Abstract:
  We attempt to identify RR Lyrae (RRL) stars in stellar streams that might
have escaped from seven globular clusters (GCs) based on proper motions,
distances, color-magnitude diagrams, and other properties extracted from the
Gaia Early Data Release 3 (EDR3) database. Specifically, we cross-match two
large RRL stars catalogs (from Gaia DR2 and Catalina Sky Survey) with each
other and with the EDR3 database and we end up with a sample of ~ 150,000
unique RRL stars. We calculate distances to RRL stars using the (M_G-[Fe/H])
and (M_V-[Fe/H]) absolute magnitude-metallicity relations and adopt [Fe/H]
values for the GCs from different spectroscopic studies. We also constrain our
search in areas where stellar streams associated with GCs were previously
suggested or identified in other studies. We identify 24 RRL stars that might
have escaped from the following seven GCs: Palomar 13 (Pal 13), NGC 6341 (M92),
NGC 5904 (M5), NGC 5466, NGC 1261, NGC 288, and NGC 1851. We list our findings
in Table 2.


Abstract:
  Hot, dust-obscured galaxies (Hot DOGs) are a population of hyper-luminous
obscured quasars identified by WISE. We present ALMA observations of the [CII]
fine-structure line and underlying dust continuum emission in a sample of seven
of the most extremely luminous (EL; L$_{\rm bol}$ $\ge$ 10$^{14}$ L$_\odot$)
Hot DOGs, at redshifts z ~ 3.0-4.6. The [CII] line is robustly detected in four
objects, tentatively in one, and likely red-shifted out of the spectral window
in the remaining two based on additional data. On average, [CII] is red-shifted
by ~ 780 km/s from rest-frame ultraviolet emission lines. EL Hot DOGs exhibit
consistently very high ionized gas surface densities, with $\Sigma_{\rm [CII]}$
~ 1-2 x 10$^{9}$ L$_\odot$ kpc$^{-2}$; as high as the most extreme cases seen
in other high-redshift quasars. As a population, EL Hot DOG hosts seem to be
roughly centered on the main-sequence of star forming galaxies, but the
uncertainties are substantial and individual sources can fall above and below.
The average, intrinsic [CII] and dust continuum sizes (FWHMs) are ~ 2.1 kpc and
~ 1.6 kpc, respectively, with a very narrow range of line-to-continuum size
ratios, 1.61 $\pm$ 0.10, suggesting they could be linearly proportional. The
[CII] velocity fields of EL Hot DOGs are diverse: from barely rotating
structures, to resolved hosts with ordered, circular motions, to complex,
disturbed systems that are likely the result of ongoing mergers. In contrast,
all sources display large line-velocity dispersions, FWHM $\gtrsim$ 500 km/s,
which on average are larger than optically and IR-selected quasars at similar
or higher redshifts. We argue that one possible hypothesis for the lack of a
common velocity structure, the systematically large dispersion of the ionized
gas, and the presence of nearby companion galaxies may be that, rather than a
single event, the EL Hot DOG phase could be recurrent.


Abstract:
  Ubiquitous mobile computing have enabled ride-hailing services to collect
vast amounts of behavioral data of riders and drivers and optimize supply and
demand matching in real time. While these mobility service providers have some
degree of control over the market by assigning vehicles to requests, they need
to deal with the uncertainty arising from self-interested driver behavior since
workers are usually free to drive when they are not assigned tasks. In this
work, we formulate the problem of passenger-vehicle matching in a sparsely
connected graph and proposed an algorithm to derive an equilibrium policy in a
multi-agent environment. Our framework combines value iteration methods to
estimate the optimal policy given expected state visitation and policy
propagation to compute multi-agent state visitation frequencies. Furthermore,
we developed a method to learn the driver's reward function transferable to an
environment with significantly different dynamics from training data. We
evaluated the robustness to changes in spatio-temporal supply-demand
distributions and deterioration in data quality using a real-world taxi
trajectory dataset; our approach significantly outperforms several baselines in
terms of imitation accuracy. The computational time required to obtain an
equilibrium policy shared by all vehicles does not depend on the number of
agents, and even on the scale of real-world services, it takes only a few
seconds on a single CPU.


Abstract:
  Cancer invasion of the surrounding tissue is a multiscale process that
involves not only tumour cells but also other immune cells in the environment,
such as the tumour-associated macrophages (TAMs). The heterogeneity of these
immune cells, with the two extremes being the pro-inflammatory and anti-tumour
M1 cells, and the anti-inflammatory and pro-tumour M2 cells, has a significant
impact on cancer invasion as these cell interact in different ways with the
tumour cells and with the ExtraCellular Matrix (ECM). Experimental studies have
shown that cancer cells co-migrate with TAMs, but the impact of these different
TAM sub-populations (which can change their phenotype and re-polarise depending
on the microenvironment) on this co-migration is not fully understood. In this
study, we extend a previous multi-scale moving boundary mathematical model, by
introducing the M1-like macrophages alongside with their exerted multi-scale
effects on the tumour invasion process. With the help of this model we
investigate numerically the impact of re-polarising the M2 TAMs into the
anti-tumoral M1 phenotype and how such a strategy affects the overall tumour
progression. In particular, we investigate numerically whether the M2-->M1
re-polarisation could depend on time and/or space, and what would be the
macroscopic effects of this spatial- and temporal-dependent re-polarisation on
tumour invasion.


Abstract:
  We study the effect of the cubic torus topology of the Universe on scalar
cosmological perturbations which define the gravitational potential. We obtain
three alternative forms of the solution for both the gravitational potential
produced by point-like masses, and the corresponding force. The first solution
includes the expansion of delta-functions into Fourier series, exploiting
periodic boundary conditions. The second one is composed of summed solutions of
the Helmholtz equation for the original mass and its images. Each of these
summed solutions is the Yukawa potential. In the third formula, we express the
Yukawa potentials via Ewald sums. We show that for the present Universe, both
the bare summation of Yukawa potentials and the Yukawa-Ewald sums require
smaller numbers of terms to yield the numerical values of the potential and the
force up to desired accuracy. Nevertheless, the Yukawa formula is yet
preferable owing to its much simpler structure.


Abstract:
  Two classes of X-ray/$\gamma$-ray sources, the Soft Gamma Repeaters and the
Anomalous X-ray Pulsars have been identified with isolated, slowly spinning
magnetars, neutron stars whose emission draws energy from their extremely
strong magnetic field ($\sim 10^{15}-10^{16}$ G). Magnetars are believed to
form with millisecond spin period and to represent an important fraction of the
whole population of young neutron stars. Newborn magnetars can convert very
quickly their rotational energy into electromagnetic and/or gravitational
waves, by virtue of their strong magnetic fields and fast spins. This chapter
provides a brief summary of astrophysical problems and scenarios in which
millisecond magnetars are believed to play a key role: these include Gamma Ray
Bursts, Supernovae, Gravitational Wave events and Fast Radio Bursts.


Abstract:
  We investigate the interplay of electronic correlations and spin-orbit
coupling (SOC) for a one-band and a two-band honeycomb lattice model. The main
difference between the two models concerning SOC is that in the one-band case
the SOC is a purely non-local term in the basis of the $p_z$ orbitals, whereas
in the two-band case with $p_x$ and $p_y$ as basis functions it is purely
local. In order to grasp the correlation effects on non-local spin-orbit
coupling, we apply the TRILEX approach that allows to calculate non-local
contributions to the self-energy approximatively. For the two-band case we
apply dynamical mean-field theory. In agreement with previous studies, we find
that for all parameter values in our study, the effect of correlations on the
spin-orbit coupling strength is that the bare effective SOC parameter is
increased. However, this increase is much weaker in the non-local than in the
local SOC case. Concerning the TRILEX method, we introduce the necessary
formulas for calculations with broken SU(2) symmetry.


Abstract:
  In this work we consider the problem of identification and reconstruction of
doubly-dispersive channel operators which are given by finite linear
combinations of time-frequency shifts. Such operators arise as time-varying
linear systems for example in radar and wireless communications. In particular,
for information transmission in highly non-stationary environments the channel
needs to be estimated quickly with identification signals of short duration and
for vehicular application simultaneous high-resolution radar is desired as
well. We consider the time-continuous setting and prove an exact resampling
reformulation of the involved channel operator when applied to a trigonometric
polynomial as identifier in terms of sparse linear combinations of real-valued
atoms. Motivated by recent works of Heckel et al. we present an exact approach
for off-the-grid superresolution which allows to perform the identification
with realizable signals having compact support. Then we show how an alternating
descent conditional gradient algorithm can be adapted to solve the reformulated
problem. Numerical examples demonstrate the performance of this algorithm, in
particular in comparison with a simple adaptive grid refinement strategy and an
orthogonal matching pursuit algorithm.


Abstract:
  In the study of correlated systems, approximations based on the dynamical
mean-field theory (DMFT) provide a practical way to take local vertex
corrections into account, which capture, respectively, particle-particle
screening at weak coupling and the formation of the local moment at strong
coupling. We show that in both limits the local vertex corrections can be
efficiently parametrized in terms of single-boson exchange, such that the
two-particle physics described by DMFT and its diagrammatic extensions is
recovered to good approximation and at a reduced computational cost. Our
investigation highlights the importance of the frequency-dependent
fermion-boson coupling (Hedin vertex) for local vertex corrections. Namely, at
weak coupling the fermion-spin-boson coupling suppresses the N\'eel temperature
of the DMFT approximation compared to the static mean-field, whereas for large
interaction it facilitates a huge enhancement of local spin-fluctuation
exchange, giving rise to the effective-exchange energy scale $4t^2/U$. We find
that parametrizations of the vertex which neglect the nontrivial part of the
fermion-boson coupling fail qualitatively at strong coupling.


