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SAO/NASA Astrophysics Data System 13

2015MNRAS.449.1018Y__Essey_et_al._2010_Instance_1

VHE gamma-rays from distant blazars suffer serious EBL absorption. For instance, the attenuation factor of the flux at ∼1 TeV emitted at z = 0.6 due to EBL absorption is ∼10−4 (Domínguez et al. 2011). If VHE gamma-rays from a blazar are produced in its jet, the intrinsic VHE spectrum after de-absorption would be very hard and not a simple power law (e.g. Archambault et al. 2014), which is hardly explained plausibly in leptonic models. In such a case, a leptohadronic jet model is used to explain VHE spectra of distant blazars (e.g. Böttcher, Reimer & Marscher 2009; Yan & Zhang 2015), in which VHE emission is attributed to synchrotron emissions of relativistic protons and pair cascades created in proton–photon (pγ) interaction. However, the jet model cannot explain the VHE emission from PKS 1424+240 if its redshift z > 0.7–0.8 (Yan & Zhang 2015). Alternatively, it is recently proposed that VHE gamma-rays from distant blazars may be the secondary gamma-rays produced in the rectilinear propagation of the UHECRs escaping from these blazars (e.g. Essey & Kusenko 2010; Essey et al. 2010). In the latter case, UHECRs interact with background photons, i.e. EBL photons and microwave background (CMB) photons, which creates UHE electrons and photons through Bethe–Heitler (BH) pair production and photo-meson production. These UHE electrons and photons would interact with background photons again, and then pair cascades are induced; the secondary photons are inverse-Compton-scattered (ICS) CMB photons by the pair cascades. Because of the large mean interaction path of UHECRs, these secondary photons are produced relatively close to the Earth (e.g. Lee 1998; Essey et al. 2011b; Murase et al. 2012). The UHECR induced cascade model is successful in explaining the observed VHE spectra of extreme high-synchrotron-peaked BL Lacertae objects (HBLs; e.g. Essey & Kusenko 2010, 2014; Murase et al. 2012; Aharonian et al. 2013; Takami et al. 2013). In particular, UHECR induced cascade model is able to explain the VHE emission from a blazar with redshift z > 1 (Aharonian et al. 2013; Essey & Kusenko 2014). However, in the previous works the primary emission produced in the jet is either simply assumed (e.g. Aharonian et al. 2013; Essey & Kusenko 2014) or neglected (e.g. Takami et al. 2013).

2018ApJ...853...12M__Weaver_et_al._1978_Instance_1

There are numerous models which lay down nucleosynthesis yields from CCSN explosions (Burbidge et al. 1957; Woosley & Weaver 1986, 1995; Thielemann et al. 1996; Heger & Woosley 2002, 2010; Rauscher et al. 2002; Kobayashi et al. 2006; Nomoto et al. 2006; Woosley & Heger 2007; Pignatari et al. 2015; Sukhbold et al. 2016). In this work, we utilize the zonal yield sets from Sukhbold et al. (2016; hereafter, S16), which used the modified 1D hydrodynamic code KEPLER4 4 https://2sn.org/kepler/doc/Introduction.html along with P-HOTB. P-HOTB stands for Prometheus-Hot Bubble and was used to study core collapse (Janka & Mueller 1996; Kifonidis et al. 2003), whereas KEPLER was used to evolve the star along zero age main sequence and calculate nucleosynthesis yields and light curves (Weaver et al. 1978). For models that exploded, isotopic yields were generated post explosion. The zonal yields were obtained for three particular models, 15.2 M⊙, 20.1 M⊙, and 25.2 M⊙, ∼200 s after the explosion, before any mixing could take place.5 5 T. Sukhbold (2017, private communication). Although all models in S16 data set assume solar metallicity and do not take into account the effects of rotation, they can account for (1) detailed neutrino transport calculations using an improved explosion mechanism, as compared to Rauscher et al. (2002) and Woosley and Heger (2007); (2) a central engine that considers matter inside the collapsed core, unlike certain other models that investigated only the matter exterior to the central engines used; and (3) unlike previous nucleosynthesis models, all models6 6 Each model has a particular progenitor mass. used here are not exploded by injecting artificial energy because (a) models below 15 M⊙ almost always explode, (b) models in 20–30 M⊙ rarely explode, and (c) most models above 30 M⊙ implode and become black holes (see Figure 14 in S16 for the probability of explosion of different progenitor masses). In fact, the few models above 30 M⊙ in which explosion does take place is due to their core being ripped apart by winds to sizes comparable to ∼15 M⊙. The decimals in the progenitor masses of these models might seem bizarre; the reason is that the authors have tried to explode all possible progenitor masses in steps of 0.1 M⊙ between 12 and 30 M⊙; however, 15.0, 15.1, 20.0, 25.0, and 25.1 M⊙ imploded in their simulations. This apparently small change in progenitor mass, which leads to an altogether different end scenario, is due to small but significant variations in the progenitor compactness (O’Connor & Ott 2011) rather than the central engine characteristics (Pejcha & Thompson 2015). This effect is more pronounced near progenitor masses of ∼20 M⊙ because the carbon burning stage changes to the radiative pathway from a convective mechanism. In fact, it has been recently shown that two similar progenitors with identical masses but slightly different input physics can lead to totally different scenarios (Sukhbold et al. 2017). Thus it is not unusual for such stark differences to show up between two similar progenitor stars. Throughout this paper, we frequently approximate 15.2–15, 20.1–20, and 25.2–25 M⊙ models for the sake of simplicity.

2018AandA...617A..94L__Joblin_et_al._2018_Instance_1

In an interstellar cloud the spatial transition from atomic to molecular gas takes place in photon dominated regions (PDRs; see reviews by Hollenbach & Tielens 1997, 1999), which are also a source of a significant fraction of the far-infrared emission from the Milky Way and other galaxies. Exterior to the PDRs the gas makes the transition from neutral to ionized hydrogen. The ionized gas can take the form of a low density ionized boundary layer (IBL) in the case of weak UV fields, or a dense H II region in the proximity to a strong UV field arising from massive star formation. PDRs and H II regions are the boundary regions where the effects of star formation on molecular clouds manifest themselves. They have been the focus of a considerable modeling effort (see Tielens & Hollenbach 1985; Sternberg & Dalgarno 1989; Kaufman et al. 1999; Abel et al. 2005; Le Petit et al. 2006; Bron et al. 2018, and references therein). The observational analysis of PDRs, H II regions, and IBLs has improved considerably since the availability of far-infrared spectroscopic data from the Herschel Space Observatory (see Ossenkopf et al. 2013; Köhler et al. 2014; Stock et al. 2015; Joblin et al. 2018; Wu et al. 2018, and references therein) and the Stratospheric Observatory for Infrared Astronomy (SOFIA; e.g., Schneider et al. 2012; Pérez-Beaupuits et al. 2015; Pabst et al. 2017; Mookerjea et al. 2018). Most of these studies of the ionized and PDR layers have focused on very bright H II regions where high UV flux, density, and temperature produce strong far-infrared emission, making such regions easily observable in key gas tracers such as the fine-structure lines of C+, N+, and O. Less is known about the IBL–PDR conditions for typical molecular clouds where the UV field is smaller and, thus, the lines are weaker. The Herschel Space Observatory HIFI GOT C+ survey (Langer et al. 2010; Pineda et al. 2013) took a step in studying molecular cloud PDRs and IBLs in that it sampled [C II] along several hundred lines of sight (LOS) in the Galaxy producing an unbiased database of a few thousand clouds of various evolutionary stages with most LOS not containing H II regions as indicated by weak [C II] emission. However, because [C II] samples both weakly and highly ionized regions, there remains some uncertainty about the relative contributions of the ionized and PDR regions. Furthermore, because [C II] has only one fine-structure transition one cannot solve uniquely for the properties of the gas. For the GOT C+ survey Langer et al. (2014) derived the column density of material traced by [C II] by assuming a thermal pressure and its Galactic gradient.

2019AandA...630A.123K__Kohutova_&_Verwichte_2016_Instance_1

The coronal rain plasma can be distinguished from the prominence material by looking at their trajectories and average speeds. The timescale on which the coronal rain forms following the heating onset is much shorter than for the quiescent scenario; in the studied event condensations appear 10 min after the reconnection event, whereas observations of quiescent rain suggests it recurs in the same loop of the order of hours (Antolin & Rouppe van der Voort 2012; Kohutova & Verwichte 2016). The period of the loop heating-condensation cycle in the quiescent scenario is equivalent to the time it takes for the sustained footpoint heating to refill the loop sufficiently with evaporated plasma to reach the thermally unstable regime, after the loop has been evacuated by the previous coronal rain event. This short timescale for coronal rain formation is likely a consequence of the heating input being much greater than in the quiescent case and of the short length of the studied loop. The 1D numerical simulations suggest that although the loop length is a contributing factor, the heating input is the main factor affecting the coronal rain formation timescale (Froment et al. 2018). The thermal instability in the case associated with magnetic reconnection is also more concentrated spatially and only a certain fraction of the loop with a cross section of around 5 Mm width becomes unstable. This implies that the heating that triggers the thermal instability is more localised and only affects a small number of field lines in the loop. As the thermal conduction acts predominantly along the magnetic field, most of the matter and energy transport occurs along the affected field lines. Comparing this to the quiescent scenario, the typical width of the loop bundles observed to undergo condensation formation is around 10−15 Mm (Antolin & Rouppe van der Voort 2012; Kohutova & Verwichte 2016), and in some cases, reaching 40 Mm (Auchère et al. 2018; Froment et al. 2019).

2022MNRAS.512.3828B__Dokkum_&_Franx_2001_Instance_1

Understanding the redshift dependence of galaxy evolution requires disentangling the evolution of an individual galaxy within a population from the evolution in the average properties of the population as a whole (due to the continual addition of newly formed galaxies with different properties to the extant population). A key method of studying how both individual and populations of galaxies evolve is by analysing their growth in mass and size. An individual star-forming galaxy is expected to evolve along the relation of star-forming galaxies in the mass–size plane (Lilly et al. 1998; Ravindranath et al. 2004; Trujillo et al. 2006; Pezzulli et al. 2015; van Dokkum et al. 2015), while the average size of the population as a whole increases with decreasing redshift due to processes such as mergers (Hopkins et al. 2009; Naab, Johansson & Ostriker 2009) and ’puffing up’ due to strong active galactic nuclei (AGNs) feedback (Fan et al. 2008, 2010), but also new galaxies forming with larger radii (van Dokkum & Franx 2001; Carollo et al. 2013). In other words, star-forming galaxies at both low and intermediate redshifts follow parallel tracks in the mass–size plane (Speagle et al. 2014; van Dokkum et al. 2015), with their starting location in the plane depending on redshift. Therefore, when analysing star-forming galaxies in the mass–size plane at $z$ ∼ 0, we are observing the combined effect of both the evolution of individual galaxies throughout their lifetimes and the evolution of the population due to the addition of new members and loss of old members (as they quench). We want to disentangle these two effects to understand how the redshift range over which a galaxy formed and evolved influences its evolutionary path. We therefore need to understand how the processes influencing a galaxy may be regulated by the broader conditions of the Universe and how these conditions change with redshift. An important tool to measure the impact of various processes is the analysis of scaling relations, which quantify the link between different galaxy parameters to determine their dependence. Specifically, scaling relations between stellar population parameters and galaxy structure allow us to quantify how processes involved in star formation and stellar mass assembly interrelate with processes dominating structural and dynamical changes.

2020MNRAS.499.5562Z__Miller_2015_Instance_1

One explanation for the low effective temperatures is that the TDE thermal emission does not originate from the accretion disc, but from an outflow supported by radiation pressure from the disc’s super-Eddington accretion rate (e.g. Loeb & Ulmer 1997; Strubbe & Quataert 2009; Lodato & Rossi 2011; Metzger & Stone 2016; Roth et al. 2016; Curd & Narayan 2019). The TDE’s high photosphere radius and low temperature can then be explained by the increased emitting area from the optically thick, expanding outflow, launched from the accretion disc or SMBH. These outflows can explain the nearly constant temperatures inferred from the spectrum of optically bright TDEs (Strubbe & Quataert 2009; Miller 2015), and may lead to observable emission or absorption line features in the TDE’s spectrum (Strubbe & Quataert 2011; Roth et al. 2016; Roth & Kasen 2018). Hydrodynamical simulations show that the outflow can be supported not only by radiation pressure from the compact disc (Dai et al. 2018; Curd & Narayan 2019) but also by shocks driven by stream–stream collisions during the circularization of stellar debris (Liptai et al. 2019; Lu & Bonnerot 2020). However, to power the outflow, a significant fraction of the tidally disrupted star’s rest-mass energy must be liberated ($0.05 \, {\rm M}_\odot \, c^2 \sim 10^{53} \, {\rm erg}$), much larger than the typical energy liberated by an optically bright TDE’s early emission ($\sim \! 10^{49}{\!-\!}10^{51} \, {\rm erg}$; e.g. Komossa 2015; van Velzen et al. 2020). This so-called missing energy problem has a number of proposed solutions. For instance, some argue most of the rest-mass energy is radiated in the unobservable far-UV wavelength bands (e.g. Lu & Kumar 2018; Jonker et al. 2020), while others propose this energy is carried away by a jet whose emission is unobservable for most TDE viewing angles (Dai et al. 2018). Some authors suggest this energy is never emitted in the first place, but rather becomes trapped due to the TDE disc and outflow’s high optical depth (photon trapping; e.g. Curd & Narayan 2019). The wind model has yet to conclusively address the missing energy problem.

2015MNRAS.452.2731S__Stroe_et_al._2013_Instance_2

The H α studies of Umeda et al. (2004) and Stroe et al. (2014a, 2015) are tracing instantaneous (averaged over 10 Myr) SF and little is known about SF on longer time-scales and the reservoir of gas that would enable future SF. An excellent test case for studying the gas content of galaxies within merging clusters with shocks is CIZA J2242.8+5301 (Kocevski et al. 2007). For this particular cluster unfortunately, its location in the Galactic plane, prohibits studies of the rest-frame UV or FIR tracing SF on longer time-scales, as the emission is dominated by Milky Way dust. However, the rich multiwavelength data available for the cluster give us an unprecedented detailed view on the interaction of their shock systems with the member galaxies. CIZA J2242.8+5301 is an extremely massive (M200 ∼ 2 × 1015 M⊙; Dawson et al. 2015; Jee et al. 2015) and X-ray disturbed cluster (Akamatsu & Kawahara 2013; Ogrean et al. 2013, 2014) which most likely resulted from a head-on collision of two, equal-mass systems (van Weeren et al. 2011; Dawson et al. 2015). The cluster merger induced relatively strong shocks, which travelled through the ICM, accelerated particles to produce relics towards the north and south of the cluster (van Weeren et al. 2010; Stroe et al. 2013). There is evidence for a few additional smaller shock fronts throughout the cluster volume (Stroe et al. 2013; Ogrean et al. 2014). Of particular interest is the northern relic, which earned the cluster the nickname ‘Sausage’. The relic, tracing a shock of Mach number M ∼ 3 (Stroe et al. 2014c), is detected over a spatial extent of ∼1.5 Mpc in length and up to ∼150 kpc in width and over a wide radio frequency range (150 MHz–16 GHz; Stroe et al. 2013, 2014b). There is evidence that the merger and the shocks shape the evolution of cluster galaxies. The radio jets are bent into a head–tail morphology aligned with the merger axis of the cluster. This is probably ram pressure caused by the relative motion of galaxies with respect to the ICM (Stroe et al. 2013). The cluster was also found to host a high fraction of H α emitting galaxies (Stroe et al. 2014a, 2015). The cluster galaxies not only exhibit increased SF and AGN activity compared to their field counterparts, but are also more massive, more metal rich and show evidence for outflows likely driven by SNe (Sobral et al. 2015). Stroe et al. (2015) and Sobral et al. (2015) suggest that these relative massive galaxies (stellar masses of up to ∼1010.0–10.7 M⊙) retained the metal-rich gas, which was triggered to collapse into dense star-forming clouds by the passage of the shocks, travelling at speeds up to ∼2500 km s−1 (Stroe et al. 2014c), in line with simulations by Roediger et al. (2014).

2019AandA...632A..40D__Sánchez-Fernández_et_al._2017_Instance_1

An extreme example of a rapid decay is V404 Cyg. The parameters of the long Porb system were chosen to be close to those of V404 Cyg, whose last outburst lasted only a couple of weeks and showed a pronounced disc outflow, conjectured to be a thermal wind (Muñoz-Darias et al. 2016). The mass in the disc at the onset of the outburst is ∼3 × 10−7 M⊙ in our models1. Blowing away most of this mass would require a sustained outflow rate of ≈ 10−5 M⊙ yr−1 ≈ 30 ṀEdd over 15 days for a 9 M⊙ black hole. Such very high mass outflow rates may be reached close to the Eddington luminosity as electron scattering contributes to the driving force of the wind. Figure 7 shows the mass outflow rate in the wind diverges near L ≈ 0.7 LEdd due to the estimated radiation driving correction (Eq. (4)). In principle, it might thus be possible to shorten the outburst of V404 Cyg to a couple of weeks by fine-tuning the model parameters to sample this high luminosity region. In support, observations of V404 Cyg do indicate the source likely reached LEdd (Kimura et al. 2016) and was enshrouded by rapidly varying Compton-thick outflowing material (Sánchez-Fernández et al. 2017) with an estimated Mw ≈ 4 × 10−6 M⊙ lost to the wind (Casares et al. 2019). The lower effective gravity due to the high radiation should enhance the wind (Proga & Kallman 2002) but the mass loss must saturate at some level as the outflow becomes optically thick. Higginbottom et al. (2019) do not find a significantly enhanced Ṁw near LEdd in their radiation-hydrodynamic simulations of thermal winds, but these neglect radiative driving by electron scattering. If winds are boosted near Eddington, a puzzle is why GRS 1915+105 has not been affected as much as V404 Cyg despite its luminosity also being close to Eddington and its disc size even greater. If the short duration of the V404 Cyg was due to a thermal wind, then this wind likely required very specific conditions. Instead, we speculate that the angular momentum transport was instead dominated by the jet. The system likely stayed in the (very) bright hard state during the outburst, where it has a strong jet which is almost certainly coupled to the accretion flow via the magnetic fields and could be responsible for angular momentum transport through the hot flow in this state (e.g. Ferreira et al. 2006).

2015ApJ...813..109D__Górski_et_al._2005_Instance_1

Photometric Calibration: Photometric calibration was performed using the stellar locus regression technique (SLR: Ivezić et al. 2004; MacDonald et al. 2004; High et al. 2009; Gilbank et al. 2011; Coupon et al. 2012; Desai et al. 2012; Kelly et al. 2014). Our reference stellar locus was empirically derived from the globally calibrated DES Y1A1 stellar objects in the region of the Y1A1 footprint with the smallest E(B − V) value from the Schlegel et al. (SFD; 1998) interstellar extinction map. We performed a 1″ match on all Y1 and Y2 objects with S/N > 10 observed in r-band and at least one other band. We then applied a high-purity stellar selection based on the weighted average of the spread_model quantity for the matched objects ( ; see below). The average zero point measured in Y1A1, ZPgrizY = {30.0, 30.3, 30.2, 29.9, 28.0}, was assigned to each star as an initial estimate. Starting from this coarse calibration, we began an iterative procedure to fix the color uniformity across the survey footprint. We segmented the sky into equal-area pixels using the HEALPix scheme (Górski et al. 2005). For each ∼0.2 deg2 (resolution nside = 128) HEALPix pixel, we chose the DES exposure in each band with the largest coverage and ran a modified version of the Big MACS SLR code (Kelly et al. 2014)41 41 https://code.google.com/p/big-macs-calibrate/ to calibrate each star from the reference exposure with respect to the empirical stellar locus. These stars became our initial calibration standards. We then adjusted the zero points of other CCDs so that the magnitudes of the matched detections agreed with the calibration set from the reference exposure. CCDs with fewer than 10 matched stars or with a large dispersion in the magnitude offsets of matched stars (σZP > 0.1 ) were flagged. For each calibration star, we computed the weighted-average magnitude in each band using these new CCD zero points; this weighted-average magnitude was used as the calibration standard for the next iteration of the SLR. In the first iteration, we assigned SLR zero points to the calibration stars based on the HEALPix pixel within which they reside. In subsequent iterations, we assigned SLR zero points to the calibration stars based on a bi-linear interpolation of their positions onto the HEALPix grid of SLR zero points. After the second iteration, the color zero points were stable at the 1–2 level. The absolute calibration was set against the 2MASS J-band magnitude of matched stars (making use of the stellar locus in color-space), which were de-reddened using the SFD map with a reddening law of AJ = 0.709 × E(B − V)SFD from Schlafly & Finkbeiner (2011). The resulting calibrated DES magnitudes are thus already corrected for Galactic reddening by the SLR calibration.

2015ApJ...801..103G___2014_Instance_2

Within the framework of the fireball shock model, Pe'er et al. (2007) proposed a method to infer central engine parameters using observed data. With the measured temperature and flux of an identified thermal component in the spectrum, along with a flux ratio between thermal and non-thermal components, one may infer the size of the jet at the base of the outflow, r0, and the dimensionless entropy of the outflow, (which is also the bulk Lorentz factor of the outflow, if the photosphere radius is greater than the fireball coasting radius). Some authors have applied this method to some Fermi GRBs (Iyyani et al. 2013; Preece et al. 2014; Ghirlanda et al. 2013). The derived central engine parameters are sometimes ad hoc or inconsistent. For instance, the analyses for GRB 110721A (Iyyani et al. 2013) and for GRB 130427A (Preece et al. 2014) led to a curious conclusion that the bulk Lorentz factor of the outflow of different layers are decreasing with time. This would lead to no, or at most very inefficient, internal shock emission. Yet both bursts have dominant non-thermal emission. More curiously, the data of GRB 110721A (Iyyani et al. 2013) require that r0 is rapidly varying with time by 2–3 orders of magnitudes. This is hard to imagine given the well-believed paradigm of the GRB central engine: If the engine is naked, the size of the engine (a hyper-accreting black hole or a millisecond magnetar) is around r0 ∼ 107 cm; if an extended envelope of a collapsar progenitor is considered, the fireball may be “re-born,” with r0 ∼ R*θj ∼ 109R*, 10θj, −1 cm (where R* is the size of the progenitor star, and θj is the jet opening angle). If one considers the depletion of the envelope, r0 should decrease with time. However, Iyyani et al. (2013) showed that r0 increases from 106 cm to 108 cm early on, and then decreases mildly after 2 s. These absurd conclusions suggest that the starting point of the analysis, i.e., the assumption of a pure fireball model, might not be valid. It is interesting to see whether a hybrid ejecta photosphere model may solve the problem. Incidentally, Ghirlanda et al. (2013) analyzed another burst, GRB 100507, using the fireball framework (Pe'er et al. 2007), but found that the derived r0 remains constant and reasonable. The jet composition of that burst may be more close to a fireball. It would be interesting to see whether a general theoretical framework can be established, which may be reduced to the standard fireball framework when σ0 1.

2021AandA...655A.111K__Rojas-Arriagada_et_al._(2019)_Instance_1

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.

2018ApJ...862..150H__Cudlip_et_al._1982_Instance_1

In Figure 1, we show the archival 850 μm polarization data from the legacy program of SCUPOL with the JCMT (Matthews et al. 2009) (effective 20″ beam ∼0.76 pc). Matthews et al. (2009) collected the JCMT data toward the GC, where the B-field is sampled on a 10″ grid. The linearly polarized light from dust grains is frequently used to probe the integrated plane-of-sky B-field morphology. Interstellar dust grains are elongated, with their minor axes parallel to the B-field. The thermal emission from the aligned dust grains is then polarized with polarization segments perpendicular to the field lines (Cudlip et al. 1982; Hildebrand et al. 1984; Hildebrand 1988; Lazarian 2000; Andersson et al. 2015). The dust polarization can, therefore, reveal the plane-of-sky projected B-field orientations. In Figure 1, the SCUPOL B-field segments are overlaid on the JCMT 850 μm map (Di Francesco et al. 2008). The segments are plotted with p/dp ≥ 2, 3, 4. The 450 μm Submillimeter Polarimeter for Antarctic Remote Observing (SPARO) B-field (Novak et al. 2003) is also overlaid with a resolution of 6′ (corresponding to a linear scale of 13.7 pc). The low-resolution SPARO map traces the large-scale B-field which is parallel to the plane of our Galaxy. This alignment of field orientations with the Galactic plane is attributed to a large-scale toroidal B-field configuration (i.e., azimuthal field). The SCUPOL 850 μm B-field as well as the continuum are clearly detected and resolved along and across the sub-features in the GC at a 20″ resolution (=0.76 pc). The detected B-field orientations (ΦB) vary enormously over the entire map, ranging from −90° to 90° (0° is west, positive is counterclockwise). Nevertheless, the ΦB varies smoothly and systematically along certain substructures, revealing organized patches in, e.g., the CND, the giant molecular cloud 20/50 MC (e.g., Güsten et al. 1981), and the HVCC CO 0.02–0.02 (Oka et al. 1999). The azimuthal correlation seen in the CND is providing the link between the model proposed by Wardle & Königl (1990) and the SCUPOL 850 μm polarization data. We are exploring this link in the following sections. A comparison of polarization data is presented in Appendix A. We find that the morphology of the B-field is consistent with different threshold cuts in p/dp. Hence, in order to work with the maximum of independent data points, we present data with p/dp ≥ 2, and we will focus on the B-field structure of the CND.

2021ApJ...920..147Z__Schneider_1959_Instance_1

Mainly four mechanisms are considered to be causing the observed solar radio wave emissions: two causing incoherent and two causing coherent emissions. Incoherent emissions can be due to bremsstrahlung and gyrosynchrotron radiation. In them, every electron radiates independent on the others. The total emission is simply the sum of the emissions of every single electron (Rybicki & Lightman 1979; Dulk 1985; Melrose 2017; Nindos 2020). Comparing with coherent emission mechanisms, the incoherent emission mechanisms are better understood. The two coherent emission mechanisms are plasma (Ginzburg & Zhelezniakov 1958; Melrose 1970a, 1970b; Zheleznyakov & Zaitsev 1970a, 1970b) and electron cyclotron maser (ECM) emissions (Twiss 1958; Gaponov 1959; Schneider 1959; Pritchett 1984a). In contrast to the incoherent emission mechanisms, coherent emission can explain (a) the high brightness temperatures, (b) the short eruption timescales, (c) the narrow frequency bands, and (d) the strong polarization of Type I, II, III solar radio bursts (SRBs) and solar radio spikes (Aschwanden 2005). And coherent radio emission mechanisms involve plasma instabilities. The plasma emission follows a beam or bump-on-tail instability, the source of free energy of which is related to an electron velocity distribution u ∥ · ∂ f u ∥ / ∂ u ∥ > 0 . On the other hand, the ECM instability requires a positive gradient in the electron velocity distribution along the direction perpendicular to the ambient magnetic field ( ∂ f u ⊥ / ∂ u ⊥ > 0 ) (see Melrose 1986, 2017). Here, f is the electron distribution function and u∥, u⊥ are the electron velocities parallel and perpendicular to the ambient magnetic field, respectively. The expressions u ∥ · ∂ f u ∥ / ∂ u ∥ > 0 and ∂ f u ⊥ / ∂ u ⊥ > 0 indicate an electron beam and a ring (or a loss cone or a horseshoe) distribution in the direction parallel and perpendicular to the ambient magnetic field, respectively. The existence of electron velocity distributions u ∥ · ∂ f u ∥ / ∂ u ∥ > 0 has been conjectured based on observations of, e.g., SRBs and hard X-ray bursts as well as confirmed by observations of solar energetic particles (Chen et al. 2015, 2018; Cairns et al. 2018). Numerical simulations have also considered possible formation mechanisms of velocity distributions with ∂ f u ⊥ / ∂ u ⊥ > 0 , e.g., by magnetic reconnection (e.g., Büchner & Kuska 1996; Bessho et al. 2014; Shuster et al. 2014; Zhou et al. 2016; Treumann & Baumjohann 2017; Muñoz & Büchner 2018a; Voitcu & Echim 2018; Yao et al. 2021a). It is, however, still under debate which coherent mechanism dominates and which role different features of the electron distribution play for the emission of coherent radio waves from the solar corona.

