5 × [(322–221 + 321–220)/303–202] ratios, adopting a 2.73 K background temperature, an average observational linewidth of 4.0 km s−1, and column densities N(para-H2CO) = 2.7 × 1012 and 3.7 × 1012 cm−2 for N113 and N159W, respectively. The results are shown in Fig. 5. The values of the para-H2CO column density were obtained with APEX data (beam size ~30″; Tang et al. 2017b), which cover similar regions. Different column densities of para-H2CO only weakly affect derived kinetic temperatures (see Fig. 3 in Tang et al. 2017b or Fig. 4 in Tang et al. 2018a; this was also shown in Fig. 13 and discussed in Sect. 4.3.1 of Mangum & Wootten 1993) as long as all lines are optically thin. Considering that the relation between the gas temperature and the para-H2CO line ratio may vary at different spatial densities (see Fig. 2 in Tang et al. 2017b), we modeled it at spatial densities 104, 105, and 106 cm−3 in Fig. 5. It appears that Tkin at n(H2) = 105 cm−3 is consistently lower than values at 104 and 106 cm−3 by ≲23% and ≲34%, respectively, for Tkin ≲ 100 K. Local thermodynamic equilibrium (LTE) is a good approximation for the H2CO level populations under optically thin and high-density conditions (Mangum & Wootten 1993; Tang et al. 2017a,b, 2018b). Following the method applied by Tang et al. (2017b) in their Eq. (2), we plot the relation between the LTE kinetic temperature, TLTE, and the para-H2CO (3–2) line ratio in Fig. 5. Apparently, TLTE agrees well with Tnon-LTE at volume densities n(H2) ~ 105 cm−3 as long as Tkin ≲ 100 K. Previous observations show that para-H2CO (3–2) is sensitive to gas temperature at density 105 cm−3 (Ginsburg et al. 2016; Immer et al. 2016; Tang et al. 2017b). The spatial density measured with para-H2CO (303–202) and C18O (2–1) in N113 and N159W is n(H2) ~ 105 cm−3 on a size of ~30″ (Tang et al. 2017b). Therefore, here we adopt 105 cm−3 as an averaged spatial gas density in the N113 and N159W regions. | [
"Tang et al. 2017b"
] | [
"Previous observations show that para-H2CO (3–2) is sensitive to gas temperature at density 105 cm−3"
] | [
"Uses"
] | [
[
1953,
1970
]
] | [
[
1811,
1910
]
] |
2021MNRAS.500.3083C__Lupi_&_Bovino_2020_Instance_2 | Previous theorethical studies have outlined that the [C ii] emission originates from the cold (with temperatures of a few 100 K) neutral medium and from photo-dissociation regions (PDR, Vallini et al. 2013). This seems to suggest that its presence closely traces star formation sites, resulting in a linear relation, as found by De Looze et al. (2014) and Herrera-Camus et al. (2015). While at low-redshift and close to solar metallicity such a relation is well established, as shown by several observations (De Looze et al. 2014; Herrera-Camus et al. 2018) and also numerical simulations (see, e.g. Lupi & Bovino 2020), significant deviations can arise in different ISM conditions, like at lower metallicity or in presence of a strong ionizations field, that are more typically found in the high-redshift Universe. To address the impact of such conditions, several studies have analysed the [C ii] emission from typical high-redshift galaxies, by post-processing hydrodynamic zoom-in cosmological simulations with cloudy (Ferland et al. 2017; see, e.g. Olsen et al. 2017; Pallottini et al. 2017, 2019; Katz et al. 2019), or via ad-hoc methods, as in Arata et al. (2020), or also via on-the-fly non-equilibrium chemistry (Lupi et al. 2020). The main conclusion in all these studies is that a [C ii] deficit exists at high redshift, most likely due to the starbursting nature of these galaxies rather than their metallicity, since most of these systems are close to solar (see, e.g. Vallini et al. 2015; Lupi & Bovino 2020). Other studies have evidenced a weak dependence of [C ii] on metallicity. Harikane et al. (2020) showed that the L[C ii]/SFR ratio does not show a strong dependence on metallicity, which to first approximation was interpreted as the result of the proportionality between C abundance and metallicity Z and an inverse proportionality between PDR column density and Z in a dust-dominated shielding regime (Kaufman, Wolfir & Hollenbach 2006). In this framework, if PDR give a large conribution to the [C ii] emissivity, the [C ii] luminosity is not expected to strongly depend on Z (see also Ferrara et al. 2019; Pallottini et al. 2019). | [
"Lupi & Bovino 2020"
] | [
"The main conclusion in all these studies is that a [C ii] deficit exists at high redshift, most likely due to the starbursting nature of these galaxies rather than their metallicity, since most of these systems are close to solar (see, e.g."
] | [
"Compare/Contrast"
] | [
[
1503,
1521
]
] | [
[
1241,
1481
]
] |
2020MNRAS.494.6012W__Middleton_et_al._2015a_Instance_1 | Walton et al. (2017) suggested that the broad-band spectral variability seen in Holmberg IX X-1, similar to that reported here for NGC 1313 X-1, could potentially be related to the presence of the expected funnel-like geometry for the inner accretion flow. In such a scenario, the funnel is expected to geometrically collimate the emission from the innermost regions within the funnel (discussed further in Section 4.2). Regardless of the nature of the accretor (black hole or neutron star), the highest energy emission probed by NuSTAR is usually expected to arise from these regions, either powered by a centrally located Compton-scattering corona (e.g. Reis & Miller 2013), or a centrally located accretion column. The stability of this emission would therefore imply that any geometrical collimation it experiences remains roughly constant, despite the change in observed broad-band X-ray flux (which would suggest a change in accretion rate, $\dot{M}$). In principle, an increase in accretion rate would be expected to result in an increase in the scale height of the funnel (e.g. King 2008; Middleton et al. 2015a). However, while this must happen over some range of $\dot{M}$ in order for the disc structure to transition from the thin disc expected for standard sub-Eddington accretion to the funnel-like geometry expected for super-Eddington accretion, as discussed by Lasota et al. (2016), once the disc reaches the point of being fully advection-dominated the opening angle of the disc should tend to a constant (H/R ∼ 1, where H is the scale height of the disc at radius R). Walton et al. (2017) speculated that once this occurs, rather than closing the funnel further, an increase in $\dot{M}$ instead simply increases the characteristic radius within which geometric beaming occurs, such that emission that is already within this region (the highest energies probed) experiences no further collimation with an increase in $\dot{M}$, while emission from larger radii (i.e. from more intermediate energies) does still become progressively more focused, and would exhibit stronger variability. In essence, this idea invokes a radially dependent beaming factor in which the beaming of the innermost regions has saturated to explain (in only a qualitative sense) the unusual, energy-dependent broad-band spectral evolution seen from Holmberg IX X-I (and now NGC 1313 X-1). | [
"Middleton et al. 2015a"
] | [
"In principle, an increase in accretion rate would be expected to result in an increase in the scale height of the funnel (e.g.",
"However, while this must happen over some range of $\\dot{M}$ in order for the disc structure to transition from the thin disc expected for standard sub-Eddington accretion to the funnel-like geometry expected for super-Eddington accretion, as discussed by Lasota et al. (2016), once the disc reaches the point of being fully advection-dominated the opening angle of the disc should tend to a constant (H/R ∼ 1, where H is the scale height of the disc at radius R)."
] | [
"Motivation",
"Motivation"
] | [
[
1097,
1119
]
] | [
[
959,
1085
],
[
1122,
1586
]
] |
2021MNRAS.507.2115M__Hoyle_2016_Instance_1 | In astrophysics, the number of studies that apply ML techniques has risen substantially in the last years. Unsupervised learning algorithms have been used to identify different kinematic components of simulated galaxies (Obreja et al. 2018, 2019), to compare stellar spectra (Traven et al. 2017), to classify pulsars (Lee et al. 2012), and to find high-redshift quasars (Polsterer, Zinn & Gieseke 2013). Supervised learning has been used to classify variable stars (Richards et al. 2011), to classify galaxies morphologically (Huertas-Company et al. 2008), and to determine the redshift of galaxies (Hoyle et al. 2015; Hoyle 2016; D’Isanto & Polsterer 2018). Recently, ML has also been used to connect the properties of galaxies and dark matter haloes using supervised learning techniques. Kamdar, Turk & Brunner (2016a), Kamdar, Turk & Brunner (2016b) use tree-based methods to predict several galaxy properties from a set of halo properties and train the models on galaxy catalogues obtained from semi-analytic models and the Illustris hydrodynamic simulation (Vogelsberger et al. 2014). Sullivan, Iliev & Dixon (2018) train a simple neural network with one hidden layer to predict the baryon fraction within a dark matter halo at high redshift, given several halo properties (features). As training data they use the results of a cosmological hydrodynamic simulation with Ramses-RT. Similarly, Agarwal, Davé & Bassett (2018) use several ML methods to link input halo properties to galaxy properties, training on the Mufasa cosmological hydrodynamical simulation. Taking a reverse approach, Calderon & Berlind (2019) train tree-based methods and a neural network to derive halo mass from galaxy properties, training on an SDSS group catalogue. The limitation of all these studies is the supervised training and the training data. As labelled galaxy-halo data is not available for observed systems, the data for supervised learning has to be taken from a model. Even if the ML algorithms learn to reproduce the training data perfectly, the connection between galaxy and halo properties is the same as in the simulations. If the simulations predict the true relations poorly, so will the ML method. Therefore ML algorithms should not be trained on simulated data, but on observed data directly. | [
"Hoyle 2016"
] | [
"Supervised learning has been used to",
"and to determine the redshift of galaxies"
] | [
"Background",
"Background"
] | [
[
619,
629
]
] | [
[
404,
440
],
[
557,
598
]
] |
2020AandA...641A.126B__Lyutikov_et_al._2005_Instance_1 | Many low-luminosity active galactic nuclei (LLAGN) display prominent jets and compact cores that are sources of highly nonthermal continuum radio emission (see, e.g., Heeschen 1970; Wrobel & Heeschen 1991). The observational signatures of the compact cores have been reproduced using models that produce self-absorbed synchrotron emission in the jet (Falcke & Biermann 1995; Falcke et al. 2004) or in a magnetized accretion flow (Narayan et al. 1998; Yuan et al. 2003; Broderick & Loeb 2006; Moscibrodzka et al. 2009; Dexter et al. 2009; see also Falcke et al. 2001). This radiation is emitted by relativistic electrons gyrating around magnetic field lines. In the optically thin limit, the emission is significantly polarized (Jones & Hardee 1979), an effect that has been observed in higher-luminosity AGN sources (Gabuzda et al. 1996; Gabuzda & Cawthorne 2000; Lyutikov et al. 2005). The polarized emission from an accreting AGN can therefore yield information about the magnetic-field morphology of the source, which may be crucial to the evolution of the accretion flow of the AGN. The Event Horizon Telescope (EHT) is a worldwide millimeter-wavelength array capable of resolving the black-hole shadow (Goddi et al. 2017; Event Horizon Telescope Collaboration 2019); this is a characteristic feature of the radio-frequency emission from optically thin AGN at the scale of the event horizon (Falcke et al. 2000; Broderick & Narayan 2006), although the black-hole shadow may be obscured or exaggerated in certain accretion scenarios (see Gralla et al. 2019 and Narayan et al. 2019). The EHT can also determine the polarization state of such emission: Johnson et al. (2015) report 1.3 mm observations (230 GHz) that indicate partially ordered magnetic fields within a region of about six Schwarzschild radii around the event horizon of Sagittarius A* (Sgr A*), the supermassive black hole in the center of the Milky Way. Bower et al. (2003) reported stable long-term behavior and short-term variability in Sgr A* rotation measure, implying a complex inner region (within 10 Schwarzschild radii) in which both emission and propagation effects are important to the observed polarization. Hada et al. (2016) studied the central black hole in the galaxy M 87, and observed a bright feature with (linear) polarization degree of 0.2 at 86 GHz at the jet base. Observations in infrared by Gravity Collaboration (2018) were consistent with a model in which a relativistic “hot spot” of material, orbiting near the innermost stable circular orbit (ISCO) of Sgr A* in a poloidal magnetic field, emits polarized synchrotron radiation. | [
"Lyutikov et al. 2005"
] | [
"In the optically thin limit, the emission is significantly polarized",
", an effect that has been observed in higher-luminosity AGN sources"
] | [
"Background",
"Background"
] | [
[
864,
884
]
] | [
[
658,
726
],
[
748,
815
]
] |
2019ApJ...873...32M__Deming_et_al._2007_Instance_1 | Inspired by these works, we investigated the possibility of introducing a color diagram for the characterization of irradiated planets using their effective temperature instead of their absolute magnitude. The effective temperature can be used as a proxy for the luminosity/absolute magnitude because the reference radius is assumed to be constant; see Section 3. To take an even more practical approach, we chose a normalized color parameter based on the Spitzer Infrared Array Camera (IRAC; Allen et al. 2004; Fazio et al. 2004) as a commonly used photometer for the observation of exoplanets (see, e.g., Charbonneau et al. 2005; Deming et al. 2007; Todorov et al. 2009; Sing et al. 2016). The IRAC photometric channels 1 and 2 are centered at 3.6 and 4.5 μm, respectively. Channel 1 (3.6 μm) is more suited to studying CH4/H2O spectral features, while channel 2 (4.5 μm) is more sensitive to CO/CO2 features (see, e.g., Désert et al. 2009; Swain et al. 2009a, 2009b). Depending on the type of spectroscopy, i.e., transmission or emission, the ratio of the transit depth or the ratio of the secondary eclipse depth at these channels could potentially provide information regarding the relative presence of these molecules in the atmosphere of a planet. For transmission spectroscopy, we define this ratio as
15
where IRACλ is the transition depth observed at the wavelength λ (μm) channel. In transmission spectroscopy, absorption features appear as positive signals in the unit of transit depth. This is not the case for emission spectroscopy, where absorption features are negative signals with respect to a blackbody curve. As a result, we rearrange the terms and define this ratio of channels for emission spectroscopy as
16
where IRACλ is the secondary eclipse depth observed at the wavelength λ (μm) channel. By applying IRAC’s spectral response curves to our 56,448 synthetic spectra, we estimated these ratios for the two spectroscopy methods. Figure 10 shows the IRAC synthetic color–temperature diagrams for cloud-free atmospheres under equilibrium chemistry conditions. | [
"Deming et al. 2007"
] | [
"To take an even more practical approach, we chose a normalized color parameter based on the Spitzer Infrared Array Camera",
"as a commonly used photometer for the observation of exoplanets (see, e.g.,"
] | [
"Uses",
"Uses"
] | [
[
632,
650
]
] | [
[
364,
485
],
[
531,
606
]
] |
2022ApJ...938...92B__Favier_et_al._2010_Instance_1 | Flows with
Rem≪1
and
N∼(1)
have the distinct property that the induced magnetic field is quickly diffused away, yet the Lorentz force is not negligible. This limit is referred to as the quasi-static approximation to MHD (which we call “QMHD” henceforth; Moffatt 1967; Sommeria & Moreau 1982; Davidson 1995; Knaepen & Moreau 2008; Davidson 2013), and has been studied mainly in metallurgy and in MHD experiments due to the typically low conductivity of liquid metals (Alemany et al. 1979; Sommeria 1988; Gallet et al. 2009; Klein & Pothérat 2010; Pothérat & Klein 2014; Baker et al. 2018), although recent numerical studies on its turbulent properties and anisotropy have been done as well (Zikanov & Thess 1998; Burattini et al. 2008; Favier et al. 2010, 2011; Reddy & Verma 2014; Verma 2017). After nondimensionalizing the equations of MHD using the uniform density ρ, ℓ, and u, and taking the limits above, one is left with a single dynamical equation for the velocity
2
∂v∂t+v·∇v=−∇p*−Ro−1xˆ∥Ω×v−N∇−2(xˆ∥B0·∇)2v+F,
where p
* is the total pressure modified by rotation and magnetic pressure, Ro
−1 ≡ 2Ωℓ/u is the inverse Rossby number (quantifying the relative strength of the Coriolis force),
xˆ∥Ω
and
xˆ∥B0
are unit vectors in the direction of rotation and the background magnetic field, respectively, and
F
is a generic forcing term that can include dissipation such as viscosity and a body force (to be specified in Section 3). The background magnetic field is fixed in time and is uniform in space, such that
∇×B0=B0∇×xˆ∥B0=0
. Care must be taken if considering a spatially dependent background magnetic field
B
0
(
x
), as the resulting equation will not be the same. See the discussion in Section 5. This equation is accompanied with the incompressibility condition ∇ ·
v
= 0. The induced magnetic field can be found using a diagnostic relation
3
b=−∇−2xˆ∥B0·∇v,
which would be
b=−∇−2B0·∇v/η
in dimensional variables. | [
"Favier et al. 2010"
] | [
"This limit is referred to as the quasi-static approximation to MHD",
"although recent numerical studies on its turbulent properties and anisotropy have been done as well"
] | [
"Background",
"Background"
] | [
[
748,
766
]
] | [
[
166,
232
],
[
602,
701
]
] |
2019MNRAS.484.4083H__Pytte,_Mcpherron_&_Kokubun_1976_Instance_1 | According to the Dst index reconstructed by Love, Hayakawa & Cliver (2019), the interval of the telegraphic glitches taking place between ∼13:35 ut and ∼17:20 ut corresponds to the storm main phase (Dst ∼ −320 nT to ∼ −570 nT). This interval also corresponds to that of the low-latitude aurorae witnessed at many points at ±40° MLAT. A large-amplitude of the GIC is induced by magnetospheric and/or ionospheric current system. One possible cause of the telegraphic disturbance is the storm-time ring current that developed between ∼11:40 ut and ∼17:40 ut. Kappenman (2004) has shown that the magnitude of GICs flowing in the Japanese power grid increases with the magnitude of the Dst index. Another possible cause is the substorm–current wedge system that consists of field-aligned current and the tail current (McPherron, Russell & Aubry 1973). Downward field-aligned current is connected to the dawnside ionosphere, and upward field-aligned current is connected to the duskside ionosphere. The pair of field-aligned currents causes magnetic disturbances at mid- and low- latitudes (Pytte, Mcpherron & Kokubun 1976). The magnetic disturbance recorded at Tokyo (Fig. 5) shows a decrease in the H-component and a positive excursion of the D-component during the interval of ∼22–23 LT (∼13–14 ut). It is probable that Tokyo would be located at southwest of the upward field-aligned current during this interval. The D-component variation shows a few negative excursions during ∼25:40–30:00 LT (∼16:40–21:00 ut). Although the disturbance of the H-component is unavailable during this interval, it can be speculated that Tokyo was located at southeast of the downward field-aligned current. In addition to the development of the ring current, the formation of the substorm current wedge may also cause the telegraphic disruption. By considering the above discussion, at mid-latitude, we suggest that there are two regions where GICs can be caused by field-aligned currents. One is southwest of the upward field-aligned current, and the other is southeast of the downward field-aligned current. In these regions, the H-component of the magnetic field is expected to decrease significantly because of the combination of the effects of the ring current and the current wedge. Tokyo was probably situated in such hazardous regions during the 25 September 1909 storm. | [
"Pytte, Mcpherron & Kokubun 1976"
] | [
"Downward field-aligned current is connected to the dawnside ionosphere, and upward field-aligned current is connected to the duskside ionosphere. The pair of field-aligned currents causes magnetic disturbances at mid- and low- latitudes"
] | [
"Uses"
] | [
[
1085,
1116
]
] | [
[
847,
1083
]
] |
2018AandA...609A..13K__Mucciarelli_et_al._(2017)_Instance_3 | Gaia 1 is a star cluster that was recently discovered by Koposov et al. (2017) in the first Gaia data release (Gaia Collaboration 2016), alongside with another system of lower mass. Its observation and previous detections were seriously hampered by the nearby bright star Sirius, which emphasized the impressive discovery power of the Gaia mission. This object was first characterized as an intermediate-age (6.3 Gyr) and moderately metal-rich (−0.7 dex) system, based on isochrone fits to a comprehensive combination of Gaia, 2MASS (Cutri et al. 2003), WISE (Wright et al. 2010), and Pan-STARRS1 (Chambers et al. 2016) photometry. Hence, this object was characterized by Koposov et al. (2017) as a star cluster, most likely of the globular confession. Further investigation of Gaia 1 found a metallicity higher by more than 0.5 dex, which challenged the previous age measurement and rather characterized it as a young (3 Gyr), metal-rich (−0.1 dex) object, possibly of extragalactic origin given its orbit that leads it up to ~1.7 kpc above the disk (Simpson et al. 2017). Subsequently, Mucciarelli et al. (2017) measured chemical abundances of six stars in Gaia 1, suggesting an equally high metallicity, but based on their abundance study, the suggestion of an extragalactic origin was revoked. While a more metal-rich nature found by the latter authors conformed with the results by Simpson et al. (2017), the evolutionary diagrams of both studies are very dissimilar and could not be explained by one simple isochrone fit. In particular, it was noted that “the Simpson et al. (2017) stars do not define a red giant branch in the theoretical plane, suggesting that their parameters are not correct” (Fig. 1 of Mucciarelli et al. 2017). Such an inconsistency clearly emphasizes that a clear-cut chemical abundance scale is inevitable for fully characterising Gaia 1, and to further allow for tailored age determinations, even more so in the light of the seemingly well-determined orbital characteristics, Thus, this work focuses on a detailed chemical abundance analysis of four red giant members of Gaia 1, based on high-resolution spectroscopy, which we complement with an investigation of the orbital properties of this transition object. Combined with the red clump sample of Mucciarelli et al. (2017) and reaching down to the subgiant level (Simpson et al. 2017), stars in different evolutionary states in Gaia 1 are progressively being sampled. | [
"Mucciarelli et al. (2017)"
] | [
"Combined with the red clump sample of",
"stars in different evolutionary states in Gaia 1 are progressively being sampled."