Abstract:
  Missing data is frequently encountered in practice. Propensity score
estimation is a popular tool for handling such missingness. The propensity
score is often developed using the model for the response probability, which
can be subject to model misspecification. In this paper, we consider an
alternative approach of estimating the inverse of the propensity scores using
the density ratio function. By partitioning the sample into two groups based on
the response status of the elements, we can apply the density ratio function
estimation method and obtain the inverse propensity scores for nonresponse
adjustment. Density ratio estimation can be obtained by applying the so-called
maximum entropy method, which uses the Kullback-Leibler divergence measure
under calibration constraints. By including the covariates for the outcome
regression models only into the density ratio model, we can achieve efficient
propensity score estimation. We further extend the proposed approach to the
multivariate missing case. Some limited simulation studies are presented to
compare with the existing methods.


Abstract:
  We introduce a new measure on regular languages: their nondeterministic
syntactic complexity. It is the least degree of any extension of the `canonical
boolean representation' of the syntactic monoid. Equivalently, it is the least
number of states of any subatomic nondeterministic acceptor. It turns out that
essentially all previous structural work on nondeterministic state-minimality
computes this measure. Our approach rests on an algebraic interpretation of
nondeterministic finite automata as deterministic finite automata endowed with
semilattice structure. Crucially, the latter form a self-dual category.


Abstract:
  We propose a new classifier based on Dempster-Shafer (DS) theory and a
convolutional neural network (CNN) architecture for set-valued classification.
In this classifier, called the evidential deep-learning classifier,
convolutional and pooling layers first extract high-dimensional features from
input data. The features are then converted into mass functions and aggregated
by Dempster's rule in a DS layer. Finally, an expected utility layer performs
set-valued classification based on mass functions. We propose an end-to-end
learning strategy for jointly updating the network parameters. Additionally, an
approach for selecting partial multi-class acts is proposed. Experiments on
image recognition, signal processing, and semantic-relationship classification
tasks demonstrate that the proposed combination of deep CNN, DS layer, and
expected utility layer makes it possible to improve classification accuracy and
to make cautious decisions by assigning confusing patterns to multi-class sets.


Abstract:
  Using the framework of higher-form global symmetries, we examine the regime
of validity of force-free electrodynamics by evaluating the lifetime of the
electric field operator, which is non-conserved due to screening effects. We
focus on a holographic model which has the same global symmetry as that of low
energy plasma and obtain the lifetime of (non-conserved) electric flux in a
strong magnetic field regime. The lifetime is inversely correlated to the
magnetic field strength and thus suppressed in the strong field regime.


Abstract:
  In this paper, we prove the compressible Euler limit from Boltzmann equation
with complete diffusive boundary condition in half-space by employing the
Hilbert expansion which includes interior and Knudsen layers. This rigorously
justifies the corresponding formal analysis in Sone's book
\cite{Sone-2007-Book} in the context of short time smooth solutions. In
particular, different with previous works in this direction, no Prandtl layers
are needed.


Abstract:
  Deep learning has become an increasingly popular and powerful option for
modern pattern recognition systems. However, many deep neural networks have
millions to billions of parameters, making them untenable for real-world
applications with constraints on memory or latency. As a result, powerful
network compression techniques are a must for the widespread adoption of deep
learning. We present DECORE, a reinforcement learning approach to automate the
network compression process. Using a simple policy gradient method to learn
which neurons or channels to keep or remove, we are able to achieve compression
rates 3x to 5x greater than contemporary approaches. In contrast with other
architecture search methods, DECORE is simple and quick to train, requiring
only a few hours of training on 1 GPU. When applied to standard network
architectures on different datasets, our approach achieves 11x to 103x
compression on different architectures while maintaining accuracies similar to
those of the original, large networks.


Abstract:
  We study when the twisted groupoid Banach $*$-algebra
$L^1(\mathcal{G},\sigma)$ is Hermitian. In particular, we prove that Hermitian
groupoids satisfy the weak containment property. Furthermore, we find that for
$L^1(\mathcal{G},\sigma)$ to be Hermitian it is sufficient that $L^1
(\mathcal{G}_\sigma)$ is Hermitian. Moreover, if $\mathcal{G}$ is ample, we
find necessary conditions for $L^1(\mathcal{G},\sigma)$ to be Hermitian in
terms of the fibers $\mathcal{G}^x_x$.


Abstract:
  In this article we extend a previous discussion about the influence of an
external magnetic field on renormalons in a self interacting scalar theory by
including now temperature effects, in the imaginary formalism, together with an
external weak external magnetic field. We show that the location of poles in
the Borel plane does not change, getting their residues, however, a dependence
on temperature and on the magnetic field.The effects of temperature and the
magnetic field strength on the residues turn out to be opposite. We present a
detailed discussion about the evolution of these residues, showing technical
details involved in the calculation.


Abstract:
  Communication using orbital angular momentum (OAM) modes has recently
received a considerable interest in free space optical (FSO) communications.
Propagating OAM modes through free space may be subject to atmospheric
turbulence (AT) distortions that cause signal attenuation and crosstalk which
degrades the system capacity and increases the error probability. In this
paper, we propose to enhance the OAM FSO communications in terms of bit error
rate and spectral efficiency, for different levels of AT regimes. The
performance gain is achieved by introducing orthogonal frequency division
multiplexing (OFDM) with index modulation technique to the OAM FSO system.


Abstract:
  Classical black holes shield us from the singularities that inevitably appear
in general relativity. Being singularity regularization one of the main
landmarks for a successful theory of quantum gravity, quantum black holes are
not obliged to hide their inner core from the outside world. Notwithstanding
the aforesaid, it is often implicitly assumed that quantum gravity effects must
remain confined to black hole interiors. In this essay we argue in the opposite
direction, discussing theoretical evidence for the existence of strong
correlations between the physics inside and outside non-singular black holes.
We conclude that astronomical tests of the surroundings of black holes can
provide invaluable information about their so-far unexplored interiors.


Abstract:
  By studying the 2-dimensional Su-Schrieffer-Heeger-Bose-Hubbard model, we
show the existence of topological Higgs amplitude modes in the strongly
interacting superfluid phase. Using the slave boson approach, we find that, in
the large filling limit, the Higgs excitations and the Goldstone excitations
above the ground state are well decoupled, and both of them exhibit nontrivial
topology inherited from the underlying noninteracting bands. At finite
fillings, they become coupled at high energies; nevertheless, the topology of
these modes are unchanged. Moreover, based on an effective action analysis, we
further provide a universal physical picture for the topological character of
Higgs and Goldstone modes. Our discovery of the first realization of the
topological Higgs mode opens the path to novel investigations in various
systems such as superconductors and quantum magnetism.


Abstract:
  PoseNet can map a photo to the position where it is taken, which is appealing
in robotics. However, training PoseNet requires full supervision, where ground
truth positions are non-trivial to obtain. Can we train PoseNet without knowing
the ground truth positions for each observation? We show that this is possible
via constraint-based weak-supervision, leading to the proposed framework:
DeepGPS. Particularly, using wheel-encoder-estimated distances traveled by a
robot along random straight line segments as constraints between PoseNet
outputs, DeepGPS can achieve a relative positioning error of less than 2%.
Moreover, training DeepGPS can be done as auto-calibration with almost no human
attendance, which is more attractive than its competing methods that typically
require careful and expert-level manual calibration. We conduct various
experiments on simulated and real datasets to demonstrate the general
applicability, effectiveness, and accuracy of DeepGPS, and perform a
comprehensive analysis of its robustness. Our code is available at
https://ai4ce.github.io/DeepGPS/.


Abstract:
  Mild Traumatic Brain Injuries (mTBI) are caused by violent head motions or
impacts. Most mTBI prevention strategies explicitly or implicitly rely on a
"brain injury criterion". A brain injury criterion takes some descriptor of the
head's motion as input and yields a prediction for that motion's potential for
causing mTBI as the output. The inputs are descriptors of the head's motion
that are usually synthesized from accelerometer and gyroscope data. In the
context of brain injury criterion the head is modeled as a rigid body. We
present an algorithm for determining the complete motion of the head using data
from only four head mounted tri-axial accelerometers. In contrast to inertial
measurement unit based algorithms for determining rigid body motion the
presented algorithm does not depend on data from gyroscopes; which consume much
more power than accelerometers. Several algorithms that also make use of data
from only accelerometers already exist. However, those algorithms, except for
the recently presented AO-algorithm [Rahaman MM, Fang W, Fawzi AL, Wan Y,
Kesari H (2020): J Mech Phys Solids 104014], give the rigid body's acceleration
field in terms of the body frame, which in general is unknown. Compared to the
AO-algorithm the presented algorithm is much more insensitive to bias type
errors, such as those that arise from inaccurate measurement of sensor
positions and orientations.


Abstract:
  For steady-state autonomous absorption refrigerators operating in the linear
response regime, we show that there exists a hierarchy between the relative
fluctuation of currents for cold, hot, and work terminals. Our proof requires
the Onsager's reciprocity relation along with the refrigeration condition that
sets the direction of the mean currents for each terminal. As a consequence,
the universal bounds on the mean cooling power, obtained following the
thermodynamic uncertainty relations, receive a hierarchy. Interestingly, within
this hierarchy, the tightest bound is given in terms of the work current
fluctuation. Furthermore, the relative uncertainty hierarchy hands over
additional bounds that can be tighter than the bounds obtained from the
thermodynamic uncertainty relations. Interestingly, all of these bounds
saturate in the tight-coupling limit. We test the validity of our results for
two paradigmatic absorption refrigerator models: (i) a four-level working fluid
and (ii) a two-level working fluid, operating, respectively, in the weak
(additive) and in the strong (multiplicative) system-bath interaction regime.


Abstract:
  Deep learning models are known to be vulnerable to adversarial examples
crafted by adding human-imperceptible perturbations on benign images. Many
existing adversarial attack methods have achieved great white-box attack
performance, but exhibit low transferability when attacking other models.
Various momentum iterative gradient-based methods are shown to be effective to
improve the adversarial transferability. In what follows, we propose an
enhanced momentum iterative gradient-based method to further enhance the
adversarial transferability. Specifically, instead of only accumulating the
gradient during the iterative process, we additionally accumulate the average
gradient of the data points sampled in the gradient direction of the previous
iteration so as to stabilize the update direction and escape from poor local
maxima. Extensive experiments on the standard ImageNet dataset demonstrate that
our method could improve the adversarial transferability of momentum-based
methods by a large margin of 11.1% on average. Moreover, by incorporating with
various input transformation methods, the adversarial transferability could be
further improved significantly. We also attack several extra advanced defense
models under the ensemble-model setting, and the enhancements are remarkable
with at least 7.8% on average.