2021ApJ...909...65K__Marsh_et_al._2016_Instance_1

As mentioned in the previous section, if a magnetized WD rotates with a misalignment between its magnetic field and rotation axes (similar configuration to a pulsar), it can emit a continuous GW. We already provided a detailed discussion on GWs emitted from WDs with different magnetic field geometries and strengths in GR (Kalita & Mukhopadhyay 2019b; Kalita et al. 2020). Figure 7 shows an illustrative diagram of a magnetized WD where the magnetic field is along the z′-axis and rotation is along the z-axis, with χ being the angle between these two axes. We calculate the amplitude of GW using the set of Equations (34) assuming the difference in radii of the WD between those along x- and z-axes to be 0.01%, i.e., , due to the presence of a very weak magnetic field and slow rotation. The choice of weak fields and slow rotation assures that the underlying WD mass–radius solutions do not practically differ from the solutions based on the f(R) gravity without magnetic fields and rotation. In future, we plan to check rigorously by solving the set of equations, if indeed such ϵ is possible in the presence of weak magnetic fields and rotation keeping the mass and radius practically intact. As we will show below, however, the chosen ϵ appears to be the minimally required value to have any appreciable effect. Nevertheless, there are examples of weakly magnetized WD pulsars, which can be explained even in the GR framework, e.g., AE Aquarii (Bookbinder & Lamb 1987) and AR Scorpii (Marsh et al. 2016), where magnetic fields hardly affect their mass–radius relations. Figure 8 shows the PSD as a function of frequency for various detectors along with over 5 s integration time for various f(R)-gravity-induced WD pulsars with different i assuming χ = 90° and r = 100 pc. It is evident that while DECIGO and BBO can immediately detect such weakly magnetized super-Chandrasekhar WDs, the Einstein Telescope can detect them in minutes with S/N ≈ 5 (see Figure 5(b)). However, for ALIA and LISA, the corresponding integration time respectively turns out to be days and yr3 3 Note that even if the threshold S/N for detection increases slightly (say, from 5 to 20), many of these sources can still be detected in a few seconds to a few days of integration time depending on the type of the detectors. . Hence, it is also possible to detect such weakly magnetized WDs using ALIA, whereas for LISA it is quite impossible. Figure 5(b) depicts for these WDs with different integration times to show that S/N increases if the integration time increases so that various detectors can detect them eventually. For such a system, the GW luminosity is given by (Zimmermann & Szedenits 1979) 43 It is expected that a source can emit electromagnetic radiation in the presence of a magnetic field, and it is the dipole radiation in the case of a WD pulsar. However, because of the presence of a weak magnetic field, the dipole radiation emitted from such a WD is minimal, and the corresponding dipole luminosity is negligible as compared to LGW. Hence, the spin-down timescale is mostly governed by LGW, given by (Kalita et al. 2020) 44 Figure 9 shows the variation of LGW and P with respect to M for various WDs with χ = 90°. The maximum LGW in the case of a WD is ∼1037 erg s−1. The empirical relations of LGW and P, in various branches, are same as in the previous case provided in Table 1. It is also clear from the figure that the massive WD pulsars are short-lived as compared to the lighter ones.

2015MNRAS.448..822X__Steinmetz_et_al._2006_Instance_1

Various methods have been developed in the past to derive stellar atmospheric parameters from large number of medium-to-low resolution spectra (Recio-Blanco, Bijaoui & de Laverny 2006; Lee et al. 2008a, Wu et al. 2011). The approaches generally fall into two main categories of method (Wu et al. 2011): the minimum distance method (MDM) and non-linear regression method. Both categories of method have been applied to large stellar spectroscopic surveys, including the SEGUE (Yanny et al. 2009), RAVE (Steinmetz et al. 2006), APOGEE (Majewski et al. 2010) and LAMOST (Zhao et al. 2012). The MDM is usually based on spectral template matching, and searches for the template spectrum that has the shortest distance in parameter space from the target spectrum. The χ2 minimization, cross-correlation, weighted mean algorithm and the k-nearest neighbour are thought to be specific cases of MDM (Wu et al. 2011). Software and pipelines developed based on those algorithms include the tgmet (Katz et al. 1998), matisse (Recio-Blanco et al. 2006), sspp (Lee et al. 2008a), ulyss (Koleva et al. 2009), that of Allende Prieto et al. (2006) and of Zwitter et al. (2008). The non-linear regression method is sometimes also referred to as the artificial neural network. The method constructs a functional mapping between the spectra and stellar atmospheric parameters by training a library of template spectra with non-linear algorithms such as the principal component analysis, and then apply the mapping to target spectra. Related work can be found in Re Fiorentin et al. (2007) and Lee et al. (2008a). In addition to the above two categories of method, other approaches have been developed, for example, the line-index method based on the relations between the stellar atmospheric parameters and the equivalent widths (EWs) of spectral features and/or photometric colours (Beers et al. 1999; Wilhelm, Beers & Gray 1999; Cenarro et al. 2002). More recently, a Bayesian approach to determine stellar atmospheric parameters combing spectral and photometric measurements has been developed by Schönrich & Bergemann (2014).

2016ApJ...832...41M__Helled_et_al._2011_Instance_1

We first discuss the relative bulk enrichment. From internal structure models one can derive the MZ necessary to reproduce the observed mass and radius, and—for the Solar System planets—the gravitational moments. Studies inferring in this way eZ,rel,int of transiting exoplanets have found that eZ,rel,int decreases with increasing mass (left panel of Figure 3). The planetary mass where defines the parity mass M1 (see Appendix B). It is shown in the right panel of Figure 3. It is extrapolated to be between ∼13 and 60 MJup (Miller & Fortney 2011; Thorngren et al. 2015). The planets analyzed in these studies have equilibrium temperatures of less than ∼1000 K (corresponding to an orbital distance of about 0.08 au for a solar-like star) so that they are not affected by the aforementioned bloating mechanisms. A similar decrease of eZ,rel,int with increasing mass is found for the bulk metal content of Solar System giants (Saumon & Guillot 2004; Helled et al. 2011), where the mass where eZ,rel,int reaches 1 is extrapolated to be at about 11 MJup. From theoretical planet population syntheses based on the core accretion theory one finally finds that the parity mass is at about 10 to 18 MJup (Mordasini et al. 2014). Considering that of the 255 extrasolar giant planets (M sin i > 0.1 M) inside of 0.1 au currently listed on www.exoplanets.org (Han et al. 2014) only 4 have a mass exceeding 10 M (which is not an observational bias). We thus deduce that at least based on their masses regarding the bulk composition of hot Jupiters, it appears that almost all of them should be dominated by planetesimal enrichment. We add the caveat that the bulk heavy element content cannot be inferred directly for typical hot Jupiters at equilibrium temperatures of Teq ≳ 1500 K because of bloating mechanisms. But the fact that both the planets analyzed by Miller & Fortney (2011), Thorngren et al. (2015) (a = 0.03–1 au, Teq ≲ 1000 K) and the solar system planets (a ≈ 5–30 au) follow the same trend, makes it appear unlikely—even though in principle not excluded—that the hot Jupiters at a ∼ 0.04 au do not follow the same enrichment pattern.

2020ApJ...888...46C__Singh_et_al._1995_Instance_2

The theoretical models mentioned above have made assumptions. The validity of these assumptions needs to be examined. Besides, all these models involve parameters to be determined. These problems could be better understood through numerical simulations. Hurlburt et al. (1994) performed a two-dimensional numerical simulation of compressible flow on downward overshooting. They investigated the dependence of subadiabatic extent δ on stability parameter S. They revealed a scaling law of δ ∝ S−1 in the penetrative layer and δ ∝ S−1/4 in the overshooting layer, respectively. This result is in good agreement with Zahn’s analytic model (Zahn 1991). Freytag et al. (1996) performed two-dimensional numerical simulations with a realistic description of radiation and ionization on A-type stars and DA white dwarf stars. They described the overshooting as a diffusive process, and derived an exponential decay parameter for the diffusion. Early attempts of low-resolution three-dimensional numerical simulations on overshooting were made by Singh et al. (1994; upward overshooting), Singh et al. (1995, 1998), and Saikia et al. (2000) (downward overshooting). The scaling laws derived from the numerical simulations of downward overshooting (Singh et al. 1995, 1998; Saikia et al. 2000) agree well with Zahn’s analytical model. Only a qualitative result was given in the numerical simulations of upward overshooting (Singh et al. 1994). High-resolution numerical simulations of downward overshooting across a wide range of parameters were presented by Brummell et al. (2002). They confirmed the −1/4 scaling law of the thermal adjustment overshooting layer, while the −1 scaling law of the nearly adiabatic penetrative layer was absent in the simulations. Based on a semianalytic model, Rempel (2004) argued that the absence of the nearly adiabatic penetrative layer is caused by the large energy flux specified in the numerical simulations. Numerical experiments on Boussinesq flow were performed by Korre et al. (2019). They reported steeper scaling laws of δ ∝ S−1/3 or δ ∝ S−1/2, depending on the steepness of the background radiative temperature gradient. Simulations with realistic physical variables on stellar core convection were performed by Browning et al. (2004) and Brun et al. (2005). The effects of rotation and magnetic field are considered. They found that the penetrative convection yields a prolate shape of a nearly adiabatic region. Kitiashvili et al. (2016) performed 3D radiative hydrodynamic simulations of the outer layer of a moderate-mass star (1.47 solar mass). Their result discovered a nearly adiabatic layer and a deeper subadiabatic layer. The recent work of Brun et al. (2017) simulated the differential rotation and overshooting in solar-like stars. Their result indicated that slow rotators favor a wider overshooting region near the poles and fast rotators at mid-to-low latitude. Hotta (2017) performed numerical simulations on the solar overshooting with very low energy fluxes F. He found that the overshooting distance obeys a scaling law of δ ∝ F0.31. Käpylä (2019) conducted numerical experiments on downward overshooting by considering the effect of the smoothness of the heat conduction profiles. He discovered that the power-law index of the overshooting distance on the energy flux is smaller in the smooth heat conduction profile than in the step profile. Efforts on prediction of 321D turbulent theory were made by Arnett et al. (2015) and Arnett & Moravveji (2017). They separated the overshooting region into three layers: a fully mixed layer, a partially mixed wave layer, and an extra diffusive mixing layer. With the scale analysis of turbulent plumes and eddies, Viallet et al. (2015) discussed the three possible regimes of turbulent overshooting: a diffusion-dominated regime (only mix composition), a penetrative regime (transition within the boundary layer), and an entrainment regime (mix both entropy and composition). The selection criterion of different regimes during a stellar evolution calculation is not well defined yet.

2020MNRAS.496.1718E__Wong_et_al._2019_Instance_2

(i) Our capability of reproducing the lensed images down to the noise level without fully correctly modelling the cored central mass density distribution of the lenses indicates some form of the source-position transformation (SPT; Schneider & Sluse 2014), in line with the previous findings by Unruh et al. (2017). As a consequence, our reconstructions lead to a systematic fractional error on the Hubble constant of $25_{-19}^{+37}$ per cent (in comparison to a statical error of $12_{-3}^{+6}$ per cent when the shape of the lensing potential is perfectly known). This result is in agreement with the latest analysis of Blum, Castorina & Simonović (2020) that shows that cored (dark matter) mass density distributions give rise to approximate MSDs, and an error on the inferred Hubble constant. The latest cosmographic analyses (see e.g. Wong et al. 2019) have attempted to break these degeneracies by including the information contained in the kinematic properties of the lens galaxies and the positions of the lensed quasar images. However, the validity of this approach has been recently debated by Kochanek (2020), who has demonstrated that departures from single power-law mass distributions are responsible for a fractional error on the Hubble constant of 30 per cent. While the cores in the simulations analysed in this paper are artefacts related to limited resolution, cored mass density distribution in real galaxies may be developed by the effect of baryonic processes (see e.g. Chan et al. 2015) or changes in the dark matter properties (Schive, Chiueh & Broadhurst 2014; Spergel & Steinhardt 2000). Moreover, similar additional complexities exist in real galaxies are related, for example, to the presence of faint discs (Hsueh et al. 2018), bars, or other (baryonic) structures (Gilman et al. 2018; Xu et al. 2013). More generally, there exist many plausible deviations from a smooth power-law distribution, such as broken power laws (see e.g. Du et al. 2020) or multiple component models (see e.g. Nightingale, Dye & Massey 2018), which can produce comparable degeneracies. Together with the findings of Blum et al. (2020), our results have important implications for the analysis of time delays and a potential solution to the H0 tension (Wong et al. 2019).

2015MNRAS.446.2468E__Choi,_Shlosman_&_Begelman_2013_Instance_1

The equations of motions and hydrodynamics are solved by the ramses code (Teyssier 2002). The gas follows a piecewise polytropic equation of state (EoS) fitting the heating/cooling equilibrium (see Kraljic et al. 2014, and references therein). A Jeans polytrope sets a pressure floor in the most refined volumes, to prevent artificial fragmentation. We refer the reader specifically to sections 2.2, 2.3 and 4.2 of R+13 and Kraljic et al. (2014) for further discussions on this and specific EoS (see Robertson & Kravtsov 2008; Tasker & Bryan 2008; Dobbs, Burkert & Pringle 2011; Bonnell, Dobbs & Smith 2013, for a few other implementation schemes). The resulting gas density probability distribution function (PDF; McKee & Ostriker 2007, and references therein) in the present simulation follows a classic log-normal shape (Nordlund & Padoan 1999; Padoan & Nordlund 2002) with an additional few per cent of the mass in a power-law tail at high density (Choi, Shlosman & Begelman 2013; R+13), as expected from gravity and observed in real molecular clouds and galaxies (Lombardi, Alves & Lada 2010; Druard et al. 2014). While changes in the AMR grid refinement can locally bias the velocity dispersion, the density and velocity power spectra are thus clearly dominated by a single turbulence cascade with a well-identified injection scale at the average Jeans length (Bournaud et al. 2010; R+13). The very high resolution of the present simulation allows to resolve the turbulent cascade with a realistic power spectrum (Combes et al. 2013; R+13) and density distribution (Druard et al. 2014) down to the parsec scale. The simulation comprises conversion of gas into stellar particles (down to 160 M⊙) where the volume density ρ0 exceed 2000 cm−3, assuming that the local star formation rate depends on the free-fall time and with the star formation efficiency set at 3 per cent (R+13). This recipe does not take into account additional physics that may impact on the formation of molecules, and we thus rely on the EoS to follow the cloud collapse, the low temperatures and the high density which triggers the formation of new stars. These newly formed ‘stars’ are evolved on the AMR grid, i.e. with gravitational softening down to 0.05 pc, much smaller than the dark matter and primordial stellar components. The implementation of stellar feedback includes photoionization through heating, radiative pressure via injection of momentum and supernova explosions in the kinetic form (see R+13 for more details). A more thorough study of the impact of resolution or metallicity in such simulations was conducted by Kraljic et al. (2014), who have shown that the artificial density threshold ρ0 does not tune the efficiency of star formation, which mostly depends on the turbulence level (e.g. Mach number; see Klessen 2000; Li et al. 2004; Audit & Hennebelle 2010; Renaud, Kraljic & Bournaud 2012).

2019AandA...631A..35B__Bridges_et_al._(1996)_Instance_2

The collision velocity dependence of the coefficient of restitution between particles was observed in experiments (Bridges et al. 1996; Higa et al. 1996) and is discussed in the literature (e.g., Ramírez et al. 1999; Zhang & Vu-Quoc 2002). However, the experiments by Heißelmann et al. (2010), used in the present paper to support our assumption of a constant coefficient of restitution, do not see a variation of the coefficient of restitution between particles at low collision velocities (≤ 1 cm s−1). This discrepancy in results might originate in the nature of the collisions studied in these different experiments: Bridges et al. (1996) and Higa et al. (1996) performed collisions of a particle with a flat surface, while Heißelmann et al. (2010) observed particle-particle collisions in a free-floating environment. The latter is an experimental environment very similar to NanoRocks. In such inter-particle collisions in free-floating environments, other physical effects lead to a different behavior of the energy dissipation during collisions. In particular, the damping behavior of a large plate or surface is expected to differ from that of a same-sized particle, so that the velocity dependence of the coefficient of restitution might be an effect of the experimental setup in Bridges et al. (1996) and Higa et al. (1996). Colwell et al. (2016) and Brisset et al. (2018) studied collisions between a round cm-sized particle and a flat surface of fine grains. They also observed an increase of the coefficient of restitution with decreasing collision velocity. While the composition of the target surface was different than in Bridges et al. (1996) and Higa et al. (1996) (fine granular material vs. solid ice), the similar behavior of the coefficient of restitution supports the fact that particle-surface collisions are very different from particle-particle collisions, and coefficients of restitution are only velocity dependent for collisions with particles with very different sizes (a much larger particle can be approximated as a target surface).

2021MNRAS.501.2934C__Dong_&_Fung_2017_Instance_1

Understanding how the diverse populations of protoplanetary discs in young stellar regions results in the range of exoplanet types and architectures found in the Galaxy is one of the major goals of planet-formation theory. This is an extremely challenging task due in part to the limited observational constraints available. The Atacama Large Millimetre/submillimetre Array (ALMA) is providing truly transformational images of protoplanetary discs with unprecedented sensitivity and resolution (Andrews 2020). However, millimetre wavelength images reveal the locations of small dust grains but provide little information on the presence of larger particles, beyond centimetre scales. Gas giant planets are mostly made of hydrogen and helium, which ALMA cannot directly observe; therefore, the information on the gas content relies on the observations of less abundant molecules, such as CO and its isotopologues, that are subjected to uncertain depletion processes in the gas-phase (e.g. Miotello et al. 2016). Planets might be detectable by ALMA, although indirectly, by the effects they have on the gas and/or dust in the disc. When planets become massive enough, they can carve gaps (e.g. Rice et al. 2006; Pinilla, Benisty & Birnstiel 2012; Zhu et al. 2012) and disturb the dynamics of the gas (Teague et al. 2018; Casassus & Pérez 2019; Pinte et al. 2019). The minimum gap-opening mass depends on the viscosity and scale-height of the disc (Crida, Morbidelli & Masset 2006; Duffell & MacFadyen 2013), but mini-Neptune-mass (Pérez et al. 2019) or even Earth-mass planets (Rosotti et al. 2016; Dong & Fung 2017) could produce detectable gaps. Gaps consistent with fully formed planets have been imaged by ALMA in discs with estimated ages ranging from 1 Myr (HL Tau and Elias 2–24; ALMA Partnership et al. 2015; Cieza et al. 2017) to ∼10 Myr (TW Hydra; Andrews et al. 2016). However, the origin of these gaps still remains to be established and several alternative explanations have been proposed, including the effect of snow-lines on the dust/gas evolution of different volatiles (Zhang, Blake & Bergin 2015), magneto-hydrodynamic effects (Flock et al. 2015), secular gravitational instability (e.g. Youdin 2011; Takahashi & Inutsuka 2014), and viscous ring-instabilities (Dullemond & Penzlin 2018). Each one of the proposed mechanisms has their merits and shortcomings, and it is possible that different mechanisms operate together or dominate in different objects or in the same object at at different times. For a recent review on disc (sub)structures, see Andrews (2020). Substructures are also expected to be ubiquitous in protoplanetary discs from a theoretical point of view. Without substructures to halt the migration of mm-size grains at large radii, dust particles should migrate towards the innermost part of the disc in time-scales shorter than 0.1 Myr (e.g. Brauer et al. 2007), which is inconsistent with the observations showing significant mm emission at large radii (≳10 au) at much older ages. Understanding the origin and evolution of substructures in protoplanetary discs and their implications for planet formation is currently one the main challenges in the field. To better understand the incidence and properties of disc substructures in any given molecular cloud, here we present 1.3 mm/230 GHz continuum ALMA long-baseline observations at 3–5 au resolution of the 10 brightest targets of the ‘Ophiuchus DIsc Survey Employing ALMA’ (ODISEA) project (Cieza et al. 2019) that were not included in ‘The disc Substructures at High Angular Resolution Project’ (DSHARP) ALMA Cycle-4 Large Program (Andrews et al. 2018). Our new observations result in the largest sample of disc images at ∼3–5 au resolution in any star-forming region observed so far at mm wavelengths (15 objects when combined with the brightest Ophiuchus objects in DSHARP). In Section 2, we discuss the sample selection, the long-baseline observations, and the data reduction. In Section 3, we characterize the observed substructures, including gaps, rings, inner discs, and cavities. In Section 4, we discuss individual objects and use the full sample of 15 bright Ophiuchus discs observed at high-resolution to construct a tentative evolutionary sequence in which the observed substructures are mostly driven by dust evolution and the formation of giant planets. We also discuss possible connections between the substructures observed in primordial discs and those seen in more evolved debris disc systems. A summary of our results and conclusions is presented in Section 5.

2020ApJ...889L..10M__McKay_et_al._2018_Instance_1

As stated earlier, during review of this manuscript Croviser et al. announced in a CBET a tentative water production rate approximately five times larger than our reported value. While the brief nature of the CBET precludes a detailed comparison, we discuss some possible reasons for this discrepancy. At the high airmass of these observations and the small dimensions of the ARCES slit, differential refraction can result in wavelength-dependent slit loss, which can skew flux measurements. However, this is not expected for [O i] 6300 Å emission because this feature is close to the guiding wavelength (∼5500 Å). We confirmed that this is indeed negligible for [O i] 6300 Å emission based on observations of comet C/2012 S1 (ISON) that were performed at a similarly high airmass with ARCES, and found that the production rates derived from the ISON [O i] 6300 Å measurements were consistent with values determined using other methods (McKay et al. 2018). Therefore, we do not consider this or other airmass-dependent phenomena as the reason for the discrepancy. At certain geocentric velocities the cometary [O i] 6300 Å emission sits on top of a strong telluric absorption, and at high airmass inaccurate removal of this feature can result in a decrease in the measured flux and therefore production rate. This was observed for C/2012 S1 (ISON) (McKay et al. 2018). However, the geocentric velocity of 2I/Borisov during our observations was ∼−35 km s−1, while the effect on observed [O i] 6300 Å line fluxes in comet ISON was only observed at geocentric velocities of ∼−50 km s−1. Therefore, this is also not a likely candidate to explain the discrepancy. It is also possible that the activity is highly variable, and we observed Borisov at a minimum in activity, while the Nançay observations, which were coadded over three weeks of observations, provide a long-term average production rate. However, no such variability is observed for CN, with the CN production rate being fairly constant over a several week period (Kareta et al. 2019; Opitom et al. 2019).

2021MNRAS.501...50S__Gupta_et_al._2019_Instance_2

There have been rather strong claims of AGN QPOs in different bands of the electromagnetic spectrum, ranging from minutes through days through months and years (e.g. Gierliński et al. 2008; Lachowicz et al. 2009; Gupta, Srivastava & Wiita 2009; Gupta et al. 2018, 2019; King et al. 2013; Gupta 2014, 2018; Ackermann et al. 2015; Pan et al. 2016; Zhou et al. 2018; Bhatta 2019; and references therein). However, many of the claimed QPOs, particularly those made earlier, were marginal detections (Gupta 2014), lasting only a few cycles, and the originally quoted statistical significances are probably overestimates (Gupta 2014; Covino, Sandrinelli & Treves 2019). Among the better recent claims of QPOs in the gamma-ray band are of ∼34.5 d in the blazar PKS 2247–131 (Zhou et al. 2018) and of ∼71 d in the blazar B2 1520+31 (Gupta et al. 2019) found as part of a continuing analysis of blazar Fermi–LAT observations. A recent claim of a ∼44 d optical band QPO in the narrow-line Seyfert 1 galaxy KIC 9650712 from densely sampled Kepler data has been made by Smith et al. (2018); it was supported by an independent analysis of the same data, indicating a QPO contribution at 52 ± 2 d (Phillipson et al. 2020). Some possibly related QPOs of a few hundred days in two widely separated bands have been reported (Sandrinelli et al. 2016a; Sandrinelli, Covino & Treves 2016b; Sandrinelli et al. 2017). However, an analysis of the Fermi–LAT and aperture photometry light curves by Covino et al. (2019) argued that some multiwaveband QPOs, along with many earlier claims of gamma-ray QPOs, are not significant. Among the gamma-ray QPOs with month-like periods, none showed simultaneous oscillations in a different wavebands. Evidence for related QPOs in multiple wavebands was observed in PG 1553+113, where a QPO was detected in the 0.1–300 GeV and the optical waveband (Ackermann et al. 2015). The observed QPO had a dominant period of ∼754 d and the source showed strong inter-waveband cross-correlations.

2018ApJ...856...94Z__Bieber_et_al._1991_Instance_2

Figures 8 and 9 show the effects of solar activity on the CR parallel λ∥ (blue line), perpendicular λ⊥ (red line), and radial mean free path λrr (gray line) for a proton with rigidity 445 MV (corresponding to a 100 MeV proton) for the inwardly and outwardly directed IMF, respectively. As described in Zank et al. (1998), the parallel mean free path (mfp) based on standard QLT and assuming magnetostatic turbulence is approximated by 13 where , , and . RL is the particle Larmor radius, P is the particle rigidity, and B0 is the mean magnetic field strength. The analytic form of the perpendicular mfp based on NLGC theory is given by (Zank et al. 2004; Shalchi et al. 2010) 14 where a2 = 1/3 is a factor related to the gyrocenter velocity. is a constant such that ν = 5/6 yields a Kolmogorov (1941) spectrum. Note that Equation (14) was derived under the assumption of a specific form of 2D wave spectrum, which is a constant at large turbulence scales. It means that the 2D turbulence spectrum is independent of wavenumber in the energy range in Equation (14). Observation of magnetic fluctuations in the SW indicates that omnidirectional power spectra approach a k−1 wavenumber dependence and that low-frequency turbulence exhibits some sunspot cycle variability (Bieber et al. 1991). Based on this, Engelbrecht & Burger (2015) derived the perpendicular mfp by specifying the energy range spectral index of 2D turbulence power spectra as −1. A more general form of the 2D power spectrum with an energy range spectral index q was proposed by Shalchi et al. (2010). They show that the spectral index has a strong influence on the perpendicular diffusion coefficient. In their model, negative values of q correspond to a decreasing spectrum in the energy range, q = 0 corresponds to the constant spectrum we use here, and positive values of q correspond to an increasing spectrum. Matthaeus et al. (2007) presented a similar spectrum in different regimes: energy range, inertial range, and intermediate regime where the spectrum is proportional to k−1 to coincide with observations (Bieber et al. 1991; Goldstein & Roberts 1999). However, Shalchi (2013) argues that a spectrum that behaves like k−1 does not provide a different perpendicular diffusion coefficient (see also Shalchi et al. 2010), since the field lines for such length scales behave superdiffusively as in the inertial range (Shalchi & Kourakis 2007). In view of this uncertainty, we do not take into account a more elaborate spectrum in the present paper. The behavior of the 2D wave spectrum in the energy range, which may also be correlated with the sunspot cycle, is an important factor in deriving the CR perpendicular mfp. A general form (e.g., Shalchi et al. 2010; Shalchi 2013) should be employed in future studies of CR diffusion.

2019MNRAS.482.5430B__Salmonson_2003_Instance_1

In light of this, the allowed structure of gamma-ray burst (GRB) jets and the efficiency at which it produces gamma-rays at large angles remains a topic of major importance, and it is useful to consider what types of jet structures are consistent with GRB observations (see also Beniamini et al. 2018b). Previous studies have considered the implications of structure models on the true energetics and rates of GRBs (Frail et al. 2001; Lipunov, Postnov & Prokhorov 2001; Rossi, Lazzati & Rees 2002; Zhang & Mészáros 2002; Eichler & Levinson 2004; van Eerten & MacFadyen 2012; Pescalli et al. 2015), on the shape of the afterglow light curve (Granot & Kumar 2003; Kumar & Granot 2003; Salmonson 2003) or on detectability of orphan afterglows (Lamb & Kobayashi 2017). Here, we propose a novel way to test the allowed structure of GRBs (in terms of both the energy and Lorentz factor angular distributions), by applying three independent techniques. We focus on long GRBs for which more detailed observations are available. First, we compare the predictions of these models regarding the EX/Eγ distribution (i.e. the isotropic equivalent early X-ray afterglow to prompt gamma-ray energy ratio) to the observations. We show that a variety of structure models predict large variations in this quantity, in contrast with results from GRB observations. Secondly, we reconsider the effect of the structure on the observed luminosity function and show that a large family of models can be ruled out as they lead to an overproduction of bursts with gamma-ray luminosities below the peak of the observed luminosity function. Both these considerations imply that while the energy angular profile may be steep, the Lorentz factor of GRBs must remain large at any region that produces gamma-rays efficiently. However, even such models typically lead to very peculiar light curves that can be ruled out by observations. The most likely implication is that efficient gamma-ray emission must be confined to a narrow opening angle around the jet’s core, where the isotropic equivalent energy is not much lower than that of the core. This will naturally resolve all the problems mentioned above.