] | [
"Compare/Contrast",
"Compare/Contrast"
] | [
[
2283,
2308
]
] | [
[
2245,
2282
],
[
2372,
2453
]
] |
2016AandA...595A..72M__Vergani_et_al._2015_Instance_2 | On the other hand, the Australia Telescope Compact Array (ATCA) 21 cm line survey of GRB host galaxies revealed high levels of atomic hydrogen (H i), suggesting that the connection between atomic gas and star formation is stronger than previously thought (Michałowski et al. 2015). Star formation may be directly fuelled by atomic gas, as has been theoretically shown to be possible (Glover & Clark 2012; Krumholz 2012; Hu et al. 2016), and this is supported by the existence of H i-dominated, star-forming regions in other galaxies (Bigiel et al. 2008, 2010; Fumagalli & Gavazzi 2008; Elmegreen et al. 2016). This can happen in a low metallicity gas that is recently acquired, even if the metallicity in other parts of a galaxy is higher, near the onset of star formation because cooling of gas (necessary for star formation) is faster than the H i-to-H2 conversion (Krumholz 2012). Indeed, large atomic gas reservoirs, together with low molecular gas masses (Hatsukade et al. 2014; Stanway et al. 2015b) and stellar masses (Perley et al. 2013, 2015; Vergani et al. 2015), indicate that GRB hosts are preferentially galaxies that have very recently started a star formation episode. This provides a natural route for forming GRBs in low-metallicity environments, as found for most GRB hosts (Fruchter et al. 2006; Modjaz et al. 2008; Levesque et al. 2010a; Han et al. 2010; Boissier et al. 2013; Schulze et al. 2015; Vergani et al. 2015; Japelj et al. 2016; Perley et al. 2016), except of a few examples of hosts with solar or super-solar metallicities (Prochaska et al. 2009; Levesque et al. 2010b; Krühler et al. 2012; Savaglio et al. 2012; Elliott et al. 2013; Schulze et al. 2014; Hashimoto et al. 2015; Schady et al. 2015; Stanway et al. 2015a). Indeed, the GRB collapsar model requires that most of the GRB progenitors have low metallicity (below solar) in order to reduce the loss of mass and angular momentum that is required for launching the jet (Yoon & Langer 2005; Yoon et al. 2006; Woosley & Heger 2006). We note however that other models, while still predicting the metallicity preference (e.g. Izzard et al. 2004; Podsiadlowski et al. 2004; Detmers et al. 2008), allow higher metallicities owing to differential rotation (Georgy et al. 2012), binary evolution (Podsiadlowski et al. 2010; van den Heuvel & Portegies Zwart 2013), or weaker magnetic fields (Petrovic et al. 2005). | [
"Vergani et al. 2015"
] | [
"This provides a natural route for forming GRBs in low-metallicity environments, as found for most GRB hosts"
] | [
"Compare/Contrast"
] | [
[
1418,
1437
]
] | [
[
1184,
1291
]
] |
2019ApJ...872..143B__Seckel_et_al._1991_Instance_1 | The gamma-ray emission from the solar disk due to CR cascades in the solar atmosphere is denoted as a disk component. This secondary gamma-ray produced by the hadronic interaction of cosmic ray with the solar surface was first proposed by Dolan & Fazio (1965). While only upper limits were obtained by early measurements over the range 20 keV–10 MeV (Peterson et al. 1966). A detailed theoretical model for gamma-rays from the collision of cosmic ray with the solar atmosphere was presented by Seckel et al. (1991). The predicted gamma-ray flux at energies from 10 MeV to 10 GeV has a large uncertainty, being sensitive to the assumptions about the cosmic-ray transport in the magnetic field near the Sun. Gamma rays from the Sun were first detected by the Energetic Gamma-ray Experiment Telescope (Orlando & Strong 2008). The measured flux from 100 MeV to 2 GeV was within the range of the theoretical predictions. The Fermi collaboration (Abdo et al. 2011) reported the detection of high energy gamma-rays at 0.1–10 GeV from the quiescent Sun using the first 1.5 yr data. However, the measured solar disk emission flux was about a factor of seven higher than that predicted about this disk component by a “nominal” model (Seckel et al. 1991). This mismatch motivated Ng et al. (2016) to analyze 6 yr of public Fermi-LAT data. The obtained gamma-ray spectrum follows a simple power-law shape (α = −2.3) in 1–100 GeV without any evident high energy cutoff. For the flux in 1–10 GeV, a significant time variation of the solar disk gamma-ray flux that anticorrelates with solar activity was discovered, suggesting that the solar magnetic field would play an important role. An updated analysis with 9 yr of Fermi-LAT data, from 2008 August 7 to 2017 July 27, was performed, and Tang et al. (2018) confirmed these results and extended the gamma-ray spectrum up to >200 GeV. Notably, the bright gamma-ray flux above 100 GeV is dominant only during solar minimum at the end of Cycle 23 (Linden et al. 2018). The HAWC measurements in periods of high solar activity may support these findings (Albert et al. 2018a). Data collected from 2014 November to 2017 December, the second half of solar cycle 24, have been used to set strong upper limits on the flux of 1–100 TeV gamma-rays from the solar disk, about 10% of the maximum gamma-ray flux estimated by Linden et al. (2018). The HAWC 95% upper limit at 1 TeV is about 13% of the flux extrapolated from the solar minimum Fermi-LAT gamma-ray spectrum. | [
"Seckel et al. (1991)"
] | [
"A detailed theoretical model for gamma-rays from the collision of cosmic ray with the solar atmosphere was presented by",
"The predicted gamma-ray flux at energies from 10 MeV to 10 GeV has a large uncertainty, being sensitive to the assumptions about the cosmic-ray transport in the magnetic field near the Sun."
] | [
"Background",
"Background"
] | [
[
494,
514
]
] | [
[
374,
493
],
[
516,
705
]
] |
2017ApJ...850...18H__Murase_et_al._2015_Instance_2 | The heating due to the reprocessing of non-thermal photons produced in the nebula can be efficient even at late times. Here, we treat these processes in a simple way as follows. At early times, electromagnetic cascades proceed in the saturation regime, leading to a flat energy spectrum up to ∼1 MeV (Metzger et al. 2014). At later times, the spectrum depends on the seed photon spectra, but it can roughly be estimated to be a flat spectrum from ∼1 eV to ∼0.1 TeV, while the supernova emission continues, which is expected based on more detailed calculations (e.g., Murase et al. 2015; K. Murase et al. 2017, in preparation). High-energy γ-rays (≳1 MeV) heat up the ejecta through the Compton scattering and the pair production process. X-ray and UV photons are absorbed and heat up the ejecta through the photoelectric (bound-free) absorption unless the ejecta are fully ionized. Here, we describe the heating rate as
12
Q
˙
rad
(
t
)
≈
(
f
γ
+
f
X
−
UV
,
bf
)
L
sd
,
where fγ and
f
X
−
UV
,
bf
are the heating efficiencies of γ-rays and X-ray and UV photons to the spin-down luminosity, respectively. We calculate the frequency dependent heating efficiency of γ-rays at each time:
13
f
γ
(
t
)
=
∫
ν
min
ν
max
d
ν
ν
min
(
K
γ
,
ν
τ
γ
,
ν
,
1
)
∫
1
eV
1
TeV
d
ν
ν
,
where the frequency range of γ-rays is
(
h
ν
min
,
h
ν
max
)
=
(
10
keV
,
1
TeV
)
, and h is the Planck constant. Here, τγ, ν is the optical depth of the ejecta to γ-rays and Kγ, ν is the photon inelasticity at a given frequency, where the Klein–Nishina cross section and the cross section for the Bethe–Heitler pair production in the field of a carbon nucleus are taken into account (Chodorowski et al. 1992; Murase et al. 2015). Note that the coefficient of the γ-ray optical depth depends on the density profile of the ejecta. Here, we simply assume a density profile to be constant with the radius. Adopting a realistic density profile may result in different ejecta mass and velocity estimates by a factor of a few. | [
"Murase et al. 2015"
] | [
"Here, τγ, ν is the optical depth of the ejecta to γ-rays and Kγ, ν is the photon inelasticity at a given frequency, where the Klein–Nishina cross section and the cross section for the Bethe–Heitler pair production in the field of a carbon nucleus are taken into account"
] | [
"Uses"
] | [
[
1845,
1863
]
] | [
[
1549,
1818
]
] |
2020ApJ...898...92C__Harrison_&_Tsang_1976_Instance_1 | We recorded the IRPD spectra of mass-selected H+MF and H+MF-Ln≤2 clusters (L = Ar/N2) in the 2950–3650 cm−1 spectral range in a tandem quadrupole mass spectrometer interfaced with an electron ionization source (Dopfer 2003, 2005), a setup used previously to record IR spectra of a variety of hydrocarbon cations and their clusters (Dopfer et al. 2002; Solcà & Dopfer 2002; Andrei et al. 2008; Patzer et al. 2010; Chatterjee & Dopfer 2017, 2018a, 2018b, 2020; Chatterjee et al. 2019). Briefly, the parent ions are produced in an ion source, which combines a pulsed supersonic expansion with electron (chemical) ionization close to the nozzle orifice. The expanding gas mixture is generated by passing a carrier gas mixture of Ar (N2) and 5% H2 in He in a ratio 5:1 at 10 bar through a reservoir containing liquid MF (Sigma-Aldrich, 99%, heated to 323 K). One possible reaction pathway begins with electron ionization of H2, followed by exothermic proton transfer reactions to form H+MF and subsequent three-body association to generate H+MF-Ln clusters (Harrison & Tsang 1976; Hopkinson et al. 1979; Dopfer et al. 1999; Lawson et al. 2012; Chatterjee & Dopfer 2018a), according to:
5
6
7
8
This route is reminiscent of the synthesis of interstellar protonated molecules (Oka 2006; Etim et al. 2017). An alternative pathway involves charge transfer from Ar+ (or
or
) and subsequent self-protonation (Lawson et al. 2012; Chatterjee & Dopfer 2018a):
5a
6a
7a
The desired ions are mass-selected in the first quadrupole and irradiated in an adjacent octupole with a tunable IR laser pulse (νIR, 10 Hz, 2–5 mJ pulse−1, 1 cm−1 bandwidth) of a Nd:YAG-pumped optical parametric oscillator. Calibration of νIR to better than 1 cm−1 is achieved by a wavemeter. Resonant vibrational excitation upon single-photon absorption leads to the fragmentation of neutral ligands or molecules:
9a
9b
9c
Resulting fragment ions are mass-selected by the second quadrupole and monitored with a Daly detector as a function of νIR to derive the IRPD spectrum of the parent ions, which is linearly normalized for the energy of the laser pulse. The contribution from metastable decay is subtracted from the laser-induced dissociation signal by triggering the ion source at twice the laser repetition rate. The observed widths of the vibrational bands mainly originate from unresolved rotational structure, sequence hot bands involving inter- and intramolecular modes, lifetime broadening, and congestion produced from overlap of various structural isomers. Low-energy collision-induced dissociation (CID) mass spectra at ∼10 eV collision energy in the laboratory frame are recorded by introducing 10−5 mbar N2 into the octople to confirm the composition of the ions and their clusters and establish their fragmentation channels. | [
"Harrison & Tsang 1976"
] | [
"One possible reaction pathway begins with electron ionization of H2, followed by exothermic proton transfer reactions to form H+MF and subsequent three-body association to generate H+MF-Ln clusters"
] | [
"Compare/Contrast"
] | [
[
1053,
1074
]
] | [
[
854,
1051
]
] |
2022AandA...658A.194P__Khata_et_al._2020_Instance_1 | The stellar photospheric parameters we collected from literature for the benchmark stars are summarized in Table A.1. Although most benchmark stars have v sini 2 km s−1 (Reiners et al. 2018), there are two stars with larger values: J07558+833 (12.1 km s−1) and J13005+056 (16.4 km s−1). These stars are useful to investigate the performance of the algorithms when dealing with higher rotational velocities. The literature values were derived with different methods. These methods include: interferometry to estimate the stellar radius and Teff (Boyajian et al. 2012; Ségransan et al. 2003; von Braun et al. 2014; Berger et al. 2006; Newton et al. 2015), synthetic model fitting using BT-Settl models to determine Teff (Gaidos et al. 2014; Lépine et al. 2013; Gaidos & Mann 2014; Mann et al. 2015) and log g (Lépine et al. 2013), empirical relations to derive stellar mass in the form of mass-luminosity relations (Mann et al. 2015; Khata et al. 2020; Boyajian et al. 2012; Berger et al. 2006; Ségransan et al. 2003), along with the mass-magnitude relations (Maldonado et al. 2015), mass-radius relations (von Braun et al. 2014), mass–Teff relations (Gaidos & Mann 2014; Gaidos et al. 2014), empirical relations to derive the stellar radius in the form of mass-radius relations (Maldonado et al. 2015) and Teff–radius relations (Gaidos & Mann 2014; Gaidos et al. 2014; Houdebine et al. 2019), pEW measurements to determine Teff (Maldonado et al. 2015; Neves et al. 2014; Newton et al. 2015) and [Fe/H] (Maldonado et al. 2015; Neves et al. 2014; Gaidos et al. 2014; Mann et al. 2015), the definition of spectral indices such as the H2O-K2 index to estimate Teff (Rojas-Ayala et al. 2012), as well as the combination of the H2O-K2 index with pEWs to derive [Fe/H] (Rojas-Ayala et al. 2012; Khata et al. 2020), the stellar radius and Teff (Khata et al. 2020), and spectral curvature indices for the determination of Teff (Gaidos & Mann 2014). Additionally, [Fe/H] was derived by using color-magnitude metallicity relations (Dittmann et al. 2016), atomic line strength relations (Gaidos & Mann 2014), and spectral feature relations (Terrien et al. 2015). Terrien et al. (2015) used K-band magnitudes and the Dartmouth Stellar Evolution Program (Dotter et al. 2008) to derive the stellar radius, whereas Mann et al. (2015) employed the Boltzmann equation with Teff determined from synthetic model fits. Last, but not least, Houdebine et al. (2019) derived Teff from photometric colors. For more details on the individual methods, we refer to the descriptions in the corresponding works. | [
"Khata et al. 2020"
] | [
"These methods include:",
"empirical relations to derive stellar mass in the form of mass-luminosity relations"
] | [
"Background",
"Background"
] | [
[
933,
950
]
] | [
[
467,
489
],
[
830,
913
]
] |
2015ApJ...813...47M__Morley_et_al._2012_Instance_1 | The consequences of a potential rainout for a planetary atmosphere can be manyfold. First of all the rainout removes metals from the atmosphere, relocating them to deeper layers. Hence the corresponding grain or droplet opacity will be missing from higher atmospheric layers. Because we do not include cloud opacities in our calculations we make the implicit assumption of a rainout of the condensed particles, although we do not model it, the net effect being the removal of metals from the higher layers. It has to be kept in mind, however, that the chemical equilibrium solution of the gas abundances in chemical contact with the condensed species is not necessarily the same as it would be when assuming a rainout. Our implicit assumption of a rainout is also applicable when considering the gaseous Na and K alkali abundances. In our models MgSiO3 condenses at temperatures below ∼1600 K. In principle this silicate material can further react with the alkali atoms to form alkali feldspars (such as albite and orthoclase), removing the gaseous alkalis from the gas for T ≲ 1600 K (see, e.g., Lodders 2010). We do not consider these feldspars in our condensation model, such that the alkali atoms stay in the gas, as they would in a silicate rainout scenario. It has been found that alkali atoms are present in cool brown dwarf atmospheres, indicating that silicate rainout may occur in these objects (Marley et al. 2002; Morley et al. 2012). Another consequence of condensed material can be the formation of a cloud deck, close to and above the layers of the atmosphere hot enough the evaporate the in-falling cloud particles again. Such cloud decks can heat the atmosphere locally and in the layers below, by making the atmosphere more opaque to the planet’s intrinsic flux, effectively acting like a blanket covering the lower layers of the atmosphere (see, e.g., Helling & Casewell 2014; Morley et al. 2014). If the cloud layer is optically thick close to the planet’s photosphere it will leave an imprint on the planet’s spectral appearance and and may reduce the contrast of absorption features. The height of the cloud deck depends critically on the planets effective temperature and also on its surface gravity since the condensation temperature is pressure-dependent. The cooler an object is, the deeper in its interior the clouds will reside. Therefore the spectral imprint of clouds will vary with temperature, similar to the behavior in brown dwarf atmospheres. Silicate clouds with a high optical depth are thought to reside in the photospheres L4–L6 type brown dwarfs (
∼ 1500–1700 K) where they affect the spectra. For cooler objects the cloud deck lies below the photosphere and the clouds are no longer seen (see, e.g., Lodders & Fegley 2006). In our atmospheres we checked the possible locations of the cloud decks (i.e., the layers below which the condensates evaporate). We found that the silicate evaporation layer of planets with
= 1000 K and
K is always located at pressures far higher than that of the photosphere, such that we do not expect any spectral impact of a cloud layer. For effective temperatures between 1500 and 1750 K the evaporation layer lies close to and above the photosphere (in altitude), such that a cloud deck could potentially affect the spectrum. For increasing log(g) the photosphere shifts to layers of deeper pressure, but so does the evaporation layer, as condensation is pressure dependent. Note that this temperature range is close to the effective temperature where L4–L6 dwarfs are thought to be most strongly affected by silicate clouds. For higher temperatures the evaporation layer is far above the photosphere such that we do not expect clouds to be of importance. | [
"Morley et al. 2012"
] | [
"It has been found that alkali atoms are present in cool brown dwarf atmospheres, indicating that silicate rainout may occur in these objects"
] | [
"Motivation"
] | [
[
1427,
1445
]
] | [
[
1265,
1405
]
] |
2019MNRAS.485.3185C__Orienti_et_al._2015_Instance_1 | We detected radio emission for six sources, but while the morphology of radio emission in four over six cases is compact on $\le \,$arcseconds scales, predominantly unresolved, for NGC 3185 and NGC 3941 we find a more complex morphology. The estimated radio luminosities at this frequency are L$\, \sim \, 5\, \times \, 10^{20}$ and ${\sim }\, 6\, \times \, 10^{18}$ W Hz−1 for NGC 3185 and NGC 3941, respectively, well below the radio-loud/radio-quiet threshold of L$\, \sim \, 10^{23}$ W Hz−1 defined by Condon (1992). Considering NGC 3185, the structure observed in L band has a size of $5\, \times \,$3.8 arcsec, which translates into a linear scale of $0.5\, \times \,$0.4 kpc.6 Analogous considerations can be made for the C and X Bands, leading to linear scales of $0.38\, \times \,$0.36 kpc. There is evidence for radio emission spread over the host galaxy scale for a number of Seyferts when observed with adequate angular resolution and sensitivity (Orienti et al. 2015). In particular, circumnuclear starburst rings with knots of star formation are observed. Orienti & Prieto (2010) observed diffuse radio emission with knots of star formation for a number of Seyferts, on scales smaller than 1 kpc (NGC 5506, NGC 7469, and NGC 7582). Analogously, the morphology of the radio emission in the case of NGC 3185 as observed in our radio maps may be consistent with emission from circumnuclear rings of star formation. In order to check this hypothesis, we overlapped L band and C band radio contours to an archivial HST image7 for NGC 3185, as shown in Fig. 4 . The radio contours overlap with optical emission, from which a nearly circular, ring-like structure emerges. However, further work is needed to understand the link between radio emission and star formation in the form of circumnuclear rings in this source. In particular, intermediate angular resolution scales radio observations (such as those of e-MERLIN) combined with H α maps would allow us to confirm the star formation hypothesis. If we consider the parent sample with our new data, then we find that the average spectral slope is compatible with flat (0.30 ± 0.10), with a nearly equal number of flat and steep slopes. If we consider the two sub-populations of type-1 and type-2 Seyferts, then no significant differences are found with respect to the average spectral index and the average radio-loudness parameter, the only difference being that type-1 sources are slightly more luminous. Considering the X-ray radio loudness parameter, the black hole mass and the Eddington ratio, we do not find significant differences between the type-1 and type-2 sub-classes. We note that, even though the sources in the Reference sample have an Eddington ratio nearly an order of magnitude smaller than the average for the Parent sample, the X-ray radio-loudness parameter does not exhibit anomalous values. | [
"Orienti et al. 2015"
] | [
"There is evidence for radio emission spread over the host galaxy scale for a number of Seyferts when observed with adequate angular resolution and sensitivity"
] | [
"Background"
] | [
[
960,
979
]
] | [
[
800,
958
]
] |
2017ApJ...845...92R__Mosqueira_&_Estrada_2003a_Instance_1 | Concerning case (1), the first explanation that has been proposed is an increasing relative velocity among the building blocks with decreasing distance from the planet leading to substantial water loss in the case of the most energetic impacts (Estrada & Mosqueira 2006), which occurred closer to Jupiter. Nonetheless, this scenario has been discarded by a detailed study showing that Io and Europa analogs exhibit an overabundance of water when they are formed via an N-body code simulating imperfect accretion and water loss during collisions (Dwyer et al. 2013). A second explanation is that the observed water gradient among the satellites results from an outwardly decreasing temperature of the CPD, leading to the existence of a snowline at a given radial distance from Jupiter (see, e.g., Lunine & Stevenson 1982). In this case, bodies that formed inward of the snowline (Io) accreted from essentially water-poor building blocks, whereas bodies that formed outward of the snowline (Ganymede, Callisto) formed from a primordial mixture of water ice and silicates (e.g., Canup & Ward 2002; Mosqueira & Estrada 2003a, 2003b; Mousis & Gautier 2004). Within this scenario, the low water content of Europa is puzzling. So far, Europa’s water content has been mostly attributed to its formation both outward and inward of the snowline due to either (i) its migration inward of the snowline during formation (i.e., growth), (ii) the progressive cooling of the disk and thus inward migration of the snowline during its formation, or (iii) an interplay between the two mechanisms (Alibert et al. 2005; Canup & Ward 2009). However, the evolution of the CPD has been systematically modeled using an ad hoc parametrization of the turbulent viscous disk (the so-called α-viscosity, Shakura & Sunyaev 1973) which governs the temperature evolution and lifetime of the disk. While providing a good starting point for evolutionary disk models, this kind of parametrization has been highly questioned in recent years (Bai & Stone 2013; Simon et al. 2013; Gressel et al. 2015). Hence, using a predefined α-viscosity prescription to describe the CPD’s evolution and provide hints on Europa’s formation remains questionable. The same remark holds for planet (or satellite) migration, which has also been extensively studied within recent years (see, e.g., Paardekooper et al. 2010; Bitsch et al. 2014). These studies have shown that in realistic disk conditions, migrating planets can behave significantly differently from what was previously thought, i.e., a persistent inward motion (e.g., Tanaka et al. 2002), due to the existence of regions where the migration is halted and even reversed. Because the studies of satellite formation have been based so far on the migration formulation of Tanaka et al. (2002; e.g., Canup & Ward 2002, 2006; Alibert et al. 2005; Sasaki et al. 2010) their proposed growth/migration scenario is questionable. | [
"Mosqueira & Estrada 2003a"
] | [
"In this case, bodies that formed inward of the snowline (Io) accreted from essentially water-poor building blocks, whereas bodies that formed outward of the snowline (Ganymede, Callisto) formed from a primordial mixture of water ice and silicates (e.g.,",
"Within this scenario, the low water content of Europa is puzzling."
] | [
"Background",
"Differences"
] | [
[
1095,
1120
]
] | [
[
822,
1075
],
[
1153,
1219
]
] |
2021AandA...646A..21C__Polyansky_et_al._(2018)_Instance_1 | (1a) Work is underway for an updated ExoMol line list for SiO which will extend into the ultraviolet. The current line list only considers vibration-rotation transitions and so the current maximum wavenumber was set at 6049 cm−1. (1b) The HITEMP line list for NO includes data from the ExoMol NOname line list (Wong et al. 2017). (1c) The Ames line list (Huang et al. 2017) and the CDSD-4000 databank (Tashkun & Perevalov 2011) are also available for CO2, as well as the HITEMP compilation (Rothman et al. 2010). (1d) The previous ExoMol line list for H2O, BT2 (Barber et al. 2006), is only complete up to temperatures of 3000 K, whereas the more accurate ExoMol POKAZATEL line list Polyansky et al. (2018) is complete up to 4000 K. (1e) There is also a line list for MgH from ExoMol Yadin (Yadin et al. 2012). However, since it only covers the ground electronic X2Σ+ state, and so is less complete than the more recent MoLLIST line list of Gharib-Nezhad et al. (2013), we use the latter. (1f) Previous to the ExoMol aCeTY line list of Chubb et al. (2020b), the main sources of data for acetylene were from HITRAN (Gordon et al. 2017) and ASD-1000 (Lyulin & Perevalov 2017). The data from HITRAN are only applicable for studies performed at room temperature, and were shown in Chubb et al. (2020b) to be inadequate for high-temperature applications. ASD-1000 was a vast improvement, although there does seem to be opacity missing from some of the hot bands when compared to ExoMol aCeTY in Chubb et al. (2020b). (1g) The previous ExoMol line list for CH4, called 10–10 (Yurchenko & Tennyson 2014), is only complete up to 1500 K. The updated 34–10 line list is therefore recommended instead. Future updates of the database will investigate using data for methane based on recent line lists from either TheoReTs (Rey et al. 2017) or HITEMP (Hargreaves et al. 2020); these are currently expected to be more accurate when considering high-resolution applications. For low-resolution applications, we expect the quality of the ExoMol line list used here to be sufficient, particularly because completeness is more important than accuracy at lower resolutions (Yurchenko et al. 2014). (1h) The energy states from Coppola et al. (2011) are used in the Amaral et al. (2019) line list for HD+. (1i) The energy states from Engel et al. (2005) are used in the Amaral et al. (2019) line list for HeH+. (1j) The pressure and temperature broadened profiles for the resonance doublets of Na and K are computed using Allard et al. (2016, 2019). See Sect. 3.2.3 for a discussion on the broadening profiles of these atoms. | [
"Polyansky et al. (2018)"
] | [
"whereas the more accurate ExoMol POKAZATEL line list",
"is complete up to 4000 K."