Abstract:
  Artificial spin ices are magnetic metamaterials comprising
geometrically-tiled interacting nanomagnets. There is significant interest in
these systems for reconfigurable magnonics due to their vast microstate
landscape. Studies to-date have focused on the in-field GHz spin-wave response,
convoluting effects from applied field, nanofabrication-imperfections
('quenched disorder') and microstate-dependent dipolar field landscapes. Here,
we study artificial spin ices in pure and disordered microstates and evaluate
their zero-field spectra. Removing the applied field allows us to deconvolute
contributions to reversal dynamics and spin-wave spectra, directly measuring
the dipolar field landscape and quenched disorder. Mode-amplitude provides
population readout of nanomagnet magnetisation direction, and hence net
magnetisation as well as local vertex populations. We demonstrate
microstate-fingerprinting via distinct spectral-readout of three microstates
with identical (zero) magnetisation, supported by simulation. These results
establish remanence 'spectral-fingerprinting' as a rapid, scalable on-chip
readout of both magnetic state and nanoscale dipolar field texture, a critical
step in realising next-generation functional magnonic devices.


Abstract:
  Bochi-Katok-Rodriguez Hertz proposed in [BKH21] a program on the flexibility
of Lyapunov exponents for conservative Anosov diffeomorphisms, and obtained
partial results in this direction. For conservative Anosov diffeomorphisms with
strong hyperbolic properties we establish extended flexibility results for
their Lyapunov exponents. We give examples of Anosov diffeomorphisms with the
strong unstable exponent larger than the strong unstable exponent of the linear
part. We also give examples of derived from Anosov diffeomorphisms with the
metric entropy entropy larger than the entropy of the linear part.
  These results rely on a new type of deformation which goes beyond the
previous Shub-Wilkinson and Baraviera-Bonatti techniques for conservative
systems having some invariant directions. In order to estimate the Lyapunov
exponents even after breaking the invariant bundles, we obtain an abstract
result (Theorem 3.1) which gives bounds on exponents of some specific cocycles
and which can be applied in various other settings. We also include various
interesting comments in the appendices: our examples are $\mathcal{C}^2$
robust, the Lyapunov exponents are continuous (with respect to the map) even
after breaking the invariant bundles, a similar construction can be obtained
for the case of multiple eigenvalues.


Abstract:
  In supervised classification problems, the test set may contain data points
belonging to classes not observed in the learning phase. Moreover, the same
units in the test data may be measured on a set of additional variables
recorded at a subsequent stage with respect to when the learning sample was
collected. In this situation, the classifier built in the learning phase needs
to adapt to handle potential unknown classes and the extra dimensions. We
introduce a model-based discriminant approach, Dimension-Adaptive Mixture
Discriminant Analysis (D-AMDA), which can detect unobserved classes and adapt
to the increasing dimensionality. Model estimation is carried out via a full
inductive approach based on an EM algorithm. The method is then embedded in a
more general framework for adaptive variable selection and classification
suitable for data of large dimensions. A simulation study and an artificial
experiment related to classification of adulterated honey samples are used to
validate the ability of the proposed framework to deal with complex situations.


Abstract:
  Deep neural networks (DNNs) are vulnerable to adversarial noise.
Preprocessing based defenses could largely remove adversarial noise by
processing inputs. However, they are typically affected by the error
amplification effect, especially in the front of continuously evolving attacks.
To solve this problem, in this paper, we propose to remove adversarial noise by
implementing a self-supervised adversarial training mechanism in a class
activation feature space. To be specific, we first maximize the disruptions to
class activation features of natural examples to craft adversarial examples.
Then, we train a denoising model to minimize the distances between the
adversarial examples and the natural examples in the class activation feature
space. Empirical evaluations demonstrate that our method could significantly
enhance adversarial robustness in comparison to previous state-of-the-art
approaches, especially against unseen adversarial attacks and adaptive attacks.


Abstract:
  We will construct a loop space formalism for general relativity, and
construct the Polyakov variables as connections for such a loop space. We will
use these Polyakov variables to construct a dual theory of gravity beyond
linear approximation. It will be demonstrated that this loop space duality
reduces to the Hodge duality for linearized gravity. Furthermore, a loop space
curvature will be constructed from this Polyakov variable. It will be shown
that this loop space curvature vanishes in the absence of topological defects,
and so it can be used to investigate gravitational monopoles. We will also
construct the suitable monopole charge for such gravitational monopoles.


Abstract:
  Eigenspectra of a spinless quantum particle trapped inside a rigid,
rectangular, two-dimensional (2D) box subject to diverse inner potential
distributions are investigated under hermitian, as well as non-hermitian
antiunitary $\mathcal{PT}$ (composite parity and time-reversal) symmetric
regimes. Four sectors or "stripes" inscribed in the rigid box comprising
contiguously conjoined parallel rectangular segments with one side equaling the
entire width of the box are studied. The stripes encompass piecewise constant
potentials whose exact, complete energy eigenspectrum is obtained employing
matrix mechanics. Various striped potential compositions, viz. real valued ones
in the hermitian regime as well as complex, non-hermitian but $\mathcal{PT}$
symmetric ones are considered separately and in conjunction, unraveling among
typical lowest lying eigenvalues, retention and breakdown scenarios engendered
by the $\mathcal{PT}$ symmetry, bearing upon the strength of non-hermitian
sectors. Some states exhibit a remarkable crossover of symmetry `making' and
`breaking': while a broken $\mathcal{PT}$ gets reinstated for an energy level,
higher levels may couple to continue with symmetry breaking. Further, for a
charged quantum particle a $\mathcal{PT}$ symmetric electric field, furnished
with a striped potential backdrop, also reveals peculiar retention and
breakdown $\mathcal{PT}$ scenarios. Depictions of prominent probability
redistributions relating to various potential distributions both under
norm-conserving unitary regime for hermitian Hamiltonians and non-conserving
ones post $\mathcal{PT}$ breakdown are presented.


Abstract:
  In this thesis we investigate some aspects of quantum field theories from a
holographic perspective. In the first chapters we examine in detail a
one-paremeter family of three-dimensional gauge theories by means of their type
IIA gravity duals. We analyse features such as their confinement nature,
spectrum, entanglement properties or thermal phase transitions. This family
interpolates between quasi-conformal and quasi-confining physics. In the last
two chapters, we use bottom-up models to study complex conformal field theories
and transport properties of dense QCD respectively.


Abstract:
  Refactorings must not alter the program's functionality. However, not all
refactorings fulfill this requirement. Hence, one must explicitly check that a
refactoring does not alter the functionality. Since one rarely has a formal
specification of the program's behavior, we utilize the original program as
functional specification. Then, we check whether the original and refactored
program are functionally equivalent. To this end, we apply a common idea and
reduce equivalence checking to program verification. To increase efficiency,
our equivalence checker PEQcheck constructs one verification task per
refactored code segment instead of one per function as typically done by prior
work. In addition, PEQcheck considers the context of the code segments. For
instance, only variables that are modified and live are required to be
equivalent and read-only variables may be shared between original and
refactored code segments. We show that PEQcheck is sound.Moreover, our
evaluation testifies that the localized and context-aware checking performed by
\peqcheck can indeed be beneficial.


Abstract:
  Recent studies have suggested a new phase in the extended Bose-Hubbard model
in one dimension at integer filling [1,2]. In this work, we show that this new
phase is phase-separated into a supersolid and superfluid part, generated by
mechanical instability. Numerical simulations are performed by means of the
density matrix renormalization group algorithm in terms of matrix product
states. In the phase-separated phase and the adjacent homogeneous superfluid
and supersolid phases, we find peculiar spatial patterns in the entanglement
spectrum and string-order correlation functions and show that they survive in
the thermodynamic limit. In particular, we demonstrate that the elementary
excitations of the homogeneous superfluid with enhanced periodic modulations
are phonons, find the central charge to be $c=1$, and show that the velocity of
sound, extracted from the intrinsic level splitting for finite systems, matches
with the propagation velocity of local excitations in dynamical simulations.
This suggests that the low-energy spectrum of the phase under investigation is
effectively captured by a spinless Luttinger liquid, for which we find
consistent results between the Luttinger parameter obtained from the linear
dependence of the structure factor and the algebraic decay of the one-body
density matrix.


Abstract:
  In this article, formulas for the calculation of force and torque between two
circular filaments arbitrarily oriented in space were derived by using
Kalantarov-Zeitlin's method. Formulas are presented in an analytical form
through integral expressions, whose kernel function is expressed in terms of
the elliptic integrals of the first and second kinds, and provide an
alternative formulation to Babic's expressions. The derived new formulas were
validated via comparison with a series of reference examples. Also, we obtained
additional expressions for the calculation of force and torque between two
circular filaments by means of differentiation of Grover's formula for the
mutual inductance between two circular filaments with respect to appropriate
coordinates. These additional expressions allow to verifying comprehensively
and independently derived new formulas.


Abstract:
  A fundamental problem in spacecraft mission design is to find a free flight
path from one place to another with a given transfer time. This problem for
paths in a central force field is known as Lambert's problem. Although this is
an old problem, we take a new approach. Given two points in the plane, we
produce the conic parameters for all conic paths between these points. For a
given central force gravitational parameter, the travel time between the launch
and destination points is computed along with the initial and final velocities
for each transfer conic. For a given travel time, we calculate the parameters
for a transfer conic having that travel time.


Abstract:
  In this letter we present the first multiparticle solutions to Einstein's
field equations in the presence of matter. These solutions are iteratively
obtained via the perturbiner method, which can circumvent gravity's infinite
number of vertices with the definition of a multiparticle expansion for the
inverse spacetime metric as well. Our construction provides a simple layout for
the computation of tree level field theory amplitudes in $D$ spacetime
dimensions involving any number of gravitons and matter fields, with or without
supersymmetry.