2022MNRAS.513.4361M__Vasudevan_&_Fabian_2007_Instance_1

The photoionization of the disc surface is characterized by two main parameters: irradiating X-ray continuum flux and disc density. Thus the measurement of the disc ionization parameter can address various aspects of the disc/corona interplay. According to Ballantyne, McDuffie & Rusin (2011), the ionization parameter of a radiation pressure supported disc illuminated by a geometrically thick corona in the SS73 model can be approximated as (11)$$\begin{eqnarray*} \xi &\approx & 4.33\times 10^{9}\left(\frac{\eta }{0.1}\right)^{-2}\left(\frac{\alpha }{0.1}\right)\left(\frac{r}{r_{\rm g}}\right)^{-\frac{7}{2}} \nonumber\\ &&\times \,f_{\rm c}(1-f_{\rm c})^{3}\Big (\frac{L_{{\rm bol}}}{L_{{\rm E}}}\Big)^{3}GR_{{\rm corr}}, \end{eqnarray*}$$where radiative efficiency η ≈ 0.1 (Davis & Laor 2011); viscosity parameter α = 0.1 (Shakura & Sunyaev 1973); coronal dissipation fraction fc ≈ 0.45 (Vasudevan & Fabian 2007); r is the disc radius in units of rg; $GR_{{\rm corr}}=R_{{\rm R}}^{3}R_{{\rm z}}^{-2}R_{{\rm T}}^{-1}$ is a general relativistic correction factor and is solely dependent on the dimensionless black hole spin a (e.g. Novikov & Thorne 1993; Krolik 1999). Therefore, the dependence of disc ionization log ξ on the Eddington ratio (Lbol/LE) is predominantly determined by two parameters: r and a: (12)$$\begin{eqnarray*} \log \xi \simeq \varPsi (r,a)\Big (\frac{L_{\rm bol}}{L_{\rm E}}\Big). \end{eqnarray*}$$Fig. 4 shows the dependence of the disc ionization parameter on the Eddington ratio for the low-mass sample. We show the SS73 model predicted log ξ–Lbol/LE relationships for five different combinations of BH spin and inner disc radius: (a = 0.998, r = 2rg), (a = 0.998, r = 6rg), (a = 0.75, r = 6rg), (a = 0.5, r = 6rg), and (a = 0.25, r = 6rg). We noticed that the inferred ionization states of low-mass AGN discs are consistent with the SS73 model predicted solutions. The derived log ξ–Lbol/LE plane suggests that if the relativistic reflection originated from within 6rg of the inner accretion disc, then the measured ionization parameters of the low-mass sample require spins to be in the range of a ∈ [0.25, 0.998] with a median value of ∼0.75.

2019MNRAS.490.2071Y__Riess_et_al._2018_Instance_3

Set II: we now focus on the observational constraints on the model parameters after the inclusion of the local measurement of H0 by Riess et al. (2018) with the previous data sets (CMB, Pantheon, and CC) in order to see how the parameters could be improved with the inclusion of this data point. Since for this present UM, the estimation of H0 from CMB alone is compatible with the local estimation of H0 by Riess et al. (2018), thus, we can safely add both the data sets to see whether we could have something interesting. Following this, we perform another couple of tests after the inclusion of R18. The observational results on the model parameters are summarized in Table 4. However, comparing the observational constraints reported in Table 3 (without R18 data) and Table 4 (with R18), one can see that the inclusion of R18 data (Riess et al. 2018) does not seem to improve the constraints on the model parameters. In fact, the estimation of the Hubble constant H0 remains almost similar to what we found in Table 3. In order to be more elaborate in this issue, we have compared the observational constraints on the model parameters before and after the inclusion of R18 to other data sets. In Figs 7 (CMB versus CMB+R18), 8 (CMB+CC versus CMB+CC+R18), 9 (CMB+Pantheon versus CMB+Pantheon+R18), and 10 (CMB+Pantheon+CC versus CMB+Pantheon+CC+R18), we have shown the comparisons which prove our claim. One can further point out that the strong correlation between the parameters μ and H0 as observed in Fig. 5 still remains after the inclusion of R18 [see specifically the (μ, H0) planes in Figs 7–10]. The physical nature of μ does not alter at all. That means the correlation between H0 and μ is still existing after the inclusion of R18 to the previous data sets, such as CMB, Pantheon, and CC. In addition to that since μ ≲ 0.9 according to all the observational data sets, thus, the transition from past decelerating era to current accelerating era occurs to be around z ≲ 0.6, similar to what we have found with previous data sets (Table 3).

2016ApJ...819L...7N___2015b_Instance_1

The gap and ring resemble those in the HL Tau system, recently found by the ALMA long baseline campaign (ALMA Partnership et al. 2015). Our result shows that gaps and rings in the (sub)millimeter dust continuum can exist, not only in relatively young disks (0.1–1 Myr) but also in relatively old disks (3–10 Myr). One possible mechanism for opening a gap is the gravitational interaction between a planet and the gas (e.g., Lin & Papaloizou 1979; Goldreich & Tremaine 1980; Fung et al. 2014). Such an interaction may also produce the spiral density waves recently found in optical and near-infrared scattered light imaging of dust grains in protoplanetary disks (e.g., Muto et al. 2012). According to recent theoretical analyses of gap structure around a planet (Kanagawa et al. 2015a, 2015b, 2016), the depth and width of the gap are controlled by the planetary mass, the turbulent viscosity, and the gas temperature. The shape of the gap is strongly influenced by angular momentum transfer via turbulent viscosity and/or instability caused by a steep pressure gradient at the edges of a gap. The observed gap has an apparent width and depth of au and , respectively. This is too shallow and too wide compared with that predicted by theory. However, the observations are limited to an angular resolution of ∼15 au, and the depth and width could be deeper and narrower in reality. For instance, if we assume that the gap depth times the gap width retains the value derived from the observations, it is possible for the gap to have a width and depth of 6 au and , which is similar to the GPI result (Rapson et al. 2015). Such a gap could be opened by a super-Neptune-mass planet, depending on the parameters of the disk, such as the turbulent viscosity (Kanagawa et al. 2015a, 2015b, 2016). If the gap in the larger dust grains is deeper than that in the gas, the planet could be lighter than super-Neptune mass. We note that a planet of even a few Earth masses, although it cannot open a gap in the gas, can open a gap in the dust distribution if a certain amount of pebble-sized particles, whose motions are not perfectly coupled to that of gas, are scattered by the planet and/or the spiral density waves excited by the planet (Paardekooper & Mellema 2006; Muto & Inutsuka 2009).

2018MNRAS.478.1884F__Widing_&_Feldman_2001_Instance_1

Several studies indicate that the solar wind produced by the WTD mechanism has higher AHe and vαp, while the solar wind may have lower AHe and vαp when the RLO mechanism is at work. While it is challenging to obtain direct observations of the AHe in the solar corona, first ionization potential (FIP) bias measurements are more readily available. It is found that generally the FIP bias is higher in AR and QS regions (mainly occupied by closed loops) than in CH regions (generally taken up by open magnetic field lines) (Widing & Feldman 2001; Feldman et al. 2005; Brooks & Warren 2011; Baker et al. 2013). It is believed that the reason for the enrichment of the low FIP ions in the corona and the solar wind is that they are ionized earlier in comparison to high FIP elements. The helium has the highest FIP and remains neutral longest. This results in the enrichment/depletion of low FIP elements/helium because only ions interact with waves (Laming 2012, 2015, 2017). It means that the helium abundance should be inversely proportional to the low FIP bias elements in the corona. Thus, the AHe is higher in open magnetic field structures and lower in closed loops if the above mechanism is valid. The helium abundance for the fast SW coming from large CHs is higher and remarkably stable (Schwenn 2006). In contrast, Rakowski & Laming (2012) suggested that the helium is depleted in closed loops and the depletion efficiency is higher in larger loops, and lower in smaller loops. Furthermore, from simulations, Laming (2017) showed that the AHe is higher in open magnetic field regions and it is lower in closed loops. Suess et al. (2009) found that the solar wind that comes from big streamers has lower helium abundance. The solar wind can be produced by interchange reconnection in the streamers (Huang et al. 2016). This gives the observational support to the notion that the AHe is lower in the closed loops as streamer structures are composed by very large closed loops.

2021MNRAS.508.4512L__Haiman_2017_Instance_1

The GW sources that LISA will observe at cosmological distances can be used as standard sirens. These include MBHBs, EMRIs, and SOBHBs. Unfortunately, only for the first of these types of sources are EM counterparts plausibly expected to be produced and observed by future EM facilities (Tamanini et al. 2016). MBHBs are in fact expected to emit a large amount of EM radiation in different bands at merger or during long-lasting (∼ weeks/months) afterglows (see, e.g. Palenzuela, Lehner & Liebling 2010; Dotti, Sesana & Decarli 2012; Giacomazzo et al. 2012; Moesta et al. 2012), and possibly even through pre-merger signals (Kocsis, Haiman & Menou 2008; Kaplan et al. 2011; O’Shaughnessy et al. 2011; Haiman 2017; Dal Canton et al. 2019). If sufficiently accurate sky localization can be attained from the GW parameter estimation analysis and if the EM counterpart is sufficiently powerful to be spotted by EM telescopes, then we expect to identify the host galaxy of up to a few LISA MBHB mergers per year (Tamanini et al. 2016; Tamanini 2017). These golden sources can then be used as high-redshift standard sirens to map the expansion of the Universe up to z ∼ 10. Although the low number of expected EM counterparts and the high redshift of MBHB mergers are not ideal to test standard cosmological models such as ΛCDM or to place constraints on late-time dark energy (DE) (Tamanini et al. 2016; Tamanini 2017; Belgacem et al. 2019b), they can efficiently be used to probe deviations from ΛCDM at earlier cosmological epochs, specifically in the interval 3 ≲ z ≲ 10 (Caprini & Tamanini 2016; Cai, Tamanini & Yang 2017; Belgacem et al. 2019b; Speri et al. 2020). Standard siren analyses with MBHBs would moreover definitely benefit from a network of space-based detectors, e.g. LISA and Taiji, which would greatly improve the sky location accuracy of each MBHBs and thus provide better chances to spot the EM counterpart (see, e.g. Shuman & Cornish 2021; Wang et al. 2021; Yang 2021).

2015MNRAS.453.3414A__Filippenko_&_Chornock_2001_Instance_2

Filippenko & Chornock (2001) first presented the dynamical estimate of mass of the source to be around 7.4 ± 1.1 M⊙. Recently, Radhika & Nandi (2014) claimed that the mass of XTE J1859+226 is perhaps in between 6.58 and 8.84 M⊙ which is similar to the prediction of Shaposhnikov & Titarchuk (2009), although the lower mass limit is estimated as 5.4 M⊙ by Corral-Santana et al. (2011). However, we consider the typical mass of the source as 7 M⊙. The distance of this source is around d ∼ 11 kpc (Filippenko & Chornock 2001). Steiner et al. (2013) measured the spin as ak ∼ 0.4; however, Motta et al. (2014b) recently reported that the spin of the source is ak ∼ 0.34. Since the spin predictions are quite close, we use ak ∼ 0.4 for this analysis. We estimate the fluxes Fx (see Table 1) of LHS and HIMS of the 1999 outburst of the source (Radhika & Nandi 2014). The corresponding disc luminosities are calculated as $L_{\rm disc}^{{\rm LHS}}=8.26 \times 10^{37}\ {\rm erg\ s^{-1}}$ and $L_{\rm disc}^{{\rm HIMS}}=1.85 \times 10^{38}\ {\rm erg\ s^{-1}}$, respectively. Now, it is reasonable to assume the accretion efficiency for rotating BH as η = 0.3 which corresponds to the accretion rate of the inflowing matter as ${\dot{M}}_{{\rm acc}}^{{\rm LHS}} = 0.304 {\dot{M}}_{{\rm Edd}}$ in LHS and ${\dot{M}}_{{\rm acc}}^{{\rm HIMS}} = 0.680 {\dot{M}}_{{\rm Edd}}$ in HIMS. For LHS, we use $R_{\dot{m}}=9.83$ per cent following our theoretical estimate where xs = 64.6rg for ak = 0.4, ${\mathcal {E}}=0.001\,98$ and λ = 3.18. Incorporating these inputs in equation (15), we obtain the jet kinetic power as $L^{{\rm LHS}}_{{\rm jet}} = 2.52\times 10^{37}\ {\rm erg\ s^{-1}}$. The maximum mass outflow rate for HIMS corresponding to ak = 0.4 is obtained from Fig. 9 as $R^{\rm max}_{\dot{m}}=17.5$ per cent for ${\mathcal {E}}=0.005\,47$ and λ = 3.1, where the shock transition occurs at 21.9rg. Using these values in equation (15), we obtain the maximum jet kinetic power as $L^{{\rm HIMS}}_{{\rm jet}} = 1.08\times 10^{38}\ {\rm erg\ s^{-1}}$ which we regard to be associated with the HIMS of this source.

2016MNRAS.455.1905H__Shields_et_al._2003_Instance_1

Galaxies hosting active galactic nuclei (AGN) are not only promising candidates for providing direct evidence for such a co-evolution, they can also be used to study the scaling relations over cosmic times. Many studies suggest that BH growth precedes spheroid assembly (Treu, Malkan & Blandford 2004; McLure et al. 2006; Peng et al. 2006a,b; Shields et al. 2006; Woo et al. 2006, 2008; Salviander et al. 2007; Treu et al. 2007; Gu, Chen & Cao 2009; Jahnke et al. 2009; Bennert et al. 2010, 2011; Decarli et al. 2010; Merloni et al. 2010; Wang et al. 2010); however, other studies find no significant evolution with redshift (e.g. Shields et al. 2003; Shen et al. 2008a; Salviander & Shields 2013; Schramm & Silverman 2013; Salviander, Shields & Bonning 2015; Shen et al. 2015; Sun et al. 2015). The likely reason for the disagreement is that the studies are differently affected by intrinsic scatter in the relation, selection effects, and observational biases (see e.g. Lauer et al. 2007; Volonteri & Stark 2011; Schulze & Wisotzki 2014). Another issue is that the MBH–σ* relation is not well constrained even for local AGN host galaxies at the high-mass end. Especially for the AGN appearing as quasi-stellar objects (QSOs), the bright nuclear point source often outshines its host galaxy. Measurements of the spheroid properties are therefore difficult, in particular the stellar velocity dispersion for which high signal-to-noise (S/N) spectra are needed. Thus, many studies focus on Seyfert galaxies often using aperture spectra which integrates over the central few kpc of the host galaxy (e.g. Greene & Ho 2006; Woo et al. 2006, 2008; Treu et al. 2007; Shen et al. 2008a; Matsuoka et al. 2015). The side effect is that, if present, a significant disc contribution may be included, questioning the definition of the spheroid stellar velocity dispersion in these cases. Bennert et al. (2015) study the effect of different definitions of σ* in the literature for a sample of 66 local Seyfert-1 galaxies and find that it can vary by up to 40 per cent.

2022ApJ...936..102A__Williams_et_al._2006_Instance_1

As regards the modeling of BGK modes, there are two main theoretical approaches: the integral solution or BGK methodology and the differential (or Schamel) technique. In the former method (BGK), one assumes that the initial particle distribution function and the electrostatic potential profiles are known, so these are substituted into the Poisson equation and the integral equation is solved to obtain the trapped particle distribution function (Bernstein et al. 1957; Aravindakshan et al. 2018a, 2018b, and the references therein). In Schamel’s approach, the form of the trapped particle distribution function and of the passing (i.e., free, nontrapped) particle distribution function is assumed and substituted in Poisson’s equation, leading to a differential equation that is then solved to obtain the form of the potential (Schamel 1986; Luque & Schamel 2005, and the references therein). A distinguishing factor in the former (BGK) approach is that it involves a condition in the form of an inequality to be satisfied by the potential parameters (width and amplitude) in order for a BGK mode to be sustained. The BGK approach will be adopted in this work. The above models tacitly assume a collisionless electron-ion plasma. These assumptions are acceptable in the Earth’s magnetosphere. However, as we move farther from near-Earth plasma environments, the presence of charged dust in the plasma cannot be neglected. In the case of Saturn, there are observations of streaming ions by the Cassini spacecraft (Badman et al. 2012a, 2012b). We know that these streaming ion flows can lead to the generation of ion holes. Electrostatic solitary waves have been observed in Saturn’s magnetosphere (Williams et al. 2006) and in the dusty environment near its moon Enceladus (Pickett et al. 2015). Williams et al. (2006) reported observations of solitary structures in the vicinity of Saturn’s magnetosphere. They detected a series of bipolar pulses and speculated that these could be either electron holes or ion holes (Williams et al. 2006). Later on, Pickett et al. (2015) observed solitary wave pulses within 10 Rs (Rs is the Saturn radius) and near Enceladus. Near the Enceladus plume, they discussed how dust impacts affected the observed solitary waves. In fact, Pickett et al. (2015) pointed out that some of the bipolar electric field pulses associated with the solitary waves observed had an inverse polarity (i.e., a positive pulse first, followed by a negative pulse in a short time period) and suggested that this might be due to either an inverse direction of propagation or to a true inverse potential pulse polarity (sign). Moreover, Farrell et al. (2017) examined the conditions that allow low-energy ions, such as those produced in the Enceladus plume, to be attracted and trapped within the sheath of negatively charged dust grains. Using particle-in-cell simulations, they showed that with dust in the system, the large electric field from the grain charge disrupts pickup and leads to ion trapping. Their simulation results also reveal that the bipolar pulses reported in the Enceladus plume by Williams et al. (2006) and Pickett et al. (2015) could most probably be ion holes. In the light of the above information, we may suggest that the formation of ion holes is highly likely in the dusty plasma of environments such as the one found in Saturn. Importantly, the instrument on board Cassini, the Radio Plasma Wave Science instrument, does not have the ability to determine the polarity of the electric fields associated with the ESWs observed with 100% certainty as it lacks the ability to perform interferometry (Williams et al. 2006).

2021ApJ...907...47L__Lee_et_al._2019_Instance_3

In Figure 8, we also find small differences in the [Na, Al, O/Fe] abundance ratios between the stars in the bright and faint RC groups, although it is not as clear as in the case of [Na, Al, O/H] abundances. In particular, unlike Figure 7, stars in the bRC group are more enhanced in [Na/Fe] but appear to be more depleted in [Al/Fe] and [O/Fe] than those in the fRC group. The mean differences are 0.053 ± 0.021 dex, 0.032 ± 0.018 dex, and 0.071 ± 0.045 dex in [Na/Fe], [Al/Fe], and [O/Fe], respectively, which are marginally significant at p-values of 0.22, 0.18, and 0.23. When the relative fraction of RC stars is taken into account (27%; see Section 4), the difference in [Na/Fe] between the genuine RC stars would correspond to Δ[Na/Fe] ∼ 0.20 dex, which is comparable to that expected from our chemical evolution model for the bulge stars (Δ[Na/Fe] = 0.2 ∼ 0.3 dex; Kim & Lee 2018; Lee et al. 2019).10 10 The previous study by Lee et al. (2019) noted a clear separation of the two groups according to Na abundance among bright RGB stars in the outer bulge. The apparent lack of such a distinct difference between the two groups in this study may be due to a larger uncertainty on abundances of relatively faint sample stars. The overall chemical patterns, however, are not identical to those observed in typical GCs, where the later-generation stars are more enhanced in [Na, Al/Fe] and more depleted in [O, Mg/Fe] than the first-generation stars at a given metallicity, although the trend of [Na, Al O/Fe] between the two RCs is less clear. Figure 9 shows the comparison of stars in this study with stars in metal-rich GCs ([Fe/H] > −1.0) on the Na–O diagram. The stars used in this study have a different distribution from stars in GCs. Although the bRC group is slightly more enhanced in [Na/Fe] and more depleted in [O/Fe] than the fRC group, the [Na/Fe] variation of RC stars is smaller than that of GC stars. This discrepancy might imply the different chemical evolution between stars in the bulge and typical GCs. We note, however, that even though we employ only metal-rich GC stars for the comparison, the majority of stars are still far more metal-poor ([Fe/H] −0.5) than stars in the bulge. Because the relatively small [Na/Fe] variation is expected from the chemical evolution model for metal-rich bulge stars and the O-depletion is indistinct in some metal-rich GCs, such as NGC 6121 and 47 Tuc (see Kim & Lee 2018; Lee et al. 2019), the direct comparison of bulge stars with similarly metal-rich GCs on the Na–O plane would require further spectroscopic observations for such GCs in the bulge.

2017MNRAS.472.1361B__Salvo_&_Stella_2002_Instance_1

Historically, the explanation of soft state spectra of NSs demanded the presence of a blackbody emission from the boundary layer of an NS (Mitsuda et al. 1984). For the harder states with a power-law tail in the energy spectrum, the need of Compton scattering became evident (White et al. 1986; Mitsuda et al. 1989). The difference between these two models was that while the former assumed a cooler boundary layer, the latter assumed a hotter one, compared to the accretion disc. Sunyaev and his collaborators (Inogamov & Sunyaev 1999, hereafter IS99; Popham & Sunyaev 2001, hereafter PS01; Gilfanov & Sunyaev 2014 , hereafter GS14) assume that the KD reaches all the way to the NS and is connected with the boundary layer where the thickness increases due to higher temperature. Most of these studies were done to address the soft state spectra of NSs. The state transition of NSs in Low Mass X-ray Binaries (LMXBs), presented another problem. The fact that disc accretion rate was not the single factor that controlled the size or temperature of the Compton cloud, used to model the hard state spectra, lead to the conclusion that some unknown parameter, related to the truncation radius of the disc, is responsible for the hard X-ray tail (Barret 2001; Barret & Olive 2002; Di Salvo & Stella 2002). Paizis et al. (2006) found a systematic positive correlation between the X-ray hard tail and the radio luminosity, inferring that the Compton cloud might serve as the base of radio jets (see Chakrabarti 2016, and references therein). Recent phenomenological works places a transition layer (TL) or Compton cloud between the KD and the boundary layer (Farinelli et al. 2008; Titarchuk, Seifina & Shrader 2014, hereafter TSS14). It has been argued in the past (Chakrabarti 1989; C96; Chakrabarti & Sahu 1997) that while in black hole accretion, passing of the flow through the inner sonic point ensures that the flow becomes sub-Keplerian just outside the horizon, in the case of NSs, the Keplerian flow velocity must slow down to match with the sub-Keplerian surface velocity. Numerical simulations clearly showed that jumping from a KD to a sub-Keplerian disc is mediated by a super-Keplerian region (Chakrabarti & Molteni 1995). In Titarchuk, Lapidus & Muslimov (1998, hereafter TLM98), a super-Keplerian TL was invoked to explain the kHz quasi-periodic oscillations (QPOs) and in TSS14 the TL was expanded several fold to explain the spectral properties. In reality, there are two such layers simultaneously present in an NS accretion: One is similar to the NBOL and the other is similar to the CENBOL in a black hole accretion (CT95). In a black hole accretion, only CENBOL is present. All these approaches clearly point to the existence of a CENBOL type hot electron reservoir, which naturally occurred in black hole accretion, confirming Chakrabarti & Sahu (1997) conclusions that the solutions of the transonic flows are modified only in the last few Schwarzschild radii as per the boundary condition of the gravitating object.

2018MNRAS.479.3254V___2000_Instance_2

The lifetime of molecular clouds (MCs) remains an active research topic in the study of the interstellar medium and star formation, and most recent studies, both observational and theoretical, place this lifetime at a few times 107 yr for clouds in the 105–106M⊙ mass range (e.g. Blitz & Shu 1980; Kawamura et al. 2009; Zamora-Avilés, Vázquez-Semadeni & Colín 2012; Zamora-Avilés & Vázquez-Semadeni 2014; Lee, Miville-Deschênes & Murray 2016). In addition, several observational studies have suggested that the star formation rate (SFR) of the clouds appears to increase over their lifetimes. For example, studies of young clusters embedded in moderate-mass MCs (∼104M⊙) (e.g. Palla & Stahler 1999, 2000; Da Rio et al. 2010) have shown that their age histograms contain a large majority of young (1–2 Myr) objects, but also a tail of older (up to several Myr) ones suggesting an accelerating star formation activity, sometimes followed by a subsequent decline (see also Povich et al. 2016; Schneider et al. 2018). In addition, Kawamura et al. (2009) reported a clear evolutionary process over the lifetime of giant molecular clouds (GMCs; of masses ∼105–106M⊙) in the Large Magellanic Cloud, evidenced by the increasing number of massive stars across the sequence of GMC ‘classes’ proposed by those authors. Finally, on the basis of the large scatter in the observed star formation efficiency (SFE) in Milky Way GMCs, Lee et al. (2016) have concluded that the SFR in those clouds must also be time variable. Numerical simulations of MC formation and evolution also exhibit time varying, increasing SFRs during their early stages (e.g. Vázquez-Semadeni et al. 2007; Hartmann, Ballesteros-Paredes & Heitsch 2012). Also, in the presence of stellar feedback, at late times the SFRs reach a maximum and begin to decrease again (e.g. Vázquez-Semadeni et al. 2010; Colín, Vázquez-Semadeni & Gómez 2013). Vázquez-Semadeni, González-Samaniego & Colín (2017) have recently shown that the simulations of Colín et al. (2013) in fact produce stellar age histograms highly resemblant of the observed ones (Palla & Stahler 1999, 2000; Da Rio et al. 2010), and reproduce observed radial age gradients in clusters (Getman et al. 2014) as well as bottom-heavy stellar initial mass functions (IMFs) in scattered regions of massive star formation (Povich et al. 2016).

2017AandA...602A..82D__Kirkpatrick_et_al._2012_Instance_1

Brown dwarfs and giant exoplanets populate the same temperature range and share many physical properties, such as their molecule-dominated atmospheres and gradual cooling from ~3000 K at formation to ~100 K like the solar system gas-giant planets. Recent discoveries of very massive planets (Chauvin et al. 2005; Marois et al. 2010; Delorme et al. 2013), some possibly more massive than the 13 MJup deuterium burning mass limit, hint that planets could overlap with brown dwarfs in mass. On the other hand, the discovery of isolated L dwarfs in young clusters (Zapatero Osorio et al. 2002, 2014; Peña Ramírez et al. 2012), in young moving groups (Liu et al. 2013; Gagné et al. 2015; Gauza et al. 2015), and very cold very nearby Y dwarf objects (e.g., Kirkpatrick et al. 2012; Luhman 2014) show that very low-mass isolated brown dwarfs exist and overlap with the planetary masses. When these low-mass brown dwarfs are close enough and bright enough to be observed spectroscopically their atmospheres are much easier to study than similar exoplanets that lie near their very bright host stars. Liu et al. (2013) notably showed that the ~8 MJup brown dwarf PSO J318.5−22, a β-pictoris moving group member shares the spectral characteristics of the young directly imaged exoplanets, as well as atypically red late-L spectral type objects (e.g., Faherty et al. 2013; Gizis et al. 2015; Kellogg et al. 2016; Schneider et al. 2014, 2016; Bonnefoy et al. 2016). When CFBDSIR J214947.2−040308.9, hereafter CFBDSIR 2149, was identified (Delorme et al. 2012), it seemed to be a candidate member of the AB Doradus young moving group and, together with the low-gravity features in its spectrum, made it a unique T-type isolated planetary-mass candidate. Another earlier-type, isolated young planetary-mass T-dwarf, SDSS J111010.01+011613.1, has been identified as a bona fide member of AB Doradus moving group (\hbox{$149^{+51}_{-19}$}149-19+51 Myr; Bell et al. 2015) by Gagné et al. (2015). The late-T spectral type of CFBDSIR 2149 is typical of the coolest known directly imaged exoplanets, such as GJ 504 b or 51 Eri b (Kuzuhara et al. 2013; Macintosh et al. 2015), that the latest generation of adaptive optics systems are detecting. We therefore carried out a multi-wavelength, multi-instrument follow-up of CFBDSIR 2149 to fully characterise it and constrain its nature.

2020MNRAS.498.1496M__Dopita_&_Sutherland_1996_Instance_1

The spectra from Sloan Digital Sky Survey (SDSS) have enabled the detection of the relatively faint He ii λ4686 line in large samples of star-forming galaxies (e.g. Shirazi & Brinchmann 2012). These studies find that the observed He ii λ4686/H β intensity ratio does not drop at low metallicities. In fact, recent studies find the ratio to be increasing as the metallicity decreases (Schaerer, Fragos & Izotov 2019). Furthermore, these low-metallicity He ii λ4686-emitting galaxies often show only a weak or no evidence of the presence of WR stars (Shirazi & Brinchmann 2012). Thus, questions have been raised on the WR stars as the sole source of ionization of He+ (Plat et al. 2019). Alternative mechanisms such as hard radiation from high-mass stars in binaries (Eldridge et al. 2017), shocks from supernova remnants (Garnett et al. 1991; Dopita & Sutherland 1996), and high-mass X-ray binaries (HMXBs; Schaerer et al. 2019; Kojima et al. 2020) are often invoked. Nearby low-metallicity systems offer an opportunity to address the He+ ionization problem by enabling study of individual star-forming knots. In a detailed study of the metal-poor (Z = 3–4 per cent Z⊙) galaxy SBS 0335−052E using MUSE, Kehrig et al. (2018) discard WR stars as the source of ionization and instead propose rotating metal-free stars or a binary population with Z = 10−5 and an extremely top-heavy initial mass function (IMF) as the only plausible way of getting around the problem of the ionization budget. In a recent study, Schaerer et al. (2019) find that the observed He ii λ4686 intensity in metal-poor star-forming galaxies can be naturally reproduced if the bulk of the He+ ionizing photons is emitted by the HMXB, whose number is found to increase with decreasing metallicity. X-ray binaries in a cluster appear only after the death of the most massive stars, and hence this scenario cannot explain the He+ ionization in young systems [H β equivalent widths (EWs) ≥ 200 Å], as illustrated by Plat et al. (2019).