] | [
"Background",
"Background"
] | [
[
683,
706
]
] | [
[
630,
682
],
[
707,
732
]
] |
2022ApJ...935..148M__Shamasundar_et_al._2011_Instance_1 | Using the high-level ab initio calculations implemented in the MOLPRO 2015 software package (Werner et al. 2015, 2020), the electronic structures of CO have been determined. In our calculations, the molecular orbitals (MOs) and ground-state energies are computed by the HF method. Then, the CASSCF method (Knowles & Werner 1985; Werner & Knowles 1985) is applied to perform the state-averaged calculation to generate multi-configuration wave functions by utilizing the HF MOs as the starting orbitals. Finally, based on the CASSCF wave functions, the internally contracted multi-reference configuration interaction method with the Davidson correction (icMRCI+Q) (Knowles & Werner 1988; Werner et al. 1988; Knowles & Werner 1992; Shamasundar et al. 2011) is performed to consider the dynamic correlation and size-consistency error. The augmented correlation consistent polarized weighted core valence quintuplet aug-cc-pwCV5Z-DK Gaussian basis set is selected to describe the carbon and oxygen atoms, which is found to give an excellent production of the potential energy and dipole moments for electronic states as the CO molecule dissociates, as mentioned in previous publications (Dunning 1989; De Jong et al. 2001; Peterson & Dunning 2002). The scalar relativistic effect is considered by the third-order Douglas–Kroll Hamiltonian approximation (Reiher & Wolf 2004, 2004). The PECs, PDMs, and TDMs for the singlet and triplet states were computed at the internuclear distances from 0.8–7.5 Å with step sizes of 0.05 Å for 0.8–0.9 Å, 0.02 Å for 0.9–1.5 Å, 0.05 Å for 1.5–2.6 Å, 0.1 Å for 2.6–6 Å, and 0.5 Å for 6–7.5 Å, and those for the quintet states were computed at the internuclear distances from 0.8–15 Å with step sizes of 0.05 Å for 0.8–0.9 Å, 0.02 Å for 0.9–1.5 Å, 0.05 Å for 1.5–2.6 Å, 0.1 Å for 2.6–6 Å, and 0.5 Å for 6–15 Å. The obtained PECs can be also used to determine the dissociation energy D
e
, the electronic excitation energy relative to the ground state T
e
, the internuclear separation R
e
, the harmonic frequency ω
e
, the first-order anharmonic constant ω
e
χ
e
, the rotational constant B
e
, and the vibrational coupling constant α
e
. | [
"Shamasundar et al. 2011"
] | [
"Finally, based on the CASSCF wave functions, the internally contracted multi-reference configuration interaction method with the Davidson correction (icMRCI+Q)",
"is performed to consider the dynamic correlation and size-consistency error."
] | [
"Uses",
"Uses"
] | [
[
729,
752
]
] | [
[
502,
661
],
[
754,
830
]
] |
2019MNRAS.487.3702O__Owen_et_al._2011b_Instance_1 | The photoevaporation model successfully explains the ‘two-time-scale’ nature of protoplanetary disc evolution, where the inner regions of protoplanetary discs appear to evolve slowly on Myr time-scales, before dispersing on a much more rapid time-scale (e.g. Kenyon & Hartmann 1995; Ercolano, Clarke & Hall 2011; Koepferl et al. 2013; Ercolano et al. 2014). Furthermore, slow-moving (∼5–10 km s−1) ionized winds are observed to be occurring in many nearby discs hosting young stars (e.g. Hartigan, Edwards & Ghandour 1995; Pascucci & Sterzik 2009; Rigliaco et al. 2013) and are consistent with the photoevaporation model (Alexander 2008; Ercolano & Owen 2010; Pascucci et al. 2011; Owen, Scaife & Ercolano 2013a; Ercolano & Owen 2016). The photoevaporation model can also explain a large fraction of observed ‘transition discs’ (e.g. Owen & Clarke 2012; Espaillat et al. 2014), specifically those with holes ≲10 au and accretion rates ≲10−9 M⊙ yr−1 (Owen et al. 2011b) and even those with larger holes and higher accretion rates in more recent models that incorporate CO depletion in the outer disc (Ercolano, Weber & Owen 2018). Transition discs are protoplanetary discs with evidence for a large hole or cavity in their discs (e.g. Espaillat et al. 2014), but they are known to be a heterogeneous class of objects (e.g. Owen & Clarke 2012; van der Marel et al. 2016) and their origins are not always clear. However, a specific prediction of the standard photoevaporation scenario is that there should be a large number of transition discs with hole sizes ≳10 au but that are no longer accreting. This final long-lived stage of disc dispersal gives rise to transition discs which have lifetimes between 105 and 106 yr, but remain optically thick – ‘relic discs’ (Owen et al. 2011b). The long disc lifetimes emerge from the simple fact that discs store most of their mass at large radii, but photoevaporative clearing proceeds from the inside out, so it will always take longer to remove the larger disc mass that resides at larger distance. While several discs satisfy this criterion (Dong et al. 2017), the number of observed non-accreting transition discs with large holes falls far below the theoretical expectations (Owen et al. 2011b; Owen & Clarke 2012). Studies by Cieza et al. (2013) and Hardy et al. (2015) showed that optically thick relic discs are rare and many non-accreting stars that show evidence for a circumstellar disc are more consistent with young, radially optically thin, debris discs. | [
"Owen et al. 2011b"
] | [
"This final long-lived stage of disc dispersal gives rise to transition discs which have lifetimes between 105 and 106 yr, but remain optically thick – ‘relic discs’"
] | [
"Background"
] | [
[
1764,
1781
]
] | [
[
1598,
1762
]
] |
2020ApJ...898...49N__Sowmya_et_al._2014_Instance_1 | In the line cores of Q/I and U/I profiles, we see depolarization and rotation for fields in the range
G. These are due to the Hanle effect. For
G, we see the signatures of level-crossings in the line cores of (Q/I, U/I) profiles, namely they tend toward the non-magnetic value (see Figures 1(b) and 2(b)). We recall that, traditionally the loops in the polarization diagram (namely, a plot of Q/I versus U/I for a given wavelength and for a range of magnetic field strength or orientation values) are identified to be due to the level-crossings in the incomplete PBE regime (see, e.g., Bommier 1980; Landi Degl’Innocenti & Landolfi 2004, see also Sowmya et al. 2014). When a given curve in the polarization diagram forms a loop the Q/I and U/I values tend toward the non-magnetic value. Based on this we identify the above noted behavior in the line cores of (Q/I, U/I) profiles for the mentioned field-strength regime as to be the signatures of level-crossings in the incomplete PBE regime. Polarization diagrams require the use of very fine grids of magnetic field strength or orientation. With the radiative transfer calculations presented in this paper, it is computationally difficult to produce such diagrams. For
G, transverse Zeeman effect like signatures are seen in the line core of (Q/I, U/I) profiles (see Figures 1(c) and 2(c)). The Faraday rotation (del Pino Alemán et al. 2016; Alsina Ballester et al. 2017; Sampoorna et al. 2017), which results in depolarization in the wings of Q/I and generation of U/I in the wings, strongly influences the wings of U/I profiles for the entire field-strength regime considered here, while it shows up in Q/I for
G. For the cases of theoretical model line and the isothermal model atmosphere considered in this section, the Voigt effect starts to show up in U/I for
G and in Q/I for
G, and its signatures are similar to those discussed in Sampoorna et al. (2019a). Also we see the signatures of incomplete PBE in the V/I profiles, which are now asymmetric about the line center for fields up to 30 G. | [
"Sowmya et al. 2014"
] | [
"We recall that, traditionally the loops in the polarization diagram (namely, a plot of Q/I versus U/I for a given wavelength and for a range of magnetic field strength or orientation values) are identified to be due to the level-crossings in the incomplete PBE regime",
"see also"
] | [
"Background",
"Background"
] | [
[
661,
679
]
] | [
[
320,
587
],
[
652,
660
]
] |
2020ApJ...888..126Z__Warren_et_al._2006_Instance_1 | Achondritic meteorites are fragments of differentiated asteroids or planetary bodies of the solar system. Ureilites are coarse-grained ultramafic (olivine–pyroxene) achondrites. They include accessory minerals of metal and sulfide associated with high abundances of carbon phases (on average 3 vol% and up to ∼7 vol%; Goodrich et al. 2015), including graphite and high-pressure diamond (Goodrich 1992; Mittlefehldt et al. 1998; Nabiei et al. 2018). According to their petrology, ureilites are further divided into main group ureilites (formerly referred to as monomict or unbrecciated ureilites; accounting for 95%) and rare polymict ureilites (or brecciated ureilites). The main group ureilites represent the mantle residues after the extraction of feldspar-rich magmas (Cohen et al. 2004; Bischoff et al. 2014; Barrat et al. 2016) and a sulfur-rich iron melt (Goodrich et al. 2004; Warren et al. 2006; Goodrich et al. 2007; Rankenburg et al. 2008; Barrat et al. 2015), whereas polymict ureilites are breccias containing fragments of main group ureilites as well as non-ureilite clasts (Goodrich et al. 2004, 2015). Unlike samples from other differentiated planetary bodies (e.g., terrestrial and lunar samples, Martian meteorites, angrites), some primitive isotopic geochemical features (e.g., O isotope heterogeneities; Greenwood et al. 2005, 2006, 2017) have been preserved in ureilites, which are considered incompatible with a magma ocean event (e.g., Goodrich 1992; Goodrich et al. 2004, 2015). Therefore, the geochemical signatures of ureilite meteorites can provide valuable information about the origin of the ureilite parent body (UPB) and the early evolution of the solar system. For instance, olivine cores from individual ureilite meteorites cover a range of Fe/Mn ratios from 3 to 57 (Goodrich 1992; Goodrich et al. 2004, 2007; Downes et al. 2008) and Δ17O values (mass-independent O isotopic variations) from −2.5‰ to −0.2‰ (Clayton & Mayeda 1988, 1996; Greenwood et al. 2017). The whole rock Δ17O values further correlate with both the Fe/Mn ratios and magnesium number (Mg#: molar ratio of Mg/Mg+Fe) of their olivine cores (Goodrich et al. 2004, 2015). The origin of these covariations is debated and multiple scenarios have been proposed to explain these features, including (1) a “smelting” process which causes redox reactions between C and FeO during UPB differentiation (Singletary & Grove 2003; Goodrich et al. 2007); (2) oxidation of metal due to the presence of water prior to igneous differentiation (Sanders et al. 2017); (3) inherited nebular redox variability from the precursor materials that were not homogenized during partial melting (Warren & Huber 2006; Warren 2012); (4) UPB accretion from the mixing of two different chemical and isotopic reservoirs (Barrat et al. 2017). As such, ureilite genesis still remains unclear. Understanding the origin of these geochemical correlations in ureilites is further complicated by the fact that the timing of formation and early evolution of the UPB is poorly constrained. | [
"Warren et al. 2006"
] | [
"The main group ureilites represent the mantle residues after the extraction of",
"and a sulfur-rich iron melt"
] | [
"Background",
"Background"
] | [
[
884,
902
]
] | [
[
671,
749
],
[
833,
860
]
] |
2018AandA...618A..38K__Kirchschlager_&_Wolf_2013_Instance_1 | In Fig. 1, we investigate the dust grain size distributions at the periastron and apastron of debris disks a belt eccentricity of eb = 0.4 (with dynamical excitation Δeb = 0.1) for different material strengths. Since the radiation pressure has a strong influence on the cutoff in the grain size distribution at smallest sizes, the wavy patterns of the grain size distributions start around the smallest bound grains. We note that the blowout size can be increased with particle porosity and increasing stellar temperature (Burns et al. 1979; Kirchschlager & Wolf 2013; Brunngräber et al. 2017). We find different characteristic wavy patterns in the grain size distributions starting with the depletion of grains with radii below the blowout radius abo, which are caused by the lack of β > 0.5 dust grains (Thébault et al. 2003), depending on different collisional evolutions (Figs. 1 and 2). For grains with radii ~3 μm at the apastron side and grains with radii ~6 μm at the periastron side, a strong wavy pattern develops. This depletion leads to an over-density of slightly larger grains (“first peak”) because grains with radii a abo are depleted and thus can no longer contribute efficiently to the destruction and erosion processes anymore. The overabundance of grains with radii around the first peak (~1.5 abo) in turn induces another depletion of grains with radii around the “second depletion” (~4–40 abo) that is caused by small high-β grains originating inside the disks. Thus, an efficient destruction is responsible for the deep depletion of objects with radii of up to ~4−40 abo. Qualitatively, this first wavy pattern is less pronounced in the size distribution of higher material strengths, where the impact velocities and thus their rate of destructive collisions is significantly lower. A strong depletion for lower material strengths is found for grains with radii ~60 μm, while the depletion in the case of higher material strengths is valid for radii ≤10 μm (Fig. 1). This depletion eventually leads to an over-density of grains with radii around the “second peak”. The overabundance of these grains is shifted from ~100 μm (high material strength) to ~1000 μm (very low material strength). | [
"Kirchschlager & Wolf 2013"
] | [
"We note that the blowout size can be increased with particle porosity and increasing stellar temperature"
] | [
"Uses"
] | [
[
542,
567
]
] | [
[
417,
521
]
] |
2021ApJ...910...84E__Rappazzo_&_Velli_2011_Instance_1 | Based on these results, a series of 3D numerical simulations solving the simplified reduced magnetohydrodynamic (RMHD) equations, introduced by Strauss (1976), in Cartesian geometry were performed. The goal of these simulations was twofold: (1) to determine how a coronal loop responds to different photospheric velocity patterns, and (2) to investigate how the electric current sheets are formed, as well as the details of the heating that occurs through the dissipation of magnetic energy (Rappazzo et al. 2007, 2008, 2010; Rappazzo & Velli 2011; Rappazzo & Parker 2013; Rappazzo 2015). The results detailed in these papers confirmed the 2D results that the energy flux entering the corona because of photospheric motions causes a turbulent cascade of energy toward small scales, with electric current sheets continuously being created and destroyed throughout the coronal loop. The turbulence that develops is highly intermittent. The dissipation of energy occurs in current sheets, which are localized structures. Hence, the heating also occurs on small spatial scales. (Note that there is also particle acceleration, although that is beyond the scope of the present model.) When the loop is fully turbulent, it achieves a statistically steady state in which, on average, the Poynting flux induced at the boundaries by footpoint convection is balanced by the dissipation of energy in the electric current sheets. In this steady state, saturation occurs for the fluctuating magnetic energy, kinetic energy, mean square electric current, enstrophy, and other quantities that are then seen to fluctuate around their mean values. When the system becomes nonlinear, its behavior is highly dynamical and chaotic. This state occurs independently of the detailed form of the boundary velocity. A statistically steady state is achieved in which, although the magnetic field footpoints are convected continuously by the boundary flows, the resulting topology of the total magnetic field is not simply a mapping of those flows. By the same token, the turbulent dynamics that occur are due to the inherent nonlinear nature of the system, rather than being a consequence of the complexity of the magnetic field footpoint configuration. | [
"Rappazzo & Velli 2011"
] | [
"The goal of these simulations was twofold: (1) to determine how a coronal loop responds to different photospheric velocity patterns, and (2) to investigate how the electric current sheets are formed, as well as the details of the heating that occurs through the dissipation of magnetic energy"
] | [
"Motivation"
] | [
[
526,
547
]
] | [
[
198,
490
]
] |
2022AandA...665A.115C__Clark_&_Steele_(2000)_Instance_2 | While different studies devoted to the near-IR spectra of Be stars show low-resolution data, many of them are restricted to a small sample, and some others analyse reduced spectral ranges. For instance, there are only a few studies done in the J band, and they focus mainly on a particular object or a specific spectral line or element (Mathew et al. 2012a,b; Štefl et al. 2009). Also, individual spectral ranges have already been studied for large samples of Be stars. Steele & Clark (2001) presented H-band spectroscopy of Be stars with a spectral resolution of R ≃ 3000. They reported Brackett and Fe ii lines in emission and, from the analysis of the strength ratio of the higher Brackett lines to Brγ, were able to distinguish early- from late-type Be stars. Later, Chojnowski et al. (2015) published high-resolution H-band spectroscopy for a great number of Be stars observed with APOGEE. They found that the Br11 emission line is formed preferentially in a circumstellar disc at an average distance of ~2.2R*, while the higher Brackett lines seem to originate in an innermost region. Several emission lines have been identified for the first time, such as C i λ 1.6895 μm, which is also formed in the inner region of the discs. In a later work, Chojnowski et al. (2017) analysed the variation of the emission strength, peak intensity ratio, and peak separation. Their analysis revealed a variety of temporal variability, including the disappearance and appearance of the line emission on different timescales. In the K band, Hanson et al. (1996), Clark & Steele (2000) and Granada et al. (2010) reported Brγ, Brδ, and Pfund lines in emission together with lines of He i in emission or absorption, and Mg ii, Fe ii and Na i lines in emission. Clark & Steele (2000) related the infrared characteristics to the underlying properties of the stars: objects that present He i features in emission or absorption are B3 or earlier; if the star presents Mg ii in emission but no He i, it is between B2 and b4; objects with Brγ emission but no evidence of He i or Mg ii are B5 or later. Lenorzer et al. (2002b) provided an extensive atlas of early type stars, including a number of Be stars, covering the K and L bands, while Lenorzer et al. (2002a) analysed the H recombination lines of those stars and constructed a diagram of flux ratios of some selected recombination lines: Hu14/Brα and Hu14/Pfγ. In this diagram, the location of the objects gives information about the density of the emitting gas. After that, Mennickent et al. (2009) presented a classification scheme for Be stars based on the intensity of the L-band hydrogen-emission lines. The objects in each group fall in different regions of Lenorzer’s diagram; thus, this classification scheme is probably connected to the density of the disc. Granada et al. (2010) analysed a sample of eight Be stars and classified them with Mennickent’s criterion. They found that for group I objects, the equivalent widths (EW) of Brα and Brγ lines are similar, while for stars in group II the EW(Brγ) is much larger (more than five times) than the EW(Brα). Besides this, Mennickent et al. (2009) and Granada et al. (2010) reported emission lines not only in Brα, Pfγ, and the Humphreys series but also in He i λ4.038 μm and He i λ4.041 μm. Sabogal et al. (2017) showed a sample of L-band Be-star spectra and correlated the infrared features with the optical Hα line behaviour. | [
"Clark & Steele (2000)"
] | [
"related the infrared characteristics to the underlying properties of the stars: objects that present He i features in emission or absorption are B3 or earlier; if the star presents Mg ii in emission but no He i, it is between B2 and b4; objects with Brγ emission but no evidence of He i or Mg ii are B5 or later."
] | [
"Background"
] | [
[
1749,
1770
]
] | [
[
1771,
2083
]
] |
2022MNRAS.511.1819S__Bengaly_et_al._2019_Instance_1 | A sky survey at multiple frequencies, carried out with the Square Kilometre Array (SKA) could be used for an independent investigation of the controversial dipole anisotropy with a much superior sensitivity and thereby settle the question of the CP, hopefully, in a more decisive manner. In fact it was argued by Crawford (2009) that it is not possible to detect a radio dipole at more than 1σ level (for a presumed radio dipole amplitude equal to the CMBR dipole, i.e. p = 1), in a survey like the NVSS as the latter does not have sufficient number of sources. The conclusion drawn instead was that in order to make a positive detection of a radio dipole we may have to wait for the SKA data, going to sub-µJy flux-density levels, and thus having much larger number of sources, to get a better signal to noise. In spite of this deterrent prediction, a radio dipole at statistically significant level was detected from the NVSS data itself (Singal 2011) which became possible only because the radio dipole amplitude turned out to be actually a factor of ∼4 larger than the CMBR dipole. Although SKA might provide number counts at sub-µJy levels (Schwarz et al. 2015; Bengaly et al. 2019), however, one may need to be wary of possible caveats in using radio source number counts at these flux-density levels as one might start seeing at sub-mJy levels, in addition to the powerful distant radio sources, a substantially increasing fraction of very different populations of radio sources, e.g. nearby normal galaxies, starburst galaxies, and even galactic sources (Windhorst 2003; Padovani 2011; Luchsinger et al. 2015). Instead what would be important is to get surveys at different frequencies from SKA, at a few mJy levels or above where the radio source population may comprise mostly powerful radio galaxies and quasars, and then investigate the dipoles to see how genuine is the difference in dipoles from surveys at widely separated frequency bands like that seen in the NVSS and TGSS dipoles. The multiple frequency flux-density measurements should also allow for the chosen sample a direct estimate of an optimum value of the spectral index, that enters in the expression for the dipole amplitude. The question of CP could be resolved in a positive manner if it is found that multiple-frequency radio source surveys yield dipoles consistent with the CMBR dipole, though it would still remain to be explained why the presently determined dipoles are not consistent with that. However, in case it does turn out that the SKA surveys with better statistical accuracies also yield dipole magnitudes which are significantly different from the CMBR dipole, even though might be pointing along the CMBR dipole direction, as is seen in the presently determined dipoles, then it will certainly be a big problem for the CP, and consequently all conventional cosmological models, including the ones dealing with the question of dark energy, could be in serious jeopardy. | [
"Bengaly et al. 2019"
] | [
"Although SKA might provide number counts at sub-µJy levels",
"however, one may need to be wary of possible caveats in using radio source number counts at these flux-density levels as one might start seeing at sub-mJy levels, in addition to the powerful distant radio sources, a substantially increasing fraction of very different populations of radio sources, e.g. nearby normal galaxies, starburst galaxies, and even galactic sources"
] | [
"Compare/Contrast",
"Compare/Contrast"
] | [
[
1167,
1186
]
] | [
[
1086,
1144
],
[
1189,
1561
]
] |
2021ApJ...909..175Y__Buzzicotti_et_al._2018_Instance_3 | The filtered MHD equations read
11
12
where we sum over repeated indices, and
13
14
15
16
denote the inertial (I), Maxwell (M), advective (A), and dynamo (D) subfilter-scale stresses, respectively. Despite their common origin through the electric field in the induction equation, we here treat
and
separately, in order to disentangle the effects of magnetic-field-line advection, encoded in
, and magnetic-field-line stretching, encoded in
. Usually, the magnetic subscale stress refers to the difference
(Aluie 2017; Offermans et al. 2018). Equations (11) and (12) differ from expressions for the filtered MHD equations found elsewhere by an additional projection of the coupling terms. The latter ensures that the dynamics defined by Equations (11) and (12) are confined to the same finite-dimensional subspace Ωℓ of the original domain Ω (Buzzicotti et al. 2018; Offermans et al. 2018). At first sight, this formulation suggests that the corresponding evolution equations for kinetic and magnetic energy feature terms are not Galilean invariant, which ought to be avoided as the measured subfilter-scale energy transfers otherwise include unphysical fluctuations (Aluie & Eyink 2009a, 2009b; Buzzicotti et al. 2018). However, the energy balance equations can be expressed in an alternative way by including terms that vanish under spatial averaging and ensure Galilean invariance of all terms (Buzzicotti et al. 2018; Offermans et al. 2018). For a statistically stationary evolution, the spatiotemporally averaged energy budget can then be written as
17
18
where
and
are the filtered kinetic and magnetic dissipation rates, respectively, and
are terms that convert kinetic to magnetic energy
and vice versa
, and
19
20
21
22
denote the four proper energy fluxes, in the sense that they vanish in the limit ℓ → 0, as can be seen from Equations (13)–(16). If positive, the inertial and Maxwell fluxes,
and
transfer kinetic energy from scales larger than or equal to ℓ to scales smaller than ℓ and vice versa if negative, while the advective and dynamo fluxes,
and
, do so with magnetic energy. Note that there is no interscale energy conversion as the conversion terms
and
only involve filtered fields; as such they are known as resolved-scale conversion terms (Aluie 2017). The total energy flux is then given by the sum
23
| [
"Buzzicotti et al. 2018"
] | [
"However, the energy balance equations can be expressed in an alternative way by including terms that vanish under spatial averaging and ensure Galilean invariance of all terms"
] | [
"Uses"
] | [
[
1468,
1490
]
] | [
[
1291,
1466
]
] |
2015AandA...580A..71L__Sutton_et_al._(2013)_Instance_2 | The simplest two component model (power law + disk) is a phenomenological model often used to describe the spectra of ULXs as an empirical description of a disk plus corona geometry. In the presence of a cool (kT ~ 0.1−0.4 keV) and luminous (L ~ 1039−1040 erg/s) disk, it allows inferring the presence of intermediate-mass black holes (e.g., Makishima et al. 2000). This is not the case for M33 X-8, where the disk component describes the high-energy part of the spectrum well and appears to be hot (kT ~ 1.15 keV), leaving a soft excess that is accounted for by the power law. The overall disk parameters are then inconsistent with a massive black hole, but instead are more typical of an ordinary stellar mass black hole: using the relationship between mass, temperature, and luminosity in a standard disk (see, e.g., Makishima et al. 2000), we derive a mass of ~10 M⊙ for a nonrotating black hole, consistent with the estimation obtained by data from other satellites (e.g., Foschini et al. 2006; Weng et al. 2009; Isobe et al. 2012). Sutton et al. (2013) developed a classification scheme based on a disk+power law fit, to be applied to ULX spectra, according to which the spectral state of an ULX source can be defined by the disk temperature, the power-law slope, and the ratio between the flux contribution of the two spectral components in the 0.3−1 keV band. Our result is consistent with that found by Sutton et al. (2013) using XMM-Newton data, and, according to their classification, it identifies M33 X-8 as a broadened disk source, or in other words, as a source whose spectrum is dominated by emission from a hot disk (see Table 2) and where the additional soft component may be the effect of an unrealistic description of the disk spectrum by the diskbb model. In fact, such hot-disk/soft power-law spectra are difficult to explain in the context of the analogy of ULXs with GBHs: the thermal state of GBHs is indeed characterized by a hot disk, but the presence of a soft power-law-like component in addition to the disk is unusual, and its physical interpretation is not simple: if this component is due to the presence of a Comptonized corona, we do not expect it to be dominant at energies lower than the temperature of the seed photons that come from the disk. | [
"Sutton et al. (2013)"
] | [
"Our result is consistent with that found by",
"using XMM-Newton data,",
"and, according to their classification, it identifies M33 X-8 as a broadened disk source, or in other words, as a source whose spectrum is dominated by emission from a hot disk (see Table 2) and where the additional soft component may be the effect of an unrealistic description of the disk spectrum by the diskbb model."