Abstract:
  We present a new library of semi-empirical stellar spectra that is based on
the empirical MILES library. A new, high resolution library of theoretical
stellar spectra is generated that is specifically designed for use in stellar
population studies. We test these models across their full wavelength range
against other model libraries and find reasonable agreement in their
predictions of spectral changes due to atmospheric $\alpha$-element variations,
known as differential corrections. We also test the models against the MILES
and MaStar libraries of empirical stellar spectra and also find reasonable
agreements, as expected from previous work. We then use the abundance pattern
predictions of the new theoretical stellar spectra to differentially correct
MILES spectra to create semi-empirical MILES (sMILES) star spectra with
abundance patterns that differ from those present in the Milky Way. The final
result is 5 families of 801 sMILES stars with [$\alpha$/Fe] abundances ranging
from $-$0.20 to 0.60 dex at MILES resolution (FWHM=$2.5\,${\AA}) and wavelength
coverage ($3540.5-7409.6\,${\AA}). We make the sMILES library publicly
available.


Abstract:
  In this paper we introduce our vision of a Cognitive Computing Continuum to
address the changing IT service provisioning towards a distributed,
opportunistic, self-managed collaboration between heterogeneous devices outside
the traditional data center boundaries. The focal point of this continuum are
cognitive devices, which have to make decisions autonomously using their
on-board computation and storage capacity based on information sensed from
their environment. Such devices are moving and cannot rely on fixed
infrastructure elements, but instead realise on-the-fly networking and thus
frequently join and leave temporal swarms. All this creates novel demands for
the underlying architecture and resource management, which must bridge the gap
from edge to cloud environments, while keeping the QoS parameters within
required boundaries. The paper presents an initial architecture and a resource
management framework for the implementation of this type of IT service
provisioning.


Abstract:
  We show that the number of configurations of the 20 Vertex model on certain
domains with domain wall type boundary conditions is equal to the number of
domino tilings of Aztec-like triangles, proving a conjecture from [P. Di
Francesco and E. Guitter, Twenty-Vertex Model with Domain Wall Boundaries and
Domino Tilings, Elec. Jour. of Combinatorics 27 (2020), no. 2, P2.13]. The
result is based on the integrability of the 20 Vertex model and uses a
connection to the U-turn boundary 6 Vertex model to re-express the number of 20
Vertex configurations as a simple determinant, which is then related to a
Lindstr\"om-Gessel-Viennot determinant for the domino tiling problem. The
common number of configurations is conjectured to be
$2^{n(n-1)/2}\prod_{j=0}^{n-1}\frac{(4j+2)!}{(n+2j+1)!}=1, 4, 60, 3328,
678912...$ The enumeration result is extended to include refinements of both
numbers.


Abstract:
  The paper develops a general methodology for analyzing policies with
path-dependency (hysteresis) in stochastic models with forward looking
optimizing agents. Our main application is a macro-climate model with a
path-dependent climate externality. We derive in closed form the dynamics of
the optimal Pigouvian tax, that is, its drift and diffusion coefficients. The
dynamics of the present marginal damages is given by the recently developed
functional It\^o formula. The dynamics of the conditional expectation process
of the future marginal damages is given by a new total derivative formula that
we prove. The total derivative formula represents the evolution of the
conditional expectation process as a sum of the expected dynamics of hysteresis
with respect to time, a form of a time derivative, and the expected dynamics of
hysteresis with the shocks to the trajectory of the stochastic process, a form
of a stochastic derivative. We then generalize the results. First, we propose a
general class of hysteresis functionals that permits significant tractability.
Second, we characterize in closed form the dynamics of the stochastic
hysteresis elasticity that represents the change in the whole optimal policy
process with an introduction of small hysteresis effects. Third, we determine
the optimal policy process.


Abstract:
  A theoretical investigation associated with obliquely propagating
ion-acoustic shock waves (IASHWs) in a three-component magnetized plasma having
inertialess non-extensive electrons, inertial warm positive and negative ions
has been performed. A Burgers equation is derived by employing the reductive
perturbation method. Our plasma model supports both positive and negative shock
structures under the consideration of non-extensive electrons. It is found that
the positive and negative shock wave potentials increase with the oblique angle
($\delta$) which arises due to the external magnetic field. It is also observed
that the magnitude of the amplitude of positive and negative shock waves is not
effected by the variation of the ion kinematic viscosity but the steepness of
the positive and negative shock waves decreases with ion kinematic viscosity.
The implications of our findings in space and laboratory plasmas are briefly
discussed.


Abstract:
  Let $\ell$ be a rational prime. Previously, abelian $\ell$-towers of
multigraphs were introduced which are analogous to
$\mathbb{Z}_{\ell}$-extensions of number fields. It was shown that for a
certain class of towers of bouquets, the growth of the $\ell$-part of the
number of spanning trees behaves in a predictable manner (analogous to a
well-known theorem of Iwasawa for $\mathbb{Z}_{\ell}$-extensions of number
fields). In this paper, we give a generalization to a broader class of regular
abelian $\ell$-towers of bouquets than was originally considered. To carry this
out, we observe that certain shifted Chebyshev polynomials are members of a
continuously parametrized family of power series with coefficients in
$\mathbb{Z}_{\ell}$ and then study the special value at $s=1$ of the
Artin-Ihara $L$-function $\ell$-adically.


Abstract:
  The muon $g-2$ anomaly was strengthened by recent experimental results at
Fermilab, which may be signatures of new physics. A scenario of leptophilic
scalar $\phi_L$ accounting for the muon $g-2$ anomaly is investigated in this
paper. Though a light $\phi_L$ mainly decaying into standard model (SM)
particles has been excluded by experiments, a dark leptophilic scalar $\phi_L$
predominantly decaying into invisible fermionic dark matter (DM) $\chi
\bar{\chi}$ is still allowed. Considering the decay mode $\phi_L \to \chi
\bar{\chi}$ opened (here $m_{\phi_L} = 3 m_\chi$), the coupling preferred by
the muon $g-2$ and the $\phi_L-\chi$ coupling are derived. The light/heavy
$\phi_L$ (roughly 1 GeV as a benchmark value) can be tested by future
experiments via DM/SM decay modes. The search of $\chi$ via $\chi-$electron
scattering in DM direct detection is not sensitive due to a tiny
$\phi_L-$electron coupling, especially for $m_\chi \gtrsim m_\mu$.


Abstract:
  We investigate the in-medium properties of hyperons and anti-hyperons in the
framework of the Non-Linear Derivative (NLD) model. We focus on the momentum
dependence of in-medium strangeness optical potentials. The NLD model is based
on the simplicity of the well-established Relativistic Mean-Field (RMF)
approximation, but it incorporates an explicit momentum dependence on a
field-theoretical level. The extension of the NLD model to the
(anti)baryon-octet is formulated in the spirit of SU(6) and G-parity arguments.
It is shown that with an appropriate choice of momentum cut-offs the $\Lambda$,
$\Sigma$ and $\Xi$ optical potentials are consistent with recent studies of the
chiral effective field theory and Lattice-QCD calculations over a wide momentum
region. In addition, we present NLD predictions for the in-medium momentum
dependence of $\overline{\Lambda}$-, $\overline{\Sigma}$- and
$\overline{\Xi}$-hyperons. This work is important for future experimental
studies such as CBM, PANDA at the Facility for Antiproton and Ion Research
(FAIR). It is relevant for nuclear astrophysics too.


Abstract:
  In the field of differential equations, particularly fluid dynamics, many
researchers have shown an interest in the behavior of time periodic solutions.
In this paper, we study isentropic gas flow in a bounded interval and apply a
time periodic outer force. This motion is described by the compressible Euler
equation with the outer force. Our purpose in this paper is to prove the
existence of a time periodic solutions. Unfortunately, little is known for the
system of conservation laws until now. The problem seems to lie in fact that
the equation does not possesses appropriate decay estimates.


Abstract:
  We obtain an exact spherically symmetric and magnetically charged black hole
solution in 4D Einstein-Gauss-Bonnet gravity coupled with nonlinear
electrodynamics with the Lagrangian ${\cal L}_{NED} = -{\cal
F}/(1+\sqrt{2\mid\beta{\cal F}\mid})$ (${\cal F}$ is the field strength
invariant). The thermodynamics of the black hole is studied within our model.
We calculate the Hawking temperature and the heat capacity of the black hole.
The phase transitions occur in the point where the Hawking temperature
possesses an extremum and the heat capacity diverges. It was shown that black
holes are thermodynamically stable in some range of event horizon radii when
the heat capacity and Hawking temperature are positive. The logarithmic
correction to the Bekenstein - Hawking BH entropy is obtained which mimics a
quantum correction. The dependence of the BH shadow radius on the model
parameters is studied. We also investigate the particle emission rate of the
BH. The stability of the BH is studied by analysing the quasinormal modes.


Abstract:
  We define an exactly solvable model for 2+1D topological phases of matter on
a triangulated surface derived from a crossed module of semisimple
finite-dimensional Hopf algebras, the "Hopf-algebraic higher Kitaev model".
This model generalizes both the Kitaev quantum double model for a semisimple
Hopf algebra and the full higher Kitaev model derived from a 2-group, and can
hence be interpreted as a Hopf-algebraic discrete higher gauge theory.
  We construct a family of crossed modules of semisimple Hopf algebras
$(\mathscr{F}_{\mathbb{C}}(X) \otimes \mathbb{C}E \xrightarrow{\partial}
\mathscr{F}_{\mathbb{C}}(Y) \rtimes \mathbb{C} G, \triangleright)$ that depends
on four finite groups $E,G,X$ and $Y$. We calculate the ground-state spaces of
the resulting model when $G=E=\{1\}$ and when $Y=\{1\}$, both properly
Hopf-algebraic constructions; prove that they are canonically independent of
the triangulations; and find a 2+1D TQFT whose state spaces on surfaces give
the ground-state spaces. These TQFTs are particular cases of Quinn's finite
total homotopy TQFT and hence the state spaces assigned to surfaces are free
vector spaces on sets of homotopy classes of maps from a surface to homotopy
finite spaces, in this case obtained as classifying spaces of finite groupoids
and finite crossed modules of groupoids.
  We leave it as an open problem whether the ground-state space of the
Hopf-algebraic higher Kitaev model on a triangulated surface is independent of
the triangulation for general crossed modules of semisimple Hopf algebras,
whether a TQFT always exists whose state space on a surface gives the
ground-state space of the model, and whether the ground-state space of the
model obtained from $E,G,X,Y$ can always be given a homotopical explanation.