2018MNRAS.478L..18T__Zhang_et_al._2004_Instance_1

The discovery of GW170817 and its electromagnetic counterparts (GRB170817A and AT2017gfo; Abbott et al. 2017a; Coulter et al. 2017; Goldstein et al. 2017) ushered in a new era of multimessenger astrophysics, in which both gravitational waves and photons provide complementary views of the same source. While observations at optical and infrared wavelengths unveiled the onset and evolution of a radioactive-powered transient, known as kilonova, observations at X-rays and, later, radio wavelengths probed a different component of emission, likely originated by a relativistic outflow launched by the merger remnant. Troja et al. (2017) explained the observed X-ray and radio data as the onset of a standard short GRB (sGRB) afterglow viewed at an angle (off-axis). However, as already noted in Troja et al. (2017) and Kasliwal et al. (2017), a standard top-hat jet model could explain the afterglow data set collected at early times, but failed to account for the observed gamma-ray emission. Based on this evidence, Troja et al. (2017) suggested that a structured jet model (e.g. Zhang et al. 2004; Kathirgamaraju, Barniol Duran & Giannios 2018) provided a coherent description of the entire broad-band data set. Within this framework, the peculiar properties of GRB170817A/AT2017gfo could be explained, at least in part, by its viewing angle (see also Lamb & Kobayashi 2017; Lazzati et al. 2017). An alternative set of models invoked the ejection of a mildly relativistic wide-angle outflow, either a jet-less fireball (Salafia, Ghisellini & Ghirlanda 2018) or a cocoon (Nagakura et al. 2014; Hallinan et al. 2017). In the latter scenario, the jet might be chocked by the merger ejecta (Mooley et al. 2017), and the observed gamma-rays and broad-band afterglow emission are produced by the expanding cocoon. The cocoon may be energized throughout its expansion by continuous energy injection. In this paper detailed models of structured jet and cocoon, from its simplest to more elaborate version, are compared with the latest radio to X-ray data. Predictions on the late-time evolution are derived, and an unambiguous measurement capable of disentangling the outflow geometry, jet versus cocoon, is presented.

2022ApJ...924...42N__Cheng_et_al._1990_Instance_1

It is generally thought that the emission from radio to medium energy gamma rays is generated by the injected electrons through the synchrotron radiative mechanism. The high-energy photon emission mainly comes from inverse Compton (IC) scattering of the high-energy electrons on the background seed photons, which include the synchrotron background, the cosmic microwave background, and infrared photons in the PWNe (see, e.g., Zhang et al. 2008; Fang & Zhang 2010; Torres et al. 2013; Lu et al. 2020). On the other hand, it is also suggested that the gamma rays could be emitted by the hadronic processes. The relativistic protons accelerated in the Crab pulsar outer gap interact with the matter inside the nebula. and this process may contribute in the high-energy gamma-ray range (see, e.g., Cheng et al. 1990; Bednarek & Protheroe 1997; Khangulyan et al. 2020; Cao et al. 2021). Therefore, it has been long debated whether the high-energy emission from the PWNe is the leptonic or hadronic origin. The details of the high-energy radiation produced by leptonic process have been discussed for the Crab Nebula (see, e.g., Venter & de Jager 2007; Zhang et al. 2008; Martín et al. 2012), and that of the gamma-ray emission about the hadronic process have been also investigated (see, e.g., Cheng et al. 1990; Bednarek & Protheroe 1997; Bednarek 2003, 2007). However, with the establishment of more and more high-energy observatories, some telescopes have possessed the performance of observing photons of exceeding to the PeV from the astronomic objects. An increasing number of observational data has been reported by the different experiments. For example, the Amenomori et al. (2019) reported that the Tibet air shower array with the underground water-Cerenkov-type muon detector array observed the highest energy photons of exceeding 100 TeV with a 5.6σ statistical significance and pointed the measured spectrum with energy extended to the sub-PeV from the Crab Nebula have an absence of high-energy cutoff. Recently, more than 530 photons at energies above 100 TeV and up to 1.4 PeV from the 12 ultra-high-energy gamma-ray sources with a statistical significance greater than seven standard deviations were reported again by LHAASO (Cao et al. 2021). Together with the earlier investigations about the leptonic scenario, the radiative spectrum from the leptons has a cutoff around the sub-PeV region (see, e.g., Zhang et al. 2008; Martín et al. 2012; Zhang et al. 2020). It seems that the other components of gamma rays have a significant contribution.

2021AandA...645A..99C__analysis,_Uttley_et_al._(2011)_Instance_1

X-ray reverberation in black hole X-ray binaries was first robustly detected in GX 339–4 by Uttley et al. (2011) when the source was in its hard state. Previous studies of GX 339–4 pointed to the approximate central mass being ≥6 M⊙ (e.g. Hynes et al. 2003) and a small disc inclination angle (De Marco et al. 2015). Miller et al. (2008) fitted the Suzaku spectra and found that the central black hole has a very high spin, a ∼ 0.998. The X-ray spectroscopic analysis of the hard state spectra from the RXTE archive carried out by García et al. (2015) suggested the black hole spin to be a ∼ 0.95. Spectral fitting of GX 339–4 during its very high flux state using NuSTAR and Swift also suggested a high spin of a ∼ 0.95 (Parker et al. 2016). According to the time-lag analysis, Uttley et al. (2011) found that the disc thermal emission (∼0.3–0.7 keV, soft band) leads the power-law variations (∼0.7–1.5 keV, hard band) on long timescales (> 1s). Mahmoud et al. (2019) assumed that the soft component that leads the power-law emission is a soft Comptontized component. Rapisarda et al. (2016) and Rapisarda et al. (2017) instead modelled it as a variable inner region of the thin disc. However, the disc black-body variations lag behind the power-law variations by a few milliseconds on short timescales ( 1s). This switch from low-frequency hard to high-frequency soft lags is thought to be produced by two distinct mechanisms. While the hard lags are likely due to inward propagating fluctuations (e.g. Kotov et al. 2001; Arévalo & Uttley 2006), the soft lags can be explained by thermal reverberation associated with the longer light-travel time the hard photons take from the central power-law X-ray source to the disc where they are reprocessed into relatively soft black-body emission. The thermal reverberation lags then provide clues to the geometry of the X-ray source and the inner accretion flow close to the event horizon of the central black hole.

2020AandA...635A..60D__Castelli_&_Kurucz_2003_Instance_1

We further constrain the stellar parameters for HD 85628 using the Virtual Observatory SED Analyzer (VOSA)5 and fitting the Hα profile of the star’s CHIRON spectrum. We fit the spectral energy distribution (SED; Fig. 8) of HD 85628 using published photometry from Tycho (BT VT; ESA 1997), APASS (BV; Henden et al. 2016), Gaia DR2 (BpRpG; Gaia Collaboration 2018), DENIS (JK; Epchtein et al. 1994), 2MASS (JHKs; Skrutskie et al. 2006), and WISE (W1W2W3W4; Wright et al. 2010), and fit Kurucz ATLAS9 stellar atmosphere models (Castelli & Kurucz 2003). Given that the star is clearly main sequence and relatively young ( 1 Gyr), we constrain the surfacegravity to be within ±0.5 dex of log g = 4.0 and metallicity within ±0.5 dex of solar, and include the extinction and 1σ uncertainty presented previously as a constraint, but allow the effective temperature to float. We find the best-fit parameters to be for a Kurucz model with Teff, = 7844 $^{57}_{-285}$−285+57 K, log g = 4.0, and solar metallicity. We also fitted the shape of the Hα line from the average high-resolution CHIRON spectra with a grid of Kurucz spectra (as used above). While we fail to meaningfully constrain its metallicity and surface gravity in this way, the spectral line shape is consistent with a temperature of 7700 ± 300 K. Based on these independentanalyses, we adopt Teff ≃ 7800 ± 200 K. We note that this is somewhat cooler than expected given the A3V classification by Houk & Cowley (1975), since typical A3V stars have Teff ≃ 8550 K (Pecaut & Mamajek 2013), however we cannot reconcile such a hot temperature given the available data, leading us to believe that the initial classification was incorrect, and that this star is in fact an A7V star. The best-fit luminosity to SED fit using the VO Sed Analyzer (VOSA) tool, and adopting the distance based on the Gaia DR2 trigonometric parallax, is L = 12.23 ± 0.0655 L⊙ or log (L∕L⊙) ≃ 1.087 ± 0.023 dex. For the adopted effective temperature, this implies that HD 85628 has a radius of 1.92 ± 0.11 R⊙ 6.

2017MNRAS.469S.731L__Hearn_et_al._2011_Instance_1

The optical, spectrocopic and infrared remote imaging system (OSIRIS) scientific imaging cameras on the Rosetta spacecraft have been monitoring the coma activity of comet 67P Churyumov–Gerasimenko (67P hereafter) since their orbital rendezvous in 2014 August (Lara et al. 2015; Lin et al. 2015; Sierks et al. 2015; Lin et al. 2016; Shi et al. 2016; Vincent et al. 2016a,b). The solar heating of the sunlit side of the nucleus surface leads to sublimation of the volatiles and to the formation of dust jets. On 2015 March 12, a small outburst was first detected from a part of the Imhotep region on the night side (Knollenberg et al. 2016). Such mini-outbursts or night-side activities have been observed before at comet 9P/Tempel 1 by the Deep Impact mission (Farnham et al. 2007, 2013) and comet 103P/Hartley 2 by the EPOXI mission (A’Hearn et al. 2011; Bruck Syal et al. 2013). Shortly before the close approach to comet 9P/Tempel 1, the high-resolution camera on the Deep Impact spacecraft found a number of small, well-defined jets whose bases were rooted at the nucleus surface. Some of these, called limb jets, appeared to come from the darker regions and appeared to be associated with the ice patches reported by Sunshine et al. (2006). A later mission of the Stardust–New Exploration of comet Tempel 1 (NExT) imaging of 9P/Tempel 1 allowed us to connect the jets with cliffs (Farnham et al. 2013). Comet 103P/Hartley 2 also displayed several narrow jet features emitting from the un-illuminated regions beyond the terminator at the time of the flyby observations (Bruck Syal et al. 2013). Unlike the less certain identification of the source regions on Tempel 1, the source region of the night-side jets of 103P/Hartley 2 could be clearly traced to some rough surface topography. However, the mechanism for this type of activity is still unknown. Fortunately, unlike the snap shots from the previous flyby observations, the OSIRIS measurements can provide precise information on the timing and location of the outbursts via a time series of high-resolution images. After the first detection in 2015 March, the OSIRIS wide-angle camera (WAC) and narrow-angle camera (NAC) captured another outburst in mid-July of 2015. Since then, many more outbursts from the night-side and sunlit regions have been detected (Feldman et al. 2016; Grün et al. 2016), with most of their source regions located in the Southern hemisphere of comet 67P (Vincent et al. 2016a). The detected outburst events show a variety of morphological features that can be classified into three different types: broad fans, narrow jets and complex plumes. In this work, we investigate the morphology of these events and characterize their physical properties in detail, including the surface brightness profiles, ejected mass and speed if there are two or more sequential images acquired by the same filter in short duration during the time frame of the outburst.

2017AandA...601A..72I__Kobayashi_&_Tanaka_2010_Instance_2

Small grains, which contribute most to infrared emission, are removed by collisional fragmentation and blown out by radiation pressure. The removal timescale is much shorter than the ages of host stars. Disruptive collisions among underlying large bodies, which are called planetesimals, produce smaller bodies and collisional fragmentation among them results in even smaller bodies. This collisional cascade continues to supply small grains. The evolution of debris disks has been explained by the steady-state collisional cascade model (e.g., Wyatt 2008; Kobayashi & Tanaka 2010): the total mass of bodies decreases inversely proportional to time t. Therefore, the excess ratio (Fdisk/F∗) is given by (2)\begin{equation} \frac{F_{\rm disk}}{F_{*}} = \frac{t_0}{t},\label{cc} \end{equation}FdiskF∗=t0t,where t0 is the dissipation timescale that is determined by the collisional cascade. Under the assumption of the steady state of collisional cascade, the power-law size distribution of bodies is analytically obtained and the power-law index depends on the size dependence of the collisional strength of bodies (see Eq. (32) of Kobayashi & Tanaka 2010). In the obtained size distribution, erosive collisions are more important than catastrophic collisions (see Fig. 10 of Kobayashi & Tanaka 2010). Taking into account the size distribution and erosive collisions, we derive t0 according to the collisional cascade (see Appendix E for derivation), (3)\begin{eqnarray} t_0&\sim& 1.3 \left( \frac{s_{\rm p}}{\rm 3000\,km} \right)^{0.96} \left( \frac{R}{\rm 2.5\,au} \right)^{4.18}\nonumber\\ &&\quad\times \left(\frac{\Delta R}{0.4 R}\right) \left( \frac{e}{\rm 0.1} \right)^{-1.4} {\rm Gyr},\label{eq:t0} \end{eqnarray}t0~1.3sp3000 km0.96R2.5 au4.18where sp is the size of planetesimals, R is the radius of the planetesimal belt, and e is the eccentricity of planetesimals. Interestingly, t0 is independent of the initial number density of planetesimals (Wyatt et al. 2007). Note that the perturbation from Moon-sized or larger bodies is needed to induce the collisional fragmentation of planetesimals (Kobayasi & Löhne 2014), which is implicitly assumed in this model.

2021MNRAS.502.2859N__Evans_&_Howarth_2008_Instance_2

It is harder to evaluate the behaviour of the young stellar population along the line of sight, since radial velocity measurements for our sample of Cepheids, needed for a thorough study, do not exist. Given this deficit, we provide only a simplified estimate using radial velocities of OBA-type stars from Evans & Howarth (2008). Since they belong to the same young population, we assume that they have a similar distance distribution and kinematics as the Cepheids. Fig. 16 shows the massive star sample in the plane of the sky. Except for the northernmost region (δ ≥ −72○), where no data exist, these stars cover a comparable area to the Cepheids (indicated as grey dots in the figure for comparison). The radial velocities show a distinct and well-known gradient across the SMC with higher velocities in the eastern part (see also fig. 5 of Evans & Howarth 2008). Such a gradient in radial velocity is also present in older (few Gyr) RGB stars (see fig. 9 of Dobbie et al. 2014). This gradient is commonly attributed to rotation of the SMC. Based on our results obtained for the Cepheids, we propose a different interpretation: this line-of-sight velocity gradient may instead be caused by the fact that the nearest parts of the galaxy, in the region of the SMC Wing, move with a higher radial velocity compared with the main body of the galaxy. Given the additional differences in tangential velocities, these outer parts might be in the process of being stripped from the SMC. Diaz & Bekki (2012) show in their simulations that tidal effects can produce a velocity gradient that is similar to that of a rotating disc. We stress again that this interpretation is based on the assumption that the Cepheid sample and the OBA-type stellar sample trace a similar three-dimensional distribution. For any conclusive answer, radial velocities of the Cepheid stars are required. Such measurements will be provided by the One Thousand and One Magellanic Fields (1001MC) survey (Cioni et al. 2019), which is a consortium survey with the forthcoming multi-object spectrograph 4MOST that will be mounted on the VISTA telescope.

2017MNRAS.465..248J__Tristram_et_al._2007_Instance_1

First direct evidence for the geometrical distribution of the dust was found by Jaffe et al. (2004) with the help of the mid-infrared interferometric instrument (MIDI; Leinert et al. 2003) at the Very Large Telescope Interferometer (VLTI). One of the best-studied parsec-sized dust distribution is harboured by the Circinus galaxy, which is the closest (4.2 Mpc, 1 arcsec ≈20 pc; Freeman et al. 1977) and the second brightest Seyfert galaxy in the MIR. High-resolution mid-infrared (MIR) interferometric observations have revealed a two-component morphology in the brightness distribution: (i) a larger scale, elongated component in direction of the ionization cone (along PA ≈ 107°) with a full-width at half-maximum (FWHM) size of roughly 0.8 × 1.9 pc, which is responsible for 80 per cent of the total MIR flux and was interpreted either as the directly illuminated funnel walls of the dusty molecular torus or as part of the (filamentary/clumpy) outflow; (ii) a disc-like component with an FWHM size of roughly 0.2 × 1.1 pc and elongated along PA ≈ 46° (Tristram et al. 2007, 2014). Both components have a dust temperature of roughly 300 K. The disc-like component was modelled by two Gaussian emitters (a highly elongated emitter plus an unresolved source) in the simple model used by Tristram et al. (2014). This was interpreted as signs for a more complex structure as well as for asymmetry in the second component. The orientation and size of the disc-like component coincides with an edge-on warped disc seen in maser emission with the help of very long baseline interferometry traced by H2O masers (Greenhill et al. 2003). It has an outer radius of roughly 0.4 pc. A similar picture emerges for NGC 1068: A hot parsec-scale disc (FWHM ≈1.35 × 0.45 pc, T ≈ 800 K) was found with similar orientation and extent as the H2O maser disc (Greenhill et al. 1996; Greenhill & Gwinn 1997). It is surrounded by warm dust extended in polar direction with an FWHM ≈3 × 4 pc and a temperature T ≈ 300 K (Jaffe et al. 2004; Raban et al. 2009). However, in a systematic study of a larger sample of objects a large range of properties of the dust distribution has been found (Burtscher et al. 2013).

2016MNRAS.456..512C__Kronberg_et_al._2004_Instance_2

Extended radio emission in galaxies is associated with both radio jets and lobes and with outflows, seen often as aligned radio sources in the opposite directions with respect to the central compact radio core. Giant radio galaxies (GRG) are extreme cases of this phenomenology with jets and lobes extending on ∼ Mpc scales suggesting that they are either very powerful or very old site for electron acceleration. In this respect, GRGs have a crucial role in the acceleration of cosmic rays over large cosmic scales (e.g. Kronberg et al. 2004), in the feedback mechanism of AGNs into the intergalactic and intracluster medium (e.g. Subrahmanyan et al. 2008) and in the seeding of large-scale magnetic fields in the universe (e.g. Kronberg et al. 2004) and they are excellent sites to determine the total jet/lobe energetics in AGN-dominated structures (see e.g. Colafrancesco 2008, Colafrancesco & Marchegiani 2011). To date our knowledge of GRGs (see e.g. Ishwara-Chandra & Saikia 1999, 2002; Lara et al. 2001; Machalski, Jamrozy & Zola 2001; Schoenmakers et al. 2001; Kronberg et al. 2004; Saripalli et al. 2005; Malarecki et al. 2013; Butenko et al. 2014) is limited by their sparse numbers and by the difficulty of detecting them over large areas of the sky. Low-frequency radio observations have an enhanced capacity to detect the extended old electron population in these objects (see e.g. the recent Low Frequency Array – LOFAR – observation of the GRG UGC095551), but high-frequency radio observations are less efficient in this task due to the steep-spectra of giant radio lobes. In this context these sources will be ideal targets for the next coming deep, wide-field surveys like, e.g. the ATLAS survey of the Australia Telescope Network Facility (ATNF; see Norris et al. 2009) or the Square Kilometre Array (SKA) deep surveys that will have the potential to study their population evolution up to high redshifts and thus clarifying their role on the feedback for the evolution of non-thermal processes in large-scale structures.

2018ApJ...853...50F__Bernard_et_al._2015b_Instance_1

However, using the well-assessed new post-AGB evolutionary models, we confined the main-sequence ages of our halo sample to be mostly ∼2–5 Gyr, with the oldest being ∼6–8 Gyr, while the outer-disk sample are mostly ≲1–4 Gyr. We thus conjecture that our targets probably formed prior to the encounter with M33. Obviously, our sample represents the population that is different from the underlying, smooth, extended (and mostly metal-poor) halo component of M31 (Ibata et al. 2007, 2014), which was formed through the repeated accretion of smaller galaxies in the distant past. These bright PNe seem to resemble the younger, metal-rich population in the outer stream of M31, as revealed by HST pencil-beam pointings on the Giant Stream (Brown et al. 2006a; Bernard et al. 2015b). The metallicity of the stream fields was enriched continuously from [Fe/H] ∼ −1.5 to at least solar level about 5 Gyr ago (Bernard et al. 2015b). This timeline of metal enrichment is generally consistent with the stellar ages of our metal-rich sample. N-body simulations suggested that the Giant Stream and other stream-like features in the halo are debris of a massive (≳109– ) progenitor that was recently disrupted during the course of a merger (e.g., Ibata et al. 2004; Fardal et al. 2006, 2007, 2008, 2013; Font et al. 2006; Geehan et al. 2006; Mori & Rich 2008; Sadoun et al. 2014). The extended star formation history and the broad range of metallicity (−1.5 ≲ [Fe/H] ≲ 0.2) discovered in the stream fields can be explained by a disk galaxy progenitor (Brown et al. 2006a, 2006b; Bernard et al. 2015b). If the stellar streams in M31's halo indeed have a common origin, our sample of halo PNe then probably formed through extended star formation in this possibly massive, disk-like progenitor. Moreover, some simulations predict that the remnant of the disrupted satellite resides in the NE Shelf (e.g., Fardal et al. 2008, 2013; Sadoun et al. 2014); PN17 in our sample is located in this region and might be associated with this substructure (see Section 4.4).

2021MNRAS.500.5009M__Bono_et_al._2003_Instance_1

RR Lyrae are old low-mass stars that, during the central helium-burning phase, show mainly radial pulsation while crossing the classical instability strip in the colour–magnitude diagram. From the observational point of view, they represent the most numerous class of pulsating stars in the Milky Way and, being associated with old stellar populations, are typically found in globular cluster and abundant in the Galactic halo and bulge. The investigation of RR Lyrae properties is motivated by their important role both as distance indicators and tracers of old stellar populations. In particular, evolving through the central helium-burning phase, they represent the low-mass, Population II counterparts of Classical Cepheids, as powerful standard candles and calibrators of secondary distance indicators. In particular, they can be safely adopted to infer distances to Galactic globular clusters (see e.g. Coppola et al. 2011; Braga et al. 2016, 2018, and references therein), the Galactic centre (see e.g. Contreras Ramos et al. 2018; Marconi & Minniti 2018; Griv, Gedalin & Jiang 2019), and Milky Way satellite galaxies (see e.g. Coppola et al. 2015; Martínez-Vázquez et al. 2019; Vivas et al. 2019, and references therein). Being associated with old stellar populations, they represent the basis of an alternative Population II distance scale (see e.g. Beaton et al. 2016, to the traditionally adopted Classical Cepheids), more suitable to calibrate secondary distance indicators that are not specifically associated with spiral galaxies (e.g. the globular cluster luminosity function, see Di Criscienzo et al. 2006, and references therein). The properties that make RR Lyrae standard candles are (i) the well-known relation connecting the absolute visual magnitude MV to the metal abundance [Fe/H] (see e.g. Sandage 1993; Caputo et al. 2000; Cacciari & Clementini 2003; Catelan, Pritzl & Smith 2004; Di Criscienzo, Marconi & Caputo 2004; Federici et al. 2012; Marconi 2012; Marconi et al. 2015, 2018; Muraveva et al. 2018, and references therein); (ii) the period–luminosity relation in the near-infrared (NIR) filters and in particular in the K 2.2 μm band (see e.g. Longmore et al. 1990; Bono et al. 2003; Dall’Ora et al. 2006; Coppola et al. 2011; Ripepi et al. 2012; Coppola et al. 2015; Marconi et al. 2015; Muraveva et al. 2015; Braga et al. 2018; Marconi et al. 2018, and references therein). In spite of the well-known advantage of using NIR filters (see e.g. Marconi 2012; Coppola et al. 2015, and references therein), in the last decades there has been a debate on the coefficient of the metallicity term of the KB and PL relation (see e.g. Bono et al. 2003; Sollima, Cacciari & Valenti 2006; Marconi et al. 2015, and references therein). On the other hand, it is interesting to note that many recent determinations (see e.g. Sesar et al. 2017; Muraveva et al. 2018) seem to converge towards the predicted coefficient by Marconi et al. (2015), with values in the range 0.16-0.18 mag dex−1. As for the optical bands, our recently developed theoretical scenario (Marconi et al. 2015) showed that, apart from the MV−[Fe/H] relation that is affected by a number of uncertainties (e.g. a possible non-linearity, the metallicity scale with the associated α elements enhancement and helium abundance variations, as well as evolutionary effects, see Caputo et al. 2000; Marconi et al. 2018, for a discussion), the metal-dependent Period–Wesenheit (PW) relations are predicted to be sound tools to infer individual distances. In particular, for the B-, V- band combination, Marconi et al. (2015) demonstrated that the inferred PW relation is independent of metallicity. In order to test this theoretical tool, we need to compare the predicted individual distances with independent reliable distance estimates, for example, the astrometric ones recently obtained by the Gaia satellite (Gaia Collaboration 2016). To this purpose, in this paper we transform the predicted light curves derived for RR Lyrae models with a wide range of chemical compositions (Marconi et al. 2015, 2018) into the Gaia bands, derive the first theoretical PW relations in these filters and apply them to Gaia Data Release 2 Data base (hereinafter Gaia DR2; Gaia Collaboration 2018; Clementini et al. 2019; Ripepi et al. 2019). The organization of the paper is detailed in the following. In Section 2, we summarize the adopted theoretical scenario, while in Section 3 we present the first theoretical light curves in the Gaia filters. From the inferred mean magnitudes and colours, the new theoretical PW relations are derived in Section 4 that also includes a discussion of the effects of variations in the input chemical abundances. In Section 5, the obtained relations are applied to Gaia Galactic RR Lyrae with available periods, parallaxes, and mean magnitudes to infer independent predictions on their individual parallaxes, to be compared with Gaia DR2 results. The conclusions close the paper.

2021AandA...656A..16C__Bruno_&_Carbone_2013_Instance_1

Investigations of the turbulent nature of solar wind fluctuations have been ongoing for more than half a century (see, e.g., Bruno & Carbone 2016). Advances have been made consistently thanks to the increasingly accurate measurements of several dedicated space mission as well as to the enormous improvement of numerical calculation, new detailed models and theoretical frameworks, and the development of specific data analysis techniques. Nevertheless, the extremely complex nature of the system and the coexistence of multiple actors, scales, and dynamical regimes have led to a number of questions that remain open (Viall & Borovsky 2020). Among these, the very nature of the turbulent cascade of the solar wind flow and its relationship with the small-scale processes still need to be described in full (Tu & Marsch 1995; Bruno & Carbone 2013; Matthaeus & Velli 2011; Chen 2016). Magnetic field fluctuations have been characterized with great detail at magnetohydrodynamic and kinetic scales, for example, through spectral and high-order moments analysis (Tu & Marsch 1995; Bruno & Carbone 2013). The anisotropic nature of magnetic turbulence has also been addressed, and is still being debated, due to the limited access to three-dimensional measurements in space (see, e.g., Horbury et al. 2008, 2012; Sorriso-Valvo et al. 2010; Yordanova et al. 2015; Verdini et al. 2018; Telloni et al. 2019a; Oughton & Matthaeus 2020). Velocity fluctuations have been studied thoroughly (see, e.g., Sorriso-Valvo et al. 1999; Bruno & Carbone 2013), although the kinetic scales still remain quite unexplored for instrumental limitations, most notably in the sampling time resolution. Both the velocity and magnetic field show highly variable turbulence properties, with well developed spectra, strong intermittency (Sorriso-Valvo et al. 1999), anisotropy, and linear third-order moments scaling (Sorriso-Valvo et al. 2007; Carbone et al. 2011). The level of Alfvénic fluctuations (mostly but not exclusively found in fast streams, see e.g., D’Amicis et al. 2011; Bruno et al. 2019) are believed to be associated with the state of the turbulence. In particular, solar wind samples containing more Alfvénic fluctuations are typically associated with less developed turbulence, as inferred from both shallower spectra and reduced intermittency (see Bruno & Carbone 2013, and references therein). This is consistent with the expectation that uncorrelated Alfvénic fluctuations contribute to reduce the nonlinear cascade by sweeping away the interacting structures (Dobrowolny et al. 1980), as also confirmed by the observed anticorrelation between the turbulent energy cascade rate and the cross-helicity (Smith et al. 2009; Marino et al. 2011a,b).