] | [
"Similarities",
"Similarities",
"Uses"
] | [
[
1412,
1432
]
] | [
[
1368,
1411
],
[
1433,
1455
],
[
1456,
1776
]
] |
2021AandA...648A..73B__Marois_et_al._2008_Instance_1 | We present the photometry of the companion in Fig. 4 in a color-magnitude diagram. The corresponding numerical values are reported in Table 2. YSES 2b is consistent with a late L to early T spectral type when comparing it to colors of field brown dwarfs from the NIRSPEC Brown Dwarf Spectroscopic Survey (McLean et al. 2003, 2007), the IRTF spectral library (Rayner et al. 2009; Cushing et al. 2005), the L and T dwarf data archive (Knapp et al. 2004; Golimowski et al. 2004; Chiu et al. 2006), and the SpeX Prism Libraries (Burgasser et al. 2004, 2008, 2010; Gelino & Burgasser 2010; Burgasser 2007; Siegler et al. 2007; Reid et al. 2006; Kirkpatrick et al. 2006, 2010; Cruz et al. 2004; Burgasser & McElwain 2006; McElwain & Burgasser 2006; Sheppard & Cushing 2009; Looper et al. 2007, 2010; Muench et al. 2007; Dhital et al. 2011). Object distances were derived from Gaia EDR3 (Gaia Collaboration 2021), the Brown Dwarf Kinematics Project (Faherty et al. 2009), and the Pan-STARRS1 3π Survey (Best et al. 2018). In color-magnitude space, YSES 2b is very close to the innermost three planets of the HR 8799 multi-planetary system (Marois et al. 2008, 2010). These three planets are classified as mid to late L type dwarfs (e.g., Greenbaum et al. 2018), which agrees well with the sequence evolution of the adjacent field brown dwarfs from L to T spectral types3. A similar spectral type in this domain, therefore, seems very likely for YSES 2b, requiring confirmation by measurements at higher spectral resolution. Whereas the masses of the spectrally similar trio of HR 8799 c, d, and e are in the range 7–12 MJup (Wang et al. 2018; Marois et al. 2008, 2010), it is likely that YSES 2b has an even lower mass as the system age of (13.9 ± 2.3) Myr is significantly younger than the age of HR 8799, which is claimed to be member of the Columba association with an age of 30–50 Myr (Zuckerman et al. 2011; Bell et al. 2015). This is supported by the AMES-COND and AMES-dusty models (Allard et al. 2001; Chabrier et al. 2000) that we present in Fig. 4 for a system age of 13.9 Myr. An individual evaluation of these isochrones yielded masses from 5.3 MJup to 8.0 MJup as presented in Table 2. The uncertainties originate from the errors in the system age and planet magnitude that were propagated by a bootstrapping approach with 1000 randomly drawn samples from Gaussian distributions around both parameters. When combining the posterior distributions for the different models and filters we derived a final mass estimate of
$6.3^{1.6}_{-0.9}\,M_{\mathrm{Jup}}$6.3−0.9+1.6 MJup
as the 68% confidence interval around the median of the sample. This estimate is based on broadband photometric measurements alone; further spectral coverage of the planetary SED will be important to constrain its effective temperature, luminosity, surface gravity, and mass. | [
"Marois et al. 2008"
] | [
"In color-magnitude space, YSES 2b is very close to the innermost three planets of the HR 8799 multi-planetary system"
] | [
"Compare/Contrast"
] | [
[
1133,
1151
]
] | [
[
1015,
1131
]
] |
2019AandA...622A.180L__Cappellari_et_al._2011_Instance_1 | Large spectroscopic and photometric surveys, such as the Sloan Digital Sky Survey (SDSS, York et al. 2000), have revolutionized astrophysics in many fields, but can only deliver a limited view of the star formation activity in the local universe, given that instruments have a small field of view (FoV) in the case of spectroscopic surveys, and a low spectral resolution in the case of photometric ones. In recent years, integral field spectroscopic (IFS) surveys such as the Calar Alto Legacy Integral Field spectroscopy Area (CALIFA, Sánchez et al. 2012a) survey used in this work, have overcome these problems with the use of instruments with larger FoVs and a fully spectral coverage (e.g SAURON, Bacon et al. 2001; ATLAS3D, Cappellari et al. 2011; SAMI, Croom et al. 2012; VENGA, Blanc et al. 2013; and MaNGA, Bundy et al. 2015). However, these surveys still have limitations, such as the lack of a large contiguous observed area to trace the environment of nearby galaxies. They also suffer from selection biases due to the exclusion of galaxies with angular sizes that do not fit in the FoV of the integral field units (IFUs) that need to be considered (Walcher et al. 2014). These problems can be circumvented with multi-filter photometric surveys, which use a set of intermediate and narrow-band filters designed to provide the required spectral information while still covering a large contiguous area. The Javalambre Photometric Local Universe Survey (J-PLUS1, Cenarro et al. 2019) is currently operating to observe thousands of square degrees of the northern sky from the Observatorio Astrofísico de Javalambre (OAJ2) in Teruel, Spain. The survey is being carried out with the 0.83 m JAST/T80 telescope and the panoramic camera T80Cam (Marin-Franch et al. 2015), with a 2 deg2 FoV. A set of twelve broad, intermediate, and narrow-band optical filters is used (Fig. 1 and Table 1), optimized to provide an adequate sampling of the spectral energy distribution (SED) of millions of stars in our galaxy. These SEDs will be required for the photometric calibration of the Javalambre Physics of the accelerating universe Astrophysical Survey (J-PAS3, Benitez et al. 2014). In addition, the position of the filters, the exposure times, and the survey strategy, are suitable to perform science that will expand our knowledge in many fields of astrophysics. Further details on the OAJ, instrumentation, filter set, J-PLUS photometric calibration process, strategy, and several science applications can be found in the J-PLUS presentation paper (Cenarro et al. 2019). | [
"Cappellari et al. 2011"
] | [
"In recent years, integral field spectroscopic (IFS) surveys",
"have overcome these problems with the use of instruments with larger FoVs and a fully spectral coverage (e.g",
"ATLAS3D,"
] | [
"Background",
"Background",
"Background"
] | [
[
729,
751
]
] | [
[
404,
463
],
[
584,
692
],
[
720,
728
]
] |
2022ApJ...934...73A__Ryan_et_al._2011_Instance_1 | In contrast, deep narrow-field surveys can reach more distant UCD populations, enabling measurement of disk structure and a greater proportion of halo and thick disk sources. The majority of deep surveys for UCDs (Table 1) have been undertaken with the Hubble Space Telescope (HST), as these objects often comprise a foreground to extragalactic surveys. Early work in this area includes measurement of M dwarf number counts in the HST Deep Field and Large Area Multi-Color Survey Groth Strip (Gould et al. 1997; Kerins 1997; Chabrier & Mera 1997). Analysis of these samples determined M dwarf thin and thick disk vertical scaleheights of ∼325 pc and ∼650 pc, respectively, and ruled out very low-mass stars as being an appreciable component (1%) of Galactic halo dark matter. Ryan et al. (2005) performed one of the first deep photometric surveys of distant UCDs, identifying 28 candidate L and T dwarfs in 135 arcmin2 of deep imaging data obtained with the HST Advanced Camera for Surveys (ACS) instrument, selected by their i − z colors to a limiting magnitude of z 25. They determined a thin disk vertical scaleheight of ∼350 pc, similar to prior measurements of deep M dwarf star counts. (Ryan et al. 2011) subsequently identified 17 candidate late-M, L, and T dwarfs in 232 arcmin2 of HST/Wide Field Camera 3 (WFC3) imaging of the Great Observatories Origins Deep Survey (Giavalisco et al. 2004) using optical and near-infrared color selection, and determined a thin disk vertical scaleheight for these sources of 290 ± 40 pc. Deep ground-based surveys have also identified samples of distant UCDs. Kakazu et al. (2010) identified seven late-L and T dwarfs in 9.3 deg2 of optical and infrared imaging data from the Subaru Suprime-Cam Hawaii Quasar and T dwarf survey to a limiting magnitude of z 23.3, spectroscopically confirming several of the targets. From this small sample, Kakazu et al. (2010) inferred a thin disk vertical scaleheight of ∼400 pc for brown dwarfs. Sorahana et al. (2019) used the larger (130 deg2) and deeper (z 24) Hyper Suprime-Cam Subaru Strategic Program survey (Aihara et al. 2018) to photometrically identify 3,665 L dwarfs, and inferred an average thin disk vertical scaleheight of 340–420 pc. Carnero Rosell et al. (2019) used multi-band imaging data from the Dark Energy Survey (The Dark Energy Survey Collaboration 2005), combined with photometry from wide-field imaging surveys, to photometrically identify and classify 11,745 L0–T9 dwarfs to a limiting magnitude of z ≤ 22, and estimated a thin disk vertical scaleheight of ∼450 pc. Recently, Warren et al. (2021) compiled a sample of 34,000 M7-L3 UCDs by searching over a large area of 3,070 deg2 in the Sloan Digital Sky Survey (SDSS; York et al. 2000) and UKIRT Infrared Deep Sky Survey (UKIDSS) down to J = 17.5, and measured a scaleheight of ∼270 pc. These last three studies, which comprise the largest compilations of UCDs to date, use multiple colors to segregate UCDs from other background sources (Skrzypek et al. 2016). | [
"Ryan et al. 2011"
] | [
"subsequently identified 17 candidate late-M, L, and T dwarfs in 232 arcmin2 of HST/Wide Field Camera 3 (WFC3) imaging of the Great Observatories Origins Deep Survey",
"using optical and near-infrared color selection, and determined a thin disk vertical scaleheight for these sources of 290 ± 40 pc."
] | [
"Background",
"Background"
] | [
[
1194,
1210
]
] | [
[
1212,
1376
],
[
1402,
1532
]
] |
2018AandA...613A...3Q__Kelly_et_al._2017_Instance_2 | As a prototypical Seyfert 2 galaxy with starburst at a distance of 14.4 Mpc (1″ = 72 pc, Bland-Hawthorn et al. 1997), NGC 1068 was observed at radio (Greenhill et al. 1996), millimeter (Schinnerer et al. 2000), infrared (Jaffe et al. 2004), optical (Antonucci & Miller 1985), UV (Antonucci et al. 1994), and X-ray (Kinkhabwala et al. 2002). High spatial resolution CO (1–0) observations show two molecular spiral arms with a diameter of ~40″ and a northern half-bar, while a CO (2–1) map reveals a nuclear ring with two bright knots in the CND region (Schinnerer et al. 2000). The dense gas fraction as traced by HCN (1–0) (Tacconi et al. 1994; Helfer & Blitz 1995) and CS (2–1) (Tacconi et al. 1997; Takano et al. 2014) in the nuclear region is higher than the two arms. Observations of CO (3–2) (Krips et al. 2011; Tsai et al. 2012; García-Burillo et al. 2014) showed that the difference of molecular gas temperatures between the nuclear region and the two arms was not as large as that of densities. Dozens of molecular lines at millimeter wavelength were detected at CND with single-dish observations (Usero et al. 2004; Nakajima et al. 2011, 2013; Aladro et al. 2013). Moreover, several molecules were detected and resolved toward NGC 1068 with interferometers in the past few years (Tosaki et al. 2017; Kelly et al. 2017; Furuya & Taniguchi 2016; Izumi et al. 2016; Imanishi et al. 2016; Nakajima et al. 2015; Viti et al. 2014; Takano et al. 2014; García-Burillo et al. 2014, 2016). The molecular gas in the CND region was denser and hotter than that in the starburst ring, while chemical properties in the two regions were also different (Viti et al. 2014). The highest molecular gas temperature was higher than 150 K, and the gas density was above 105 cm−3 in the CND region (Viti et al. 2014). The distribution of different species of molecules were also different: CO isotopic species, for instance, were enhanced in the starburst ring, while the shock/dust related molecules were enhanced in the CND region (Nakajima et al. 2015). The spatially resolved observations showed that the CND region was a complex dynamical system. For instance, the east and west dots were dominated by a fast shock and a slower shock (Kelly et al. 2017), while the dust torus also showed complex kinematics (García-Burillo et al. 2016). Gas inflow was driven by a past minor merger (Furuya & Taniguchi 2016), while the outflow was AGN driven (García-Burillo et al. 2014). We conducted adeeper survey of millimeter lines toward the CND region of NGC 1068 with the IRAM 30 m telescope, with the goal to quantify the gas properties in the CND. Compared to previous single-dish observations, our data probe weaker transition lines, which could place more constraints on the physical and chemistry properties of the CND. | [
"Kelly et al. 2017"
] | [
"The spatially resolved observations showed that the CND region was a complex dynamical system. For instance, the east and west dots were dominated by a fast shock and a slower shock"
] | [
"Background"
] | [
[
2225,
2242
]
] | [
[
2042,
2223
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] |
2022MNRAS.512..439C__Johnson,_Sangwan_&_Shankaranarayanan_2022_Instance_1 | It is still unclear whether this incompatibility is evidence against the spatially flat ΛCDM model or is caused by unidentified systematic errors in one of the established cosmological probes or by evolution of the parameters themselves with the redshift (Dainotti et al. 2021b, 2022). Newer, alternate cosmological probes could help alleviate this issue. Recent examples of such probes include reverberation-mapped quasar (QSO) measurements that reach to redshift z ∼ 1.9 (Czerny et al. 2021; Khadka et al. 2021a,b; Yu et al. 2021; Zajaček et al. 2021), H ii starburst galaxy measurements that reach to z ∼ 2.4 (Mania & Ratra 2012; Chávez et al. 2014; González-Morán et al. 2019, 2021; Cao, Ryan & Ratra 2020, 2022a; Cao et al. 2021a; Johnson, Sangwan & Shankaranarayanan 2022; Mehrabi et al. 2022), QSO angular size measurements that reach to z ∼ 2.7 (Cao et al. 2017, 2020, 2021a; Ryan, Chen & Ratra 2019; Lian et al. 2021; Zheng et al. 2021), QSO flux measurements that reach to z ∼ 7.5 (Risaliti & Lusso 2015, 2019; Khadka & Ratra 2020a,b, 2021, 2022; Lusso et al. 2020; Yang, Banerjee & Ó Colgáin 2020; Li et al. 2021; Lian et al. 2021; Luongo et al. 2021; Rezaei, Solà Peracaula & Malekjani 2021; Zhao & Xia 2021),1 and the main subject of this paper, gamma-ray burst (GRB) measurements that reach to z ∼ 8.2 (Amati et al. 2008, 2019; Cardone, Capozziello & Dainotti 2009; Cardone et al. 2010; Samushia & Ratra 2010; Dainotti et al. 2011, 2013a,b; Postnikov et al. 2014; Wang, Dai & Liang 2015; Wang et al. 2016, 2022; Fana Dirirsa et al. 2019; Khadka & Ratra 2020c; Hu, Wang & Dai 2021; Dai et al. 2021; Demianski et al. 2021; Khadka et al. 2021c; Luongo et al. 2021; Luongo & Muccino 2021; Cao et al. 2021a). Some of these probes might eventually allow for a reliable extension of the Hubble diagram to z ∼ 3–4, well beyond the reach of Type Ia supernovae. GRBs have been detected to z ∼ 9.4 (Cucchiara et al. 2011), and might be detectable to z = 20 (Lamb & Reichart 2000), so in principle GRBs could act as a cosmological probe to higher redshifts than 8.2. | [
"Johnson, Sangwan & Shankaranarayanan 2022"
] | [
"Newer, alternate cosmological probes could help alleviate this issue.",
"Recent examples of such probes include",
"H ii starburst galaxy measurements that reach to z ∼ 2.4"
] | [
"Motivation",
"Background",
"Background"
] | [
[
736,
777
]
] | [
[
286,
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],
[
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[
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2015AandA...573A.102B__Fernández_et_al._1999_Instance_1 | The cumulative total absolute magnitude distribution of the comets obeys N( HT) ∝ 10− αTHT. Since we have imposed that the total brightness of the comets scales as BT ∝ fD2, it is easy to show that the slope of the total absolute magnitude distribution, αT, is equal to the slope of the nuclear absolute magnitude distribution, α. The latter is related to the cumulative size-frequency distribution, N( >D) ∝ D− γ, where γ = 5α. Even though there is a lot of scatter in the D − HT diagram caused by variation in f from one comet to the next (Fernández et al. 1999), there is a clear correlation between D and HT in Fig. 1 which must be caused by the underlying size distribution. For JFCs with diameters between approximately 2 km and 10 km the slope γ ~ 2 (Meech et al. 2004; Snodgrass et al. 2011), corresponding to α = 0.4. The number of JFCs with q 2.5 AU and HT 10.8 is then \hbox{$N_{\rm vJFC}=294_{-235}^{+556}$}NvJFC=294-235+556, about three times higher than the number reported in Levison & Duncan (1997) and Di Sisto et al. (2009). This is likely to be a lower limit because of the aforementioned incompleteness. However, the fading alters the mean active lifetime, τvFJC, as well. From the output of our simulations and using the delayed power law we computed a weighted mean period of JFCs with q 2.5 AU of 7.94 yr and a corresponding active lifetime \hbox{$\tau_{\rm vJFC} =1969^{+7479}_{-1540}$}τvJFC=1969-1540+7479 yr, lower than previous estimates (Di Sisto et al. 2009; Duncan & Levison 1997; Fernández et al. 2002). Following Brasser & Morbidelli (2013) the corresponding number of objects in the scattered disc with this updated active lifetime, taking into account the uncertainties in all relevant quantities, is then \hbox{$N_{\rm SD}= 5.9^{+2.2}_{-5.1} \times 10^9$}NSD=5.9-5.1+2.2×109. That same work computed an Oort cloud population of NOC = (7.6 ± 3.3) × 1010 for objects with D> 2.3 km. From our new analysis the Oort cloud to scattered disc population ratio turns out to be 13\hbox{$_{-11}^{+77}$}+77-11, which is consistent with the ratio of 12 ± 1 from simulations (Brasser & Morbidelli 2013). Thus, it is likely that the Oort cloud and scattered disc formed at the same time from the same source, and thus is consistent with a formation during the giant planet instability. | [
"Fernández et al. 1999"
] | [
"Even though there is a lot of scatter in the D − HT diagram caused by variation in f from one comet to the next"
] | [
"Uses"
] | [
[
543,
564
]
] | [
[
430,
541
]
] |
2017MNRAS.471.4286F__Colpi_2014_Instance_1 | Following the first detection by ROSAT (Komossa & Bade 1999; Bade, Komossa & Dahlem 2016), about 50 TDEs have been observed (Komossa 2015) in hard X-ray (Bloom et al. 2011; Burrows et al. 2011; Cenko et al. 2012; Pasham et al. 2015), soft X-ray (Komossa & Bade 1999; Donley et al. 2002; Esquej et al. 2008; Maksym et al. 2010; Saxton et al. 2012, 2017; Bade et al. 2016), UV (Stern et al. 2004; Gezari et al. 2006, 2008, 2009) and optical (van Velzen et al. 2011; Gezari et al. 2012; Arcavi et al. 2014; Chornock et al. 2014; Holoien et al. 2014; Vinko et al. 2015) wavelengths. Some of the observed TDEs exhibit unusual properties. In particular, one of the detected TDEs shows an excess of variability in its light curve (Saxton et al. 2012) which can be explained if the black hole is actually a binary with a mass of 106 M⊙, mass ratio of 0.1 and semimajor axis of 0.6 milliparsecs (Liu, Li & Komossa 2014). This candidate appears to have one of the most compact orbits among the known SMBH binaries and has overcome the ‘final parsec problem’ (Colpi 2014). Upon coalescence, it will be a strong source of gravitational wave emission in the sensitivity range of the evolved Laser Interferometer Space Antenna (eLISA). Three other TDEs appear to be very bright in X-rays with peak soft X-ray isotropic luminosity being highly super-Eddington (Burrows et al. 2011; Cenko et al. 2012; Brown et al. 2015), while follow-up observations showed that these events were also associated with bright, compact, variable radio synchrotron emission (Zauderer et al. 2011; Cenko et al. 2012). The observed high X-ray luminosity can be explained if the tidal disruption of stars in these cases powered a highly beamed relativistic jet pointed at the observer (Tchekhovskoy et al. 2014). Based on these three observations, Kawamuro et al. (2016) concluded that 0.0007 per cent–34 per cent of all TDEs source relativistic jets, while Bower et al. (2013) and van Velzen et al. (2013) estimated that ≲10 per cent of TDEs produce jetted emission at the observed level. Formation of jets in TDEs is a topic of active research, e.g. works by Metzger, Giannios & Mimica (2012), Mimica et al. (2015) and Generozov et al. (2017). | [
"Colpi 2014"
] | [
"This candidate appears to have one of the most compact orbits among the known SMBH binaries and has overcome the ‘final parsec problem’"
] | [
"Compare/Contrast"
] | [
[
1049,
1059
]
] | [
[
912,
1047
]
] |
2022MNRAS.517.4529B__Zaroubi,_Hoffman_&_Dekel_1999_Instance_1 | The other criteria that we can use to categorize the reconstruction methods is whether the reconstruction is performed using forward-modelling or uses a direct inversion from the data. Inverting non-linear problems from partial, noisy, observations is an ill-posed inverse problem, which makes forward-modelled Bayesian methods particularly suitable for the task of reconstruction of high-dimensional fields. Bayesian reconstruction methods have become increasingly popular in cosmology and have been applied in a range of different applications such as initial conditions reconstruction (Jasche & Wandelt 2013; Modi, Feng & Seljak 2018; Jasche & Lavaux 2019), weak lensing (Fiedorowicz et al. 2022; Porqueres et al. 2021, 2022; Boruah, Rozo & Fiedorowicz 2022), and CMB lensing (Millea et al. 2021; Millea, Anderes & Wandelt 2020). Such methods have also been used for the local velocity field reconstruction. The simplest of such methods uses a Wiener filtering technique (Zaroubi, Hoffman & Dekel 1999). This approach assumes that the density/velocity field is described as a Gaussian random field and the Wiener filtered reconstruction is the maximum-a-posteriori (MAP) solution for the problem. The Wiener filtering approach has been extended to account for uncertainties and biases in the reconstruction using a constrained realization approach (Hoffman & Ribak 1991; Hoffman, Courtois & Tully 2015; Hoffman et al. 2018; Lilow & Nusser 2021) An alternative way to account for the biases in the reconstruction in Wiener filtering is using the unbiased minimal variance approach (Zaroubi 2002). Another similar approach is the Bayesian hierarchical method, virbius (Lavaux 2016), which is based on the constrained realization approach but accounts for many different systematic effects in its analysis. This approach has been been applied to the Cosmicflows-3 (Tully, Courtois & Sorce 2016) data set by Graziani et al. (2019). A similar reconstruction code, hamlet, was introduced in Valade et al. (2022). However, these methods fail to account for the inhomogeneous Malmquist (IHM) bias which is an important source of systematic error in peculiar velocity analysis. The IHM bias arises from an incorrect assumption on the distribution of peculiar velocity tracers due to neglecting the line-of-sight inhomogeneities. | [
"Zaroubi, Hoffman & Dekel 1999"
] | [
"The simplest of such methods uses a Wiener filtering technique",
"This approach assumes that the density/velocity field is described as a Gaussian random field and the Wiener filtered reconstruction is the maximum-a-posteriori (MAP) solution for the problem."