Abstract:
  The precise calibration of the strain readout of the LIGO gravitational wave
observatories is paramount to the accurate interpretation of gravitational wave
events. This calibration is traditionally done by imparting a known force on
the test masses of the observatory via radiation pressure. Here we describe the
implementation of an alternative calibration scheme: the Newtonian Calibrator.
This system uses a rotor consisting of both quadrupole and hexapole mass
distributions to apply a time-varying gravitational force on one of the
observatory's test masses. The force produced by this rotor can be predicted to
$<1\%$ relative uncertainty and is well-resolved in the readout of the
observatory. This system currently acts as a cross-check of the existing
absolute calibration system.


Abstract:
  This paper considers the design of On-Demand Multimodal Transit Systems
(ODMTS) that combine fixed bus/rail routes between transit hubs with on-demand
shuttles to serve the first/last miles to/from the hubs. The design problem
aims at finding a network design for the fixed routes to allow a set of riders
to travel from their origins to their destinations, while minimizing the sum of
the travel costs, the bus operating costs, and rider travel times. The paper
addresses two gaps in existing tools for designing ODMTS. First, it generalizes
prior work by including ridesharing in the shuttle rides. Second, it proposes
novel fleet-sizing algorithms for determining the number of shuttles needed to
meet the performance metrics of the ODMTS design. Both contributions are based
on Mixed-Integer Programs (MIP). For the ODMTS design, the MIP reasons about
pickup and dropoff routes in order to capture ridesharing, grouping riders who
travel to/from the same hub. The fleet-sizing optimization is modeled as a
minimum flow problem with covering constraints. The natural formulation leads
to a dense graph and computational issues, and is refined in an optimized model
working on a sparse graph. The methodological contributions are evaluated on a
real case study: the public transit system of the broader Ann Arbor and
Ypsilanti region in Michigan. The results demonstrate the substantial potential
of ridesharing for ODMTS, as costs are reduced by about 26% with minimal
increase in transit times. Compared to the existing system, the designed ODMTS
also cuts down costs by 35% and reduces transit times by 38%.


Abstract:
  Let $A$ be a right linear operator on a two-sided quaternionic Banach space
$X$. The paper studies the Drazin inverse for right linear operators on a
quaternionic Banach space. It is shown that if $A$ is Drazin invertible then
the Drazin inverse of $A$ is given by $f(A)$ where $f$ is $0$ in an axially
symmetric neighborhood of $0$ and $f(q) = q^{-1}$ in an axially symmetric
neighborhood of the nonzero spherical spectrum of $A$. Some results analogous
to the ones concerning the Drazin inverse of operators on complex Banach spaces
are proved in the quaternionic context.


Abstract:
  The space-weather conditions that result from stellar winds significantly
impact the habitability of exoplanets. The conditions can be calculated from
first principles if the necessary boundary conditions -- namely on the plasma
density in the outer corona and the radial distance at which the plasma forces
the closed magnetic field into an open geometry -- are specified. Low frequency
radio observations ($\nu \lesssim 200$ MHz) of plasma and cyclotron emission
from stars probe these magneto-ionic conditions. Here we report the detection
of low-frequency ($120-167\,{\rm MHz}$) radio emission associated with the dMe6
star WX UMa. If the emission originates in WX UMa's corona, we show that the
closed field regions extends to at least $\approx 10$ stellar radii, that is
about a factor of a few larger than the solar value, and possibly to $\gtrsim
20$ stellar radii. Our results suggest that the magnetic-field structure of M
dwarfs is in between Sun-like and planet-like configurations, where compact
over-dense coronal loops with X-ray emitting plasma co-exist with a large-scale
magnetosphere with lower plasma density and closed magnetic geometry.


Abstract:
  The Ensemble Empirical Mode Decomposition (EEMD) has become a preferred
technique to decompose nonlinear and non-stationary signals due to its ability
to create time-varying basis functions. However, current EEMD signal cleaning
techniques are unable to deal with situations where a signal only occurs for a
portion of the entire recording length. By combining change point detection and
statistical hypothesis testing, we demonstrate how to clean a signal to
emphasize unique local changes within each basis function. This not only allows
us to observe which frequency bands are undergoing a change, but also leads to
improved recovery of the underlying information. Using this technique, we
demonstrate improved signal cleaning performance for acoustic shockwave signal
detection. The technique is implemented in R via the LCDSC package.


Abstract:
  A search for a heavy resonance decaying to a top quark and a W boson in the
fully hadronic final state is presented. The analysis is performed using data
from proton-proton collisions at a center-of-mass energy of 13 TeV,
corresponding to an integrated luminosity of 137 fb$^{-1}$ recorded by the CMS
experiment at the LHC. The search is focused on heavy resonances, where the
decay products of each top quark or W boson are expected to be reconstructed as
a single, large-radius jet with a distinct substructure. The production of an
excited bottom quark, b*, is used as a benchmark when setting limits on the
cross section for a heavy resonance decaying to a top quark and a W boson. The
hypotheses of b* quarks with left-handed, right-handed, and vector-like
chiralities are excluded at 95% confidence level for masses below 2.6, 2.8, and
3.1 TeV, respectively. These are the most stringent limits on the b* quark mass
to date, extending the previous best limits by almost a factor of two.


Abstract:
  Injecting frozen deuterium pellets into an ELMy H-mode plasma is a well
established scheme for triggering edge localized modes (ELMs) before they
naturally occur. Based on an ASDEX Upgrade H-mode plasma, this article presents
a comparison of extended MHD simulations of spontaneous type-I ELMs and
pellet-triggered ELMs allowing to study their non-linear dynamics in detail. In
particular, pellet-triggered ELMs are simulated by injecting deuterium pellets
into different time points during the pedestal build-up described in [A. Cathey
et al. Nuclear Fusion 60, 124007 (2020)]. Realistic ExB and diamagnetic
background plasma flows as well as the time dependent bootstrap current
evolution are included during the build-up to capture the balance between
stabilising and destabilising terms for the edge instabilities accurately.
Dependencies on the pellet size and injection times are studied. The
spatio-temporal structures of the modes and the resulting divertor heat fluxes
are compared in detail between spontaneous and triggered ELMs. We observe that
the premature excitation of ELMs by means of pellet injection is caused by a
helical perturbation described by a toroidal mode number of n = 1. In
accordance with experimental observations, the pellet-triggered ELMs show
reduced thermal energy losses and narrower divertor wetted area with respect to
spontaneous ELMs. The peak divertor energy fluency is seen to decrease when
ELMs are triggered by pellets injected earlier during the pedestal build-up.


Abstract:
  We present the discovery of 24 pulsars in 15 Globular Clusters (GCs) using
the Five-hundred-meter Aperture Spherical radio Telescope (FAST). These include
the first pulsar discoveries in M2, M10, and M14. Most of the new systems are
either confirmed or likely members of binary systems. M53C, NGC6517H and I are
the only three pulsars confirmed to be isolated. M14A is a black widow pulsar
with an orbital period of 5.5 hours and a minimum companion mass of 0.016 \Ms.
M14E is an eclipsing binary pulsar with an orbital period of 20.3 hours. With
the other 8 discoveries that have been reported elsewhere, in total 32 GC
pulsars have been discovered by FAST so far. In addition, We detected M3A
twice. This was enough to determine that it is a black widow pulsar with an
orbital period of 3.3 hours and a minimum companion mass of 0.0125 \Ms.


Abstract:
  We report the detection of a short-lived narrow quasi-periodic oscillation
(QPO) at ~88 mHz in an Insight-HXMT observation during the soft state of the
persistent black hole high mass X-ray binary Cygnus X-1. This QPO is
significantly detected in all the three instruments of Insight-HXMT, so in the
broad energy range 1-250 keV. The fractional rms of the QPO does not show
significant variations above 3 keV (~5%) while decreases at lower energy (~2%).
We show that this QPO is different from the type-A, -B, and -C QPOs usually
observed in black hole X-ray binaries. We compare QPOs at similar frequencies
that have been previously detected in other persistent high-mass X-ray binaries
in the soft state; we speculate that such QPOs might relate to some local
inhomogeneity rarely formed in the accretion flow of wind-fed accretion
systems.


Abstract:
  Low resource Handwritten Text Recognition (HTR) is a hard problem due to the
scarce annotated data and the very limited linguistic information (dictionaries
and language models). For example, in the case of historical ciphered
manuscripts, which are usually written with invented alphabets to hide the
message contents. Thus, in this paper we address this problem through a data
generation technique based on Bayesian Program Learning (BPL). Contrary to
traditional generation approaches, which require a huge amount of annotated
images, our method is able to generate human-like handwriting using only one
sample of each symbol in the alphabet. After generating symbols, we create
synthetic lines to train state-of-the-art HTR architectures in a segmentation
free fashion. Quantitative and qualitative analyses were carried out and
confirm the effectiveness of the proposed method.


Abstract:
  In this short note, we compute the rational $C_{2^n}$-equivariant stable
stems and give minimal presentations for the $RO(C_{2^n})$-graded Bredon
cohomology of the equivariant classifying spaces $B_{C_{2^n}}S^1$ and
$B_{C_{2^n}}\Sigma_2$ over the rational Burnside functor $A_{\mathbf Q}$. We
also examine for which compact Lie groups $L$ the maximal torus inclusion $T\to
L$ induces an isomorphism from $H^*_{C_{2^n}}(B_{C_{2^n}}L;A_{\mathbf Q})$ onto
the fixed points of $H^*_{C_{2^n}}(B_{C_{2^n}}T;A_{\mathbf Q})$ under the Weyl
group action. We prove that this holds for $L=U(m)$ and any $n,m\ge 1$ but does
not hold for $L=SU(2)$ and $n>1$.