2021ApJ...917...24Z__Coughlin_et_al._2020b_Instance_1

Our simulation results show that the median detectable distances of targeted GW events from BH–NS mergers for a single 2nd generation GW detector and a network of such detectors are ∼300 Mpc and ∼700 Mpc, respectively (see Table 4). For comparison, Figure 12 shows that the detection rate and detectable distance for HLV (O3) are approximately the same as those for the case when only bKAGRA is running. This is basically consistent with the detection rate and the distance distribution of BH–NS merger candidates detected during LVC O3 (e.g., Anand et al. 2020; Antier et al. 2020b; Coughlin et al. 2020b; Gompertz et al. 2020; Kasliwal et al. 2020). In Section 3, we have shown that the kilonova absolute magnitude at 0.5 days after a BH–NS merger is mainly distributed in the range ∼–10 to ∼–15.5. In view of the fact that the limiting magnitude of the follow-up wide-field survey projects is almost ≲21 mag (e.g., Antier et al. 2020b; Gompertz et al. 2020; Coughlin et al. 2020b; Kasliwal et al. 2020; Wyatt et al. 2020), the maximum detectable distance for BH–NS kilonovae would be ≲200 Mpc, which can hardly cover the horizon of GW-triggered BH–NS merger events that O3 found (as shown in Figure 10). However, although BH–NS merger kilonovae can hardly be detected for the present search depths, Figures 9 and 11 reveal that there are great opportunities to discover on-axis afterglows associated with sGRBs or orphan afterglows if the BH components have a high-spin distribution. In order to cover the distance range for searching for BH–NS kilonovae for the network of 2nd generation GW detectors as completely as possible, a search limiting magnitude mlimit ≳ 23–24 is required as shown in Figure 10. Present survey projects could reach this search limiting magnitude by increasing exposure times and the number of simultaneous exposures. However, the GW candidates during O3 had very large localization areas with an average of thousands of square degrees (Antier et al. 2020b). Increasing exposure times makes it hard for the present survey projects to cover such large localization areas. Therefore, during the HLVK era, we recommend that survey projects may search for jet afterglows after GW triggers with a relatively shallow search limiting magnitude. If BH–NS mergers have a high location precision, a limiting magnitude of mlimit ≳ 23–24 can be reached, which gives a higher probability of discovering associated kilonovae.

2020AandA...641A..85S__Dallacasa_et_al._2000_Instance_1

Compact symmetric objects are very powerful (P1.4 GHz > 1025 W Hz−1), compact (linear size of 50–100 pc), and young (≲104 yr) objects with a rather symmetric radio structure and convex synchrotron radio spectra (Wilkinson et al. 1994; Murgia 2003; Polatidis & Conway 2003). The characterized convex synchrotron radio spectrum peaks at around 100 MHz in the case of compact steep spectrum (CSS) sources, at about 1 GHz in the case of GHz-peaked spectrum (GPS) objects, and up to a few GHz (e.g., 5 GHz) in the case of high-frequency peakers (HFPs; Dallacasa et al. 2000). The turnover is explained as synchrotron self-absorption (SSA) affecting in a small radio-emitting region or the free-free absorption (FFA) by the dense ambient medium. In a “young scenario”, as the source grows, the inner region (possibly a tiny radio lobe) expands, and as a result, the turnover frequency moves to lower frequencies. In this scenario, the HFPs are newborn radio sources that develop into extended radio sources (e.g., FR I, FR II) after evolving through GPS and CSS stages. It is possible that the activity is recurrent in at least some sources: there have been observations of faint extended emission around a few GPS sources (e.g., Baum et al. 1990; Stanghellini et al. 1990; Marecki et al. 2003). The extended emission could be a relic of an earlier active period, into which the reborn radio jets are expanding. Another popular explanation for the turnover and compact natures of CSS, GPS, and HFP is the “frustration” hypothesis. This theory argues that these sources are confined in small spatial scale and high-density environments, and as a consequence the radio emission is frustrated by the abundant nuclear plasma (van Breugel et al. 1984; Peck et al. 1999; Tingay & de Kool 2003; Callingham et al. 2015; Tingay et al. 2015). In addition, An & Baan (2012) also proposed that young sources with strong constant AGN power breaking through the dense inner region of the host galaxy could result in the compact morphology and the turnover properties of CSOs.

2019AandA...630A.131M__Chartas_et_al._2009_Instance_1

Comptonisation Monte Carlo code (MoCA; see Tamborra et al. 2018 for a detailed description of the code) is based on a single photon approach, working in a fully special relativistic scenario. MoCA allows for various and different physical and geometrical conditions of the accretion disc and of the Comptonising corona. In this paper, the corona is assumed to have either a spherical or a slab-like geometry, and to be as extended as the disc, whose radii have been set to be Rout = 500 rg and Rin = 6 rg, respectively. Even though arguments (e.g. variability, Uttley et al. 2014, and references therein, microlensing Chartas et al. 2009; Morgan et al. 2012 and timing Kara et al. 2016; De Marco et al. 2013) exist that favour a compact corona, we used extended coronae. In fact, as discussed by Marinucci et al. (2019), Comptonised spectra emerging from compact corona (Rout = 100 rg–Rin = 6) do not deviate significantly from those produced in more extended corona; see their Fig. 3. The adoption of even more compact coronae (Rout = 20 rg, Rin = 6) results only in the need for higher optical depths to recover the same spectral shape for a given temperature. However, in such cases, general relativity (GR) effects are not negligible (see Tamborra et al. 2018, for a detailed discussion on this topic), and the present version of MoCA does not include GR. For the slab-like geometry case, MoCA allows the user to set up the corona height above the accretion disc (set to 10 rg in our simulations). We use synthetic spectra computed assuming the source BH mass and accretion rate to be the same as those of Ark 120 (e.g. Marinucci et al. 2019, and references therein), namely MBH = 1.5 × 108 M⊙ and ṁ = Lbol/LEdd = 0.1. For both the slab and spherical hot electron configurations, we simulated the Comptonised spectra using a wide range of values for electron temperature and optical depth: 0.1   τ   7 and 20 kT 200 keV, and in Fig. 1 we show a sample of spectra obtained by MoCA. Moreover, spectra are computed from 0.01 keV up to 700 keV using 1000 logarithmic energy bins, and a Poissonian error accompanies each spectral point. The obtained spectra are averaged over the inclination angle and in Fig. 1 we show some exemplificative spectra normalised at 1 keV accounting for the two geometries considered in this work.

2022MNRAS.517.4119T___2017_Instance_1

SN 2011fe, discovered a mere ≈11 h after explosion (Nugent et al. 2011) by the Palomar Transient Facility (PTF; Law et al. 2009), is the brightest SN Ia since the advent of modern astronomical detectors. Located at just $d_L \approx 6.5~\rm {Mpc}$ (e.g. Shappee & Stanek 2011; Beaton et al. 2019), SN 2011fe exploded in a region of M101 uncontaminated by intervening dust (Patat et al. 2013) providing an ideal location for testing SN Ia progenitor and explosion models. The early detection allowed extensive follow-up observations across the electromagnetic spectrum (e.g. Matheson et al. 2012; Parrent et al. 2012; Pereira et al. 2013; Hsiao et al. 2013; Johansson, Amanullah & Goobar 2013; Tsvetkov et al. 2013; Munari et al. 2013; Mazzali et al. 2014; Zhang et al. 2016) and provided direct constraints on the radius of the exploding star (Nugent et al. 2011; Bloom et al. 2012). Stringent non-detections in radio (Chomiuk et al. 2012; Horesh et al. 2012; Kundu et al. 2017) and X-ray (Horesh et al. 2012; Margutti et al. 2012) observations exclude nearby CSM at high significance. Early ultraviolet (UV) photometry did not show any evidence for the ejecta encountering a nearby companion star (Brown et al. 2012) and nebular spectra lacked the Balmer emission lines from material ablated off the donor star by the ejecta impact (Shappee et al. 2013b; Lundqvist et al. 2015; Tucker et al. 2022). Pre-explosion imaging excludes the presence of a RG or He donor star (Li et al. 2011) and disfavor an accreting WD in the ∼105 yr prior to explosion (Graur, Maoz & Shara 2014). Multi-epoch spectropolarimetry reveal consistently-low continuum polarization suggestive of a symmetric ejecta distribution with evidence for minor oblateness (Milne et al. 2017). Finally, nebular-phase observations at ≳ 1 year after maximum light allows a direct view to the inner ejecta and provides unique constraints on the explosion conditions (McClelland et al. 2013; Kerzendorf et al. 2014, 2017; Mazzali et al. 2015; Graham et al. 2015; Taubenberger et al. 2015; Dimitriadis et al. 2017; Friesen et al. 2017; Shappee et al. 2017; Tucker et al. 2022). SN 2011fe is one of the best-studied astronomical objects in the past decade and remains a key benchmark for any SN Ia theory or model.

2015AandA...580A.135D__Hunt_et_al._2010_Instance_1

How does the propagation of radiation and the ISM composition affect ISM observables in low-metallicity galaxies? Addressing this question is important to understand the evolution of low-metallicity galaxies, which undergo more bursty star formation than normal galaxies. Nearby star-forming dwarf galaxies present distinct observational signatures compared to well-studied disk galaxies. Dwarfs are usually metal poor, H i rich, and molecule poor as a result of large-scale photodissociation (e.g., Kunth & Östlin 2000; Hunter et al. 2012; Schruba et al. 2012). Mid-IR (MIR) and far-IR (FIR) observations have revealed bright atomic lines from H ii regions ([S iii], [Ne iii], [Ne ii], [O iii], etc.) and PDRs ([C ii], [O i]) (e.g., Hunter et al. 2001; Madden et al. 2006; Wu et al. 2008; Hunt et al. 2010; Cormier et al. 2015). Their spectral energy distributions (SEDs) are also different from spiral and elliptical galaxies and indicative of altered dust properties, with a relatively low abundance of polycyclic aromatic hydrocarbons (PAHs) and perhaps a different dust composition (e.g., Madden et al. 2006; Galliano et al. 2008; Rémy-Ruyer et al. 2013). It is still unknown, however, whether these differences between dwarf and disk galaxies are the direct result of recent star formation activity shaping the ISM or instead a consequence of the low-metallicity ISM that is independent of star formation activity. To answer this, one needs to observe tracers of the interplay between the ISM and various stages of star formation activity. While there are now a number of important studies available on PDR properties modeling FIR lines on large scales in various extragalactic environments (e.g., Kaufman et al. 2006; Vasta et al. 2010; Graciá-Carpio et al. 2011; Cormier et al. 2012; Parkin et al. 2013) or in our Galaxy under solar-metallicity conditions (e.g., Cubick et al. 2008; Bernard-Salas et al. 2012, 2015), only a few studies are published on individual extragalactic regions (Mookerjea et al. 2011; Lebouteiller et al. 2012). Of particular interest are dwarf galaxies, where the effect due to radiative feedback is expected to be most significant. The goal of this paper is to investigate how the low-metallicity ISM reacts under the effects of star formation in regions that have undergone different histories. The nearby low-metallicity galaxy NGC 4214 provides an excellent environment to perform this experiment because it has well-separated star-forming centers, one hosting a super star cluster, which allows us to study the effects of extreme star-forming conditions on the surrounding ISM.

2018ApJ...854...26L__Tian_2017_Instance_1

The hot emission line of Fe xxi 1354.09 Å and the cool emission line of Si iv 1402.77 Å have been used in many spectroscopic studies to investigate chromospheric evaporation (e.g., Tian et al. 2014, 2015; Li et al. 2015b, 2017a, 2017b; Brosius et al. 2016; Zhang et al. 2016a, 2016b). It is widely accepted that the forbidden line of Fe xxi 1354.09 Å is a hot (log T ∼ 7.05) and broad emission line during solar flares (Doschek et al. 1975; Cheng et al. 1979; Mason et al. 1986; Innes et al. 2003a, 2003b). Meanwhile, IRIS spectroscopic observations show that Fe xxi 1354.09 Å is always blended with a number of cool and narrow emission lines, which are from neutral or singly ionized species. Those blended emission lines can be easily detected at the position of the flare ribbon, including known and unknown emission lines, such as the C i line at 1354.29 Å, the Fe ii lines at 1353.02 Å, 1354.01 Å, and 1354.75 Å, the Si ii lines at 1352.64 Å and 1353.72 Å, and the unidentified lines at 1353.32 Å and 1353.39 Å (e.g., Li et al. 2015a, 2016a; Polito et al. 2015, 2016; Tian et al. 2015, 2016; Young et al. 2015; Tian 2017). In order to extract the hot line of Fe xxi 1354.09 Å and the cool line of C i 1354.29 Å (log T ∼ 4.0; Huang et al. 2014), we apply a multi-Gaussian function superimposed on a linear background to fit the IRIS spectrum at the “O i” window (e.g., Li et al. 2015a, 2016a), which has been pre-processed (i.e., IRIS spectral image deformation, bad pixel despiking and wavelength calibration) with the standard routines in Solar Soft Ware (SSW; Freeland et al. 2000). In short, the line positions and widths of these blended emission lines are fixed or constrained, and their peak intensities are tied to isolated emission lines from similar species. More details can be found in our previous papers (Li et al. 2015a, 2016a). On the other hand, the cool line of Si iv 1402.77 Å (log T ∼ 4.8) at the “Si iv” window is relatively isolated, and it can be well fitted with a single-Gaussian function superimposed on a linear background (Li et al. 2014, 2017a). Using the relatively strong neutral lines (i.e., “O i” 1355.60 Å and “S i” 1401.51 Å), we also perform an absolute wavelength calibration for the spectra at the “O i” and “Si iv” windows, respectively (Tian et al. 2015; Tian 2017). Finally, the Doppler velocities of Fe xxi 1354.09 Å, C i 1354.29 Å, and Si iv 1402.77 Å are determined by fitting line centers removed from their rest wavelengths (Cheng & Ding 2016b; Guo et al. 2017; Li et al. 2017a). As the hot Fe xxi line is absent in the non-flaring spectrum, the rest wavelength for the Fe xxi line (i.e., 1354.09 Å) is determined by averaging the line centers of the Fe XXI profiles which were used in the previous IRIS observations (Brosius & Daw 2015; Polito et al. 2015, 2016; Sadykov et al. 2015; Tian et al. 2015; Young et al. 2015; Brosius et al. 2016; Lee et al. 2017), while the rest wavelengths for the C i and Si iv lines, i.e., 1354.29 Å and 1402.77 Å, respectively, are determined from their quiet-Sun spectra (Li et al. 2014, 2015a).

2018ApJ...862....8T__Hull_et_al._2017a_Instance_1

Interstellar turbulence is supposed to be one of the most important factors to regulate star formation activities. Shocks induced by supersonic turbulence dramatically increase the density and temperature in the post-shock layer and promote the structure formation, such as dense cores and protostars (e.g., Padoan 1995; Padoan & Nordlund 2002; Klessen et al. 2005; Matsumoto et al. 2015a; Inoue et al. 2018). Observational studies have been attempting to search for dense cores that originated from turbulent phenomena. Recent systematic surveys with ALMA found that there are no or a few starless cores with their internal substructures originating from turbulent fragmentation (cf., Padoan & Nordlund 2002; Offner et al. 2010) in each star-forming region (Dunham et al. 2016; Kirk et al. 2017). On the contrary, complex spatial/velocity gas structures in the protostellar envelopes with the spatial scale from 0.1 pc down to a few tens of astronomical units are also revealed both by the single-dish observations and the interferometric observations (e.g., Tobin et al. 2011; Tokuda et al. 2014, 2016; Maureira et al. 2017). Some multiscale polarization observations and numerical simulations suggest that turbulent motions, rather than magnetic fields, are dynamically important to form complex gas morphologies of protostellar envelopes (Hull et al. 2017a, 2017b). To understand such diversities/complexities at early stages of star formation, it is important to investigate physical properties of structures originating from the turbulent gas kinematics. In early phases of star formation, the shock waves can be formed by interactions among different density gas with the different velocities because the gas motions, such as infalling/outflowing gas, are supersonic. Detections of high-J transitions of molecular lines (e.g., CO) excited by magnetohydrodynamic (MHD) shocks have been expected by theoretical modelings (e.g., Pon et al. 2012; Lehmann & Wardle 2016). Recent submillimeter observations (e.g., Shinnaga et al. 2009; van Kempen et al. 2009a, 2009b; Kristensen et al. 2013) have detected warm envelopes seen in high-J CO lines from protostellar sources. However, the origin and heating mechanisms of warm gas in low-mass star-forming dense cores are still under debate. For example, van Kempen et al. (2009b) suggested several origins to produce the high-J CO lines; (1) inner envelope heated by protostellar luminosity, (2) shocked gas in the outflow, and (3) quiescent gas heated by UV photons. Shinnaga et al. (2009) also detected the extended CO (J = 6–5, 7–6) emission with the size scale of a few thousand astronomical units in our current target, MC27/L1521F (see also later descriptions in this section). They argued that the warm gas may be coming from shock regions created by interactions between the collapsing envelopes and the internal disk-like materials around the protostar. Although their observations were not able to resolve the internal substructures of the dense core due to the lack of the angular resolution, they pointed out the importance for investigating such warm gas formed in an early phase of star formation to understand the evolution from dense cores to protostars.

2022ApJ...939..103R__Markwardt_2009_Instance_1

We analysed the change as a function of time, by using annual groups of line intensities for each instrumental setup as independent data points d i . The baseline is taken as time t 0 = 2012.45, which is the mean time point of our original data, 16.31 years after the discovery of the event (Nakano et al. 1996). The total process follows an exponential decline (see Equation (7)). As the total timescale τ rec is so much longer than the epoch of our investigation, a free parameter, giving the curvature of the exponential, cannot be derived unambiguously and numerically stably. Thus we use the Taylor series linear approximation here. We derive independent model regression points m i of the type 2 mi=c(ti−t0)+n,where∑idi−mi2σi2→Min, with c being the average annual change. As mentioned above the errors σ i vary strongly for some lines (see also Table 2). Thus Equation (2) does not resemble the χ 2 definition where σi∝mi anymore. Thus standard regression algorithms used widely do not apply (York 1966; Giordano & Iavernaro 2021; Lecuna et al. 2020). The regression analysis follows Tellinghuisen (2020). The derived value of n normalizes each of the data sets with respect to the line strengths at t 0. This is slightly different from using just a weighted mean for the time t 0, but is numerically more stable against the strong year-on-year variations of the errors, which are seen especially for the helium lines. For the regression the mpfit library (Markwardt 2009) was used, with the variable errors handled according to York (1966) in the implementation of Tellinghuisen (2020). The errors given by the mpfit library for the c parameter represent the statistical error with two parameters for the calculation of the degrees of freedom. However, we are primarily interested in the significance of any slope, rather than the parameter c (respectively, its normalized counterpart C k from Equation (3)) and its potential contribution to the statistical error budget. To derive the significance of the slope, a C program was written to perform a Monte Carlo (MC) simulation. The value n from Equation (2) defines the normalized values d¯i≔di/n and σ¯i≔σi/n given in Table 2. Each data point d¯i was varied independently 10 million times in agreement with its individual Gaussian error distribution, and a new regression for the normalized change C k ∀ k ∈ [1, 107] was calculated with model points M i types as 3 Mi=Ck(ti−t0)+Ni,where∑id¯i−Mi2σ¯i2→Min. Moreover, a similar set of parameters from the same MC simulated data points, assuming that there was no change in time-defining model points M, was derived 4 Mi=Ni,where∑id¯i−Mi2σ¯i2→Min. The fractional area of overlap A between the “sloping” and “non-sloping” distribution functions yields the statistical significance (1 − A) of the slope as a single parameter. This significance is lower than what would be derived from the standard deviation of the inclination (relative change per year) given by the fit with two free parameters. Figure 7 shows an example of such a pair of histograms. A priori this solution of the MC simulation, caused by the wide spread of errors between the individual data points, does not have to be distributed as a Gaussian. Tests indeed showed that it deviates from solutions with large slopes. As the result for our cases only shows very small slopes, there is only a marginal deviation from a Gaussian. As the assumption of a regular standard deviation holds we are able to use the error function erf from the integral of the Gaussian according to Equation (5) to derive the size of the intersect 5 A=1−erf−x2, and from this the level x × σ of significance.

2017ApJ...839...83W__Orlando_et_al._2016_Instance_1

A closer look at the known ejecta-dominated SNRs supports the role of surrounding winds and/or shells, and may provide additional insight into why such remnants are so rare. Several, and perhaps all of them, are ones where the ejecta are expanding into a pre-SN stellar wind from the progenitor, or into a cavity carved out by such winds. The clearest case is for Cas A, where the light-echo spectrum of the actual SN that shows it to have been a Type IIb event (Rest et al. 2008; Krause et al. 2008). These are produced from the collapse of the helium core of a red supergiant that had lost most of its hydrogen envelope before exploding, so the ejecta expand into the stellar wind from the pre-SN star (Chevalier & Oishi 2003; Orlando et al. 2016). The extreme luminosity of NGC4449-1 has been best explained by its expansion into a dense and extensive circumstellar environment produced by winds from its massive progenitor, possibly with additional contributions due to winds from other massive stars in the surrounding dense OB cluster (Milisavljevic & Fesen 2008). For G292.0+1.8 and E0102–7219, the fact that fast knots of ejecta are expanding ballistically 2000–3000 yr after the explosion requires that they must be expanding into low-density cavities—ones evacuated by pre-SN winds. In both cases, there is an outer shell of X-ray emission where the SN blast wave is interacting with the CSM. As with Cas A, this interaction also leads to the reverse shock that excites the dense fragments of ejecta, producing the optical emission. For both Puppis A and N132D, spectra of the outer radiative filaments show them to be very high in nitrogen; these too are likely overtaking winds enriched by dredged-up nitrogen. These stripped-envelope SNe—types Ib and Ic—are relatively rare compared to their cousins, types II and IIL, that explode with their envelopes more or less intact; the recent review by Smartt (2009) indicates that together SN Ib and Ic comprise only ∼20%–30% of core-collapse events.

2017ApJ...835L...1W__Peixoto_&_Oort_1992_Instance_1

In this work, we investigate how the climate of an Earth-like planet is affected when its orbit is perturbed by the presence of a nearby giant planet. For the first time, a GCM coupled with analytical equations that describe the orbital evolution of a terrestrial planet are used. An additional major difference between our work and previous studies is that we utilize a fully coupled ocean model and an Earth continental layout. This is in contrast to WP2002 who used a 50 m “thermodynamic slab” ocean model without horizontal ocean heat transport or Linsenmeier et al. (2015), who used an aquaplanet model and a 50 m slab ocean, but again with no horizontal ocean heat transport. We use a fully coupled ocean model because alongside atmospheric heat transport, ocean heat transport plays a vital role in the climate of Earth (Peixoto & Oort 1992). In particular, the work of Hu & Yang (2014) has shown that the effects of a fully coupled ocean versus a shallow slab ocean can be significant when looking at synchronously rotating worlds around M-dwarf stars. Godolt et al. (2015) demonstrated stark differences for planets orbiting F-type stars when changing ocean heat transport, while Rose (2015) nicely demonstrated the climatic effects of changing ocean heat transport equations for aqua-type and ridge-type worlds. The downside of a fully coupled ocean approach is that it can take hundreds of model years for a fully coupled ocean to come into equilibrium with the atmosphere. Yet, it will provide a more accurate picture of the climate of the world being modeled. In this study we focus on the effects of the terrestrial planet’s orbital eccentricity on the planet’s climate, which is an under-researched area in 3D GCM studies. At the same time, we keep θp = 235, following for modern Earth. The latter is a necessary requirement for comparing with past and future work in the literature since obliquity plays such an important role in the possible climate states of terrestrial planets.

2022ApJ...936..102A__Williams_et_al._2006_Instance_4

As regards the modeling of BGK modes, there are two main theoretical approaches: the integral solution or BGK methodology and the differential (or Schamel) technique. In the former method (BGK), one assumes that the initial particle distribution function and the electrostatic potential profiles are known, so these are substituted into the Poisson equation and the integral equation is solved to obtain the trapped particle distribution function (Bernstein et al. 1957; Aravindakshan et al. 2018a, 2018b, and the references therein). In Schamel’s approach, the form of the trapped particle distribution function and of the passing (i.e., free, nontrapped) particle distribution function is assumed and substituted in Poisson’s equation, leading to a differential equation that is then solved to obtain the form of the potential (Schamel 1986; Luque & Schamel 2005, and the references therein). A distinguishing factor in the former (BGK) approach is that it involves a condition in the form of an inequality to be satisfied by the potential parameters (width and amplitude) in order for a BGK mode to be sustained. The BGK approach will be adopted in this work. The above models tacitly assume a collisionless electron-ion plasma. These assumptions are acceptable in the Earth’s magnetosphere. However, as we move farther from near-Earth plasma environments, the presence of charged dust in the plasma cannot be neglected. In the case of Saturn, there are observations of streaming ions by the Cassini spacecraft (Badman et al. 2012a, 2012b). We know that these streaming ion flows can lead to the generation of ion holes. Electrostatic solitary waves have been observed in Saturn’s magnetosphere (Williams et al. 2006) and in the dusty environment near its moon Enceladus (Pickett et al. 2015). Williams et al. (2006) reported observations of solitary structures in the vicinity of Saturn’s magnetosphere. They detected a series of bipolar pulses and speculated that these could be either electron holes or ion holes (Williams et al. 2006). Later on, Pickett et al. (2015) observed solitary wave pulses within 10 Rs (Rs is the Saturn radius) and near Enceladus. Near the Enceladus plume, they discussed how dust impacts affected the observed solitary waves. In fact, Pickett et al. (2015) pointed out that some of the bipolar electric field pulses associated with the solitary waves observed had an inverse polarity (i.e., a positive pulse first, followed by a negative pulse in a short time period) and suggested that this might be due to either an inverse direction of propagation or to a true inverse potential pulse polarity (sign). Moreover, Farrell et al. (2017) examined the conditions that allow low-energy ions, such as those produced in the Enceladus plume, to be attracted and trapped within the sheath of negatively charged dust grains. Using particle-in-cell simulations, they showed that with dust in the system, the large electric field from the grain charge disrupts pickup and leads to ion trapping. Their simulation results also reveal that the bipolar pulses reported in the Enceladus plume by Williams et al. (2006) and Pickett et al. (2015) could most probably be ion holes. In the light of the above information, we may suggest that the formation of ion holes is highly likely in the dusty plasma of environments such as the one found in Saturn. Importantly, the instrument on board Cassini, the Radio Plasma Wave Science instrument, does not have the ability to determine the polarity of the electric fields associated with the ESWs observed with 100% certainty as it lacks the ability to perform interferometry (Williams et al. 2006).

2021MNRAS.500.2564O__Ziurys_1987_Instance_1

Phosphorus, which is isoelectronic with both nitrogen and the CH group, is a key element of living systems as a major component of nucleic acids and nucleotides, performing many relevant biochemical functions (Pasek & Lauretta 2005). Conversely, despite significant progress in the recent years (Jiménez-Serra et al. 2018; Rivilla et al. 2018; Fontani et al. 2019; Chantzos et al. 2020) and its importance to astrobiology, the interstellar chemistry of phosphorus is still poorly understood. The first identified phosphorus compound in the ISM was PN through observations of its rotational transitions in Orion-KL, W51M, and Sgr B2 (Turner & Bally 1987; Ziurys 1987). This observation was followed by the detection of free CP in the carbon star envelope IRC +10216 (Guelin et al. 1990). The other phosphorus-bearing molecules detected so far are HCP (Agúndez, Cernicharo & Guélin 2007), CCP (Halfen, Clouthier & Ziurys 2008), PO (Tenenbaum, Woolf & Ziurys 2007), and PH3 (Agúndez et al. 2014b), while a tentative detection of NCCP is also reported (Agúndez, Cernicharo & Guélin 2014a). Phosphorus was also detected in the coma of the comet 67P/Churyumov–Gerasimenko (Altwegg et al. 2016), with recent analysis indicating PO as its main carrier (Rivilla et al. 2020). In addition, PH3 was recently detected in the cloud decks of Venus through millimetre waveband observations (Greaves et al. 2020). Larger phosphorus-bearing molecules, such as phosphorus oxoacids (Turner et al. 2018a) and alkylphosphonic acids (Turner et al. 2018b) – the latter detected in the Murchison meteorite (Cooper, Onwo & Cronin 1992) – were identified in PH3-doped interstellar ice analogues exposed to ionizing radiation. These results, in combination with the increasing literature on phosphorus-bearing molecules in circumstellar envelopes (Ziurys, Schmidt & Bernal 2018) and solar-type star-forming regions (Lefloch et al. 2016) and protostars (Lefloch et al. 2018; Bergner et al. 2019), suggest that their role in the ISM might be greater than previously thought.