] | [
"Background",
"Background"
] | [
[
975,
1004
]
] | [
[
911,
973
],
[
1007,
1199
]
] |
2020AandA...641A.155V__Elmegreen_et_al._2007_Instance_1 | It has also become evident that the normalization of the MS rapidly increases with redshift: distant galaxies form stars at higher paces than in the local Universe, at fixed stellar mass (e.g., Daddi et al. 2007; Elbaz et al. 2007; Whitaker et al. 2012; Speagle et al. 2014; Schreiber et al. 2015). This trend could be explained by the availability of copious molecular gas at high redshift (Daddi et al. 2010a; Tacconi et al. 2010, 2018; Scoville et al. 2017a; Riechers et al. 2019; Decarli et al. 2019; Liu et al. 2019a), ultimately regulated by the larger accretion rates from the cosmic web (Kereš et al. 2005; Dekel et al. 2009a). Moreover, higher SFRs could be induced by an increased efficiency of star formation due to the enhanced fragmentation in gas-rich, turbulent, and gravitationally unstable high-redshift disks (Bournaud et al. 2007, 2010; Dekel et al. 2009b; Ceverino et al. 2010; Dekel & Burkert 2014), reflected on their clumpy morphologies (Elmegreen et al. 2007; Förster Schreiber et al. 2011; Genzel et al. 2011; Guo et al. 2012, 2015; Zanella et al. 2019). IR-bright galaxies with prodigious SFRs well above the level of the MS are observed also in the distant Universe, but their main physical driver is a matter of debate. While a star formation efficiency (SFE = SFR/Mgas) monotonically increasing with the distance from the main sequence (ΔMS = SFR/SFRMS, Genzel et al. 2010, 2015; Magdis et al. 2012; Tacconi et al. 2018, 2020) could naturally explain the existence of these outliers, recent works suggest the concomitant increase of gas masses as the main driver of the starbursting events (Scoville et al. 2016; Elbaz et al. 2018). In addition, if many bright starbursting (sub)millimeter galaxies (SMGs, Smail et al. 1997) are indeed merging systems as in the local Universe (Gómez-Guijarro et al. 2018, and references therein), there are several well documented cases of SMGs hosting orderly rotating disks at high redshift (e.g., Hodge et al. 2016, 2019; Drew et al. 2020), disputing the pure merger scenario. The same definition of starbursts as galaxies deviating from the main sequence has been recently questioned with the advent of high spatial resolution measurements of their dust and gas emission. Compact galaxies with short depletion timescales typical of SBs are now routinely found on the MS, being possibly on their way to leave the sequence (Barro et al. 2017a; Popping et al. 2017; Elbaz et al. 2018; Gómez-Guijarro et al. 2019; Puglisi et al. 2019; Jiménez-Andrade et al. 2019); or galaxies moving within the MS scatter, due to mergers unable to efficiently boost the star formation (Fensch et al. 2017) or owing to gravitational instabilities and gas radial redistribution (Tacchella et al. 2016). | [
"Elmegreen et al. 2007"
] | [
"Moreover, higher SFRs could be induced by an increased efficiency of star formation due to the enhanced fragmentation in gas-rich, turbulent, and gravitationally unstable high-redshift disks",
"reflected on their clumpy morphologies"
] | [
"Background",
"Background"
] | [
[
961,
982
]
] | [
[
636,
826
],
[
921,
959
]
] |
2016ApJ...820..113J__Malanushenko_et_al._2009_Instance_1 | There have been previous studies that utilized coronal extreme ultraviolet (EUV) images in combination with models to try to more accurately determine the magnetic field. Conlon and Gallagher (Conlon & Gallagher 2010) used Extreme Ultraviolet Imager (EUVI) images to choose the best value of the parameter α in an LFFF model of a coronal active region. Aschwanden and co-authors (Aschwanden & Sandman 2010; Aschwanden 2013; Aschwanden & Malanushenko 2013) created NLFFF models of active regions by forward-fitting the underlying magnetograms with sets of buried magnetic monopoles and selecting the corresponding α values for each monopole that produced the greatest agreement with coronal loops traced in EUVI images. Malanushenko and co-authors (Malanushenko et al. 2009, 2012) have presented a method for deriving an NLFFF model from sparsely distributed EUV loop observations. These studies have focused on modeling the field in active regions, where the high density results in bright EUV emission and the limited size of the region allows for a reasonable number of free parameters. Additionally, the complexity of these methods suggests that their primary application would be the detailed study of a specific region of interest, rather than casual production of models for programmatic use. In contrast, the purpose of our study has been to develop a method for the fast production of global coronal magnetic field models based on widely available synoptic magnetograms and coronal images. Global models are necessary for studies on a wide array of topics, including the connectivity of active regions (Tadesse et al. 2012; Schrijver et al. 2013), the topology of the corona through the solar cycle (Wang & Sheeley 2003; Platten et al. 2014), and as a larger context for studies of coronal activity in localized regions (Conlon & Gallagher 2010; Schrijver et al. 2013). They are also instrumental for global heliospheric simulation and interpreting in situ measurements by upcoming near-Sun missions, Solar Orbiter (SO) and Solar Probe Plus (SPP). | [
"Malanushenko et al. 2009"
] | [
"Malanushenko and co-authors",
"have presented a method for deriving an NLFFF model from sparsely distributed EUV loop observations.",
"These studies have focused on modeling the field in active regions, where the high density results in bright EUV emission and the limited size of the region allows for a reasonable number of free parameters. Additionally, the complexity of these methods suggests that their primary application would be the detailed study of a specific region of interest, rather than casual production of models for programmatic use. In contrast, the purpose of our study has been to develop a method for the fast production of global coronal magnetic field models based on widely available synoptic magnetograms and coronal images."
] | [
"Background",
"Background",
"Compare/Contrast"
] | [
[
748,
772
]
] | [
[
719,
746
],
[
780,
880
],
[
881,
1497
]
] |
2015AandA...584A..75V__Essen_et_al._(2014)_Instance_7 | The data presented here comprise quasi-simultaneous observations during secondary eclipse of WASP-33 b around the V and Y bands. The predicted planet-star flux ratio in the V-band is 0.2 ppt, four times lower than the accuracy of our measurements. Therefore, we can neglect the planet imprint and use this band to measure the stellar pulsations, and most specifically to tune their current phases (see phase shifts in von Essen et al. 2014). Particularly, our model for the light contribution of the stellar pulsations consists of eight sinusoidal pulsation frequencies with corresponding amplitudes and phases. Hence, to reduce the number of 24 free parameters and the values they can take, we use prior knowledge about the pulsation spectrum of the star that was acquired during von Essen et al. (2014). As the frequency resolution is 1/ΔT (Kurtz 1983), 3.5 h of data are not sufficient to determine the pulsations frequencies. Therefore, during our fitting procedure we use the frequencies determined in von Essen et al. (2014) as starting values plus their derived errors as Gaussian priors. As pointed out in von Essen et al. (2014), we found clear evidences of pulsation phase variability with a maximum change of 2 × 10-3 c/d. In other words, as an example after one year time a phase-constant model would appear to have the correct shape with respect to the pulsation pattern of the star, but shifted several minutes in time. To account for this, the eight phases were considered as fitting parameters. The von Essen et al. (2014) photometric follow-up started in August, 2010, and ended in October, 2012, coinciding with these LBT data. We then used the phases determined in von Essen et al. (2014) during our last observing season as starting values, and we restricted them to the limiting cases derived in Sect. 3.5 of von Essen et al. (2014), rather than allowing them to take arbitrary values. The pulsation amplitudes in δ Scuti stars are expected to be wavelength-dependent (see e.g. Daszyńska-Daszkiewicz 2008). Our follow-up campaign and these data were acquired in the blue wavelength range. Therefore the amplitudes estimated in von Essen et al. (2014), listed in Table 1, are used in this work as fixed values. This approach would be incorrect if the pulsation amplitudes would be significantly variable (see e.g., Breger et al. 2005). Nonetheless, the short time span of LBT data, and the achieved photometric precision compared to the intrinsically low values of WASP-33’s amplitudes, make the detection of any amplitude variability impossible. | [
"von Essen et al. (2014)"
] | [
"and we restricted them to the limiting cases derived in Sect. 3.5 of",
"rather than allowing them to take arbitrary values."
] | [
"Uses",
"Uses"
] | [
[
1830,
1853
]
] | [
[
1761,
1829
],
[
1855,
1906
]
] |
2021MNRAS.503..354G__Hou_&_Han_2014_Instance_2 | The spatial distribution of OB stars and associations, young long-period Cepheids and open clusters, star-forming regions, H ii regions, interstellar dust, and giant molecular and neutral gas clouds in the solar vicinity that have been in existence generally τ ≲ 108 yr is known to correlate with the location of the inner Sagittarius, the closest Orion, and outer Perseus spiral arm segments. (The distances for the vast majority of these spiral tracers have been determined in the literature with trigonometric or photometric methods.) The Sun is situated at the inner edge of the Orion arm (Levine et al. 2006; Hou & Han 2014; Nakanishi & Sofue 2016; Xu et al. 2018, 2021; Lallement et al. 2019; Reid et al. 2019; Skowron et al. 2019; Cantat-Gaudin et al. 2020; Fig. 2 above).3 These three spatial features nearby to the Sun appear to form part of the global spiral structure in the Galaxy. Contrary, the objects of older population with larger random velocities, for instance, main-sequence A–K stars or the oldest Cepheids and open clusters, do not currently follow the exact location of those arms (e.g. Cantat-Gaudin et al. 2020, fig. 8 therein; Griv et al. 2020, fig. 7 therein). The latter can be explained by the difference in rotation velocity between the spiral density waves and the objects. Investigating the velocity field of Xu et al.’s (2018) O and early B-type stars in the framework of the Lin–Shu density-wave proposal, we also found that the Sun lies within the Orion arm, at the inner edge of this spiral. The radial distance from the Sun to the centre of the Orion arm is ≈0.2 kpc in the direction of the Galactic anticentre, the centre of the Sagittarius arm is ≈1.8 kpc from the Sun in the direction of the GC, and the width of the arms is ≈0.5 kpc. The radial distance between the centres of the Orion and Sagittarius arms near the Sun is λrad ≈ 2 kpc (cf. Hou & Han 2014; Wu et al. 2014; Bovy et al. 2015). As for us, the nearest Orion spiral arm forms part of the dominant density-wave structure of the system. | [
"Hou & Han 2014"
] | [
"The radial distance between the centres of the Orion and Sagittarius arms near the Sun is λrad ≈ 2 kpc (cf."
] | [
"Background"
] | [
[
1883,
1897
]
] | [
[
1775,
1882
]
] |
2019ApJ...871...82G__Tarr_et_al._2014_Instance_1 | By considering the UV emission at several wavelengths, we have been able to reconstruct the evolution of the EFR at different layers using radiance maps. The optically thin view provided by the O i λ1355.6 line (Lin & Carlsson 2015) images the AFS that formed above the EFR. AFSs are typically observed in absorption in the chromospheric layers during flux emergence and reflect the serpentine nature of the emerging fields (Bruzek 1980; Spadaro et al. 2004; Zuccarello et al. 2005; Murabito et al. 2017). They also can reconnect with the ambient field (e.g., Zuccarello et al. 2008; Tarr et al. 2014; Su et al. 2018). Here the AFS appears in emission when observed in the O i λ1355.6 line, being brighter than the background. Some brightness enhancements are found along the AFS, suggesting the occurrence of small-scale energy release events related to the reconnection of the emerging field lines with the ambient field (see, e.g., Huang et al. 2018). The view of optically thick Mg ii k and C ii λ1335 lines (Leenaarts et al. 2013; Rathore et al. 2015) offers the possibility to see the counterpart of the AFS in the upper chromosphere. Threads observed in absorption, departing from the AFS, cover the whole structure. It should be stressed that the reconstructed radiance maps image the EFR along the entire IRIS scan: this means that the individual threads at every single slit position along the x-direction were only transiently observed. From the comparison with IRIS SJIs in the 2796 Å passband, it can be deduced that threads correspond to the surges, being viewed as individual ejections in slice imaging. The westernmost part of the UV burst, being not covered by threads, is seen as a compact brightening in the Mg ii k and C ii λ1335 radiance maps, in the latter having a higher contrast with respect to the background. Conversely, the optically thin emission in the Si iv λλ1402 and 1394 lines clearly illustrates the UV burst and other bright knots in the EFR area. Apparently, threads have no counterpart at Si iv λλ1402 and 1394 formation heights, although fluffy elongated structures appear in the northern part of the UV burst. Finally, dark elongated absorption structures are distinctly visible in the SDO/AIA 193 filtergrams, which are highly reminiscent of the threads seen by IRIS. To their west, a compact brightening cospatial to the UV burst is also detected, being not obscured by such structures. | [
"Tarr et al. 2014"
] | [
"They also can reconnect with the ambient field (e.g.,"
] | [
"Background"
] | [
[
584,
600
]
] | [
[
506,
559
]
] |
2017AandA...603A.107A__Leconte_et_al._(2015)_Instance_1 | The second equation of our system is the conservation of mass, (12)\begin{equation} \dfrac{\partial \rho}{\partial t} + \boldsymbol{\nabla}. \left( \rho {\vec V} \right) = 0, \end{equation}∂ρ∂t+∇.ρV=0,which, in spherical coordinates, writes (13)\begin{equation} \dfrac{\partial \delta \rho}{\partial t } + \frac{1}{r^2} \dfrac{\partial }{\partial r} \left( r^2 \rho_0 V_r \right) + \frac{\rho_0}{r \sin \theta} \left[ \dfrac{\partial }{\partial \theta} \left( \sin \theta V_\theta \right) + \dfrac{\partial V_\varphi}{\partial \varphi} \right] = 0. \label{conservation_masse} \end{equation}∂δρ∂t+1r2∂∂r(r2ρ0Vr)+ρ0rsinθ∂∂θsinθVθ+∂Vϕ∂ϕ=0.The thermal forcing (J) appears on the right-hand side of the linearized heat transport equation (see CL70, Gerkema & Zimmerman 2008) given by (14)\begin{equation} \frac{1}{\Gamma_1 p_0} \dfrac{\partial \delta p}{\partial t} - \frac{1}{\rho_0} \dfrac{\partial \delta \rho}{\delta t} + \frac{N^2}{g} V_r = \kappa \frac{\rho_0}{p_0} \left[ J - J_{\rm rad} \right], \label{transport_chaleur_1} \end{equation}1Γ1p0∂δp∂t−1ρ0∂δρδt+N2gVr=κρ0p0J−Jrad,where \hbox{$ \kappa = \left( \Gamma_1 - 1 \right)/\Gamma_1 $}κ=Γ1(−1)/Γ1 and Jrad is the power per mass unit radiated by the atmosphere, supposed to behave as a grey body. We consider that Jrad∝δT. This hypothesis is known as “Newtonian cooling” and was used by Lindzen & McKenzie (1967) to introduce radiation analytically in the classical theory of atmospheric tides (see also Dickinson & Geller 1968). Physically, it corresponds to the case of an optically thin atmosphere in which the flux emitted by a layer propagates upwards or downwards without being absorbed by the other layers. In optically thick atmospheres, such as on Venus (Lacis 1975), this physical condition is not verified. Indeed, because of a stronger absorption, the power emitted by a layer is almost totally transmitted to the neighbourhood. Therefore, this significant thermal coupling within the atmospheric shell should ideally be taken into account in a rigorous way, which would lead to great mathematical difficulties (e.g. complex radiative transfers, Laplacian operators) in our analytical approach. However, recent numerical simulations of thermal tides in optically thick atmospheres by Leconte et al. (2015) show behaviour of the flow that is in good agreement with a model that uses radiative cooling. Therefore, in this work we assumeNewtonian cooling as a first model of the action of radiation on atmospheric tides. Newtonian cooling brings a new characteristic frequency, denoted σ0, which we call radiative frequency and which depends on the thermal capacity of the atmosphere. The radiative power per unit mass is thus written (15)\begin{equation} J_{\rm rad} = \frac{p_0 \sigma_0}{\kappa \rho_0 T_0} \delta T. \label{phirad} \end{equation}Jrad=p0σ0κρ0T0δT.Like the basic fields p0, ρ0, and T0, the radiative frequency varies with r and defines the transition between the dynamical regime, where the radiative losses can be ignored, and the radiative regime, where they predominate in the heat transport equation. Assuming that the radiative emission of the gas is proportional to the local molar concentration C0 = ρ0/M, it is possible to express Jrad and σ0 as functions of the physical parameters of the fluid (Appendix D), (16)\begin{equation} J_{\rm rad} = \frac{8 \epsilon_a}{M} \mathscr{S} T_0^3 \delta T \label{phirad2} \end{equation}Jrad=8ϵaMST03δTand (17)\begin{equation} \sigma_0 \left( r \right) = \frac{8 \kappa \epsilon_a \mathscr{S} }{\mathscr{R}_{\rm GP} } T_0^3, \label{sigma0} \end{equation}σ0(r)=8κϵaSRGPT03,the parameter ϵa being an effective molar emissivity coefficient of the gas and S= 5.670373 × 10-8 W m-2 K-4 the Stefan-Boltzmann constant (Mohr et al. 2012). The substitution of Eq. (15) in Eq. (14) yields (18)\begin{equation} \frac{1}{\Gamma_1 P_0} \dfrac{\partial \delta p}{\partial t} - \frac{1}{\rho_0} \dfrac{\partial \delta \rho}{\delta t} + \frac{N^2}{g} V_r = \kappa \frac{\rho_0}{p_0} J - \sigma_0 \frac{\delta T}{T_0}\cdot \label{transport_chaleur_2} \end{equation}1Γ1P0∂δp∂t−1ρ0∂δρδt+N2gVr=κρ0p0J−σ0δTT0·Finally, the system is closed by the perfect gas law (19)\begin{equation} \frac{\delta p}{p_0} = \frac{\delta T}{T_0} + \frac{\delta \rho}{\rho_0}\cdot \label{GPlaw} \end{equation}δpp0=δTT0+δρρ0·Substituting Eq. (19) in Eq. (18), we eliminate the unknown δT, and obtain (20)\begin{equation} \frac{1}{\Gamma_1 p_0} \left( \dfrac{\partial \delta p}{\partial t} \! +\! \Gamma_1 \sigma_0 \delta p \right) + \frac{N^2}{g} \dfrac{\partial \xi_r}{\partial t} = \frac{ \kappa \rho_0}{p_0} J + \frac{1}{\rho_0} \left( \dfrac{\partial \delta \rho}{\partial t}\! +\! \sigma_0 \delta \rho \right). \label{transport_chaleur_3} \end{equation}1Γ1p0∂δp∂t+Γ1σ0δp+N2g∂ξr∂t=κρ0p0J+1ρ0∂δρ∂t+σ0δρ.Because of the rotating motion of the perturber in the equatorial frame (RE;T), a tidal perturbation is supposed to be periodic in time (t) and longitude (ϕ). So, any perturbed quantity f of our model can be expanded in Fourier series of t and ϕ(21)\begin{equation} f = \sum_{m,\sigma} f^{m,\sigma} \left( \theta , r \right) e^{i \left( \sigma t + m \varphi \right)}, \label{perturbation} \end{equation}f=∑m,σfm,σ(θ,r)eiσt+mϕ,the parameter σ being the tidal frequency of a Fourier component and m its longitudinal degree1. We also introduce the spin parameter (22)\begin{equation} \nu \left( \sigma \right) = \frac{2 \Omega}{\sigma}, \label{nu} \end{equation}ν(σ)=2Ωσ,which defines the possible regimes of tidal gravito-inertial waves: | [
"Leconte et al. (2015)"
] | [
"However, recent numerical simulations of thermal tides in optically thick atmospheres by",
"show behaviour of the flow that is in good agreement with a model that uses radiative cooling.",
"Therefore, in this work we assumeNewtonian cooling as a first model of the action of radiation on atmospheric tides."