Abstract:
  Silicon microstrip detectors are widely used in experiments for space
astronomy. Before the detector is assembled, extensive characterization of the
silicon microstrip sensors is indispensable and challenging. This work
electrically evaluates a series of sensor parameters, including the depletion
voltage, bias resistance, metal strip resistance, total leakage current, strip
leakage current, coupling capacitance, and interstrip capacitance. Two methods
are used to accurately measure the strip leakage current, and the test results
match each other well. In measuring the coupling capacitance, we extract the
correct value based on a SPICE model and two-port network analysis. In
addition, the expression of the measured bias resistance is deduced based on
the SPICE model.


Abstract:
  Ranked list truncation is of critical importance in a variety of professional
information retrieval applications such as patent search or legal search. The
goal is to dynamically determine the number of returned documents according to
some user-defined objectives, in order to reach a balance between the overall
utility of the results and user efforts. Existing methods formulate this task
as a sequential decision problem and take some pre-defined loss as a proxy
objective, which suffers from the limitation of local decision and non-direct
optimization. In this work, we propose a global decision based truncation model
named AttnCut, which directly optimizes user-defined objectives for the ranked
list truncation. Specifically, we take the successful transformer architecture
to capture the global dependency within the ranked list for truncation
decision, and employ the reward augmented maximum likelihood (RAML) for direct
optimization. We consider two types of user-defined objectives which are of
practical usage. One is the widely adopted metric such as F1 which acts as a
balanced objective, and the other is the best F1 under some minimal recall
constraint which represents a typical objective in professional search.
Empirical results over the Robust04 and MQ2007 datasets demonstrate the
effectiveness of our approach as compared with the state-of-the-art baselines.


Abstract:
  With the expressed goal of improving system transparency and visual grounding
in the reasoning process in VQA, we present a modular system for the task of
compositional VQA based on scene graphs. Our system is called "Adventurer's
Treasure Hunt" (or ATH), named after an analogy we draw between our model's
search procedure for an answer and an adventurer's search for treasure. We
developed ATH with three characteristic features in mind: 1. By design, ATH
allows us to explicitly quantify the impact of each of the sub-components on
overall VQA performance, as well as their performance on their individual
sub-task. 2. By modeling the search task after a treasure hunt, ATH inherently
produces an explicit, visually grounded inference path for the processed
question. 3. ATH is the first GQA-trained VQA system that dynamically extracts
answers by querying the visual knowledge base directly, instead of selecting
one from a specially learned classifier's output distribution over a pre-fixed
answer vocabulary. We report detailed results on all components and their
contributions to overall VQA performance on the GQA dataset and show that ATH
achieves the highest visual grounding score among all examined systems.


Abstract:
  The vertices of the Cayley graph of a finitely generated semigroup form a set
of sites which can be labeled by elements of a finite alphabet in a manner
governed by a nonnegative real interaction matrix, respecting nearest neighbor
adjacency restrictions. To the set of these configurations one can associate a
pressure, which is defined as the limit, when it exists, of averages of the
logarithm of the partition function over certain finite subgraphs. We prove
that for shifts of finite type on generalized Fibonacci trees, under an added
condition, the limit exists and is given by an infinite series. We also show
that the limit of any cluster points of the pressure on finite subtrees as the
number of generators grows without bound, which we call the asymptotic
pressure, equals the logarithm of the maximum row sum of the interaction
matrix.


Abstract:
  Data hiding is the art of hiding secret data into a cover object such as
digital image for covert communication. In this paper, we make the first step
towards hiding ``data hiding'', which is totally different from many
conventional works that directly embed secret data in a given cover object. In
detail, we propose a novel method to disguise data hiding tools, including a
data embedding tool and a data extraction tool, as a deep neural network (DNN)
with an ordinary task (i.e., style transfer). After training the DNN for both
style transfer and data hiding, while the DNN can transfer the style of an
image to the target one, it can also hide secret data into a cover image or
extract secret data from a stego image. In other words, the tools of data
hiding are hidden to avoid arousing suspicion. Experimental results and
analysis have shown the feasibility, applicability and superiority of the
proposed method.


Abstract:
  Disordered quantum systems feature an energy scale know as the Thouless
energy. For energy ranges below this scale, the properties of the energy
spectrum can be described by random matrix theory. Above this scale a different
behavior sets in. For a metallic system it has been long ago shown by Altshuler
and Shklovskii that the number variance should increase as a power law with a
power dependent only on the dimensionality of the system. Although tantalizing
hints for this behavior have been seen in previous numerical studies, it is
quite difficult to verify this prediction using the standard local unfolding
methods. Here we use a different unfolding method, i.e., the singular value
decomposition, and establish a connection between the power law behavior of the
scree plot (the singular values ranked by their amplitude) and the power law
behavior of the number variance. Thus we are able to numerically verify the
Altshuler and Shklovskii's prediction for disordered $3D$, $4D$, and $5D$
single-electron Anderson models on square lattices in the metallic regime. The
same method could be applied to systems such as the Sachdev-Ye-Kitaev model and
various interacting many body models for which the many body localization
occurs. It has been recently reported that such systems exhibit a Thouless
energy and analyzing the spectrum's behavior on larger scales is of much
current interest.


Abstract:
  The microscopic processes underlying electro-optic sampling of quantum-vacuum
fluctuations are discussed, leading to the interpretation of these experiments
in terms of an exchange of virtual photons. With this in mind it is shown how
one can directly study the Purcell effect, i.e. the changes induced by cavities
upon the quantum vacuum, in the frequency and time domains. This forges a link
between electro-optic sampling of the quantum vacuum and geometry-induced
vacuum effects.


Abstract:
  Nonzero neutrino masses imply the existence of degrees of freedom and
interactions beyond those in the Standard Model. A powerful indicator of what
these might be is the nature of the massive neutrinos: Dirac fermions versus
Majorana fermions. While addressing the nature of neutrinos is often associated
with searches for lepton-number violation, there are several other features
that distinguish Majorana from Dirac fermions. Here, we compute in great detail
the kinematics of the daughters of the decays into charged-leptons and
neutrinos of hypothetical heavy neutral leptons at rest. We allow for the decay
to be mediated by the most general four-fermion interaction Lagrangian. We
demonstrate, for example, that when the daughter charged-leptons have the same
flavor or the detector is insensitive to their charges, polarized
Majorana-fermion decays have zero forward/backward asymmetry in the direction
of the outgoing neutrino (relative to the parent spin), whereas Dirac-fermion
decays can have large asymmetries. Going beyond studying forward/backward
asymmetries, we also explore the fully-differential width of the three-body
decays. It contains a wealth of information not only about the nature of the
new fermions but also the nature of the interactions behind their decays.


Abstract:
  Line segmentation from handwritten text images is one of the challenging task
due to diversity and unknown variations as undefined spaces, styles,
orientations, stroke heights, overlapping, and alignments. Though abundant
researches, there is a need of improvement to achieve robustness and higher
segmentation rates. In the present work, an adaptive approach is used for the
line segmentation from handwritten text images merging the alignment of
connected component coordinates and text height. The mathematical justification
is provided for measuring the text height respective to the image size. The
novelty of the work lies in the text height calculation dynamically. The
experiments are tested on the dataset provided by the Chinese company for the
project. The proposed scheme is tested on two different type of datasets;
document pages having base lines and plain pages. Dataset is highly complex and
consists of abundant and uncommon variations in handwriting patterns. The
performance of the proposed method is tested on our datasets as well as
benchmark datasets, namely IAM and ICDAR09 to achieve 98.01% detection rate on
average. The performance is examined on the above said datasets to observe
91.99% and 96% detection rates, respectively.


Abstract:
  Using {\it Gaia} Early Data Release 3 (EDR3) parallaxes and Bayesian
inference, we infer a parallax of the Westerlund 1 (Wd1) cluster. We find a
parallax of $0.34\pm{0.05}$ mas corresponding to a distance of
$2.8^{+0.7}_{-0.6}$ kpc. The new {\it Gaia} EDR3 distance is consistent with
our previous result using {\it Gaia} DR2 parallaxes. This confirms that Wd1 is
less massive and older than previously assumed. Compared to DR2, the EDR3
individual parallax uncertainties for each star decreased by 30\%. However, the
aggregate parallax uncertainty for the cluster remained the same. This suggests
that the uncertainty is dominated by systematics, which is possibly due to
crowding, motions within the cluster, or motions due to binary orbits.


Abstract:
  Very recently, To et al.~have experimentally explored granular flow in a
cylindrical silo, with a bottom wall that rotates horizontally with respect to
the lateral wall \cite{Kiwing2019}. Here, we numerically reproduce their
experimental findings, in particular, the peculiar behavior of the mass flow
rate $Q$ as a function of the frequency of rotation $f$. Namely, we find that
for small outlet diameters $D$ the flow rate increased with $f$, while for
larger $D$ a non-monotonic behavior is confirmed. Furthermore, using a
coarse-graining technique, we compute the macroscopic density, momentum, and
the stress tensor fields. These results show conclusively that changes in the
discharge process are directly related to changes in the flow pattern from
funnel flow to mass flow. Moreover, by decomposing the mass flux (linear
momentum field) at the orifice into two main factors: macroscopic velocity and
density fields, we obtain that the non-monotonic behavior of the linear
momentum is caused by density changes rather than by changes in the macroscopic
velocity. In addition, by analyzing the spatial distribution of the kinetic
stress, we find that for small orifices increasing rotational shear enhances
the mean kinetic pressure $\langle p^k \rangle$ and the system dilatancy. This
reduces the stability of the arches, and, consequently, the volumetric flow
rate increases monotonically. For large orifices, however, we detected that
$\langle p^k \rangle$ changes non-monotonically, which might explain the
non-monotonic behavior of $Q$ when varying the rotational shear.