2018ApJ...866...15N__Collet_et_al._2007_Instance_1

We find that it is possible to infer and , at the precision of spectroscopy and relatively imprecise and for red-giant stars. We attempted to infer the [Fe/H]; this label is available from the apogee spectroscopy for our stars. However, this label failed and, on inspection, no pixels correlated with [Fe/H]. Therefore, contrary to the findings by Corsaro et al. (2017), we find that there is no information with respect to [Fe/H] in the granulation signal from the Kepler multiepoch photometry. We note that corrections to scaling relations between and fundamental stellar parameters include both and [Fe/H] (White et al. 2011; Guggenberger et al. 2016; Sharma et al. 2016). Furthermore, Viani et al. (2017) showed, in the case of , a dependence on mean molecular weight. While we do not find the signature in the ACF amplitude, this does indicate that a [Fe/H] dependence might be expected, as was also suggested by 3D hydrodynamical simulations of convection (Collet et al. 2007; Ludwig & Steffen 2016). For our proposed methodology, the model should be applied to test data that is assumed to be derived from the underlying population as the training data. Nevertheless, to assess the impact of stellar metallicity on the inference of our labels, we performed a test where we divided stars into two groups around the mean metallicity of the sample. We created a training set of stars with [Fe/H] > 0 and a test set with [Fe/H] 0 dex. These stars broadly cover the same , , and and ranges, although the means of these labels are shifted. We find that the label is impacted at test time when training on a sample of stars with metallicities not covered in the test sample. The inferred is biased to be about 85 K too hot, for training on the metal-rich stars and testing on the more metal-poor stars and 85 K too cold, for the reverse (although with a similar precision as before). This indicates that the [Fe/H] of the star is constraining as to the scale of the , even if we cannot learn this information from the data. The inference of the other three labels is not similarly affected by drawing the test and training set from different metallicity distributions. It is interesting that metallicity affects the and not the other labels. This means that temperature manifests itself differently in the spectra of stars with low and high metallicities. When we do not include stars with low metallicity in the training sample, we cannot accurately predict the temperatures of low metallicity stars during test, and vice versa, as temperature-induced variations in the spectrum must depend on metallicity. The fact that this is not true for other parameters implies that variations in seismic parameters produce variations in the ACF that are independent of metallicity; we therefore do not need to know the metallicity of our stars to infer these parameters to the precision captured using this technique. There is a theoretical expectation that the asteroseismic observables will vary with stellar metallicity (e.g., White et al. 2011; Guggenberger et al. 2016; Kallinger et al. 2018; Viani et al. 2017). Following on from this, there is also opportunity to investigate this in more detail with a data-driven approach.

2016ApJ...823...20K__Xue_et_al._2011_Instance_1

Ouchi et al. (2008) find that there is a possible excess of the Lyα LFs at z = 3.1 and 3.7 similar to the bright-end hump, and they claim that 100% of LAEs host AGNs at the bright ends of and 43.4 erg s−1, respectively, based on the large-area LAE survey with the multiwavelength data set. Thus, the bright-end hump of our z = 2.2 Lyα LF may be produced by AGNs. To examine whether our LAEs at the bright end include AGNs, we use the multiwavelength data of X-ray, UV, and radio available in the SXDS, COSMOS, CDFS, HDFN, and SSA22 fields. For the X-ray data, we use the XMM-Newton source catalog in the SXDS field (Ueda et al. 2008), the Chandra1.8 Ms catalog in the COSMOS field (Elvis et al. 2009), the Chandra 4 Ms source catalog in the CDFS field (Xue et al. 2011), and the Chandra 2 Ms catalog in the HDFN field (Alexander et al. 2003). The typical sensitivity limits of these X-ray data are ∼10−16 to 10−15 erg cm −2 s−1 for the SXDS and COSMOS fields and ∼10−17 to 10−16 erg cm −2 s−1 for the CDFS and HDFN fields. We use GALEX far-UV (FUV) and near-UV (NUV) images for the UV data and obtain these images from the Multimission Archive at STScI (see also Zamojski et al. 2007 for the COSMOS field). The GALEX images reach the 3σ detection limit of ∼25–26 mag. The Very Large Array 1.4 GHz source catalogs of Simpson et al. (2006) (SXDS), Schinnerer et al. (2007) (COSMOS), and Miller et al. (2013) (CDFS) are used for the radio data. These radio data reach an rms noise level of ∼10 μJy beam−1. We find that a majority of our bright LAEs are detected in the multiwavelength data, and we summarize the numbers of these LAEs in Table 2. Under the column of “culled sample” in Table 2, we show the numbers of LAEs with no counterpart detection(s) in the X-ray, UV, and radio data. As shown in Table 2, the SXDS and COSMOS fields have the data that cover all of the X-ray, UV, and radio wavelengths. Moreover, the X-ray, UV, and radio data spatially cover the entire fields of SXDS and COSMOS with the similar sensitivities. We make a subsample that is composed of all 1576 LAEs found in the SXDS and COSMOS fields, and we refer to this subsample as SXDS+COSMOS/All. We then make another subsample consisting of 1538 LAEs with no multiwavelength counterpart detection(s) in the SXDS and COSMOS fields, which is dubbed SXDS+COSMOS/Culled.

2019MNRAS.485.4841R__Creminelli_et_al._2010_Instance_1

Although, the standard form of Press–Schechter mass function with $f(\nu)=\sqrt{{2}/{\pi }} \nu \mathrm{ e}^{-\frac{\nu }{2}}$ which discussed in Press & Schechter (1974) and Bond et al. (1991) can provide a good approximation of the predicted number density of haloes, it fails by predicting approximation too many low-mass haloes and too few high-mass ones (Sheth & Tormen 1999, 2002; Lima & Marassi 2004). Thus, in this study we apply another well-known fitting formula which first proposed in Sheth & Tormen (1999): (24) \begin{eqnarray*} f(\nu)=0.2709\sqrt{\dfrac{2}{\pi }}(1+1.1096\nu ^{0.6})\mathrm{ exp}(-\dfrac{0.707 \nu ^2}{2})\,\, . \end{eqnarray*} In a Gaussian density field, σ is given by (25) \begin{eqnarray*} \sigma ^2(R)=\dfrac{1}{2 \pi ^2}{\int _0}^\infty k^2 P(k) W^2(kR) \, {\rm d}k\,\, , \end{eqnarray*} where R = (3M/4πρm0)1/3 is the radius of the spherical overdense region, W(kR) is the Fourier transform of a spherical top-hat profile with radius R and P(k) is the linear power spectrum of density fluctuations (Peebles 1993). To obtain the value of σ, we follow the procedure presented in Abramo et al. (2007a). Following on Ade et al. (2016), we use the normalization of matter power spectrum σ8 = 0.815 for ΛCDM cosmology. The number density of virialized haloes above a certain value of mass M at zc, the collapse redshift obtained by (26) \begin{eqnarray*} N(\: M,z)={\int _0}^\infty \dfrac{{\rm d}n(z)}{{\rm d}M^{\prime }}\, {\rm d}M^{\prime }\,\,. \end{eqnarray*} The above limit of integration in equation (26) is $M=10^{18}\, \mathrm{ M}_{\rm \odot}\, \mathrm{ h}^{-1}$ which such gigantic structures could not in practice be observed. Now we can calculate the number density of virialized haloes in both homogeneous and clustered DE scenarios using equations (23) and (26). In this way the total mass of a halo is equal to the mass of pressureless matter perturbations. However, the virialization of dark matter perturbations in the non-linear regime cannot be independent from the properties of DE (Lahav et al. 1991; Maor & Lahav 2005; Creminelli et al. 2010; Basse, Bjlde & Wong 2011). Thus, in clustered DE scenarios, we should consider the contribution of perturbated DE components to the total mass of the haloes (Creminelli et al. 2010; Basse et al. 2011; Batista & Pace 2013). Based on the behaviour of wde(z), DE can reduce or enhance the total mass of the virialized halo. One can obtain ϵ(z), the ratio of DE mass to be taken into account with respect to the mass of dark matter, from: (27) \begin{eqnarray*} \epsilon (z)=\dfrac{m_{\rm DE}}{m_{\rm DM}}\,\, , \end{eqnarray*} where the value of mDE depends on what we consider as the mass of DE component. When one only considers the contribution of the perturbations of DE, the mDE takes the form (28) \begin{eqnarray*} {m_{\rm DE}}^{\mathrm{ Perturbed}}=4 \pi \bar{\rho }_{\rm DE}{\int _0}^{R_{\rm vir}} \, {\rm d}R R^2 \delta _{\rm DE}(1+3{c_{\rm eff}}^2)\,\,. \end{eqnarray*} In the other hand, if we assume both DE contributions of perturbation and background level, the total mass of DE in virialized haloes takes this new form (29) \begin{eqnarray*} {m_{\rm DE}}^{\mathrm{ Total}}=4 \pi \bar{\rho }_{\rm DE}{\int _0}^{R_{\rm vir}} {\rm d}R R^2 [(1+3 w_{\rm DE})+ \delta _{\rm DE}(1+3{c_{\rm eff}}^2)]. \end{eqnarray*} The quantities inside a spherical collapsing region in the framework of the top-hat profile, evolve only with cosmic time. Thus from equation (28) one can find (30) \begin{eqnarray*} \epsilon (z)=\dfrac{\Omega _{\rm DE}}{\Omega _{\rm DM}}\dfrac{\delta _{\rm DE}}{1+\delta _{\rm DM}}\,\, \end{eqnarray*} and from equation (29) we can obtain (31) \begin{eqnarray*} \epsilon (z)=\dfrac{\Omega _{\rm DE}}{\Omega _{\rm DM}}\dfrac{1+3 w_{\rm DE}+\delta _{\rm DE}}{1+\delta _{\rm DM}}\,\, . \end{eqnarray*} The mass of dark matter also is obtained from (see also Batista & Pace 2013): (32) \begin{eqnarray*} {m_{\rm DM}}=4 \pi \bar{\rho }_{\rm DM}{\int _0}^{R_{\rm vir}} \, {\rm d}R R^2 (1+ \delta _{\rm DM})\,\,. \end{eqnarray*} In Fig. 5 we plot the evolution of ϵ(z) using equation (30) as the definition of DE mass. We observe that, at high redshift, where the role of DE is less important, ϵ for both of parametrizations becomes negligible. This parameter has a greater value in the case of parametrization (2).

2016ApJ...829..120A__Perron_et_al._1988_Instance_1

Annealing is sometimes used to avoid effects of temperature fluctuations during the etching and/or to remove a background consisting of tracks of light ions. We did not anneal samples before etching. The reason is that nanometric structure transformations of olivine along the heavy projectile trajectory provide enhanced etching of this region. Figure 3 and simulations made in Gorbunov et al. (2015) demonstrate that the diameter of an emerging amorphized track core is up to about 10 nm in the trajectory sector where the Bragg peak of the electronic stopping of heavy ions is realized. The chemical activity of this track core may be reduced due to recrystallization during annealing. To stimulate such recrystallization within etching, the etching temperature must reach thresholds activating (a) fast diffusion of atoms/structure defects supplying structure modifications at times much shorter than the etching time, or (b) melting of the track core followed by its rapid solidification. Because of olivines’ high melting temperatures (1800°C–1850°C) the second scenario cannot be realized at the etching temperatures used (110°C) or during the hand-polishing of samples before etching. Such a temperature increase arising during treatments of samples cannot stimulate a fast diffusion of atoms, either, due to their high migration barriers (e.g., migration barriers of vacancies and interstitials in oxides with covalent binding exceeding 1–2 eV). This is well-illustrated in some experiments (Perelygin et al. 1985) when the procedure of track annealing is applied to study ancient tracks from GCR in olivine crystals from meteorites. Dissipation of “background” tracks of light iron group nuclei from GCR (initial density 1010–1011 cm−3) was detected in Perelygin & Stetsenko (1989) after annealing these crystals at higher temperatures (430 ± 1)°C for 32 hr before etching, and in a 6–8-fold decrease of track lengths for nuclei with Z ≥ 54. This correlates with the analysis (Perron et al. 1988), which demonstrated that the preliminary track annealing led to unpredictable changes in track lengths, resulting in a lower accuracy of nuclear charge determination. For example, path length variations of accelerated Kr and Xe nuclei (with energies of 12.5 and 10.0 MeV per nucleon, respectively), decelerated in olivine crystals from Marjalahti pallasite, depend on annealing time (Lal et al. 1969). The etched lengths of tracks of these nuclei are reduced by 2–3 times for the first 10–20 hr of annealing (382°C). A further increase of annealing time (up to 240 hr) is not followed by any significant decrease in track length, but these final lengths of tracks of Kr ions vary from 18 ± 3 μm to 11 ± 3 μm (40% difference), i.e., the dispersion of the measured lengths is too high. Annealing of tracks of U, Au, and Xe decelerated in olivine crystals from Marjalahti pallasite at temperatures of 430°C, 435°C, and 450°C resulted in a similar distribution of etched track lengths (Perron et al. 1988). Dispersion of L values measured in individual olivine crystals from Marjalahti pallasite sometimes reaches a 3–4-fold value. This effect has been observed, in particular, for tracks from U ions, annealed for 5 hr at a temperature of 450°C, when the L value measured in the same crystals varied within the range of Lmin = (217 ± 52) μm up to Lmax = (762 ± 77) μm. The annealing of tracks from U ions held for 5 hr at T = 435° gave the L values within the range of Lmin = (440 ± 100) μm to Lmax = (869 ± 53) μm (Perelygin & Stetsenko 1989). Similarly, almost twofold intervals of L variation were obtained for Xe and Au ion tracks. Taking into account these causes, the technique without preliminary annealing at a higher temperature is used in the presented work, i.e., we did not apply annealing of samples before their etching at a temperature of 110°C. The search for the heavy component in GCR within the framework of the OLIMPIYA project is based on the registration and measurement of the dynamic and geometric parameters of chemically etched tracks generated by nuclei with Z > 40 in combination with calibration experiments at heavy ion accelerator facilities. The detection method is an annealing-free technique based on layer-by-layer grinding and chemical etching. This technique provides for the geometrical parameters of tracks and the lengthwise track etching rate along the ion trace, as an additional parameter for identification of charges Z of the particle producing tracks.

2022AandA...666A..95H__Hartman_et_al._2022_Instance_2

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.

2016ApJ...826...54D__Schlickeiser_1984_Instance_1

In both models, the particles interact with magnetohydrodynamic (MHD) Alfvén waves in the plasma. If the Doppler-shifted wave frequency is a constant multiple of the particle gyrofrequency in the particle guiding center frame, then a resonant interaction between the particle and the transverse component of the electric field of the MHD wave will occur (Dermer et al. 1996; Becker et al. 2006; Dermer & Menon 2009). The particle will experience either an accelerating or decelerating electric field in the transverse direction of motion over a fraction of the cyclotron period, resulting in an increase or decrease in energy. The accelerating or decelerating electric field causes the particle distributions to diffuse in energy, pushing particles to higher or lower energies in a diffusion pattern. This stochastic acceleration process typically causes the particle distributions to have a pronounced curvature in the energy spectrum (Schlickeiser 1984). The strength of the particle diffusion depends on the spectral index of the MHD turbulence, p. A Kolmogorov, p = 5/3, or a Kraichnan, p = 3/2, spectrum are most often used to model MHD turbulence. In this study, we restrict the spectral index of the turbulence to p = 2 to simulate hard sphere scattering between the MHD waves and the particle spectra. The stochastic acceleration timescale can be expressed as 3 where tdyn represents the dynamical timescale over the region in which turbulence generated (which may be smaller than the entire emission region), βA represents the Alfvén velocity of the plasma normalized to the speed of light and ξi represents the ratio of the magnetic field fluctuations relative to the background magnetic field, . The stochastic acceleration timescale is independent of particle mass and will therefore be the same for all charged-particle species (protons, electrons/positrons, pions, and muons). The diffusion term in Equation (1) describes the stochastic acceleration of particles in the quasi-linear approximation (Dermer et al. 1996). For gyro-resonant interactions to occur in the quasi-linear regime, the magnetic field fluctuations must be much smaller than the background magnetic field, . If the energy density in the plasma waves starts to approach the energy density of the magnetic field, then the field becomes disordered and there exists no well defined gyrofrequency. In both models, we use a ratio between the acceleration timescale and the escape timescale as an input parameter. The ratio between the acceleration and escape timescales constrain the maximum size in which turbulence is injected for stochastic acceleration to occur in the quasi-linear regime; see Section 5.

2018MNRAS.478.3890B__Heckman_et_al._2017_Instance_5

Rather than AGN feedback, it is possible that the effects we are seeing are from a different process coeval or prior to the onset of AGN accretion. Several works have pointed out that AGN activity coincides with a recent starburst, with the AGN having significant accretion events at least ∼200 Myr after the starburst has occurred (Davies et al. 2007; Wild et al. 2007; Wild, Heckman & Charlot 2010; Yesuf et al. 2014) giving the neutral material time to propagate out to the impact parameters probed by COS-AGN (Heckman et al. 2017). With a sample of QSO sightlines probing the CGM around 17 low-redshift starburst and post-starburst galaxies, Heckman et al. (2017) have observed a similar signature of enhanced EWs of Ly α, Si iii, and C iv (the latter of which is not measured in our control sample) relative to a control-matched sample (matched in stellar mass and impact parameter). In the range of impact parameters and stellar masses probed by COS-AGN, the strength of our enhanced EW signature is consistent with the values probed by Heckman et al. (2017). However, the results of Heckman et al. (2017) show strong offsets in the kinematics of the gas from the host galaxy (≈100 km s−1; see fig. 5 from Heckman et al. 2017), whereas the COS-AGN sightlines do not (bottom panel of Fig. 6). Assuming that the AGN activity was triggered by the starburst, a minimum delay time of 200 Myr could allow for any starburst-driven winds to dissipate and kinematic offsets to no longer be present at the impact parameters of the COS-AGN sample. Although this starburst picture provides a possible explanation of our observations, we caution that starbursts are not the only astrophysical event linked to AGN accretion activity. For example, mergers that trigger the AGN (Ellison et al. 2011, 2013; Satyapal et al. 2014; Silverman et al. 2014; Goulding et al. 2018) could potentially affect the surrounding CGM gas. Past and future work focusing on the CGM of galaxy mergers can further test this result (Johnson et al. 2014; Hani et al. 2017; Bordoloi et al. in preparation).

2020AandA...643A.128K__Younes_et_al._2015_Instance_1

In order to allow us to compare the continuum shape with earlier analyses, we use phenomenological continuum models rather than more physically motivated models such as those by Becker & Wolff (2007)2 or Farinelli et al. (2016). As discussed by Müller et al. (2013), among others, phenomenological spectral models typically used to describe the continua of accreting neutron stars are the exponentially cutoff power law (cutoffpl), the power law with Fermi-Dirac cutoff (FDcut, Tanaka 1986), a negative-positive cutoff power law (NPEX, Mihara 1995), and a model consisting of a blackbody disk (diskbb, Mitsuda et al. 1984) and thermally comptonized continuum (nthcomp, Zdziarski et al. 1996; Życki et al. 1999). The residuals of the cutoffpl, FDcut, NPEX, and diskbb+nthcomp models are shown in Fig. 2, and the best-fit parameters are given in Table 1. The NPEX and FDcut residuals look very similar because they are driven to parameters that effectively mimic the cutoffpl solution. All tested continuum models describe the data similarly well. Due to its simplicity and in order to allow comparison with previous work (e.g., Younes et al. 2015), we used the cutoffpl model for all subsequent analysis. Photoelectric absorption in the interstellar medium is accounted for with the tbnew model (TBabs in XSPEC) with cross sections and abundances according to Verner et al. (1996) and Wilms et al. (2000), respectively. The iron fluorescence line complex can formally be described by a slightly broadened ( σ = 0 . 23 − 0.04 + 0.05 $ \sigma=0.23^{+0.05}_{-0.04} $ keV) Gaussian component at 6.59 ± 0.04 keV. This is most likely a blend of different ionization states that cannot be resolved with NuSTAR. The strongest fluorescence lines are often produced by neutral (6.4 keV), He-like (6.7 keV), and H-like iron (7.0 keV), and the structure seen in the data is also consistent with a set of narrow Kα lines from these ions, as well as neutral Kβ (7.1 keV) with a Kβ/Kα flux ratio of 13% (Palmeri et al. 2003). With fixed energies and widths, this approach is also statistically valid and has the same degrees of freedom as using one broad emission feature, but shows less interference with the continuum modeling because all line energies and widths are fixed and broadening is only due to the detector response. Using both approaches, slight residuals still remain at the iron K edge. These residuals are due to a combination of a gain-shift in NuSTAR energy calibration and the fact that the tbnew model only includes neutral iron.

2018MNRAS.478.4357S__Peebles_&_Ratra_2003_Instance_1

Observations over the years seem to firmly support the current acceleration of the Universe and therefore the possible existence of a generic cause responsible for it which we call dark energy (DE; see e.g. Riess et al. 1998; Perlmutter et al. 1999; WMAP collaboration 2013; Planck collaboration XVI 2014; Planck collaboration XIII 2016; Planck collaboration XIV 2016, and references therein). Cosmologists have worked hard to decipher the dark energy code, but we still ignore the physical nature of the DE and hence of the ultimate cause of the observed acceleration of the Universe. Such theoretical conundrum is the so-called Cosmological Constant Problem (CCP) (Weinberg 1989; Sahni & Starobinsky 2000; Padmanabhan 2003; Peebles & Ratra 2003; Copeland, Sami & Tsujikawa 2006; Solà 2013). In fact, the cosmological constant (CC), Λ, or equivalently the vacuum energy density associated to it, $\rho _\Lambda =\Lambda /(8\pi G)$ (G being Newton’s gravitational coupling), is usually regarded as the simplest possible explanation for the DE. Historically, the CC was introduced by Einstein in the gravitational field equations 101 yr ago (Einstein 1917). A positive, constant, tiny value (in particle physics units) of order $\rho _\Lambda \sim 2.7\times 10^{-47}$ GeV4 ∼ (2.3 × 10−3 eV)4 can explain the needed speed up of our cosmos according to the observations. The standard or ‘concordance’ cosmological model embodies such an assumption as a fundamental built-in principle, together with the hypothesis of dark matter (DM), and for this reason is called the ΛCDM model. Formulated in terms of the current cosmological parameters, the ΛCDM assumes that $\rho _\Lambda =$const. throughout the history of the Universe, with $\Omega _\Lambda \simeq 0.7$ and Ωm ≃ 0.3 at present. Unfortunately, no convincing theoretical explanation is provided about the measured value of $\rho _\Lambda$. At the end of the day, no fundamental theory, not even quantum field theory (QFT), can explain this value; and, what is worse, the typical prediction is preposterously large as compared to the measured value. The difficulties inherent to this concept were recognized as of the time when Y.B. Zeldovich first observed (Zeldovich 1967) that the contribution from QFT to the vacuum energy density should be of the order of ∼m4 for any quantum field of mass m, and therefore many orders of magnitude bigger than the existing upper bound on $\rho _\Lambda$ in those days.

2020MNRAS.492.3021R__Machacek,_Bryan_&_Abel_2001_Instance_1

In Fig. 4, we plot the mass growth of each candidate DCBH halo as a function of redshift. In both the panels, we plot the mass of the halo versus the redshift. The left-hand panel contains haloes from the Normal simulation while the right-hand panel contains haloes from the Rarepeak simulation. The grey region in each panel below 106$\rm {M_{\odot }}~$ signifies the region below which the mass resolution of Renaissance becomes insufficient to confidently model haloes. Generally, we are able to track haloes below this threshold and into the grey region but below 106$\rm {M_{\odot }}~$ results should be treated with caution. The dashed blue line is the limit above which a halo must grow in order to overwhelm the impact of LW radiation, Mmin, LW (Machacek, Bryan & Abel 2001; O’Shea & Norman 2008; Crosby et al. 2013, 2016). The dashed red line is the approximate atomic cooling threshold, Matm, at which point cooling due to atomic hydrogen line emission becomes effective.5 Focusing first on the Normal region in the left-hand panel, we plot the growth rate of the three DCBH candidate haloes identified in the left-hand panel of Fig. 2. The DCBH candidate haloes are rapid growers but are not necessarily the fastest growing haloes in the Normal region. To emphasize this comparison, we also plot the growth of three rapidly growing haloes that contain stars. We select the three star-forming haloes from the final output of the Normal region but haloes at other redshifts do of course exist, which are rapidly growing and contain stars. In this case, we see that haloes with high dM/dz (i.e. the mass as a function of redshift) values can be star free or star forming and hence having a high dM/dz does not necessarily discriminate between DCBH halo candidates by itself. Rapidly growing haloes can become metal enriched through external enrichment processes. The enrichment allows the halo interior to cool and to form stars even in the presence of dynamical heating. Therefore, any semi-analytical model or subgrid prescription that uses dM/dz alone as a predictor for DCBH candidates will inevitably overestimate the number of candidates.

2018AandA...612A..77M__Gromadzki_&_Mikołajewska_(2009)_Instance_2

“Wiggling” outflows are often observed among young stellar jets and protostellar molecular outflows (Eisloffel et al. 1996; Terquem et al. 1999). Terquem et al. (1999) investigated such binary systems where the accretion disk, from which the jet originates, is inclined to the binary orbital plane. They concluded that the observed jet “wiggling” is a consequence of the jet precession caused by tidal interactions in such non-coplanar binary systems. Nichols & Slavin (2009) as well as Hollis & Michalitsianos (1993) suggested that the precession of the accretion disk around the WD may be responsible for the bending of the wide-angle outflow found in the previous studies. In analogy to these observations of young stellar jets, we suggest that the “wiggling” that we also find here for the R Aqr jet may result from disk precession as well. We estimated the precession period using the theory from Terquem et al. (1999) and the binary parameters taken from Gromadzki & Mikołajewska (2009) – Mh = 0.8M⊙ (the mass of the hot WD companion), Mp∕Mh = 1.65 (where Mp is the mass of the primary companion), D = 15.5 AU (the mean semi-major axis of the system), and e = 0.25 (eccentricity). The value of Rd is unknown in our case and we used Rd = 5 AU giving D∕Rd ≈ 3 which corresponds to the average value of 2 ≤ D∕Rd ≤ 4 (the range taken from Terquem et al. 1999). For this calculation, we assumed that the angle δ between the disk plane and that of the binary orbit is small enough (10°) and we adopted cosδ = 1. Using Eq. (1) from Gromadzki & Mikołajewska (2009), we derived the precession time of T ≈ 530 yr. This value is quite large for the wiggling waves that we see. We estimated the projected spatial wavelength λproj of the “wiggling” wave according to λ = λproj∕sin i, where i is the angle between the jet symmetry axis and the line of sight, and T = λ∕υ, where υ is the jet velocity, from Gromadzki & Mikołajewska (2009). Using i = 72° and υ ~ 100 km/s, we derive λproj ≈ 10 500 AU which is more than 20 times larger than the projected length of the observed wiggling outflow (2′′ ≈ 440 AU). However, we should note that the precessing time strongly depends on the D∕Rd; the T decreases significantly with increasing R. It may also be the case that the “wiggling” model developed for YSO jets is not fitting for R Aqr which consists of evolved objects, and both the WD and the disk where the jet probably forms are much hotter than YSO systems. Furthermore, we cannot exclude that the steady wiggling might be a sequence of dynamical interactions of the two collimated flows tilted to each other.

2016ApJ...819L...7N___2015b_Instance_2

The gap and ring resemble those in the HL Tau system, recently found by the ALMA long baseline campaign (ALMA Partnership et al. 2015). Our result shows that gaps and rings in the (sub)millimeter dust continuum can exist, not only in relatively young disks (0.1–1 Myr) but also in relatively old disks (3–10 Myr). One possible mechanism for opening a gap is the gravitational interaction between a planet and the gas (e.g., Lin & Papaloizou 1979; Goldreich & Tremaine 1980; Fung et al. 2014). Such an interaction may also produce the spiral density waves recently found in optical and near-infrared scattered light imaging of dust grains in protoplanetary disks (e.g., Muto et al. 2012). According to recent theoretical analyses of gap structure around a planet (Kanagawa et al. 2015a, 2015b, 2016), the depth and width of the gap are controlled by the planetary mass, the turbulent viscosity, and the gas temperature. The shape of the gap is strongly influenced by angular momentum transfer via turbulent viscosity and/or instability caused by a steep pressure gradient at the edges of a gap. The observed gap has an apparent width and depth of au and , respectively. This is too shallow and too wide compared with that predicted by theory. However, the observations are limited to an angular resolution of ∼15 au, and the depth and width could be deeper and narrower in reality. For instance, if we assume that the gap depth times the gap width retains the value derived from the observations, it is possible for the gap to have a width and depth of 6 au and , which is similar to the GPI result (Rapson et al. 2015). Such a gap could be opened by a super-Neptune-mass planet, depending on the parameters of the disk, such as the turbulent viscosity (Kanagawa et al. 2015a, 2015b, 2016). If the gap in the larger dust grains is deeper than that in the gas, the planet could be lighter than super-Neptune mass. We note that a planet of even a few Earth masses, although it cannot open a gap in the gas, can open a gap in the dust distribution if a certain amount of pebble-sized particles, whose motions are not perfectly coupled to that of gas, are scattered by the planet and/or the spiral density waves excited by the planet (Paardekooper & Mellema 2006; Muto & Inutsuka 2009).