] | [
"Similarities",
"Similarities",
"Uses"
] | [
[
2251,
2272
]
] | [
[
2162,
2250
],
[
2273,
2367
],
[
2368,
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]
] |
2019AandA...629A..63J__XIX_2015_Instance_1 | Our knowledge of magnetic fields in molecular clouds is based mainly on light polarisation, the optical and near-infrared (NIR) observations of background stars (Goodman et al. 1995; Whittet et al. 2001; Pereyra & Magalhães 2004; Alves et al. 2008; Chapman et al. 2011; Cox et al. 2016; Neha et al. 2018; Kandori et al. 2018), and the polarised dust emission at far-infrared (FIR), sub-millimetre, and radio wavelengths (Ward-Thompson et al. 2000; Koch et al. 2014; Matthews et al. 2014; Fissel et al. 2016; Pattle et al. 2017). The Planck survey provides a large amount of data for polarisation studies at cloud scales (Planck Collaboration Int. XX 2015; Planck Collaboration Int. XIX 2015; Planck Collaboration Int. XXXIII 2016). The Planck data have been used especially to study the polarisation fraction and the correlations in the relative morphology of column density and magnetic field structures (Planck Collaboration Int. XX 2015; Planck Collaboration Int. XXXIII 2016; Malinen et al. 2016; Soler et al. 2016; Alina et al. 2019). Particularly, the drop of polarisation fraction p towards PGCC clumps has been observed with high significance in the Planck 353 GHz data (Alina et al. 2019; Ristorcelli et al, in prep.). The variations ofp are interesting because they are related to the configuration of the magnetic fields in clumps and cores during the star formation process. However, p is also affected by variations in the efficiency of the grain alignment, as predicted, for example, by the theory of radiative torque alignment (RAT; Lazarian et al. 1997; Cho & Lazarian 2005; Hoang & Lazarian 2014) and demonstrated by numerical simulations (Pelkonen et al. 2009; Brauer et al. 2016; Reissl et al. 2018). These suggest that high optical depths and more frequent gascollisions should significantly reduce the grain alignment and thus the polarised emission observable from within the clumps. ThePGCC provides a statistically significant sample to study these questions observationally, although the Planck resolution limits the investigations to structures that are typically much larger than an individual cloud core. However, polarisation of selected PGCCs has already been studied at higher resolution with the SCUBA-2 POL-2 instrument at JCMT (Liu et al. 2018b,c; Juvela et al. 2018c), and many more will be covered by ongoing surveys (Ward-Thompson et al. 2017). | [
"Planck Collaboration Int. XIX 2015"
] | [
"The Planck survey provides a large amount of data for polarisation studies at cloud scales"
] | [
"Background"
] | [
[
656,
690
]
] | [
[
529,
619
]
] |
2017AandA...604A.118T__Pilkington_et_al._(2012)_Instance_1 | A large effort has been invested in understanding the chemical patterns of galaxies using analytical and numerical chemical modelling (e.g. Brook et al. 2007; Calura et al. 2012; Mollá et al. 2015). In particular, hydrodynamical simulations provide the chemical enrichment of baryons as galaxies are assembled in a cosmological framework, opening the possibility of understanding the interplay of different physical processes in the non-linear regime of evolution (e.g. Mosconi et al. 2001; Lia et al. 2002; Wiersma et al. 2009). Pilkington et al. (2012) carried out a comparison of the metallicity gradients in the ISM (traced by young SPs) obtained by different numerical and analytical models. Gibson et al. (2013) analysed different models of SN feedback schemes reporting different evolution for the gas-phase metallicity gradients. No evolution was reported when an enhanced SN model was used. Tissera et al. (2016b) studied the gas-phase metallicity gradients in discs and the specific star formation of the galaxies. For gas-phase metallicities, the simulated galaxies showed a correlation with stellar mass, which was erased when the metallicity gradients were renormalised by the effective radius, reproducing observations by Ho et al. (2015, and references there in). They also found indications of a correlation between the abundance slopes and the specific star formation rate (sSFR) in agreement with observational findings (Stott et al. 2014). As a function of redshift, the metallicity gradients of the gas-phase disc components were found to be more negative at higher redshift, principally for lower stellar-mass galaxies. The fraction of galaxies with positive metallicity gradients increased with increasing redshift and were found to be associated to mergers and interactions. The trends found for the gas-phase metallicity gradients by Tissera et al. (2016b) are relevant to the discussion of this paper because we are using the same set of simulated galaxies. | [
"Pilkington et al. (2012)"
] | [
"carried out a comparison of the metallicity gradients in the ISM (traced by young SPs) obtained by different numerical and analytical models"
] | [
"Background"
] | [
[
530,
554
]
] | [
[
555,
695
]
] |
2017AandA...600A..67P__Nakariakov_et_al._2003_Instance_1 | Many theoretical models have been proposed to explain the generation of QPPs. The most elaborated model of QPPs considers MHD oscillations, which affect almost all aspects of the flare emission generation. Indeed, QPPs are involved in triggering the magnetic reconnection, modulating the reconnection rate, accelerating and transporting non-thermal electrons, and changing the physical conditions in emitters (Nakariakov & Melnikov 2009). Other models are based on a sandpile system with self-organized critical states (Lu & Hamilton 1991; Baiesi et al. 2008), the quasi-stabilized system of non-linear plasmas governed by an oscillatory phase of wave-wave or wave-particle interactions (Aschwanden 1987). Different MHD oscillation modes have been identified to be responsible for QPPs in a single flaring loop (Nakariakov et al. 2003; Melnikov et al. 2005; Warmuth et al. 2005; Inglis et al. 2008; Kupriyanova et al. 2010, 2013; Kim et al. 2012). Kolotkov et al. (2015) studied the QPPs of the microwave emission generated in a X3.2-class solar flare. They found three well-defined intrinsic modes with mean periods of 15, 45, and 100s. These authors proposed that the 100 s and 15s modes are likely to be associated with fundamental kink and sausage modes of the flaring loop, respectively. The 100 s oscillations could also be caused by the fundamental longitudinal mode. The 45 s mode, on the other hand, could be the second standing harmonic of the kink mode. Inglis & Nakariakov (2009) reported a multi-periodic oscillatory event with three distinct periods, namely 28s, 18s, and 12s. They argued that the cause of this multi-periodic event is likely to be a kink mode that periodically triggers magnetic reconnection. Similar QPPs could be generated by different mechanisms. To discover, understand, and distinguish these mechanisms correctly, detailed and multi-wavelength observations are required. Within the framework of the EU FP7-project SOLSPANET1, we are developing a solar and space-weather knowledge base that will allow such extensive and detailed studies. | [
"Nakariakov et al. 2003"
] | [
"Different MHD oscillation modes have been identified to be responsible for QPPs in a single flaring loop"
] | [
"Background"
] | [
[
812,
834
]
] | [
[
706,
810
]
] |
2017MNRAS.472..205S__Becerra_et_al._2015_Instance_1 | Throughout the initial collapse the halo structure is well approximated by ellipsoidal collapse models. We therefore explore radial profiles of various physical quantities to extract information about the galactic environment. The density is illustrated in Fig. 2, which is reasonably approximated by a broken power law over the range r ∈ (10−3, 103) pc. The break radius is due to the choice of the density resolution threshold, or equivalently, the limited resolution implies the pre-formation profile corresponds to roughly a dynamical time, as evaluated at the maximum resolved density, of ∼10 kyr prior to the formation of the protostar. If the evolution proceeds under self-similar, isothermal collapse then the break in the profile will shift to smaller scales, eventually reaching the radius of the protostar (Abel, Bryan & Norman 2002; Becerra et al. 2015). We note that secondary infall and accretion results in a density distribution that is steeper than the ρ ∝ r−2 profile produced by violent relaxation. We find a power-law scaling of ρ ≈ r− 7/3 in good agreement with Bertschinger (1985) where ρ ∝ r−9/4 and Wise, Turk & Abel (2008) where ρ ∝ r−12/5, except in the core where the slope flattens off to ρ ∝ r−0.4 around r ≈ 0.3 pc. During the initial collapse and formation, the gas remains neutral with only a small abundance of free protons. Specifically, the ionization fraction, $x_{\rm {H \small {II}}} \equiv n_{\rm {H \small {II}}} / n_{\rm H}$, is typically of order 10−5 to 10−3 depending on the density, such that $n_{\rm {H \small {II}}} \sim 0.1\,{\rm cm}^{-3}\,(r/10\,{\rm pc})^{-5/3}$. As expected for direct collapse, the central region has access to at least 105 M⊙ of gas within a radius of ≈1.3 pc. More broadly, the enclosed baryonic mass is $M_{<r} \approx 4 \pi \int _0^r \rho (r) r^2 {\rm d}r$ (for 1D profiles), calculated explicitly as Mr ≡ ∑rρiVi where the sum is over all Voronoi cells within a radius r, and the subscript denotes cell quantities for density ρi and volume Vi. For convenience and completeness, in Table 1 we provide radial scaling relations for several relevant quantities, calculated as mass-weighted averages within shell volumes, i.e.
(1)
\begin{eqnarray}
\langle q \rangle _{\rm shell} \equiv \frac{\int q \rho \, {\rm d}V}{\int \rho \, {\rm d}V} \approx \frac{\sum q_i \rho _i V_i}{\sum \rho _i V_i} \,,
\end{eqnarray}
where the discretized version sums over all cells within each shell. Similarly, we obtain mass-weighted line of sight averages with
(2)
\begin{eqnarray}
\langle q \rangle _{\rm LOS} \equiv \frac{\int q \rho \, {\rm d}\ell }{\int \rho \, {\rm d}\ell } \approx \frac{\sum q_i \rho _i \Delta \ell _i}{\sum \rho _i \Delta \ell _i} \,,
\end{eqnarray}
where the integral is along radial rays within each shell and the summation is the discretized version calculated by ray tracing. | [
"Becerra et al. 2015"
] | [
"If the evolution proceeds under self-similar, isothermal collapse then the break in the profile will shift to smaller scales, eventually reaching the radius of the protostar"
] | [
"Uses"
] | [
[
845,
864
]
] | [
[
643,
816
]
] |
2021ApJ...910..120K__Schlafly_et_al._2018_Instance_1 | Many of these objects have been confirmed as DNe through an identification spectrum or a measurement of the superhump period, but we find that 27 sources were not confirmed through any method. Quiescent multiband photometry of these remaining candidates can provide insights into the distance and ultimately constrain the luminosity of the transient. In the Galactic plane, a candidate that is relatively blue is likely close by and therefore will have a lower luminosity at peak brightness, suggesting a DN outburst. Conversely, a candidate that is brighter in redder filters is likely reddened by dust, implying a higher luminosity and a CN outburst. This strategy—identifying highly reddened quiescent counterparts—is only possible for candidates within a few degrees of the Galactic plane and that can be securely matched to multiband optical catalogs. As described in Section 2.4, we find quiescent counterparts in Pan-STARRS and also add in coverage of southerly declinations by using the DeCAPS catalog (Schlafly et al. 2018; cross-matching for both catalogs is as explained in Appendix A.3). We use the griz photometry to estimate reddening by fitting the observed spectral energy distributions of the CVs in question to dereddened SDSS CV colors from Kato et al. (2012) by varying the amount of reddening according to extinction laws (Cardelli et al. 1989; Mathis 1990). For each of our candidates, this results in a distribution of extinction values that are plugged into the three-dimensional all-sky extinction map stitched together in Bovy et al. (2016) to find a range of plausible distances. This strategy only worked for 19 of the candidates: those that we were able to cross-match and in fields close to the plane, where a large amount of dust can constrain the distance. We find that all 19 are consistent with the peak luminosity of a dwarf nova, and none are consistent with the peak luminosity of a classical nova. This analysis will also be useful to shed light on the nature of CV candidates that are discovered in the future, so it is made publicly available as an iPython notebook at https://github.com/amkawash/CV_colors_luminosity.
| [
"Schlafly et al. 2018"
] | [
"As described in Section 2.4, we find quiescent counterparts in Pan-STARRS and also add in coverage of southerly declinations by using the DeCAPS catalog (",
"; cross-matching for both catalogs is as explained in Appendix A.3)."
] | [
"Uses",
"Uses"
] | [
[
1011,
1031
]
] | [
[
857,
1011
],
[
1031,
1099
]
] |
2022AandA...666A..95H__Hartman_et_al._2022_Instance_1 | Scaling relations for the core radii rc, core densities δc, and core masses Mc as functions of the total halo mass M200 were fitted to the simulated halo populations, which largely agree with hydrostatic considerations of the halo cores where rc is nearly constant, as well as velocity dispersion tracing in the halo envelope,
v
c
2
≈
v
200
2
$ v^2_{\rm c} \approx v^2_{200} $
. However, these trends do not agree with those obtained by fitting the Burkert profile to nearby galaxies in the SPARC dataset and the classical Milky Way dSphs. This poses an issue for SIBEC-DM with Rc ≳ 1 kpc and a largely CDM-like matter power spectrum at late times (Harko 2011; Harko & Mocanu 2012; Velten & Wamba 2012; Freitas & Gonçalves 2013; Bettoni et al. 2014; de Freitas & Velten 2015; Hartman et al. 2022), as was used in our simulations, although these scenarios are not well-motivated. For SIBEC-DM given by the field Lagrangian in Eq. (1), the self-interaction is constrained to Rc 1 kpc, otherwise an early radiation-like period and a large comoving Jeans’ length washes out too much structure to be consistent with observations (Shapiro et al. 2021; Hartman et al. 2022). In fact, Shapiro et al. (2021) found by using constraints on FDM as a proxy for SIBEC-DM, and matching their transfer function cut-offs and HMFs, that the SIBEC-DM self-interaction should be as low as Rc ∼ 10 pc to not be in conflict with observations. We were unable to probe SIBEC-DM with initial conditions and parameters consistent with the Lagrangian in Eq. (1), since the large gap between the halo cores and the cut-off scale requires both a large simulation box and very high spatial resolution. It should be noted that our SIBEC-DM-only simulations do provide a better agreement with the slopes in observed scaling relations than FDM. In particular, FDM simulations generally find
M
c
∼
M
200
γ
$ M_{\mathrm{c}}\sim M_{200}^{\gamma} $
with 1/3 γ 0.6, while we find γ ≈ 0.75, which is closer to the observed γ ≈ 1.1. Additionally, FDM halos have core radii that generally decrease with the halo mass, while we find a slightly increasing trend due to larger halos experiencing more thermal heating, although not as steep as in the SPARC dataset and the Milky Way dSphs. | [
"Hartman et al. 2022"
] | [
"However, these trends do not agree with those obtained by fitting the Burkert profile to nearby galaxies in the SPARC dataset and the classical Milky Way dSphs. This poses an issue for SIBEC-DM with Rc ≳ 1 kpc and a largely CDM-like matter power spectrum at late times",
"as was used in our simulations, although these scenarios are not well-motivated."
] | [
"Compare/Contrast",
"Compare/Contrast"
] | [
[
789,
808
]
] | [
[
392,
660
],
[
811,
891
]
] |
2021ApJ...919..140S__Bartos_et_al._2017_Instance_1 | Resonant dynamical friction may have applications beyond the relaxation of IMBHs examined in this paper. It may affect all objects in stellar clusters much more massive than the individual constituents of the disk, if present, including massive stars, stellar mass black holes (BHs), or the center of mass of massive binaries. Furthermore, it is also expected to operate in any type of disk with a high number of particles, including active galactic nucleus (AGN) accretion disks. Previously, it has been argued that stars and BHs crossing the disk on low-inclination orbits get captured by Chandrasekhar dynamical friction into the disk (Bartos et al. 2017; Panamarev et al. 2018; Tagawa et al. 2020). An interesting implication is that, if BHs settle into the disk, they interact dynamically and form BH–BH binaries efficiently, and frequent dynamical interactions and gas effects drive the BHs to merger, producing gravitational waves (GWs) detectable by LIGO, VIRGO, and KAGRA (McKernan et al. 2014, 2018; Bartos et al. 2017; Leigh et al. 2018; Yang et al. 2019; Tagawa et al. 2020, 2021; Samsing et al. 2020). Mergers are also facilitated by Lidov–Kozai oscillations in anisotropic systems (Heisler & Tremaine 1986; Petrovich & Antonini 2017; Hamilton & Rafikov 2019). The results in this paper show that resonant dynamical friction may accelerate the capture of objects in the accretion disks by a factor proportional to the SMBH mass over the local disk mass for large orbital inclinations. Pressure and viscosity in a gaseous disk do not inhibit the orbit-averaged torque from the IMBH, which leads to realignment and the warping of the disk (Bregman & Alexander 2012). Thus, RDF may efficiently catalyze the alignment of the orbital planes of BHs even in low-luminosity AGN or Seyfert galaxies with relatively small disk masses, which may not be possible for Chandrasekhar dynamical friction. In fact, this mechanism extends the scope of the “AGN merger channel” for GW source populations even beyond low-luminosity AGN and Seyfert galaxies, as it may organize BHs into disks also in nonactive galaxies with nuclear stellar disks. | [
"Bartos et al. 2017"
] | [
"Previously, it has been argued that stars and BHs crossing the disk on low-inclination orbits get captured by Chandrasekhar dynamical friction into the disk"
] | [
"Background"
] | [
[
639,
657
]
] | [
[
481,
637
]
] |
2022MNRAS.516.4833J__Munday_et_al._2020_Instance_1 | Bond & Ciardullo (2018) identify a periodicity of 2.06 d in their data, with a similar period clearly evident in the newly acquired data. However, no single period and time of first minima could be found that fits all the data (perhaps not unexpected given that the variability is clearly not constant, see Section 2.3 for further discussion). In order to better constrain the period, as well as the changes between observing epochs, we focus on the periodicitiy of all the data taken between 2011 and 2015 (shown in the lower left panel of Fig. 1). Given the nature of the variability, we measure the period via the reduced χ2 of a sinusoidal fit as a function of frequency (ideally suited to sinusoidal variability, e.g. Horne, Wade & Szkody 1986; Munday et al. 2020). The resulting periodogram is shown in Fig. 2. Two strong minima in the reduced χ2 are found, the strongest at 2.061 ± 0.005 d (consistent with the period of Bond & Ciardullo 2018) and a second slightly shallower at 1.938 ± 0.005 d. The data from 2010, combining that of Bond & Ciardullo (2018) and our own from SAAO, phases well on the first period but not the second, lower period, likely indicating that this is an alias. As such, we conclude that the rotation period is indeed ≈2.06 d and that there is no strong evidence for a change in period before and after the phase of negligible variability in early 2011. There is, however, a clear shift in phase between the 2010 data and the later data used to derive the period (see Fig. 2). There is no statistically significant evidence for a shift between the 2011–2015 data and the later data from 2022, although the lack of data in the intervening seven years as well as the uncertainty on the period mean that we cannot exclude a phase shift between these two data sets. The 2022 data does, however, appear to have a larger photometric amplitude, more consistent with the 2010 data. None the less, if the variability did remain constant throughout this time, we can refine the period to P = 2.060561 ± 0.000002 d. | [
"Munday et al. 2020"
] | [
"Given the nature of the variability, we measure the period via the reduced χ2 of a sinusoidal fit as a function of frequency (ideally suited to sinusoidal variability, e.g."
] | [
"Uses"
] | [
[
750,
768
]
] | [
[
550,
722
]
] |
2022MNRAS.516.3175B__Law_et_al._2015_Instance_1 | We use the final version of the MaNGA data (Abdurro’uf et al. 2022). MaNGA is the survey project in SDSS-IV (Sloan Digital Sky Survey) using IFU observations of galaxies to produce spatially resolved spectroscopic data (Gunn et al. 2006; Bundy et al. 2015; Drory et al. 2015; Blanton et al. 2017; Aguado et al. 2019; Abdurro’uf et al. 2022). MaNGA observed approximately 10 000 galaxies, selected as an unbiased sample in terms of stellar mass (${\it M}_{\star } \gt 10^{9}\, {\rm M}_{\odot }$) and environments (Law et al. 2015; Yan et al. 2016a; Wake et al. 2017). The MaNGA targets were selected as two main subgroups and two minor subgroups. Among the main subgroups, the primary sample of about 5000 galaxies was selected to observe the central part out to $\rm 1.5{\it R}_{eff}$. The secondary sample of the main subgroups includes about 3300 galaxies, observed by the IFU bundle out to $\rm 2.5{\it R}_{eff}$. These samples were selected without bias and covers a wide range in galaxy masses. The first of the two minor subgroups is a ‘colour-enhanced sample’ of about 1700 galaxies. It is selected to include blue massive galaxies and green valley galaxies that are important to study the quenching process. These targets are observed with an IFU coverage of $\rm 1.5{\it R}_{eff}$. A second minor sample includes about 1000 ancillary targets, selected for various observations using the unique capability of the MaNGA instrument (Yan et al. 2016a). The IFU bundles of the MaNGA consist of 19–127 fibres with hexagonal shape covering 12–$\rm 32~arcsec$ in diameter on sky. The spatial resolution of MaNGA is $\rm 2.5~arcsec$, which corresponds to 1.3–$\rm 4.5~kpc$ for the primary sample and 2.2–$\rm 5.1~kpc$ for the secondary sample. The BOSS spectrographs used by MaNGA provide spectra from 3600 to 10 300 Å with a spectral resolution of about 2100–6000 Å (Smee et al. 2013; Yan et al. 2016b). The observations were conducted to reach an signal-to-noise ratio (S/N) in the stellar continuum at $\rm 1{\it R}_{eff}$ of $\rm 14$–$\rm 35$ per spatial sample, which required about 3 h net integration for each target. | [
"Law et al. 2015"
] | [
"MaNGA observed approximately 10 000 galaxies, selected as an unbiased sample in terms of stellar mass (${\\it M}_{\\star } \\gt 10^{9}\\, {\\rm M}_{\\odot }$) and environments"
] | [
"Background"
] | [
[
513,
528
]
] | [
[
342,
511
]
] |
2020MNRAS.492.5247S__Sasaki_et_al._2018_Instance_1 | A lognormal mass function:
(7)$$\begin{eqnarray}
\psi (M;\mu ,\sigma)=\frac{1}{M\sqrt{2\pi \sigma ^2}}\exp {\left(- \frac{\ln ^2(M/\mu)}{2\sigma ^2}\right)},
\end{eqnarray}$$where μ > 0 and σ > 0. The mean PBH mass in the assumption of a lognormal mass function is $\bar{M}=\mu \exp \left(-\sigma ^2/2\right)$. Such mass function is a good approximation for a large class of PBH formation scenarios, e.g. axion-curvaton, running-mass, and single field double inflation (Green 2016; Kannike et al. 2017). The (μ, σ) pairs allowed in the window relevant for the operational gravitational wave detectors [$\mathcal {O}(1\operatorname{-}100)\, {\rm M}_\odot {}$; Abbott et al. 2019] are mainly constrained by (i) the results from searches for microlensing events on stars in our Galactic neighbourhood and (ii) the effect PBH gas accretion would have on the CMB temperature and ionization history (Carr et al. 2017; Sasaki et al. 2018). Together, the allowed points roughly constitute a sub-plane described as (see fig. 3 in Carr et al. 2017):
(8)$$\begin{eqnarray}
(\mu ,\sigma)\in [25\, {\rm M}_\odot ,100\, {\rm M}_\odot ]\times [0.0,1.0].