Abstract:
  In this short note, we observe that Theorem 3.1 in arXiv:1508.00682 for
semiorthogonal indecomposability of the derived category of smooth DM stacks
based on the canonical bundle can be extended to the case of projective
varieties with Cohen-Macaulay singularities. As a consequence, all projective
curves of positive arithmetic genus have weakly indecomposable bounded derived
categories and indecomposable categories of perfect complexes. Here weak
indecomposablility refers to the admissibility of components.


Abstract:
  We present an audio-visual speech separation learning method that considers
the correspondence between the separated signals and the visual signals to
reflect the speech characteristics during training. Audio-visual speech
separation is a technique to estimate the individual speech signals from a
mixture using the visual signals of the speakers. Conventional studies on
audio-visual speech separation mainly train the separation model on the
audio-only loss, which reflects the distance between the source signals and the
separated signals. However, conventional losses do not reflect the
characteristics of the speech signals, including the speaker's characteristics
and phonetic information, which leads to distortion or remaining noise. To
address this problem, we propose the cross-modal correspondence (CMC) loss,
which is based on the cooccurrence of the speech signal and the visual signal.
Since the visual signal is not affected by background noise and contains
speaker and phonetic information, using the CMC loss enables the audio-visual
speech separation model to remove noise while preserving the speech
characteristics. Experimental results demonstrate that the proposed method
learns the cooccurrence on the basis of CMC loss, which improves separation
performance.


Abstract:
  This paper focuses on inverse reinforcement learning for autonomous
navigation using distance and semantic category observations. The objective is
to infer a cost function that explains demonstrated behavior while relying only
on the expert's observations and state-control trajectory. We develop a map
encoder, that infers semantic category probabilities from the observation
sequence, and a cost encoder, defined as a deep neural network over the
semantic features. Since the expert cost is not directly observable, the model
parameters can only be optimized by differentiating the error between
demonstrated controls and a control policy computed from the cost estimate. We
propose a new model of expert behavior that enables error minimization using a
closed-form subgradient computed only over a subset of promising states via a
motion planning algorithm. Our approach allows generalizing the learned
behavior to new environments with new spatial configurations of the semantic
categories. We analyze the different components of our model in a minigrid
environment. We also demonstrate that our approach learns to follow traffic
rules in the autonomous driving CARLA simulator by relying on semantic
observations of buildings, sidewalks, and road lanes.


Abstract:
  Let $\Delta+V$ be the discrete Schr\"odinger operator,
  where $\Delta$ is the discrete Laplacian on $\Z^d$ and the potential
$V:\Z^d\to \R$ is periodic.
  We prove three rigidity theorems for discrete periodic Schr\"odinger
operators in any dimension $d\geq 3$:
  \begin{enumerate}
  \item if at some energy level, Fermi varieties of the $\Gamma$-periodic
potential $V$ and the $\Gamma$-periodic potential $Y$ are the same (referred to
as {\it Fermi isospectrality} of $V$ and $Y$), and $Y $ is a separable
function, then $V$ is separable;
  \item if potentials $V$ and $Y$ are {\it Fermi isospectral} and both
$V=\bigoplus_{j=1}^rV_j$ and $Y=\bigoplus_{j=1}^r Y_j$ are separable functions,
then, up to a constant, lower dimensional decompositions $V_j$ and $Y_j$ are
Floquet isospectral, $j=1,2,\cdots,r$;
  \item if a potential $V$ and the zero potential are {\it Fermi isospectral},
then $V$ is zero.
  \end{enumerate} In particular, all conclusions in (1), (2) and (3) hold if we
replace the assumption ``Fermi isospectrality" with a stronger assumption
``Floquet isospectrality".


Abstract:
  Readout errors on near-term quantum computers can introduce significant error
to the empirical probability distribution sampled from the output of a quantum
circuit. These errors can be mitigated by classical postprocessing given the
access of an experimental \emph{response matrix} that describes the error
associated with measurement of each computational basis state. However, the
resources required to characterize a complete response matrix and to compute
the corrected probability distribution scale exponentially in the number of
qubits $n$. In this work, we modify standard matrix inversion techniques using
two perturbative approximations with significantly reduced complexity and
bounded error when the likelihood of high order bitflip events is strongly
suppressed. Given a characteristic error rate $q$, our first method recovers
the probability of the all-zeros bitstring $p_0$ by sampling only a small
subspace of the response matrix before inverting readout error resulting in a
relative speedup of $\text{poly}\left(2^{n} / \big(\begin{smallmatrix} n \\ w
\end{smallmatrix}\big)\right)$, which we motivate using a simplified error
model for which the approximation incurs only $O(q^w)$ error for some integer
$w$. We then provide a generalized technique to efficiently recover full output
distributions with $O(q^w)$ error in the perturbative limit. These approximate
techniques for readout error correction may greatly accelerate near term
quantum computing applications.


Abstract:
  A positive integer $n$ is called perfect if $ \sigma(n)=2n$, where
$\sigma(n)$ denote the sum of divisors of $n$. In this paper we study the ratio
$\frac{\sigma(n)}{n}$. We define the function Abundancy Index $I:\mathbb{N} \to
\mathbb{Q}$ with $I(n)=\frac{\sigma(n)}{n}$. Then we study different properties
of the Abundancy Index and discuss the set of Abundancy Index. Using this
function we define a new class of numbers known as superabundant numbers.
Finally, we study superabundant numbers and their connection with Riemann
Hypothesis.


Abstract:
  Can a dynamically robust bosonic star (BS) produce an (effective) shadow that
mimics that of a black hole (BH)? The BH shadow is linked to the existence of
light rings (LRs). For free bosonic fields, yielding mini-BSs, it is known that
these stars can become ultra-compact - i.e., possess LRs - but only for
perturbatively unstable solutions. We show this remains the case even when
different self-interactions are considered. However, an effective shadow can
arise in a different way: if BSs reproduce the existence of an innermost stable
circular orbit (ISCO) for timelike geodesics (located at $r_{\rm ISCO}=6M$ for
a Schwarzschild BH of mass M), the accretion flow morphology around BHs is
mimicked and an effective shadow arises in an astrophysical environment. Even
though spherical BSs may accommodate stable timelike circular orbits all the
way down to their centre, we show the angular velocity along such orbits may
have a maximum away from the origin, at $R_{\Omega}$; this scale was recently
observed to mimic the BH's ISCO in some scenarios of accretion flow. Then: (i)
for free scalar fields or with quartic self-interactions, $R_{\Omega}\neq 0$
only for perturbatively unstable BSs; (ii) for higher scalar self-interactions,
e.g. axionic, $R_{\Omega}\neq 0$ is possible for perturbatively stable BSs, but
no solution with $R_{\Omega}=6M$ was found in the parameter space explored;
(iii) but for free vector fields, yielding Proca stars (PSs), perturbatively
stable solutions with $R_{\Omega}\neq 0$ exist, and indeed $R_{\Omega}=6M$ for
a particular solution. Thus, dynamically robust spherical PSs can mimic the
shadow of a (near-)equilibrium Schwarzschild BH with the same M, in an
astrophysical environment, despite the absence of a LR, at least under some
observation conditions, as we confirm by comparing the lensing of such PSs and
Schwarzschild BHs.


Abstract:
  Cell-free massive MIMO (CF-mMIMO) systems represent a promising approach to
increase the spectral efficiency of wireless communication systems. However,
near-optimal beamforming solutions require a large amount of signaling exchange
between access points (APs) and the network controller (NC). In this letter, we
propose two unsupervised deep neural networks (DNN) architectures, fully and
partially distributed, that can perform decentralized coordinated beamforming
with zero or limited communication overhead between APs and NC, for both fully
digital and hybrid precoding. The proposed DNNs achieve near-optimal sum-rate
while also reducing computational complexity by 10-24x compared to conventional
near-optimal solutions.


Abstract:
  Medical image segmentation, or computing voxelwise semantic masks, is a
fundamental yet challenging task to compute a voxel-level semantic mask. To
increase the ability of encoder-decoder neural networks to perform this task
across large clinical cohorts, contrastive learning provides an opportunity to
stabilize model initialization and enhance encoders without labels. However,
multiple target objects (with different semantic meanings) may exist in a
single image, which poses a problem for adapting traditional contrastive
learning methods from prevalent 'image-level classification' to 'pixel-level
segmentation'. In this paper, we propose a simple semantic-aware contrastive
learning approach leveraging attention masks to advance multi-object semantic
segmentation. Briefly, we embed different semantic objects to different
clusters rather than the traditional image-level embeddings. We evaluate our
proposed method on a multi-organ medical image segmentation task with both
in-house data and MICCAI Challenge 2015 BTCV datasets. Compared with current
state-of-the-art training strategies, our proposed pipeline yields a
substantial improvement of 5.53% and 6.09% on Dice score for both medical image
segmentation cohorts respectively (p-value<0.01). The performance of the
proposed method is further assessed on natural images via the PASCAL VOC 2012
dataset, and achieves a substantial improvement of 2.75% on mIoU
(p-value<0.01).


Abstract:
  In \cite{NNM} the author with A. N\'emethi computed the multiplicity of
generic surface singularities, the formula is purely topological computable
from the resolution graph of the surface singularity. In the present paper we
extend the results partly to the relative case, when there is a pair of
resolution graphs $\mathcal{T}_1 \subset \mathcal{T}$, a fixed singularity
$\tX_1$ with resolution graph $\mathcal{T}_1$, a relatively generic singularity
$\tX$ corresponding to the subsingularity $\tX_1$ with resolution graph
$\mathcal{T}$.
  We determine the base points of the natural line bundles (under some mild
conditions) on $\tX$ from the resolution graph $\mathcal{T}$ and the analytic
invariants of the subsingularity $\tX_1$. For each base point $p$ we determine
a lower bound for the number $t_p$ such that $p$ is $t_p$-simple and we compute
from it a lower bound of the multiplicity of $\tX$, which is sharp in all known
cases.