2019ApJ...885..165M__Wilman_et_al._2009_Instance_1

Morphology, colors, and star formation rate (SFR) primarily depend on the small-scale (1 Mpc) environment (Hogg et al. 2004; Kauffmann et al. 2004; Wetzel et al. 2012). This result has been extended by studying galaxy group samples; they show that colors and SF history most directly depend on the properties of the host dark matter (DM) halo (Blanton & Berlind 2007; Wei et al. 2010; Tinker et al. 2012), in agreement with the results of smooth particle hydrodynamic (SPH) simulations by Mazzei & Curir (2003, hereafter MC03). In this context, the investigation of the evolution of group members in the nearby universe acquires a great cosmological interest because more than half of galaxies reside in such environments. Furthermore, since the velocity dispersion of galaxies is significantly lower in groups than in clusters, the merger probability and the effects of interaction on galaxy evolution are much higher. Consequently, groups provide a zoom-in on phenomena driving the galaxy evolution before the galaxies fall into denser environments (e.g., Wilman et al. 2009; Just et al. 2010). Starting from the pioneering works of Toomre & Toomre (1972, and references therein), several papers contributed to shed light on the important role of mergers/interactions in galaxy evolution—Toomre (1977), Combes et al. (1990), Mihos & Hernquist (1994, 1996), Barnes & Hernquist (1996), Naab & Burkert (2003), Bournaud et al. (2005), and Di Matteo et al. (2007), to name a few—up to the most recent papers of Eliche-Moral et al. (2018) and Martin et al. (2018, and references therein). The dissipative merger simulations of Eliche-Moral et al. (2018) start from systems just formed, composed of a spherical nonrotating DM halo, and by a disk of gas particles with or without the presence of a stellar bulge. These simulations explore about 3–3.5 Gyr of evolution. Martin et al. (2018) focused on processes triggering galaxy transformations of massive galaxies (M > 1010 M⊙) exploiting cosmological hydrodynamic simulations by Kaviraj et al. (2017). These simulations, based on an adaptive mesh refinement code (RAMSES) and including the baryon treatment with stellar and active galactic nucleus (AGN) feedback, are able to resolve baryonic physics on kiloparsec scales, larger than we use in this paper (Section 3). They derived important statistical assessments about the processes that drive morphological transformation across cosmic time.

2021ApJ...920..145H__Damone_et_al._2018_Instance_1

Over the past decade, many attempts to address this issue have been carried out, such as from the perspective of conventional nuclear physics and even exotic physics beyond the standard BBN framework (Angulo et al. 2005; Cyburt et al. 2008, 2016; Boyd et al. 2010; Pospelov & Pradler 2010; Fields 2011; Kirsebom & Davids 2011; Wang et al. 2011; Broggini et al. 2012; Coc et al. 2012, 2013, 2014; Cyburt & Pospelov 2012; Kang et al. 2012; Voronchev et al. 2012; Bertulani et al. 2013; Hammache et al. 2013; He et al. 2013; Kusakabe et al. 2014; Pizzone et al. 2014; Yamazaki et al. 2014; Hou et al. 2015, 2017; Famiano et al. 2016; Damone et al. 2018; Hartos et al. 2018; Luo et al. 2019; Rijal et al. 2019; Clara & Martins 2020). However, despite the fact some solutions using exotic physics have succeeded in resolving this issue, it appears there is still no universally accepted solution in the academic community since validations of these mysterious exotic physics are beyond the capabilities of current science. Conversely, it seems more worthwhile to exclude any potential possibility of resolving the 7Li discrepancy from the perspective of nuclear physics. It is known that the majority of the primordial 7Li production arises from the decay of 7Be by electron capture during the 2 months after BBN stops. Thus, for the solution of the Li problem, reactions involving 7Be could be more significant than those involving 7Li. Therefore, many reactions that potentially destroy 7Be were investigated to solve this discrepancy over past 10 yr (Kirsebom & Davids 2011; Broggini et al. 2012; Hammache et al. 2013; Hou et al. 2015; Hartos et al. 2018). Meanwhile, enormous efforts have been made to refine the reaction rates of key BBN reactions in the past 20 yr (Smith et al. 1993; Descouvemont et al. 2004; Serpico et al. 2004; Cyburt & Davids 2008; Neff 2011; Pizzone et al. 2014; Tumino et al. 2014; Hou et al. 2015; Barbagallo et al. 2016; Iliadis et al. 2016; Kawabata et al. 2017; Lamia et al. 2017, 2019; Damone et al. 2018; Rijal et al. 2019; Mossa et al. 2020), but the probability of solving or alleviating the 7Li problem by improving our knowledge of relevant nuclear reaction rates still cannot be eliminated. Recent experiments for key nuclear reactions like 7Be(n,p)7Li and 7Be(d,p)24He allow for a reduction of the 7Li production by about 12% (Damone et al. 2018; Rijal et al. 2019) compared to previous calculations. At present, nuclear uncertainties cannot rule out that some of the reactions destroying 7Li are indeed more efficient than those currently used (Boyd et al. 2010; Chakraborty et al. 2011).

2022AandA...663A.105P__Brunetti_et_al._2008_Instance_2

Regardless of the cluster orientation, the spectral index observed for the halo at all available frequencies suggests that it is a USSRH. Despite the number of detected USSRH is still low, radio halos with steep indices are being discovered more and more frequently in the last years thanks to the improved observational capabilities of low-frequency instruments such as GMRT, MWA (Murchison Widefield Array) and LOFAR (Shimwell et al. 2016; Wilber et al. 2018; Bruno et al. 2021; Di Gennaro et al. 2021; Duchesne et al. 2022). An in-depth analysis of all radio halos hosted in Planck clusters and observed in LoTSS, including A1550, has recently been presented in Botteon et al. (2022). USSRH are a prediction of turbulent re-acceleration models (Cassano et al. 2006; Brunetti et al. 2008), in which particles are re-accelerated by turbulence (Brunetti et al. 2001, 2017; Petrosian 2001; Brunetti & Lazarian 2011). On the other hand, the detection of such steep indices is not expected from hadronic (or secondary) models, in which the emission of halos comes from the production of secondary electrons from hadronic collisions between thermal and CR protons (Blasi & Colafrancesco 1999; Dolag & Enßlin 2000; Pfrommer et al. 2008). Given that the integrated spectral index observed for the USSRH with LOFAR is α 54 MHz 144 MHz ∼ − 1.6 $ \alpha_{54\,\rm MHz}^{144\,\rm MHz} \sim -1.6 $ , we expect an index for the spectral energy distribution8δ = 2α − 1 = −4.2. If there is no break in the spectrum, the energy budget for these particles would be untenable (Brunetti et al. 2008). Therefore, a break at low energies (∼GeV) should exist, suggesting a possible interplay between radiative losses and turbulent re-acceleration during the lifetime of emitting electrons (Brunetti & Jones 2014). Moreover, re-acceleration models predict that a large fraction of halos associated with clusters of masses between 4 and 7 × 1014 M⊙ should exhibit steep spectra (Cassano et al. 2010, 2012; Brunetti & Jones 2014; Cuciti et al. 2021). The mass of A1550 of ∼6 × 1014 M⊙ estimated from Planck Collaboration XXVII (2016) falls in this range9.

2015ApJ...811...57A__Choi_et_al._2014_Instance_1

Shown in Figures 2(a) and (b) are the z-component of the electric field, Ez, and y-component of the magnetic field, By, respectively. Panels 2(c)–(e) show the transversally averaged (in the yz-plane) electric and magnetic field components, . The energy distribution (total of jet+ambient) and average energy along the x-direction for electron and ion species are shown in Figures 2(f)–(i). All panels are at t∗ = 500. Where high-speed jet particles interact with the ambient medium (behind the RS at x∗ ≤ 340) or scattered ambient particles blend with the upstream ambient (in front of the FS at 430 ≤ x∗), particles distribution becomes strongly anisotropic. Anisotropies result in the Weibel instability which generates current filaments in these regions with currents in the x-direction. According to Ampere’s law, these current filaments are encircled by transverse magnetic fields, and we see that in Figure 2(c). The transverse electric fields are related to the magnetic fields via where is the velocity of the electron (ion) carrier. The carriers move roughly at the speed of light in the x-direction, . Therefore, the transverse electric field components are Ey = Bz, and Ez = −By, as are observed in the simulation results for (Figures 2(a)–(e)). Additionally, there is a longitudinal ambipolar electric field within the RS transition region, 140 ≤ x∗ ≤ 340 for t∗ = 500 (Figure 2(c)). This electric field is generated by the density gradient and different mobilities of electrons and ions (Forslund & Shonk 1970; Forslund & Freidberg 1971; Hoshino 2001; Choi et al. 2014). The magnetic fields act to isotropize the momentum distribution, while the electric fields function to thermalize, and accelerate the particles afterwards. In Figures 2(f)–(i), the shocked region lies between x∗ = 340 and x∗ = 430. Within the RS transition region (140 ≤ x∗ ≤ 340) jet electrons are trapped by the ambipolar electric field and effectively accelerated up to γe = 200 by the transverse electric fields (Figures 2(f) and (g)). A tenuous population of these electrons convect upstream due to reflection by the magnetic fields in the shocked region (ellipse in Figure 2(f)). On the other hand, jet ions are slowed in the RS transition region (140 ≤ x∗ ≤ 340) by 40% from the initial Lorentz factor γi = 10, due to the effect of the ambipolar electric field. In the shocked region, jet electrons have been fully thermalized and are well merged with the thermalized ambient electrons. Thus, only a single electron population is present in the hot shocked region (Figure 2(f)). On the other hand, the kinetic energy of jet ions is transferred to the heating of ambient particles by means of the electromagnetic fields generated by the ion Weibel instability (Figure 2(h)). Full thermalization of the two ion populations (jet and ambient) has not yet occured (demands a longer simulation time), i.e., the two populations are distinguishable in Figure 2(h). Electrons located in the FS transition region (430 ≤ x∗ ≤ 500), predominantly ambient electrons, also undergo the Weibel instability and are thermalized by the jet upstream kinetic energy. In this region, penetrating jet ions interact with ambient particles and are slowed down gradually by 50% from the jet front Lorentz factor γi = 10 to a minimum value of γi = 5 (Figures 2(h) and (i)).

2021ApJ...908..248D__Guseva_&_Martynenko_1981_Instance_1

Where is the straggle or standard deviation of the implantation distribution, D is the diffusion coefficient, and t is the irradiation time. In the case of gas implantation via ion irradiation, it is often assumed that irradiation damage produces enough defects to serve as trapping sites that the diffusion coefficient is negligible (Martynenko 1977; Scherzer 1983). In Section 2.5, an estimate of the effective diffusion in the presence of damage produced by relativistic light ion impacts is made. Lattice defects caused by ion irradiation also provide nucleation for fixed helium bubbles (Kornelsen 1972). We can assume additional trapping due to the interaction of hydrogen with helium in the material, since helium bubbles serve as trapping sites for hydrogen atoms through synergistic effects (Hayward & Deo 2012), leading to a lower critical dose in the case of mixed hydrogen and helium exposure (Guseva & Martynenko 1981). At temperatures well below the melting point, such as that expected for a relativistic interstellar spacecraft, high-flux hydrogen irradiation damage effects have been reproduced in low-flux experiments (Gao et al. 2019). However, for an interstellar probe, the flux is sufficiently low that diffusion effects may play a non-negligible role. Classical diffusion of individual gas atoms could lead to lower local gas atom concentrations as the implantation distributions widen, or increased gas atom concentrations around trapping sites such as grain boundaries; the effect of diffusion is discussed in Section 2.5. Helium bubble nucleation and migration could lead to increased gas atom concentrations and damage near surfaces, grain boundaries, and other defects (Nakamura et al. 1977; Goodhew 1983; Lane & Goodhew 1983). No single theoretical framework exists to summarily treat these effects. However, simple models such as that presented here immediately offer compelling mitigation strategies. To perform this analysis, we find implantation profiles of ISM gas atoms at relativistic speeds using an ion–material interactions code, calculate critical concentrations for blistering onset for hydrogen and helium individually assuming a worst-case scenario of negligible diffusion, and show the effect of non-negligible diffusion on local gas concentrations.

2016MNRAS.460..590F__Miralda-Escudé_et_al._1996_Instance_1

It is important to note that the above procedure differs from the observational one, whereby Voigt profiles are fit to the absorption features in transmission spectra (e−τ) in order to extract column densities and Doppler broadening parameters. This approach enables deblending of multiple-component absorption, and takes into account the broadening of the lines due to the instrumental profile, enabling accurate recovery of their column densities. The technique was originally devised under the premise that the intervening absorption lines in QSO spectra arose from discrete absorbing clouds, but this picture was challenged early by the smoothly distributed IGM captured in cosmological hydrodynamical simulations (e.g. Cen et al. 1994; Hernquist et al. 1996; Miralda-Escudé et al. 1996; Theuns et al. 1998; Davé et al. 1999). Absorbers that have a large spatial extent take part in the Hubble expansion, which leads to a line profile that deviates from a Voigt profile. Voigt profile fitting the transmission spectra will therefore glean slightly different results to simply taking peaks in the τ distribution. In particular, we might expect a larger number of absorbers, and some differences in the derived Doppler broadening parameters and column densities. As a check, we derived Voigt profiles for lines recovered in some of the sight-lines extracted from the simulation using our τ peak method, and plotted these on top of the transmission spectrum. An example is shown in Fig. 3. The transmission spectrum is shown as the black dashed line, and the predicted Voigt profiles are shown in green. More structure is apparent in the real spectrum, which would yield a larger number of Voigt components in Voigt profile fitting, and column densities and Doppler broadening parameters that differ slightly from those we have recovered via the τ peak method. This is an obvious caveat to our approach, which we bear in mind when interpreting our results later on.

2017AandA...601A.143F___2015_Instance_1

Although wind observations are very common in AGN (see Elvis 2000; Veilleux et al. 2005; and Fabian 2012, for reviews), most studies concern ionised gas and uncertain spatial scales. In the past few years the situation changed drastically. Several fast (vOF of the order of 1000 km s-1), massive outflows of ionised, neutral and molecular gas, extended on kpc scales, have been discovered thanks to three techniques: 1) deep optical/NIR spectroscopy, mainly from integral field observations (IFU, e.g. Nesvadba et al. 2006, 2008; Alexander et al. 2010; Rupke & Veilleux 2011; Riffel & Storchi-Bergmann 2011; Cano-Diaz et al. 2012; Greene et al. 2012; Harrison et al. 2012, 2014; Liu et al. 2013a,b; Cimatti et al. 2013; Tadhunter et al. 2014; Genzel et al. 2014; Brusa et al. 2015a; Cresci et al. 2015; Carniani et al. 2015; Perna et al. 2015a,b; Zakamska et al. 2016); 2) interferometric observations in the (sub)millmetre domain (e.g. Feruglio et al. 2010, 2013a,b, 2015; Alatalo et al. 2011; Aalto et al. 2012; Cicone et al. 2012, 2014, 2015; Maiolino et al. 2012, Krips et al. 2011; Morganti et al. 2013a,b; Combes et al. 2013; Garcia-Burillo et al. 2014); and 3) far-infrared spectroscopy from Herschel (e.g. Fischer et al. 2010; Sturm et al. 2011; Veilleux et al. 2013; Spoon et al. 2013; Stone et al. 2016; Gonzalez-Alfonso et al. 2017). In addition, AGN-driven winds from the accretion disk scale up to the dusty torus are now detected routinely both in the local and in the distant Universe, as blue-shifted absorption lines in the X-ray spectra of a substantial fraction of AGN (e.g. Piconcelli et al. 2005; Kaastra et al. 2014). The most powerful of these winds, observed in 20–40% of local AGN (e.g. Tombesi et al. 2010) and in a handful of higher redshift objects (e.g. Chartas et al. 2009; Lanzuisi et al. 2012), have extreme velocities (ultra-fast outflows, UFOs, v 0.1-0.3c) and are made by highly ionised gas which can be detected only at X-ray energies.

2021MNRAS.503.4387A__Neronov_&_Vovk_2010_Instance_1

Observations of large-scale magnetic fields offer clear insights about regular ordered patterns of the field lines, suggesting that mean-field dynamo processes are responsible for their order and structure, as well as the existence of additional transport processes carrying magnetic energy into huge regions of space (Clarke, Kronberg & B”ohringer 2001; Bonafede et al. 2010; Arlen et al. 2012; Govoni, F. et al. 2017; Han 2017). Magnetic fields cannot be directly observed, so their impact on radiation processes need to be considered (see, for instance, Rybicki & Lightman 1979, and references therein). In addition, observations of magnetic fields in voids provide bounds on their strength, depending on the analytical model: From the simplest ones, it is possible to obtain lower bounds, although when improving such models a bounded range of magnetic field strength values can be provided, ranging from 10−25 to 10−15 nG (Neronov & Vovk 2010; Tavecchio et al. 2010; Essey, Ando & Kusenko 2011; Takahashi et al. 2013). Other authors argue magnetic field strengths between 10−16 and 10−15 G (Einstein 1915; Einstein 1916; Hubble 1929; Hubble & Humason 1931; Bull et al. 2016). Magnetic fields from astrophysical voids are relevant since they could evidence truly cosmological magnetic fields, which could have served as seeds for magnetic fields in lower scales (such as galactic fields). Observations in galaxy clusters yield values of the order of 10−6 G (Boulanger et al. 2018). Interest in primordial magnetic fields generated during inflation has recently increased. This scenario has driven the search for phenomenologically viable mechanisms to explain the observed magnetic fields in a broad set of scales (Grasso & Rubinstein 2001; Brandenburg & Subramanian 2005; Demozzi, Mukhanov & Rubinstein 2009; Ferreira, Jain & Sloth 2013; Green & Kobayashi 2016). The latest data on reionization and the observed UV luminosity function of high-redshift galaxies place limits on the magnetic field strength due to its impact on the reionization process.

2015MNRAS.448...42L__Shetrone_et_al._2003_Instance_1

GCs formed in dwarf galaxies may differ from those found in the Galactic halo, depending on their age and metallicity. Dwarf galaxies show a wide variety of star formation histories (Hidalgo et al. 2011, 2013; Weisz et al. 2014) that are predicted to lead to variations in their metallicity distribution functions and chemical abundances. It has also been suggested these variations could be attributed to differences in the IMFs of these galaxies (McWilliam, Wallerstein & Mottini 2013). If the IMFs are the root cause of these differences, then this would also lead to differences in the age–metallicity relationship, which is observed by both Forbes & Bridges (2010) and Leaman et al. (2013). From observations, field stars in dwarf galaxies do exhibit different abundance ratios from MW field stars, e.g. lower [α/Fe] ratios and variations in neutron-capture element ratios at intermediate metallicities. However, these typically do not show up until [Fe/H] ∼ −1.5 (Shetrone, Bolte & Stetson 1998; Shetrone, Côté & Sargent 2001; Shetrone et al. 2003; Venn et al. 2004; Okamoto et al. 2012; Tolstoy, Hill & Tosi 2009; Frebel 2010). At metallicities below [Fe/H] = −1.5, the abundance variations between field and GC stars become less pronounced in dwarfs and the MW (Hill et al. 2000; Pritzl, Venn & Irwin 2005; Carretta et al. 2010; Letarte et al. 2010); a good example of this is M54, located at the heart of the Sagittarius (Sgr) dwarf accretion remnant. M54 has a much lower metallicity than the Sgr field stars (e.g. Carretta et al. 2010) and the [α/Fe] ratios resemble the field stars in the MW halo and its detailed chemical abundance ratios resemble the patterns seen in other GC systems (e.g. the Na–O anticorrelation; Carretta et al. 2009). Therefore, other than its physical association with the Sgr remnant, M54 does not stand out from other GCs in terms of its chemical abundance patterns, similar to the metal-poor GCs Terzan 8 and Arp 2 (both also kinematically and spatial associated with the Sgr stream; Mottini, Wallerstein & McWilliam 2008). On the other hand, Hodge 11 in the large magellanic cloud at [Fe/H] = −2.0 does have lower [α/Fe] than MW field and GC stars(Mateluna et al. 2012), and Ruprecht 106 has an anomalously low [α/Fe] ratio for a MW GC (Villanova et al. 2013).

2016ApJ...827...75L__Gal-Yam_et_al._2006_Instance_1

The coalescence of a binary compact object system (either a neutron star (NS) binary or a stellar-mass black hole (BH) and NS binary) has been widely suggested to account for short-duration gamma-ray burst (SGRB) events (Eichler et al. 1989; Narayan et al. 1992; Nakar 2007; Berger 2014) that last typically less than 2 s in the soft γ–ray band (Kouveliotou et al. 1993). Since 2006, it has been suspected that mergers of compact objects could also produce the so-called long–short GRBs (also known as the supernova-less long GRBs, which are apparently long-lasting but do not show any signal of supernovae down to very stringent limits), which share some properties of both long- and short-duration GRBs (Della Valle et al. 2006; Gal-Yam et al. 2006; Gehrels et al. 2006; Zhang et al. 2007). Compact binary coalescence (CBC) is generally expected to be a strong source of gravitational wave (GW) radiation and such events are prime targets for some GW detectors like advanced Laser Interferometer Gravitational-Wave Observatory (LIGO)/VIRGO (Abadie et al. 2015; Acernese et al. 2015; Belczynski et al. 2010, 2016; see also the latest LSC–Virgo white paper at https://dcc.ligo.org/LIGO-T1400054/public). On 2015 September 14, the two detectors of the LIGO simultaneously detected a transient gravitational wave signal from the merger of two BHs (GW150914, Abbott et al. 2016). GW150914 is the first direct detection of gravitational waves and the first identification of a binary BH merger (Abbott et al. 2016). Surprisingly, the observations from the Fermi Gamma-ray Burst Monitor (GBM) at the time of GW150914 claimed a detection of a weak gamma-ray transient (i.e., GBM transient 150914) 0.4 s after GW150914 with a false alarm probability of 0.0022 (Connaughton et al. 2016). If true, this is the first GW/SGRB association (see, however, Savchenko et al. 2016 for some arguments). Li et al. (2016) compared GBM transient 150914 with other SGRBs and found that such an event is remarkably different in its prompt emission properties. The binary BH merger origin as well as its property of “distinguished” prompt emission suggest that GW150914/GBM transient 150914 is not a typical GW/SGRB association.

2018AandA...611A..85S__Schleicher_&_Dreizler_(2014)_Instance_1

After the detection of V391 Peg b, some other planet or brown dwarf (BD) candidates orbiting sdB stars were proposed using different detection methods. From eclipse timing, about one-third of the known detached sdB/sdO + dM (dM = M-dwarf) post-common-envelope binaries (PCEB) are suspected to host planets/BDs: HW Vir (Beuermann et al. 2012 and references therein), HS 0705+6700 (alias V470 Cam, Qian et al. 2013 and references therein), HS 2231+2441 (Qian et al. 2010 and references therein; but see also Lohr et al. 2014), NSVS 14256825 (Almeida et al. 2013; Hinse et al. 2014 and references therein), NY Vir (Lee et al. 2014 and references therein), and 2M 1938+4603 (Baran et al. 2015). Interesting explorations on the origin of PCEB (and specifically sdB+MS/BD) circumbinary planets can be found in Zorotovic & Schreiber (2013), Schleicher & Dreizler (2014), Bear & Soker (2014), and Völschow et al. (2016). Very different planets or planetary remnants with terrestrial radii have been proposed from tiny reflection effects detected by the Kepler spacecraft in KIC 05807616 (Charpinet et al. 2011) and KIC 10001893 (Silvotti et al. 2014). However, none of these sdB planet/BD candidates has been confirmed with at least two independent detection methods. More robust detections of a few brown dwarfs (BDs) in eclipsing sdB binaries (also called HW Vir systems from the sdB+dM protoptype) were obtained by combining stellar radial velocities (RVs) with photometric measurements: J08205+0008, J1622+4730 and V2008-1753 have companion masses of about 71, 67, and 69 MJup, respectively (Geier et al. 2011; Schaffenroth et al. 2014a, 2015). At least two more sdB+BD eclipsing systems were recently found from the OGLE survey (Schaffenroth, in prep., priv. comm.). Finally, two more BD candidates in sdB binaries were found by combining radial velocities (RVs) with photometric reflection effects: CPD-64°6481 and PHL 457, with minimum masses of 50 and 28 MJup, respectively (Schaffenroth et al. 2014b).

2020ApJ...889...29C__Kalapotharakos_et_al._2014_Instance_1

The global magnetospheric structures for the oblique rotator are very similar to the aligned one. We show the structure of magnetic field lines and the distribution of the accelerating electric field E0 in the x–z plane for a 60° rotator with the pair multiplicity κ = {0, 1, 3} in Figure 4. As the pair multiplicity κ increases, the field structure tends to the force-free solution with an equatorial current sheet outside the LC. We observer a dissipative region where E > B outside the LC. The spatial extension of the dissipative region decreases with increasing pair multiplicity and the E0 region is more confined to the equatorial current sheet outside the LC as the pair multiplicity κ increases. In fact, the E0 distribution for the high κ solution is qualitatively similar to the FIDO one (see, e.g., Kalapotharakos et al. 2014; Cao & Yang 2019). We also compare the field structures for κ = 0 with Figure 1 of Contopoulos (2016) for α = 0° and α = 60° respectively. We find that the field structures are qualitatively very similar to those of Contopoulos (2016). For comparison, we also show the magnetic field lines and the E0 distributions for a 60° rotator with the pair multiplicity κ = 0 by implementing the AE formulation everywhere in Figure 5. The magnetospheric structure is very similar to the aligned one with a force-free zone bounded by a radiation zone. We observe a strong E0 distribution inside the LC, which is very different from those in the SG and OG models. A strong E0 region with E > B also appears outside the LC. We show the distributions of magnetic field lines and the accelerating electric field E0 in the x–z plane for a 30° rotator with the pair multiplicity κ = 3 in Figure 6. We see that the field structure is very close to the force-free one and the E0 region is restricted to only near the current sheet outside the LC for this high κ value. We also show the normalized Poynting flux L/Laligned as a function of radius r for a 90° rotator with different pair multiplicities in Figure 7. We see that the Poynting flux increases with increasing κ values and approaches the force-free solution for the high κ value. Our simulation shows a more than 1% dissipation rate outside the LC for a 90° dissipative rotator. A similar dissipation rate is also found by the PIC simulation for the aligned and perpendicular rotator (Philippov et al. 2015). In fact, the spectral numerical methods present an unphysical dissipation beyond the LC due to discontinuity in the current sheet. A higher resolution is necessary to catch the discontinuity in the current sheet and reduce the unphysical dissipation.

2015AandA...579A.132P__Simha_et_al._(2009)_Instance_2

A common feature of all previous models is that the relation between the central galaxy stellar mass and the halo mass reaches a maximum at halo masses ~1012 M⊙. According to Yang et al. (2012), below this threshold the mass accretion of the central galaxy is dominated by star formation. Thus, when the halo mass reaches ~1012 M⊙ a process takes place that quenches the star formation. Interestingly, this mass scale is very similar to the cold-mode to hot-mode transition scale (Birnboim & Dekel 2003; Kereš et al. 2005) in the theory of gas accretion, as derived in hydrodynamic simulations, whereas large halos primarily accrete hot gas and low mass halos cold gas. This would suggest that the quenching of central galaxies coincides with the formation of a hot gaseous halo, and thus with a lack of cold gas supply. What would be the fate of satellites? According to Simha et al. (2009), the subhalos also retain their identity for quite some time after accreting a larger halo, so satellites in subhalos less massive than ~1012 M⊙ do not immediately see the effect of the hot gas in the larger halo and accrete in cold mode. Thus, consistent with the results of Yang et al. (2012) and Béthermin et al. (2013), satellite galaxies continue to accrete gas and convert it to stars over a rather long period, which according to Simha et al. (2009) is about of 0.5−1 Gyr after the merger. The gas accretion declines steadily over this period. Since star formation follows mass accretion with a short delay, satellites should experience quenching in a similar amount of time. This scenario would be consistent with our observations. Indeed, at z ~ 1 when massive halos are just forming via merger, the SF activity in the accreted subhalos is still high. At later epochs, instead, the transition to the hot mode accretion of the satellites and the consequent progressive quenching of their SF activity would lead to the faster decline of their contribution to the CSFH with respect to lower mass halos, which evolve in a cold mode accretion phase maintaining a high SFR.