\end{eqnarray}$$It is worth mentioning that these points are ruled out completely if one further takes the following constraints into account (Carr et al. 2017): (iii) the survival of the stellar cluster in Eridanus II and of the entire stellar populations in UFDGs (Brandt 2016; Green 2016; Koushiappas & Loeb 2017; Zhu et al. 2018) and (iv) the survival of wide binaries in the Milky Way (Monroy-Rodríguez & Allen 2014). These constraints are somewhat less restrictive, as they rely on further astrophysical assumptions (Carr et al. 2017). For instance, the stellar cluster in Eridanus II could have only recently spiralled down into the centre of the galaxy, where dynamical heating by PBHs becomes effective (Brandt 2016). Additionally, wide binaries are in principle hard to detect, yielding some uncertainty in identifying them and consequently in drawing any conclusion on the PBH abundance (Sasaki et al. 2018). Moreover, we emphasize that, most recently, even previous microlensing constraints were called into question as spatial PBH clustering (García-Bellido & Clesse 2018) and updated galactic rotation curves (Hawkins 2015) tend to relax them. | [
"Sasaki et al. 2018"
] | [
"The (μ, σ) pairs allowed in the window relevant for the operational gravitational wave detectors",
"are mainly constrained by (i) the results from searches for microlensing events on stars in our Galactic neighbourhood and (ii) the effect PBH gas accretion would have on the CMB temperature and ionization history"
] | [
"Uses",
"Uses"
] | [
[
914,
932
]
] | [
[
506,
602
],
[
681,
894
]
] |
2021MNRAS.507.5882S__Mackereth_et_al._2018_Instance_3 | Cosmological hydro dynamical N-body simulations offer another possibility to investigate the origin of the bimodality in the ([Fe/H], [α/Fe]) plane. Earlier simulations, e.g. full N-body simulations by Loebman et al. (2011), Brook et al. (2012) or hybrid simulations in which a semi-analytic chemical evolution was added on top of a cosmological simulation (Minchev, Chiappini & Martig 2013, 2014), were able to show that the thin and thick discs lie along different tracks in the ([Fe/H], [α/Fe]) plane, with the thick disc being old metal poor and rich in [α/Fe] and the thin disc being young, metal-rich and poor in [α/Fe]. They also showed that migration was important to generate the two discs. However, a clear bimodality in the ([Fe/H], [α/Fe]) plane was not seen. In the past few years good progress has been made to improve the spatial resolution as well as the chemical enrichment prescriptions. The bimodality has now been observed in some simulations (Grand et al. 2018; Mackereth et al. 2018; Clarke et al. 2019), and some of the simulations, in addition to the bimodality, also reproduce the basic trends of the ([Fe/H], [α/Fe]) distribution with radius R (Buck 2020; Vincenzo & Kobayashi 2020). Unlike analytical models, such simulations cannot be fine tuned to reproduce the Milky Way data, hence, the focus of these simulations is to qualitatively reproduce the abundance trends seen in the Milky Way, to understand how frequently do we get the bimodality and what is the mechanism for it. However, there is a lack of consensus between the different studies. Clarke et al. (2019) and Buck (2020) suggest that bimodality should be common in disc galaxies, whereas Mackereth et al. (2018) suggest that it is rare. Each simulation suggests slightly different mechanisms for the existence of the bimodality. Clarke et al. (2019) attribute bimodality to vigorous star formation in clumps at high redshift. Grand et al. (2018) suggest two distinct pathways, a centralized starbust pathway induced by mergers and a shrinking gas disc pathway. Buck (2020) suggest that after the formation of the high-[α/Fe] sequence a gas-rich merger dilutes the metallicity of the ISM leading to the formation of the low-[α/Fe] sequence. Mackereth et al. (2018) attribute the bimodality to unusually rapid gas accretion at earlier times, which is also characterized by a short time-scale to convert gas to stars. While some simulations clearly identify migration as key process to shape the sequences, others do not. In spite of the differences, it seems that some of the simulations (e.g. Mackereth et al. 2018; Buck 2020; Vincenzo & Kobayashi 2020) are not inconsistent with the Schönrich & Binney (2009a) paradigm. | [
"Mackereth et al. (2018)"
] | [
"attribute the bimodality to unusually rapid gas accretion at earlier times, which is also characterized by a short time-scale to convert gas to stars."
] | [
"Compare/Contrast"
] | [
[
2232,
2255
]
] | [
[
2256,
2406
]
] |
2021AandA...648A.109G__Talon_&_Charbonnel_2005_Instance_1 | The transport of angular momentum (AM) and chemical elements in stars strongly affects their evolution, from pre-main sequence (PMS) to evolved stages. These processes are particularly crucial in the stellar radiative zones, but their modelling remains an open question. In standard evolution models, these stably stratified zones are assumed to be motionless despite early works pointing out the lack of a static solution in uniformly rotating stars (Von Zeipel 1924) and a related large-scale meridional circulation driven by the centrifugal acceleration (Eddington 1925; Sweet 1950). A more complete formalism was then introduced by Zahn (1992) including a self-consistent meridional flow and models of the turbulent transport driven by hydrodynamical instabilities. The importance of additional processes such as internal waves (e.g., Talon & Charbonnel 2005) and magnetic fields (Spruit 2002) has also been investigated. Zahn’s formalism successfully explained a number of observed stellar properties, such as the nitrogen abundances at the surface of red supergiants or the observed blue-to-red supergiant ratio in the Small Magellanic Cloud (Maeder & Meynet 2001). The dynamics of internal gravity waves could possibly explain the flat rotation profile of the solar radiative zone (Talon et al. 2002 and Charbonnel & Talon 2005) inferred through helioseismology (Schou et al. 1998), as well as the lithium dip in solar-like stars (Charbonnel & Talon 2005). Despite these early encouraging results many stellar observations remain unexplained, especially the internal rotation rates revealed by asteroseismology in evolved stars and in intermediate-mass main sequence stars (see Aerts et al. 2019 for a review). The current theoretical understanding of the structure of the differential rotation in stellar radiative zones, crucial for the development of instabilities and thus for the related turbulent transport, is still largely incomplete. In particular, the assumption that the differential rotation is mostly radial, rather than radial and latitudinal, is at the base of Zahn’s formalism, but the validity of this assumption has never been thoroughly tested. In this paper we are particularly interested in the differential rotation and the large-scale meridional flows generated in periods of the stellar life when contraction, expansion, or both processes occur. This is the case for example for PMS stars which are gravitationally contracting before starting their core nuclear reactions, or for subgiant and giant stars which undergo contraction of their core and expansion of their envelope. Within these stars a strong redistribution of AM is expected to happen, producing differential rotation and thus potentially unstable shear flows. | [
"Talon & Charbonnel 2005"
] | [
"The importance of additional processes such as internal waves (e.g.,"
] | [
"Background"
] | [
[
839,
862
]
] | [
[
770,
838
]
] |
2020MNRAS.492.5247S__Sasaki_et_al._2018_Instance_2 | A lognormal mass function:
(7)$$\begin{eqnarray}
\psi (M;\mu ,\sigma)=\frac{1}{M\sqrt{2\pi \sigma ^2}}\exp {\left(- \frac{\ln ^2(M/\mu)}{2\sigma ^2}\right)},
\end{eqnarray}$$where μ > 0 and σ > 0. The mean PBH mass in the assumption of a lognormal mass function is $\bar{M}=\mu \exp \left(-\sigma ^2/2\right)$. Such mass function is a good approximation for a large class of PBH formation scenarios, e.g. axion-curvaton, running-mass, and single field double inflation (Green 2016; Kannike et al. 2017). The (μ, σ) pairs allowed in the window relevant for the operational gravitational wave detectors [$\mathcal {O}(1\operatorname{-}100)\, {\rm M}_\odot {}$; Abbott et al. 2019] are mainly constrained by (i) the results from searches for microlensing events on stars in our Galactic neighbourhood and (ii) the effect PBH gas accretion would have on the CMB temperature and ionization history (Carr et al. 2017; Sasaki et al. 2018). Together, the allowed points roughly constitute a sub-plane described as (see fig. 3 in Carr et al. 2017):
(8)$$\begin{eqnarray}
(\mu ,\sigma)\in [25\, {\rm M}_\odot ,100\, {\rm M}_\odot ]\times [0.0,1.0].
\end{eqnarray}$$It is worth mentioning that these points are ruled out completely if one further takes the following constraints into account (Carr et al. 2017): (iii) the survival of the stellar cluster in Eridanus II and of the entire stellar populations in UFDGs (Brandt 2016; Green 2016; Koushiappas & Loeb 2017; Zhu et al. 2018) and (iv) the survival of wide binaries in the Milky Way (Monroy-Rodríguez & Allen 2014). These constraints are somewhat less restrictive, as they rely on further astrophysical assumptions (Carr et al. 2017). For instance, the stellar cluster in Eridanus II could have only recently spiralled down into the centre of the galaxy, where dynamical heating by PBHs becomes effective (Brandt 2016). Additionally, wide binaries are in principle hard to detect, yielding some uncertainty in identifying them and consequently in drawing any conclusion on the PBH abundance (Sasaki et al. 2018). Moreover, we emphasize that, most recently, even previous microlensing constraints were called into question as spatial PBH clustering (García-Bellido & Clesse 2018) and updated galactic rotation curves (Hawkins 2015) tend to relax them. | [
"Sasaki et al. 2018"
] | [
"Additionally, wide binaries are in principle hard to detect, yielding some uncertainty in identifying them and consequently in drawing any conclusion on the PBH abundance"
] | [
"Uses"
] | [
[
2042,
2060
]
] | [
[
1870,
2040
]
] |
2019AandA...632A.129W__Feng_&_Wang_2015_Instance_2 | In this study, the 272 eV suprathermal electron pitch-angle distributions (PADs) measured by ACE are used. The electron PADs are obtained from the Solar Wind Electron Proton Alpha Monitor (SWEPAM) with angular and time resolutions of 9° and 64 s respectively (McComas et al. 1998). Here we examined 16 s average magnetic field, 64 s average plasma, 1 h average O7+/O6+ ratio, and mean Fe charge state ⟨Fe⟩ data from 1998 to 2008 measured by ACE and identified 272 ICMEs in total. The ICMEs were identified by the following process: (1) We take the events in previous ICME lists of Jian et al. (2006), Chi et al. (2016), and Richardson & Cane (2004)1 as candidate ICMEs. (2) Some lists also report short-duration ( 10 h) structures as ICMEs. As the origin of these smaller-scale ICMEs and flux ropes are still debated (Feng et al. 2007; Rouillard et al. 2011; Janvier et al. 2014; Feng & Wang 2015; Wang et al. 2019), we excluded them from this study. (3) The high Fe charge states (⟨Fe⟩ ≥ 12) and abnormally high O7+/O6+ ratio (≥1) are the result of flare-related heating in the corona (Lepri & Zurbuchen 2004; Reinard 2005), and therefore they are independently reliable ICME indicators (Feng & Wang 2015). If the candidate ICMEs have high Fe charge states and/or abnormally high O7+/O6+ ratio, they are identified as ICMEs. (4) If the candidate ICMEs have no high Fe charge states and abnormally high O7+/O6+ ratio, we look for the following five characteristics: declining speed (apparent expansion), increasing total magnetic magnitude and helium abundance (He/P > 0.06) (Richardson & Cane 2004), and decreasing proton temperatures and proton densities. If the candidate ICMEs have three or more of the above characteristics they are identified as ICMEs. Given that magnetic flux ropes are special field topologies characterized by bundles of helical magnetic-field lines collectively spiraling around a common axis, the essential observational properties of magnetic flux ropes should be enhanced magnetic field strength and smooth rotations (Feng et al. 2008, 2010), namely, measured enhanced magnetic field strength, the center-enhanced magnetic components, and bipolar curve magnetic components. Therefore, if an ICME was found to have enhanced magnetic field strength, both center-enhanced and bipolar field components, it was identified as MC. Among the 272 ICMEs, 101 (37.1%) events were identified as MCs. All 272 ICMEs are listed in Table A.1. The second and third columns show the start and end times, the fourth column gives the duration of the ICMEs, and the fifth column provides the types of ICMEs (MC or nonMC). | [
"Feng & Wang 2015"
] | [
"The high Fe charge states (⟨Fe⟩ ≥ 12) and abnormally high O7+/O6+ ratio (≥1) are the result of flare-related heating in the corona",
"and therefore they are independently reliable ICME indicators"
] | [
"Uses",
"Uses"
] | [
[
1189,
1205
]
] | [
[
955,
1085
],
[
1126,
1187
]
] |
2021ApJ...906...57S__Lee_et_al._2016_Instance_1 | Complementary to studies using the integrated emission and angular power spectrum of DM annihilation from a population of Galactic subhalos, in this paper we present a novel strategy using one-point photon statistics to search for the annihilation signature. Our technique takes advantage of the information in the entire population of sources, including both those that are resolved and those that are faint and unresolved. The concept of leveraging the one-point photon-count distribution to search for DM has previously been studied in Dodelson et al. (2009) and Feyereisen et al. (2015) in the context of emission from extragalactic sources and in Lee et al. (2009) and Koushiappas et al. (2010) with application to Galactic subhalos. We introduce a method to search for signatures of DM annihilation from a Galactic subhalo population using the non-Poissonian template fitting (NPTF) framework (Malyshev & Hogg 2011; Lee et al. 2015, 2016; Mishra-Sharma et al. 2017), which has previously been applied to characterize unresolved point sources in the inner Galaxy (Lee et al. 2016; Linden et al. 2016; Leane & Slatyer 2019, 2020a, 2020b; Chang et al. 2020; Buschmann et al. 2020) and at high latitudes (Zechlin et al. 2016; Lisanti et al. 2016; Zechlin et al. 2018). Using simulations, we show that the NPTF can constrain DM annihilation from a population of subhalos in the face of astrophysical background emission. We find that using photon statistics to look for collective emission from a subhalo population can be especially promising when a large number of individual subhalo candidates are identified in point-source catalogs. This establishes a method complementary to the established ones based on characterizing individual resolved point sources as subhalo candidates, as well as those based on using the measured 0-point (overall flux) and two-point (angular power spectrum) statistics to characterize a subhalo population. Moreover, note that our methodology is completely independent of assumptions about, e.g., the location of stellar overdensities, so we are less sensitive to certain uncertainties which can bias dwarf galaxy constraints such as those in modeling tracer populations. Thus, this framework provides an important comparison for the dwarf galaxy analyses as well. | [
"Lee et al.",
"2016",
"Lee et al. 2016"
] | [
"We introduce a method to search for signatures of DM annihilation from a Galactic subhalo population using the non-Poissonian template fitting (NPTF) framework",
"which has previously been applied to characterize unresolved point sources in the inner Galaxy"
] | [
"Uses",
"Motivation"
] | [
[
922,
932
],
[
939,
943
],
[
1069,
1084
]
] | [
[
739,
898
],
[
973,
1067
]
] |
2018ApJ...868..139W__Schlickeiser_&_Jenko_2010_Instance_2 | By radio continuum surveys of interstellar space and direct in situ measurements in the solar system, it is well established that for many scenarios the background magnetic fields are spatially varying. However, the above research about parallel and perpendicular diffusion only explored the uniform mean magnetic field. One can show that the spatially varying background magnetic fields lead to the adiabatic focusing effect of charged energetic particle transport and introduces correction to the particle diffusion coefficients (see, e.g., Roelof 1969; Earl 1976; Kunstmann 1979; Beeck & Wibberenz 1986; Bieber & Burger 1990; Kóta 2000; Schlickeiser & Shalchi 2008; Shalchi 2009b, 2011; Litvinenko 2012a, 2012b; Shalchi & Danos 2013; Wang & Qin 2016; Wang et al. 2017b). To explore the influence of adiabatic focusing on particle transport, the perturbation method is frequently used (see, e.g., Beeck & Wibberenz 1986; Bieber & Burger 1990; Schlickeiser & Shalchi 2008; Schlickeiser & Jenko 2010; Litvinenko & Schlickeiser 2013; He & Schlickeiser 2014). To use the perturbation method, since the anisotropic distribution function is an implicit function, by using the iteration method, one can find that the anisotropic distribution function becomes an infinite series of the spatial and temporal derivatives of the isotropic distribution function. Therefore, the governing equation of the isotropic distribution function derived from the Fokker–Planck equation contains infinite terms because of the infinite series of the anisotropic distribution function. By using the truncating method to neglect the higher-order derivative terms, the approximate correction formulas of parallel or perpendicular diffusion coefficients were obtained (see, e.g., Schlickeiser & Shalchi 2008; Schlickeiser & Jenko 2010; He & Schlickeiser 2014). However, the higher-order derivative terms probably also make the correction to the parallel and perpendicular diffusion much like the lower-order derivative ones do. The magnitude of the correction from higher-order derivative term might not necessarily be a higher-order small quantity than the magnitude of the lower-order derivative terms. Therefore, the correction obtained by the previous authors is likely to contain significant errors. In this paper, by considering the higher-order derivative terms, we derive the parallel and perpendicular diffusion coefficients and obtain the correction formulas coming from all order derivative terms by using the improved perturbation method (He & Schlickeiser 2014) and the iteration operation. And for the weak adiabatic focusing limit we evaluate the correction to the parallel diffusion coefficient and compare it with the correction obtained in the previous papers. | [
"Schlickeiser & Jenko 2010"
] | [
"By using the truncating method to neglect the higher-order derivative terms, the approximate correction formulas of parallel or perpendicular diffusion coefficients were obtained (see, e.g.,"
] | [
"Background"
] | [
[
1783,
1808
]
] | [
[
1563,
1753
]
] |
2019AandA...630A..37S__Behar_et_al._2017_Instance_2 | Solar wind velocity distribution moments are described in Behar et al. (2017). The ion density nsw is the moment of order 0, and the ion bulk velocity usw (a vector) appears in the moment of order 1, the flux density
$n_{\mathrm{sw}} \ \underline{\mathbf{u}_{\mathrm{sw}}}$
n
sw
u
sw
_
. The bulk speed can be defined as the norm of the bulk velocity, that is,
$u_{\mathrm{sw}} = |\underline{\vec{u}_{\mathrm{sw}}}$
u
sw
=|
u
sw
_
|. However, this bulk speed is representative of single-particle speeds as long as the velocity distribution function is compact (e.g., a Maxwellian distribution). Complex velocity distribution functions were observed by RPC-ICA within the atmosphere of 67P. For instance, partial ring distributions were frequently observed for solar wind protons at intermediate heliocentric distances, when the spacecraft approached the SWIC (Behar et al. 2017). To illustrate the effect of such distorted distributions, a perfect ring (or shell) distribution centered on the origin of the plasma reference frame can be imagined, in which all particles have the same speed of 400 km s−1. The norm of the bulk velocity in this case would be 0 km s−1, whereas the mean speed of the particles is 400 km s−1, which is the relevant speed for SWCX processes. This mean speed, noted Usw, of the particles is calculated by first summing the differential number flux over all angles, and then taking the statistical average (Behar 2018). Over the entire mission, the deceleration of the solar wind using the mean speed of the particles is much more limited than the deceleration shown by the norm of the bulk velocity (Behar et al. 2017): there is more kinetic energy in the solar wind than the bulk velocity vector would let us think. This is the main difference with the paradigm used at previously studied (and more active) comets (Behar et al. 2018b). These complex, nonthermal velocity distribution functions also prevent us from reducing the second-order moment (the stress tensor) to a single scalar value, which, for a Maxwellian distribution, could be identified with a plasma temperature. In the context of 67P and for an important part of the cometary orbit around the Sun, the temperature of the solar wind proton has no formal definition. | [
"Behar et al. 2017"
] | [
"For instance, partial ring distributions were frequently observed for solar wind protons at intermediate heliocentric distances, when the spacecraft approached the SWIC"
] | [
"Background"
] | [
[
892,
909
]
] | [
[
722,
890
]
] |
2020ApJ...895...82V__Fryer_et_al._2018_Instance_2 | The shock is then revived by adding an energy injection following the parameterized method of Fryer et al. (2018). In this model, roughly
was deposited into the inner
in the first
. Some of this energy is lost through neutrino emission and the total explosion energy at late times for this model is
. This explosion is then mapped into our three-dimensional calculations, using one million SPH particles. The mapping took place when the supernova shock had moved out of the iron core and propagated into the Si–S rich shell at
. We note that our 1D methods employed for modeling the collapse, core bounce, and initial explosion do not capture the full physics of the central engine (for a discussion, see Fryer et al. 2018), and this is a source of uncertainty in our yield calculations. The details of the engine change the shock trajectories, and neutrino chemistry can change Ye values (Saez et al. 2018; Fujimoto & Nagakura 2019). The nature of the shock affects mostly the yields after the shock falls below NSE (before it falls out of NSE, the yields are set by the equilibrium values, not the time-dependent evolution). Our model captures one instance of the range of asymmetric trajectories, and it should be noted that no model at this time is sufficiently accurate to dictate exactly the properties of the asymmetries (Janka et al. 2016). In addition, any model that does not include convection-driven asymmetries from the progenitor star cannot properly capture the asymmetries (Arnett et al. 2015). The 3D explosion model used here also displays stochastic asymmetries, implying that any manner of convective asymmetry could generate similar results. If this behavior is universal, it could have important implications. These points taken together indicate that nucleosynthetic patterns arising from convection-like behavior are robust, regardless of the driver. As discussed below, this increases the utility of NSE nucleosynthesis, particularly of
and
, as diagnostics of the conditions in the progenitor star. | [
"Fryer et al. 2018"
] | [
"We note that our 1D methods employed for modeling the collapse, core bounce, and initial explosion do not capture the full physics of the central engine (for a discussion, see",
"and this is a source of uncertainty in our yield calculations."
] | [
"Compare/Contrast",
"Compare/Contrast"
] | [
[
737,
754
]
] | [
[
561,
736
],
[
757,
819
]
] |
2019AandA...627A.130D__Broadhurst_et_al._2019_Instance_1 | Gravitational-wave astronomy has recently become a reality with the first detection of gravitational waves (GW hereafter) by the Laser Interferometer Gravitational-Wave Observatory (LIGO) and Virgo ground-based interferemeters. To date, eleven events have been reported by the LIGO and Virgo detectors (Abbott 2018), and this number will quickly increase to tens of events in the coming years. Some of these events may correspond to gravitationally lensed events with magnification factors ranging from a few tens to a few hundreds (Dai et al. 2017; Ng et al. 2018; Li et al. 2018a; Smith et al. 2018a,b; Broadhurst et al. 2019). Recent works have studied lensing effects in the existing LIGO/Virgo O1 and O2 events (Hannuksela et al. 2019; Broadhurst et al. 2019), while Smith et al. (2018c) searched for candidate galaxy cluster lenses for the GW170814 event. The most likely lenses for such events would be massive galaxies or galaxy clusters (Ng et al. 2018; Dai et al. 2017; Smith et al. 2018b; Broadhurst et al. 2019). On the other extreme of the lens mass regime, compact objects with masses of a few hundreds to a few tens M⊙ can also act as lenses (Lai et al. 2018). In this case, the geometric optics limit is not valid since the Schwarszchild radius of the lens is comparable to the wavelength of the wave. For these relatively low masses, the lensing effect has a modest impact on the average magnification, but it can introduce a frequency dependence on the magnification (see for instance, Jung & Shin 2019; Lai et al. 2018). An even smaller mass regime was considered in Christian et al. (2018) where the authors find that lenses with a mass as low as 30 M⊙ could be detected with current experiments. They also consider future, higher-sensitivity experiments and show how they can push the limit to even smaller masses of order 1 M⊙. These conclusions are, however, obtained assuming isolated microlenses and without accounting for the effect of the macromodel, or other nearby microlenses. In the small mass regime, microlenses such as neutron stars have been also considered as scattering sources of GWs, and it is found that a GW can be focussed at a focal point near the neutron star surface (Halder et al. 2019; Stratton & Dolan 2019). | [
"Broadhurst et al. 2019"
] | [
"Some of these events may correspond to gravitationally lensed events with magnification factors ranging from a few tens to a few hundreds"
] | [
"Background"
] | [
[
605,
627
]
] | [
[
394,
531
]
] |
2019MNRAS.484.1946G__Biesiadzinski_et_al._2012_Instance_1 | Secondly, we focus on galaxies to discuss some remaining solutions. The miscentring (e.g. A1986, A1961) decreases the X-ray luminosity/SZ signal, as some flux moves outside of the aperture. Sehgal et al. (2013) demonstrated the effect of miscentring on decreasing SZ signal. They also proposed that the miscentring effect causes their lower measured SZ signal compared to Planck due to the finer resolution of ACT. However, as they point out, the miscentring distribution from their sample alone can only explain part of the discrepancy between optical and SZ, unless an unrealistic larger offset exists. Moreover, most miscentred clusters are merging or disturbed clusters with lower X-ray or SZ surface brightness, which makes them more difficult to be detected. The discrepancy of SZ signal is at a level of 10 per cent in our richness range (Biesiadzinski et al. 2012). The projection (e.g. A750, A1319) will increase the optical richness. As the cluster mass-richness relation is close to a linear relation, projection causes the projected clusters to simply slide up and down the mass-richness relation, without deviating from it (Simet et al. 2017). However, the LX−M or YSZ−M relation is a power-law relation with an index greater than one (∼1.6; Rozo et al. 2014a). For example, if we have two clusters with N200 = 80 ($M_{500|N=80}=5\times 10^{14} \, \mathrm{M}_{\odot}$, bolometric X-ray luminosity LX|N = 80 = 11 × 1044 erg s−1) projected together, they will be detected as a N = 160 cluster, the corresponding expected mass and X-ray luminosity are $M_{500|N=160}=10\times 10^{14} \, \mathrm{M}_{\odot}$ and LX|N = 160 = 43 × 1044 erg s−1, respectively. Though the mass is equal to the sum of two subclusters, the total X-ray luminosity is overestimated by a factor of ∼2 than the linear combination of 2LX|N = 80 = 22 × 1044 erg s−1. Thus, projection causes the expected X-ray luminosity or the SZ signal from the summed optical richness to be higher than the actual summed values. The projection fraction of samples extending to much lower richness is around 10 per cent (Simet et al. 2017), even higher for these richest maxBCG clusters (Fig. 2). The above two effects can act together, especially in super clusters and large-scale filaments (Fig. D1). The contamination of low-mass haloes, whose true halo mass is far below the value suggested by the optical richness, would also dilute and reduce the mean mass of the sample. We note that there is contamination of such low-mass systems based on Fig. A2. These low-mass haloes are mostly blended systems with boosted richness affected by nearby large-scale structure. Thus there is a mixture of halo masses at very high N200, the clean and the blended, and the PDF of M given N200 (or λ) will be asymmetric with a low-mass tail. A skew-normal or Hermite polynomial expansion (Shaw, Holder & Dudley 2010) are good alternatives to mixture modelling. Next, we roughly estimate the contamination fraction. There are four low LX systems beyond the 2σ line of LX−N relation from Rozo et al. (2014b) in Fig. A2 (and seven beyond the 1.5σ line towards lower LX versus 1 beyond the 1.5σ line towards higher LX). Taking these numbers at face value, the contamination is 10–15 per cent. | [
"Biesiadzinski et al. 2012"
] | [
"Moreover, most miscentred clusters are merging or disturbed clusters with lower X-ray or SZ surface brightness, which makes them more difficult to be detected. The discrepancy of SZ signal is at a level of 10 per cent in our richness range"
] | [
"Compare/Contrast"
] | [
[
846,
871
]
] | [
[
605,
844
]
] |
2021MNRAS.503.5385Z__Barnes_et_al._2001_Instance_1 | ‘Blind’ searches through H i surveys performed by large aperture single-dish telescopes provide chances to uncover more H i absorption systems. Although such surveys usually utilize the non-tracking, drift scan observing strategy, with integration time for each individual source is limited, the collecting areas of the participating telescopes can still achieve considerable sensitivities. Allison, Sadler & Meekin (2014) identified four H i absorbers, including one previously unknown source, with the archival data of the H i Parkes All-Sky Survey (H i PASS; see Barnes et al. 2001), while Darling et al. (2011), Wu et al. (2015), as well as Song et al. (in preparation) have made attempts to perform ‘blind’ searches for absorption features using part of Arecibo Legacy Fast Arecibo L-Band Feed Array (ALFA) Survey (ALFALFA; see Giovanelli et al. 2005; Haynes et al. 2018) data, respectively, with 10 sources identified in total, including 3 samples remained undetected by other instruments so far, i.e., UGC 00613, CGCG 049-033, and PGC 070403, thus proving the feasibility of searching for new H i absorbers with massive blind sky surveys. Compared with radio interferometers, large single-dish telescopes such as Arecibo can provide better sensitivities and usually higher spectral resolution, which are all crucial to reveal the characteristics of extragalactic H i lines. And although the spatial resolution for such instruments are quite limited compared with interferometers, the chance of having two or more H i absorbing systems lying within the beamwidth with similar redshift is quite low, thus making confusions in source identification unlikely to happen. However, it should be noted that due to temporal variations in spectral baseline commonly seen during drift scans, follow-up observations are needed for reliable characterization of the newly identified absorbers, especially for the weak ones. Also, interferometric mappings are usually required to discern possible fine structures within each absorbing system. | [
"Barnes et al. 2001"
] | [
"Allison, Sadler & Meekin (2014) identified four H i absorbers, including one previously unknown source, with the archival data of the H i Parkes All-Sky Survey (H i PASS; see"
] | [
"Background"
] | [
[
566,
584
]
] | [
[
391,
565
]
] |
2022AandA...666A.134S__Snyder_et_al._2005_Instance_1 | Observation of amino acids and their most essential isomers and potential precursors in the interstellar medium (ISM) should be crucial for revealing the chemistry that may have led to life's origin (Ehrenfreund et al. 2001). In particular, the central question of whether glycine (CH2(NH2)C(O)OH) exists or not in the ISM is one of the most pursued targets in astrochemistry. Although several attempts to observe glycine have been reported (Hollis et al. 2003; Cunningham et al. 2007; Jones et al. 2007; Jiménez-Serra et al. 2016, 2020), its detection has never been confirmed (Snyder et al. 2005). Nevertheless, it has been found in the coma of comets 67P/Churyumov–Gerasimenko through in situ mass spectrometry (Altwegg et al. 2016). The presence of glycine in the volatile cometary material thus strongly suggests the existence of a process capable of generating amino acids in cold environments (Bizzocchi et al. 2020). Hence, as a prerequisite step for its astronomical identification, the rotational spectra of glycinamide (CH2 (NH2)C(O)NH2; Alonso et al. 2018; Kisiel et al. 2022) and aminoacetonitrile (CH2(NH2)CN; Kolesniková et al. 2017), which are relevant intermediates in the Strecker synthesis of glycine; hydantoin (CH2C(O)NHC(O)NH; Alonso et al. 2017) and hydantoic acid (C(O)OHCH2NHC(O)NH2; Kolesniková et al. 2019), potential glycine precursors through a different hydrolytic pathway (Ozeki et al. 2017), and the glycine isomer glycolamide (CH2(OH)C(O)NH2); Sanz-Novo et al. 2020) have been recently reported. In addition, Sanz-Novo et al. (2019) very recently carried out a computational study of the potential energy surfaces (PES) corresponding to the formation reactions of several protonated glycine isomers. Surprisingly, the only exothermic process with no net activation barrier led to protonated acetohydroxamic acid [CH3C(O)NH2OH]+. Its formation could therefore be feasible under interstellar conditions. Consequently, the corresponding neutral counterpart, CH3C(O)NHOH, might be a candidate molecule to be searched for in the ISM. Our previous simulations (Sanz-Novo et al. 2019) suggest that this glycine isomer should be searched for in the ISM, eventually, but there is no experimental rotational data available for this molecular system. | [
"Snyder et al. 2005"
] | [
"In particular, the central question of whether glycine (CH2(NH2)C(O)OH) exists or not in the ISM is one of the most pursued targets in astrochemistry.",
"its detection has never been confirmed"
] | [
"Motivation",
"Motivation"
] | [
[
579,
597
]
] | [
[
226,
376
],
[
539,
577
]
] |
2015AandA...577A.118M__Swift_et_al._2011_Instance_1 | On the other hand, meteoroid rates on the Moon can be related to rates on Earth by taking into account the different gravitational focusing effect between both bodies. The gravitational focusing factor Φ is given by (6)\begin{equation} \Phi=1+\frac{V^{2}_{\rm esc}}{V^{2}}, \end{equation}Φ=1+Vesc2V2,where Vesc is the escape velocity of the central body and V the meteoroid velocity. The different gravitational focusing effect for the Moon and the Earth is given by the quotient γ between the gravitational focusing factors for both bodies. For sporadic meteoroids, with an average velocity of 20 km s-1 (Brown et al. 2002), this velocity-dependent focusing effect is higher for the Earth by a factor of 1.3 (Ortiz et al. 2006), and so γSPO = 0.77. According to this we have \begin{eqnarray} &&{\rm HR}^{\rm SPO}_{\rm Moon} =\gamma^{\rm SPO}{\rm HR}^{\rm SPO}_{\rm Earth}, \\[3mm] &&{\rm ZHR}^{\rm ST}_{\rm Moon} =\sigma\gamma^{\rm ST}{\rm ZHR}^{\rm ST}_{\rm Earth}. \end{eqnarray}HRMoonSPO=γSPOHREarthSPO,ZHRMoonST=σγSTZHREarthST.For the average hourly rate of sporadic events we have HR\hbox{$^{\rm SPO} _{\rm Earth} =10$}SPOEarth=10 meteors h-1 (Dubietis & Artl 2010). In Eq. (8) an additional factor σ is included to take into account that the distances from the Earth and the Moon to the meteoric filament will in general be different, and this would give rise to a different density of stream meteoroids for both bodies. If we assume a simple situation where this filament can be approximated as a tube where the meteoroid density decreases linearly from its central axis, the following definition can be adopted for σ, (9)\begin{equation} \sigma=\frac{d_{\rm Earth}}{d_{\rm Moon}}, \end{equation}σ=dEarthdMoon,where dEarth and dMoon are the distance from the center of the meteoric tube to the Earth and the Moon, respectively. On the other hand, the ZHR on Earth at solar longitude λ (which corresponds to the time of detection of the impact flash) can be related to the peak ZHR by means of (Jenniskens 1994) (10)\begin{equation} {\rm ZHR}^{\rm ST}_{\rm Earth}={\rm ZHR}^{\rm ST}_{\rm Earth}({\rm max})10^{-b|\lambda-\lambda_{\rm max}|}, \end{equation}ZHREarthST=ZHREarthST(max)10−b|λ−λmax|,where ZHR\hbox{$^{\rm ST} _{\rm Earth}$}STEarth(max) is the peak ZHR on Earth (corresponding to the date given by the solar longitude λmax). The values for the peak ZHR for different meteoroid streams and the corresponding solar longitudes for these maxima can be obtained, for instance, from (Jenniskens 2006). For streams with non-symmetrical ascending and descending activity profiles or with several maxima, Eq. (10) should be modified according to the expressions given in Jenniskens (1994). By putting all these pieces together in Eq. (2), we can write the following expression for the probability parameter: (11)\begin{equation} p^{\rm ST}=\frac{\gamma^{\rm ST}\cos(\phi)\sigma {\rm ZHR}^{\rm ST}_{\rm Earth}({\rm max})10^{-b|\lambda-\lambda_{\rm max}|}}{\gamma^{\rm SPO}{\rm HR}^{\rm SPO}_{\rm Earth}+\gamma^{\rm ST}\cos(\phi)\sigma {\rm ZHR}^{\rm ST}_{\rm Earth}({\rm max})10^{-b|\lambda-\lambda_{{\rm max}}|}}\cdot \end{equation}pST=γSTcos(φ)σZHREarthST(max)10−b|λ−λmax|γSPOHREarthSPO+γSTcos(φ)σZHREarthST(max)10−b|λ−λmax|·However, this formula does not take into account the fundamental fact that only those meteoroids capable of producing impact flashes detectable from Earth should be included in the computations. In fact, by employing only the hourly rates measured on Earth in Eq. (11), which measures the flux of meteor brighter than mag. +6.5, it is implicitly assumed that meteoroids producing meteor events on Earth can also produce detectable impact flashes on the Moon. However, this assumption is incorrect. Thus, for a given meteoroid stream (i.e., for a given meteoroid geocentric velocity), the mass mo of meteoroids giving rise to mag. +6.5 meteors on Earth can be obtained from Eqs. (1) and (2) in Hughes (1987). For instance, this mass yields 5.0 × 10-8 kg for Perseid meteoroids (Vg = 59 km s-1), 2.4 × 10-8 kg for Leonids (Vg = 70 km s-1), and 5.0 × 10-6 kg for sporadic meteoroids with an average velocity of 20 km s-1 (Brown et al. 2002). However, the masses corresponding to impact flashes recorded on the Moon are several orders of magnitudes larger than mo (see, e.g., Ortiz et al. 2006; Yanagisawa et al. 2006; Swift et al. 2011). This means that the minimum kinetic energy Emin to produce a detectable impact flash on the Moon is much higher than the kinetic energy of a portion of the meteoroids included in the computation of hourly rates on Earth. This means that the velocity and mass distribution of meteoroids must be somehow included in Eq. (11) to take into consideration for the computation of the probability parameter p only those meteoroids with a kinetic energy above the threshold kinetic energy given by Emin (the method for the computation of Emin will be explained below). According to Eq. (2) in Bellot Rubio et al. (2000a,b), this can be accomplished by including in Eqs. (2) and (11) the factor (12)\begin{equation} \nu=\left(\frac{m_{\rm o}V^{2}}{2}\right)^{s-1}E^{1-s}_{\rm min}, \end{equation}ν=moV22s−1Emin1−s,where V is the impact velocity, mo is the mass of a shower meteoroid producing on Earth a meteor of magnitude +6.5, and s is the mass index, which is related to the population index r (the ratio of the number of meteors with magnitude m + 1 or less to the number of meteors with magnitude m or less) by means of the relationship (13)\begin{equation} s=1+2.5\log(r). \end{equation}s=1+2.5log(r).According to the definition of ν, this parameter is different for each meteoroid stream (and for sporadic meteoroids, of course). By taking this into account Eq. (11) should be modified as follows: (14)\begin{equation} p^{\rm ST}=\frac{\nu^{\rm ST}\gamma^{\rm ST}\cos(\phi)\sigma {\rm ZHR}^{\rm ST}_{\rm Earth}({\rm max})10^{-b|\lambda-\lambda_{\rm max}|}}{{\nu^{\rm SPO}\gamma^{\rm SPO}{\rm HR}^{\rm SPO}_{\rm Earth}}{+\nu^{\rm ST}\gamma^{\rm ST}\cos(\phi)\sigma {\rm ZHR}^{\rm ST}_{\rm Earth}({\rm max})10^{-b|\lambda-\lambda_{\rm max}|}}}\cdot \end{equation}pST=νSTγSTcos(φ)σZHREarthST(max)10−b|λ−λmax|νSPOγSPOHREarthSPO+νSTγSTcos(φ)σZHREarthST(max)10−b|λ−λmax|·If by the time of detection of the impact flash n additional meteoroid streams with significant contributions to the impact rate (and with compatible impact geometry) must be considered, the denominator in Eq. (14) must be modified in the following way, (15)\begin{equation} p^{\rm ST}=\frac{\nu^{\rm ST}\gamma^{\rm ST}\cos(\phi)\sigma {\rm ZHR}^{\rm ST}_{\rm Earth}({\rm max})10^{-b|\lambda-\lambda_{\rm max}|}}{{\nu^{\rm SPO}\gamma^{\rm SPO}{\rm HR}^{\rm SPO}_{\rm Earth}}{+\nu^{\rm ST}\gamma^{\rm ST}\cos(\phi)\sigma {\rm ZHR}^{\rm ST}_{\rm Earth}({\rm max})10^{-b|\lambda-\lambda_{\rm max}|}+\kappa}} , \end{equation}pST=νSTγSTcos(φ)σZHREarthST(max)10−b|λ−λmax|νSPOγSPOHREarthSPO+νSTγSTcos(φ)σZHREarthST(max)10−b|λ−λmax|+κ,where (16)\begin{equation} \kappa=\sum_{i\,=\,1}^{n}\nu^{\rm ST}_i\gamma^{\rm ST}_i \cos(\phi_i)\sigma {\rm ZHR}^{\rm ST}_{i,{\rm Earth}}({\rm max})10^{-b_i|\lambda_i-\lambda_{i,{\rm max}}|} \end{equation}κ=∑i = 1nνiSTγiSTcos(φi)σZHRi,EarthST(max)10−bi|λi−λi,max|accounts for these n additional streams. The minimum kinetic energy Emin defined above corresponds to the minimum radiated energy Er_min on the Moon detectable from observations on Earth, which in turn is related to the maximum visual magnitude for detectable impacts (mmax). And these values depend on, among other factors, the experimental setup employed. The kinetic energy of the impactor and the radiated energy are linked by the luminous efficiency: (17)\begin{equation} E_{r\_{\rm min}}=\eta E_{\rm min}. \end{equation}Er_min=ηEmin.With our experimental setup, the maximum visual magnitude for detectable impact is mmax ~ 10. The radiated energy can be obtained by integrating the radiated power P defined by the equation (18)\begin{equation} P=1.36949\times 10^{-16}10^{(-m+21.1)/2.5}f \pi \Delta \lambda R^2, \end{equation}P=1.36949×10-1610(−m+21.1)/2.5fπΔλR2,where P is given in Joules, m is the magnitude of the flash, 1.36949 × 10-16 is the flux density in W m-2 μm-1 for a magnitude 21.1 source according to the values given in Bessel (1979), Δλ is the width of the filter passband (about 6000 Å for our devices), and R is the Earth-Moon distance at the instant of the meteoroid impact. The factor f is related to the degree of anisotropy of light emission. Thus, for those impacts where light is isotropically emitted from the surface of the Moon f = 2, while f = 4 if light is emitted from a very high altitude above the lunar surface. As expected, according to Eq. (18) the minimum radiated power for flash detectability (and hence the minimum radiated energy and the minimum meteoroid kinetic energy), which is obtained by using m = mmax, is higher when the distance between Earth and Moon is greater. So, the detectability limit is time-dependent. | [
"Swift et al. 2011"
] | [
"However, the masses corresponding to impact flashes recorded on the Moon are several orders of magnitudes larger than mo",
"This means that the minimum kinetic energy Emin to produce a detectable impact flash on the Moon is much higher than the kinetic energy of a portion of the meteoroids included in the computation of hourly rates on Earth. This means that the velocity and mass distribution of meteoroids must be somehow included in Eq. (11) to take into consideration for the computation of the probability parameter p only those meteoroids with a kinetic energy above the threshold kinetic energy given by Emin"
] | [
"Differences",
"Uses"
] | [
[
4365,
4382
]
] | [
[
4189,
4309
],
[
4385,
4878
]
] |
2022ApJ...929....7V__Caprioli_&_Spitkovsky_2014a_Instance_1 | Diffusive shock acceleration (DSA), a process entering the category of first-order Fermi acceleration, is the process by which astrophysical shocks accelerate charged particles to relativistic speeds. DSA requires the magnetic field near the shock front to reflect the particle, leading to repeated shock-crossings with the particle gaining energy at each crossing (e.g., Bell 1978; Blandford & Ostriker 1978; Drury 1983). DSA is a self-sustaining process because the presence of high-energy particles triggers instabilities in the magnetic field, which in turn allow the magnetic field to reflect the particles more efficiently (e.g., Bell 1978, 2004). DSA has been explored numerically using the particle-in-cell (PIC) method, as well as the PIC-hybrid method, whereby the ions are treated as particles and the electrons as a fluid. Simulations of this type seem to indicate that although this process is effective in the case of (quasi-)parallel shocks where the magnetic field is aligned with the direction of motion, it becomes ineffective once the angle between the magnetic field and the shock exceeds approximately 50° (Caprioli & Spitkovsky 2014a,2014b, 2014c).
4
4
Notice that most of the studies on DSA including the present one assume shocks are propagating into a homogeneous medium; effects of a nonmonotonous shock are discussed in Hanusch et al. (2019). Most simulations also assume that the pre-shock medium is fully ionized. Simulations for a partially ionized medium (Ohira 2013, 2016) show an increased injection rate, allowing for DSA even in oblique shocks. Also, studies by Kumar & Reville (2021) demonstrate that DSA can be triggered by the shock emitted waves at highly oblique shocks. However, different results were obtained by van Marle et al. (2018), using a combined PIC-MHD approach. This method, which treats the thermal gas as a fluid but nonthermal ions as individual particles, showed that, given a sufficient injection rate, even for magnetic obliquity up to 70°, shocks can accelerate particles through the DSA process. Several factors were believed to contribute to this discrepancy between PIC-MHD and PIC or PIC-hybrid methods:1.Time-period covered by the simulation. The DSA occurring in PIC-MHD simulations is only effective after more than 200 ion-gyrotimes (
ωci−1
) and it takes more than 500 ion-gyrotimes to fully develop whereas published hybrid simulations where limited to scales of the order of 200 ion-gyrotimes. Notice that at the time ∼200
ωci−1
both PIC-hybrid and PIC-MHD simulations find similar results, namely that particles are accelerated by the shock-drift acceleration (SDA).2.Effective number of particles per cell. DSA requires an upstream current of CRs in order to develop. Because only a small fraction of the particles that cross the shock is reflected, a large particle population is required to produce sufficient nonthermal particles in the upstream medium.3.Simulation box size. van Marle et al. (2018) showed that the relevant upstream instabilities operate on long wavelengths, larger than the box size of hybrid simulations.
| [
"Caprioli & Spitkovsky 2014a"
] | [
"Simulations of this type seem to indicate that although this process is effective in the case of (quasi-)parallel shocks where the magnetic field is aligned with the direction of motion, it becomes ineffective once the angle between the magnetic field and the shock exceeds approximately 50°"
] | [
"Compare/Contrast"
] | [
[
1128,
1155
]
] | [
[
835,
1126
]
] |
2016AandA...593A..95C__Smith_1963_Instance_1 | Galactic fountains or infall are the possible origins for the ECs in this sample. Both scenarios present possible explanations and restrictions. The accretion of low metallicity gas from the intergalactic medium may occur through filamentary structures with the gas cooling into clouds (Fernández et al. 2012). Subsequently HVCs may be destroyed or fragmented into smaller clouds by drag forces from the halo and phenomena such as Rayleigh-Taylor and Kelvin-Helmholtz instabilities. Star formation can be triggered by these interactions, within clouds that reach sufficient density (Figs. 9 and 10). However, there is evidence that star formation is possible only within dark-matter encapsulated HVCs such as the Smith Cloud (Smith 1963; Heitsch & Putman 2009; Nichols & Bland-Hawthorn 2009; Joung et al. 2012). Christodoulou et al. (1997) argue that without dark matter, HVCs are unable to reach the mass required to collapse. On the other hand, C 932, C 934, and C 939 are located right above the Local spiral arm (Fig. 11), which would be consistent with the chimney scenario. Schlafly et al. (2015) mapped various bubble-like structures vertically along the range 0.3 to 2.8 kpc, which form the Orion superbubble. The expansion of these substructures powered by massive stellar winds and supernovae triggers star formation in various shells and rings, inputting energy to the superbubble (Lee & Chen 2009). The star formation engine in the Galactic fountain may work in a similar way to the infall scenario, through the interaction of a cloud with the surrounding halo environment. However, high-latitude clusters in this study are located at distances from the disc larger than has been expected for a chimney-like event in recent studies (Melioli et al. 2009). Regardless of the scenario, a possible cloud-cloud interaction may be leading the clouds analysed in Fig. 9 to collapse and triggering not only star formation, but also cluster formation. However, the timescale for cloud-cloud collision in a cloud complex appears to be larger than 1 Gyr (Christodoulou et al. 1997). Therefore, additional studies are required to check the presence of dark-matter in HVCs, estimate the cloud-cloud interaction timescales, and provide more insight into the effect of the halo environment on the HVCs and chimney-like events. That is beyond the purpose of this study. | [
"Smith 1963"
] | [
"Star formation can be triggered by these interactions, within clouds that reach sufficient density (Figs. 9 and 10). However, there is evidence that star formation is possible only within dark-matter encapsulated HVCs such as the Smith Cloud"
] | [
"Compare/Contrast"
] | [
[
726,
736
]
] | [
[
483,
724
]
] |
Subsets and Splits