2017AandA...598A..66P___2016_Instance_1

In both models, as we will see, the thick disc scale length is about a factor of two shorter than that of the thin disc, in agreement with the results by Bovy et al. (2012a). The choice of presenting two mass models for the mass distribution of our Galaxy is mainly dictated by two reasons. First, the need to add a central bulge to the global gravitational potential to reproduce the rotation curve in the inner kpcs of the Milky Way strongly depends on the observational data with which one compares the theoretical curve: to reproduce the rise observed in the inner kpcs (see the observational data adopted by Caldwell & Ostriker 1981), Allen & Santillan (1991) introduced a central mass concentration, whose mass is about 15% of the disc mass. However, the central rise observed in the rotation of the molecular gas in the inner Galaxy (for more recent estimates see, for example, Sofue 2012) may be an effect of non circular motions generated by large scale asymmetries like the bar, as has been shown recently by Chemin et al. (2015). Moreover, this feature is not reported in all the observational studies (see, for example, Reid et al. 2014). Secondly, there is growing evidence that the mass of any classical bulge, if present in the Milky Way, must be small (Shen et al. 2010; Kunder et al. 2012, 2016; Di Matteo et al. 2014, 2015). For these reasons, we prefer to present a second model, our Model II, which does not include any spherical central component, and which is still compatible with the rotation curve of the Galaxy, as given by Reid et al. (2014). Because it has been widely used in the last decades, and due to the facility of its implementation, we explicitly aim at generating Galactic models similar to the Allen & Santillan (1991) model, so to make any implementation of these new models, and any comparison with Allen & Santillan (1991), straightforward. As for the model proposed by Allen & Santillan (1991), Models I and II are axisymmetric and time-independent, and do not include stellar asymmetries such as a bar or spiral arms. No truncation is assumed for the discs, while the halo is truncated at 100 kpc, in agreement with the choice of Allen & Santillan (1991). As we describe in the following section, the analytic forms for the discs, halo, and bulge potentials are the same as those adopted by Allen & Santillan (1991). To allow an easy comparison with the Allen & Santillan (1991) model, in the following we will make use of the same system of units adopted by these authors: the potential is given in units of 100 km2/ s2, lengths are in kpc, masses in units of 2.32 × 107M⊙, time in units of 0.1 Gyr, velocities in units of 10 km s-1 and the vertical force in units of 10-9 cm s2. In these units, the gravitational constant G is equal to 1 and the mass volume density is in units of 2.32 × 107M⊙/ kpc3.

2021MNRAS.501.3781R___2017_Instance_1

While spatially extended optical jets and bipolar CO molecular outflows have been observed in numerous Class 0/I protostars (e.g. Reipurth & Bally 2001; Bally 2016, and references therein), near-infrared high-resolution spectroscopy and spectroimaging observations in the past two decades have made it possible to study the kinematics of the outflowing gas and physical properties at the base of the jet within a few hundred au of the driving source in Class 0/I protostars (e.g. Davis et al. 2001, 2003, 2011; Nisini et al. 2005, 2016; Caratti o Garatti et al. 2006; Takami et al. 2006; Antoniucci et al. 2008, 2011, 2017; Garcia Lopez et al. 2008, 2013). These microjets are bright in [Fe ii] forbidden and H2 rovibrational emission lines, hence showing the presence of forbidden emission-line (FEL) regions and molecular hydrogen emission-line (MHEL) regions in low-mass Class 0/I protostars. While multiple low- and high-velocity components are observed in both MHELs and FELs, the higher velocity gas is slightly further offset from the driving source than the slower gas, and the kinematics of the H2 emission differs from [Fe ii] emission, revealing complicated kinematic structures. Evidence of H2 emission from cavity walls is also seen in some protostars, suggesting the presence of a wide-angled wind. Strong emission in the well-known accretion diagnostics of Paschen and Brackett hydrogen recombination lines is observed in protostars, with the ratio of the accretion luminosity to bolometric luminosity spanning from ∼0.1 to ∼1. The mass accretion and loss rates for Class 0/I low-mass protostars span the range of 10−6–10−8 M⊙ yr−1, and the derived jet efficiencies (ratio between mass ejection and accretion rates) range between ∼1 per cent and 10 per cent (e.g. Davis et al. 2001, 2003, 2011; Nisini et al. 2005, 2016; Caratti o Garatti et al. 2006; Takami et al. 2006; Antoniucci et al. 2008, 2011, 2017; Garcia Lopez et al. 2008, 2013). These measurements are within the range predicted by the magnetohydrodynamic jet launching models (e.g. Frank et al. 2014).

2019ApJ...871..243Y__Yen_et_al._2011_Instance_1

There are two possibilities resulting in the different magnetic field strengths inferred from the polarimetric and molecular-line observations: (1) the rotational-to-gravitational energy βrot is overestimated, and (2) there are additional contributions in the polarized intensity from other mechanisms, such as dust scattering. In our MHD simulations, βrot is adopted to be 0.4% based on the observational estimates of the core mass of ∼1 M and the angular speed of the core rotation of 4 × 10−14 s−1. The angular speed was estimated based on the global velocity gradient along the major axis of the dense core observed with single-dish telescopes (Saito et al. 1999; Yen et al. 2011; Kurono et al. 2013). Numerical simulations of dense cores including synthetic observations show that the specific angular momentum derived from the synthetic images of the dense cores can be a factor of 8–10 higher than their actual specific angular momentum computed by the sum of the angular momenta contributed by the individual gas parcels in the dense cores (Dib et al. 2010). In addition, if there are filamentary structures in the dense core in B335, which could not be resolved with the single-dish observations, infalling motions along the filamentary structures could also contribute to the observed velocity gradient, leading to an overestimated angular speed of the core rotation (Tobin et al. 2012). We have also performed our simulations with a lower βrot, and we find that the rotational velocity on a 100 au scale in the simulations decreases with decreasing βrot. Thus, the discrepancy in the magnetic field strengths inferred from the field structures and the gas kinematics can be reconciled, if the core rotation in B335 is overestimated by a factor of a few in the observations, and these results would suggest a weak magnetic field of initial λ of 9.6 in B335. Further observations combining single dishes and interferometers to have a high spatial dynamical range and to map the velocity structures of the entire dense core in B335 at a high angular resolution are needed to study coherent velocity features and provide a better estimate of the core rotation.

2022AandA...662A..42M__Vázquez_2007_Instance_3

A number of fundamental results have been rigorously proved in the mathematical literature concerning the asymptotic behaviour in time of some of the solutions of the porous medium equation and related equations (e.g. Kamin & Vázquez 1991; Bernis et al. 1993; Hulshof et al. 2001). What is of interest for us here is, primarily, the results that can be applied to the cylindrically symmetric case with diffusion coefficient which is proportional to the square of the dependent variable (n = 2, m = 3 in the notation of Eq. (7)). The most basic result, already mentioned in Sect. 4.4.1, is that initial conditions which have a finite nonzero flux integral (called ‘the mass’ in the mathematical literature for the PME) converge toward the ZKBP solution with the same flux integral (‘mass’) asymptotically in time (Vázquez 2007, Theorem 18.2); here, allowance is made for either a positive or negative flux integral by globally changing the sign of the ZKBP solution; also, ‘convergence’ is meant in the sense that the Lp norm of the difference between the actual solution and the ZKBP function tends to zero as t → ∞ faster than a negative power of the time with an exponent which is a function of n, m, and p (e.g. −1/3 for n = 2 and m = 3 in the L2 norm; see details in the book by Vázquez 2007). A complementary result is the following: when the initial condition has positive net flux and its negative part has compact support, then the whole solution evolves into a positive function after a finite time (Vázquez 2007, Theorem 18.29). Since we are dealing with signed functions which have zero flux integral, these results are of interest mainly because they impose a strict condition on the possible flux imbalance caused by numerical errors (as discussed in Sect. 4.4.1, final paragraph): if it is not small, the numerical solutions will approach the ZKBP solution in a comparatively short time. However, the flux imbalance in all the Bifrost experiments discussed in the present paper is small enough that they have not shown this behaviour even though they have been run until a very long diffusive time.

2021MNRAS.506.3313G__Surana_et_al._2020_Instance_1

Deep learning (DL) is the paradigm of machine learning which uses multilayer neural networks. Neural networks are ML models inspired from the network of brain cells or neurons. The differentiating factor between DL and conventional ML is in the process of feature selection. In conventional ML, performance strongly depends on the features used. More often than not, new features are created for a task to better capture correlations in the data. This is called feature engineering. ML models perform poorly if not given good features to learn from. Deep learning eliminates this dependence by defining its own features to learn from, which are relevant to the task at hand. This makes deep learning a versatile, high performing solution for a variety of supervised ML tasks. The Artificial Neural Networks (ANNs) have found application in not only the traditional tasks in extragalactic astronomy such as photometric redshift estimation (e.g. Firth, Lahav & Somerville 2003; Tagliaferri et al. 2003; Collister & Lahav 2004; Vanzella et al. 2004; Sadeh, Abdalla & Lahav 2016; Bilicki et al. 2018; Pasquet et al. 2019), but also in more specialized problems such as predicting infrared luminosity of galaxies (Ellison et al. 2016), estimation of star formation properties (Surana et al. 2020), and ranking the quenching parameters of galaxies (Teimoorinia, Bluck & Ellison 2016). In particular, Convolutional Neural Networks (CNN) are now becoming increasingly popular in studies using imaging data on galaxies. The CNNs are deep learning models designed to extract features from images. They have provided state-of-the-art performance in majority of computer vision tasks in recent times (Krizhevsky, Sutskever & Hinton 2012; He et al. 2017). CNNs have been utilized for galaxy morphological classification e.g. classifying the optical morphologies broadly into spheroidal, disc, and irregular types (Huertas-Company et al. 2015) and even for classification of various radio galaxy morphologies (Wu et al. 2019). Recently, Ribli, Dobos & Csabai (2019) have shown that CNNs can be used to predict galaxy shapes, needed for weak lensing studies, from a wide field but shallow sky survey images using the ‘ground truth’ images from a deeper but narrower field survey. CNNs have also found application in the automated detection of features in sky-survey images such as galactic bars (Abraham et al. 2018) and strong gravitational lenses (Canameras et al. 2020; Li et al. 2020). Further, ML and CNNs in particular have also been used to detect outliers in large area Sloan Digital Sky Survey (SDSS) data (e.g. Baron & Poznanski 2017; Sharma et al. 2019). In this study, we want to determine the bulge to total luminosity ratio (B/T) of a galaxy using its optical multiband images as input. Due to the use of a data set with galaxy images labelled by $B/T\, \in [0,1]$ in a continuous space $\rm I\!R$, we have performed CNN based regression in this work.

2019AandA...623A.156D__Cacciari_&_Clementini_2003_Instance_1

Cepheids and RR Lyrae stars are primary standard candles of the cosmological distance ladder because they follow canonical relations linking their intrinsic luminosity to the pulsation period and/or the metal abundance. Specifically, for Cepheids the intrinsic luminosity (L) at any passband depends on the period (P) of light variation. This is traditionally referred to as the Cepheid period–luminosity relation or Leavitt law, after its discoverer Mrs Henrietta Swan Leavitt (Leavitt & Pickering 1912). Modern realisations of the Cepheid PL relations from optical to infrared passbands include, among others, the ground-based studies of Madore & Freedman (1991), Ripepi et al. (2012), and Gieren et al. (2013), works based on Hubble Space Telescope (HST) data such as those by Freedman et al. (2001), Saha et al. (2006), and Riess et al. (2011), and theoretical investigations such as those by Marconi et al. (2005). Among the most recent studies of the Cepheid period–luminosity relations are those based on Gaia trigonometric parallaxes of Galactic Cepheids (e.g. Clementini 2017; hereafter Paper I and references therein; Riess et al. 2016, 2018). For RR Lyrae stars the intrinsic luminosity (L) in the infrared passbands depends on P and possibly stellar metallicity (Z; PL – metallicity relation – PL(Z)), as first shown by Longmore et al. (1986) and later confirmed by (i) empirical studies of field and cluster RR Lyrae stars (e.g. Sollima et al. 2006, 2008; Borissova et al. 2009), (ii) theoretical models by Marconi et al. (2015) and Neeley et al. (2017), and (iii) the Gaia parallax-calibrated relations of Sesar et al. (2017), Paper I and references therein, and Muraveva et al. (2018a,b). In the visual passband, the luminosity L depends on Z in the form of the so-called RR Lyrae luminosity–metallicity relation (see e.g. Cacciari & Clementini 2003; Clementini et al. 2003; the pulsation models by Bono et al. 2003; the theoretical calibration by Catelan et al. 2004; or the Gaia-based relations in Paper I; Muraveva et al. 2018a and references therein). The predicted precision of the Gaia end-of-mission parallaxes for local Cepheids and RR Lyrae stars1 will allow us to determine the slope and zero-point of these fundamental relations with unprecedented accuracy, thus setting the basis for a global reassessment of the whole cosmic distance ladder. As a first anticipation of the Gaia potential in this field of the cosmic distance ladder and a first assessment of improved precision with respect to previous astrometric missions such as HIPPARCOS, and the dramatic increase in statistics compared to what is achievable, for instance, through measuring parallaxes with the HST, Gaia DR1 published parallaxes for more than 700 Galactic Cepheids and RR Lyrae stars, computed as part of the Tycho-Gaia Astrometric Solution (TGAS; Lindegren et al. 2016). A number of papers after Gaia intermediate data releases in 2016 and 2018 (Gaia Data Release 1 – DR1 and DR2, respectively) have discussed Gaia Cepheids and RR Lyrae stars, specifically presenting the released samples (Clementini et al. 2016, 2019), their parallaxes (e.g. Lindegren et al. 2016) and possible offsets affecting them (Arenou et al. 2017, 2018); and addressing in particular their use as standard candles (Casertano et al. 2017 and Paper I for Gaia DR1 and Riess et al. 2018; Muraveva et al. 2018a for Gaia DR2). In Paper I we have used TGAS parallaxes, along with literature photometry and spectroscopy, to calibrate the zero-point of the PL relations of classical and type II Cepheids, and the near-infrared PL and PL(Z) relations of RR Lyrae stars by fitting these relations through adopting different techniques that operate either in parallax or absolute magnitude space. In that paper, different sources of biases affecting the TGAS samples of Cepheids and RR Lyrae stars were discussed at some length, and the possible systematic errors caused in the inferred luminosity calibrations were analysed in detail.

2016MNRAS.458.3181C__Trujillo_et_al._2011_Instance_1

To explain the observed evolution, the physical processes invoked have to result in a large growth in size but not in stellar mass, nor drastic increase in the star formation rate. Most plausible candidates are mass-loss driven adiabatic expansion (‘puffing-up’) (e.g. Fan et al. 2008, 2010; Ragone-Figueroa & Granato 2011) and dry mergers scenarios (e.g. Bezanson et al. 2009; Naab, Johansson & Ostriker 2009; Trujillo, Ferreras & de La Rosa 2011). In the former scenario, galaxies experience a mass-loss from wind driven by active galactic nuclei (AGNs) or supernovae feedback, which lead to an expansion in size due to a change in the gravitational potential. In the latter, mergers either major involving merging with another galaxy of comparable mass, or minor that involves accretion of low mass companions, have to be dry to keep the low star formation rate (Trujillo et al. 2011). Nevertheless, major mergers are not compatible with the observed growth in mass function in clusters as well as the observed major merger rates since z ∼ 1 (e.g. Nipoti, Londrillo & Ciotti 2003; Bundy et al. 2009). On the other hand, minor mergers are able to produce an efficient size growth (see e.g. Trujillo et al. 2011; Shankar et al. 2013). The rates of minor mergers are roughly enough to account for the size evolution only up to z ≲ 1 Newman et al. (2012), at z ∼ 2 additional mechanisms are required (e.g. AGN feedback-driven star formation Ishibashi, Fabian & Canning 2013). In addition, the effect of continual quenched galaxies on to the red sequence as well as morphological mixing (known as the ‘progenitor bias’) further complicates the situation (e.g van Dokkum & Franx 2001). Processes that are specific in clusters such as harassment, strangulation and ram-pressure stripping (e.g. Treu et al. 2003; Moran et al. 2007) might play an important role in quenching and morphologically transforming galaxies. Several studies have already shown that the progenitor bias has a non-negligible effect on the size evolution (e.g. Saglia et al. 2010; Valentinuzzi et al. 2010b; Carollo et al. 2013; Poggianti et al. 2013; Beifiori et al. 2014; Delaye et al. 2014; Belli, Newman & Ellis 2015; Shankar et al. 2015).

2020ApJ...903....8H__Finn_1987_Instance_1

We note that during these encounters, energy is also lost due to tidal oscillations in the neutron star excited by the black hole (e.g., Press & Teukolsky 1977), and contributes to σ. To check whether we should include this effect in our calculations or whether it can be safely neglected, we approximate the tidal energy dissipated during a parabolic encounter according to the formalism presented in Press & Teukolsky (1977): 6 where RNS is the radius of the neutron star, Rmin is the periastron of the approach, and Tl are dimensionless values associated with each spherical harmonic l (see Press & Teukolsky 1977 for calculation of Tl). We only consider the quadrupole mode (l = 2), which dominates over the other modes (Press & Teukolsky 1977). We approximate the NS as a polytropic star of index n = 0.5 (e.g., Finn 1987), and use values from Table 1 of Kokkotas & Schafer (1995) to aid in the calculation of Tl. Note that since there is a minimum impact parameter, there is a minimum possible value of Rmin. For a parabolic encounter the relationship between the impact parameter and the periastron distance is: 7 Thus, combining Equations (4) and (7), we find the minimum possible Rmin to be: 8 Encounters with Rmin Rmin(bmin) will result in a direct collision between the BH and NS instead of a bound binary. In Figure 1 we plot —the ratio of energy lost to tidal oscillations to the energy lost to gravitational waves—as a function of Rmin, for a 5 BH and a 1.4 NS. We have also marked the region where . We see that in the region of interest where , i.e., where bound binaries can form, , an extremely small value. We have verified (not shown to avoid clutter) that for larger BH masses, is even smaller. This is consistent with previous studies about NS–NS captures (e.g., Gold et al. 2012; Chirenti et al. 2017). Thus, we can safely neglect tides in our calculation of the capture cross section.

2021AandA...655A..99D__Carigi_et_al._2005_Instance_3

Another way of obtaining information about the nucleosynthesis processes involved in producing carbon is to compare it with other elements that are characterised by a well-known source of production, as in the case of oxygen. In Fig. 5, we show the variation of [C/O] as a function of [Fe/H], which serves as a first-order approximation to the evolution with time. To calculate the [C/O] ratios, two oxygen abundance indicators are used independently. At subsolar metallicities, the abundance ratios with both oxygen indicators are mostly negative and show an increasing trend towards higher metallicity. This is explained by the fact that oxygen is entirely produced by SNe Type II from massive progenitors, which started to release theiryields at earlier ages in the Galaxy and, hence, at lower metallicities (e.g. Woosley & Weaver 1995). The massive stars producing carbon at low metallicities might be less massive than those producing oxygen (i.e. having a longer life), explaining a delayed contribution of carbon, hence, the negative [C/O] ratios. Alternatively, this could be explained by increasing O/C yields for more massive progenitors of SNeII. Once metallicity starts to increase, low- and intermediate-mass stars release carbon and massive stars start to eject more carbon than oxygen (Carigi et al. 2005). The [C/O] ratio seems to have a constant rise towards higher metallicities when using the forbidden oxygen line. However, in the case when the O I 6158 Å line is employed, we do observe that the maximum in [C/O] takes places close to solar metallicity to then become flat or decrease. This suggests that low-mass stars mostly contribute to carbon around solar metallicity, whereas at super-solar metallicities, massive stars produce carbon together with oxygen, thereby flattening or even decreasing the [C/O] ratio. This trend is in agreement with the metallicity dependent yields from Carigi et al. (2005), which provide higher carbon as [Fe/H] increases from massive stars (i.e. also increasing the O production) but lower carbon from low and intermediate mass stars as [Fe/H] increases (i.e. less production of C). The turning point of increased relative production of carbon from massive stars takes place at A(O) ~ 8.7 dex (see Fig. 2 of Carigi et al. 2005) which equals to [O/H] ~ 0.0 dex. This observed behaviour of [C/O] is in contrast to the steady increase of [C/O] up to [Fe/H] ~ 0.3 dex found, for example, by Franchini et al. (2021). Nevertheless, the general trend we find when using the [O I ] 6300 Å line is similar to the reported by Franchini et al. (2021), who use also that oxygen indicator. All thick-disk stars present negative [C/O] ratios and when using the oxygen line at 6158 Å thin-disk stars with [Fe/H] ≲ –0.2 have [C/O] 0 as well. Thick-disk stars and low-metallicity thin-disk stars at the same metallicity have similar [C/O] ratios, meaning that the balance between different production sites for oxygen and carbon is the same among both populations, despite [C/Fe] and [O/Fe] being systematically higher for thick-disk stars at a given metallicity.

2022ApJ...924...42N__Cheng_et_al._1990_Instance_2

It is generally thought that the emission from radio to medium energy gamma rays is generated by the injected electrons through the synchrotron radiative mechanism. The high-energy photon emission mainly comes from inverse Compton (IC) scattering of the high-energy electrons on the background seed photons, which include the synchrotron background, the cosmic microwave background, and infrared photons in the PWNe (see, e.g., Zhang et al. 2008; Fang & Zhang 2010; Torres et al. 2013; Lu et al. 2020). On the other hand, it is also suggested that the gamma rays could be emitted by the hadronic processes. The relativistic protons accelerated in the Crab pulsar outer gap interact with the matter inside the nebula. and this process may contribute in the high-energy gamma-ray range (see, e.g., Cheng et al. 1990; Bednarek & Protheroe 1997; Khangulyan et al. 2020; Cao et al. 2021). Therefore, it has been long debated whether the high-energy emission from the PWNe is the leptonic or hadronic origin. The details of the high-energy radiation produced by leptonic process have been discussed for the Crab Nebula (see, e.g., Venter & de Jager 2007; Zhang et al. 2008; Martín et al. 2012), and that of the gamma-ray emission about the hadronic process have been also investigated (see, e.g., Cheng et al. 1990; Bednarek & Protheroe 1997; Bednarek 2003, 2007). However, with the establishment of more and more high-energy observatories, some telescopes have possessed the performance of observing photons of exceeding to the PeV from the astronomic objects. An increasing number of observational data has been reported by the different experiments. For example, the Amenomori et al. (2019) reported that the Tibet air shower array with the underground water-Cerenkov-type muon detector array observed the highest energy photons of exceeding 100 TeV with a 5.6σ statistical significance and pointed the measured spectrum with energy extended to the sub-PeV from the Crab Nebula have an absence of high-energy cutoff. Recently, more than 530 photons at energies above 100 TeV and up to 1.4 PeV from the 12 ultra-high-energy gamma-ray sources with a statistical significance greater than seven standard deviations were reported again by LHAASO (Cao et al. 2021). Together with the earlier investigations about the leptonic scenario, the radiative spectrum from the leptons has a cutoff around the sub-PeV region (see, e.g., Zhang et al. 2008; Martín et al. 2012; Zhang et al. 2020). It seems that the other components of gamma rays have a significant contribution.

2019MNRAS.489.2355D__Chevallard_et_al._2018a_Instance_1

As a comparison, we also use the publicly available mock catalogue JAdes extraGalactic Ultradeep Artificial Realizations (JAGUAR; Williams et al. 2018) to derive the relation between UV and [O iii] + H β luminosity of simulated z ∼ 8 galaxies. The JAGUAR mock catalogue has been produced by matching luminosity and stellar mass functions as well as the relation between the stellar mass and UV luminosity, mostly at z ≤ 4. The galaxy properties are then extrapolated up to z ∼ 15. The JAGUAR catalogue provides emission line fluxes and EWs for the main lines based on modelling with the beagle code (Chevallard & Charlot 2016; Chevallard et al. 2018a). We identify all galaxies from the fiducial JAGUAR mock in the redshift range 7.11 z 9.05 and we randomly select 1000 of them to match the absolute UV magnitude distribution of our sample, and then fit the UV-[O iii] + H β luminosity data. The result is shown in red in Fig. 6. Similarly to our sample, the z ∼ 8 galaxies from the JAGUAR catalogue exhibit a tight relation between UV and [O iii] + H β luminosity (Spearman rank correlation coefficient ρ = 0.73, standard deviation from null hypothesis σ > 40). However, the mock galaxies exhibit a significantly lower [O iii] + H β luminosity (∼0.5 dex) at a given LUV compared to the relation of our galaxies. The detailed reason for this discrepancy relative to the JAGUAR mock is unclear, but one possible reason is differences in the median physical properties. For instance, while the mock galaxies exhibit (3.6–4.5)$\mu$m colour similar to the ones from our sample at a given UV luminosity, the average F125W-3.6$\mu$m colour in JAGUAR is smaller by ∼0.3 mag compared to the observed F125W-3.6$\mu$m colour in our sample. This means that while (3.6–4.5)$\mu$m colour and EW([O iii] + H β) are on average similar between JAGUAR and our sample, the absolute [O iii] + H β line luminosity scales with the 3.6$\mu$m flux which is larger in our sample compared to the JAGUAR mock catalogue. Furthermore, JAGUAR models a small field comparatively to our data, therefore the overlap in UV luminosity is small.

2022ApJ...926..151Z__Jennings_et_al._2020_Instance_1

Unlike the CMB, the 21 cm signal is highly non-Gaussian, because patchy, bubble-like structures of ionized hydrogen (H ii) regions are produced surrounding the ionizing sources. Thus, there is potentially a wealth of information in the 21 cm signal that is not contained in the 21 cm power spectrum, a two-point statistics of 21 cm brightness temperature fluctuations that is traditionally well studied in the literature. It is therefore essential to develop new methods that maximally exploit the full information in the 3D 21 cm images obtained by the SKA. Toward this goal, conventionally, new summary statistics that can only be measured with imaging have been proposed. These include the three-point correlation function (Hoffmann et al. 2019; Jennings et al. 2020), bispectrum (Yoshiura et al. 2015; Shimabukuro et al. 2016, 2017; Majumdar et al. 2018, 2020; Hutter et al. 2020; Saxena et al. 2020; Kamran et al. 2021), one-point statistics (Harker et al. 2009; Shimabukuro et al. 2015; Gorce et al. 2021), topological quantities such as the Minkowski functionals (Gleser et al. 2006; Chen et al. 2019; Kapahtia et al. 2021) and Betti numbers (Giri & Mellema 2021), the cross correlation between the 21 cm line and other probes, such as the CO line (Gong et al. 2011; Lidz et al. 2011), the C ii line (Gong et al. 2012; Beane & Lidz 2018), the kinetic Sunyaev–Zel’dovich (kSZ) effect (Ma et al. 2018; La Plante et al. 2020), and novel techniques such as the antisymmetric cross correlation between the 21 cm line and CO line (Zhou et al. 2021). Since those summary statistics are fully determined by the parameters in the reionization models (hereafter “reionization parameters”), in principle, Monte Carlo Markov Chain (MCMC) methods can be employed to constrain the reionization parameters from measurements of those statistics with futuristic 21 cm experiments (see, e.g., Watkinson et al. 2022), just as the MCMC analysis with the 21 cm power spectrum (Greig & Mesinger 2015, 2017, 2018).

2019ApJ...871..176X__Eldridge_et_al._2013_Instance_2

The progenitors of SNe Ib/c have been thought to be Wolf-Rayet (W-R) stars with high initial masses (MZAMS ≳ 25 M⊙; Crowther 2007). Before core collapse, these stars usually have experienced severe mass loss through strong stellar winds or due to interaction with companion stars (van der Hucht 2006; Paxton et al. 2015). As the evolution of massive stars is usually dominated by binary evolution (Heger et al. 2003) and also depends largely on metallicity, rotation, and so on (Heger et al. 2003; Georgy et al. 2013, 2012), this makes the direct identification of their progenitors complicated (Smartt 2015). However, there are increasing studies suggesting that a lower-mass binary scenario is more favorable for most SNe Ib/c, considering the measured low ejecta masses (Eldridge et al. 2013; Lyman et al. 2016). In addition, the H/He envelopes of the progenitor stars are stripped by binary interaction. There are many detections of progenitor stars for SNe II. For example, most SNe IIP are found to originate from red supergiants (Smartt et al. 2009), while SNe IIL are typically from progenitors with somewhat warmer colors (see Smartt 2015, for a review), and SNe IIb are from those with higher effective temperatures such as yellow supergiants that have had their H/He envelopes partially stripped through binary interaction (e.g., SN 1993J; Podsiadlowski et al. 1993; Maund et al. 2004; Fox et al. 2014). Until recently, there has been only one report of the possible identification of a progenitor star for SNe Ib, namely, iPTF 13bvn, which was proposed to spatially coincide with a single W-R-like star identified on the pre-explosion Hubble Space Telescope (HST) images (Cao et al. 2013; Groh et al. 2013). But such an identification is still controversial (e.g., Bersten et al. 2014; Fremling et al. 2014; Eldridge et al. 2015; Eldridge & Maund 2016). Direct detection of progenitor stars is still elusive for SNe Ic, which prevents us from further testing the theoretical evolution of massive stars (Eldridge et al. 2013).