Abstract:
  For a compact convex set F in R^n, with the origin in its interior, we
present a formula to compute the curvature at a fixed point on its boundary, in
the direction of any tangent vector. This formula is equivalent to the existing
ones, but it is easier to apply.


Abstract:
  The organising principles underlying the structure of phenomenologically
viable string vacua can be accessed by sampling such vacua. In many cases this
is prohibited by the computational cost of standard sampling methods in the
high dimensional model space. Here we show how this problem can be alleviated
using reinforcement learning techniques to explore string flux vacua. We
demonstrate in the case of the type IIB flux landscape that vacua with
requirements on the expectation value of the superpotential and the string
coupling can be sampled significantly faster by using reinforcement learning
than by using metropolis or random sampling. Our analysis is on conifold and
symmetric torus background geometries. We show that reinforcement learning is
able to exploit successful strategies for identifying such phenomenologically
interesting vacua. The strategies are interpretable and reveal previously
unknown correlations in the flux landscape.


Abstract:
  Cybersecurity is a very emerging field that protects systems, networks, and
data from digital attacks. With the increase in the scale of the Internet and
the evolution of cyber attacks, developing novel cybersecurity tools has become
important, particularly for Internet of things (IoT) networks. This paper
provides a systematic review of the application of deep learning (DL)
approaches for cybersecurity. This paper provides a short description of DL
methods which is used in cybersecurity, including deep belief networks,
generative adversarial networks, recurrent neural networks, and others. Next,
we illustrate the differences between shallow learning and DL. Moreover, a
discussion is provided on the currently prevailing cyber-attacks in IoT and
other networks, and the effectiveness of DL methods to manage these attacks.
Besides, this paper describes studies that highlight the DL technique,
cybersecurity applications, and the source of datasets. Next, a discussion is
provided on the feasibility of DL systems for malware detection and
classification, intrusion detection, and other frequent cyber-attacks,
including identifying file type, spam, and network traffic. Our review
indicates that high classification accuracy of 99.72% is obtained by restricted
Boltzmann machine (RBM) when applied to a custom dataset, while long short-term
memory (LSTM) achieves an accuracy of 99.80% for KDD Cup 99 dataset. Finally,
this article discusses the importance of cybersecurity for reliable and
practicable IoT-driven healthcare systems.


Abstract:
  This paper presents a general procedure based on using the method of types to
calculate the box dimension of sets. The approach unifies and simplifies
multiple box counting arguments. In particular, we use it to generalize the
formula for the box dimension of self-affine carpets of Gatzouras-Lalley and of
Bara\'nski type to their higher dimensional sponge analogues. In addition to a
closed form, we also obtain a variational formula which resembles the
Ledrappier-Young formula for Hausdorff dimension.


Abstract:
  In quantum fluids, the quantisation of circulation forbids the diffusion of a
vortex swirling flow seen in classical viscous fluids. Yet, a quantum vortex
accelerating in a superfluid may lose its energy into acoustic radiation, in a
similar way an electric charge decelerates upon emitting photons. The
dissipation of vortex energy underlies central problems in quantum
hydrodynamics, such as the decay of quantum turbulence, highly relevant to
systems as varied as neutron stars, superfluid helium and atomic condensates. A
deep understanding of the elementary mechanisms behind irreversible vortex
dynamics has been a goal for decades, but it is complicated by the shortage of
conclusive experimental signatures. Here, we address this challenge by
realising a programmable quantum vortex collider in a planar, homogeneous
atomic Fermi superfluid with tunable inter-particle interactions. We create
on-demand vortex configurations and monitor their evolution, taking advantage
of the accessible time and length scales of our ultracold Fermi gas.
Engineering collisions within and between vortex-antivortex pairs allows us to
decouple relaxation of the vortex energy due to sound emission and interactions
with normal fluid, i.e. mutual friction. We directly visualise how the
annihilation of vortex dipoles radiates a sound pulse in the superfluid.
Further, our few-vortex experiments extending across different superfluid
regimes suggest that fermionic quasiparticles localised inside the vortex core
contribute significantly to dissipation, opening the route to exploring new
pathways for quantum turbulence decay, vortex by vortex.


Abstract:
  The destructive interference of the neighbouring field configurations with
infinite classical action in the gravitational path integral approach serves as
a dynamical mechanism resolving the black hole singularity problem. It also
provides an isotropic and homogeneous early universe without the need of
inflation. In this work, we elaborate on the finite action in the framework of
Horava-Lifshitz gravity -- a ghost-free QFT. Assuming the mixmaster chaotic
solutions in the projectable H-L theory, we show that the beginning of the
universe is homogeneous and isotropic. Furthermore, we show that the H-L
gravity action selects only the regular black-hole spacetimes. We also comment
on possibility of traversable wormholes in theories with higher curvature
invariants.


Abstract:
  Owing to the discrete frequency spectrum of whispering gallery resonators
(WGRs), the resonance and phase-matching conditions for the interacting waves
in the case of second-harmonic generation (SHG) cannot generally be fulfilled
simultaneously. To account for this, we develop a model describing SHG in WGRs
with non-zero frequency detunings at both the pump and second-harmonic
frequencies. Our model predicts strong distortions of the line shape of pump
and second-harmonic resonances for similar linewidths at both frequencies; for
much larger linewidths at the second-harmonic frequency, this behavior is
absent. Furthermore, it describes the SHG efficiency as a function of detuning.
Experimentally, one can change the WGR eigenfrequencies, and thus the relative
detuning between pump and second-harmonic waves by a number of means, for
example electro-optically and thermally. Using a lithium niobate WGR, we show
an excellent quantitative agreement for the SHG efficiency between our
experimental results and the model. Also, we show the predicted distortions of
the pump and second-harmonic resonances to be absent in the lithium niobate
WGR, but present in a cadmium silicon phosphide WGR, as expected from the
linewidths of the resonances involved.


Abstract:
  The empirical success of deep convolutional networks on tasks involving
high-dimensional data such as images or audio suggests that they can
efficiently approximate certain functions that are well-suited for such tasks.
In this paper, we study this through the lens of kernel methods, by considering
simple hierarchical kernels with two or three convolution and pooling layers,
inspired by convolutional kernel networks. These achieve good empirical
performance on standard vision datasets, while providing a simple enough
description of the functional space to shed light on their inductive bias. We
show that the RKHS consists of additive models of interaction terms between
patches, and that its norm encourages structured spatial similarities between
these terms through pooling layers. We then provide generalization bounds which
illustrate how pooling yields improved sample complexity guarantees when the
target function presents such regularities.


Abstract:
  Orbits of automorphism groups of partially ordered sets are not necessarily
congruence classes, i.e. images of an order homomorphism. Based on so-called
orbit categories a framework of factorisations and unfoldings is developed that
preserves the antisymmetry of the order Relation. Finally some suggestions are
given, how the orbit categories can be represented by simple directed and
annotated graphs and annotated binary relations. These relations are reflexive,
and, in many cases, they can be chosen to be antisymmetric. From these
constructions arise different suggestions for fundamental systems of partially
ordered sets and reconstruction data which are illustrated by examples from
mathematical music theory.


Abstract:
  We prove that two analytic branches in $(\mathbb{C}^n,0)$ whose dual
resolution graph is the same admit an ambient isotopy which is smooth outside
the origin. A weaker version of the converse is also proved.


Abstract:
  The need to evaluate treatment effectiveness is ubiquitous in most of
empirical science, and interest in flexibly investigating effect heterogeneity
is growing rapidly. To do so, a multitude of model-agnostic, nonparametric
meta-learners have been proposed in recent years. Such learners decompose the
treatment effect estimation problem into separate sub-problems, each solvable
using standard supervised learning methods. Choosing between different
meta-learners in a data-driven manner is difficult, as it requires access to
counterfactual information. Therefore, with the ultimate goal of building
better understanding of the conditions under which some learners can be
expected to perform better than others a priori, we theoretically analyze four
broad meta-learning strategies which rely on plug-in estimation and
pseudo-outcome regression. We highlight how this theoretical reasoning can be
used to guide principled algorithm design and translate our analyses into
practice by considering a variety of neural network architectures as
base-learners for the discussed meta-learning strategies. In a simulation
study, we showcase the relative strengths of the learners under different
data-generating processes.


Abstract:
  We consider the infrared factorisation of non-abelian multi-particle
scattering amplitudes, and we study the form of the universal colour operator
responsible for infrared divergences, when expressed in terms of coordinates on
the `celestial sphere' intersecting the future light-cone at asymptotic
distances. We find that colour-dipole contributions to the infrared operator,
to all orders in perturbation theory, have a remarkably simple expression in
these coordinates, with scale and coupling dependence factorised from
kinematics and colour. Generalising earlier suggestions in the abelian theory,
we then show that the infrared operator can be computed as a correlator of
vertex operators in a conformal field theory of Lie-algebra-valued free bosons
on the celestial sphere. We verify by means of the OPE that the theory
correctly predicts the all-order structure of collinear limits, and the
tree-level factorisation of soft real radiation.


Abstract:
  First-order convergence in time and space is proved for a fully discrete
semi-implicit finite element method for the two-dimensional Navier--Stokes
equations with $L^2$ initial data in convex polygonal domains, without extra
regularity assumptions or grid-ratio conditions. The proof utilises the
smoothing properties of the Navier--Stokes equations, an appropriate duality
argument, and the smallness of the numerical solution in the discrete
$L^2(0,t_m;H^1)$ norm when $t_m$ is smaller than some constant. Numerical
examples are provided to support the theoretical analysis.


Abstract:
  Improvements in rechargeable batteries are enabling several electric urban
air mobility (UAM) aircraft designs with up to 300 miles of range with payload
equivalents of up to 7 passengers. We find that novel UAM aircraft consume
between 130 Wh/passenger-mile up to ~1,200 Wh/passenger-mile depending on the
design and utilization, relative to an expected consumption of over 220
Wh/passenger-mi for terrestrial electric vehicles and 1,000 Wh/passenger-mile
for combustion engine vehicles. We also find that several UAM aircraft designs
are approaching technological viability with current Li-ion batteries, based on
the specific power-and-energy while rechargeability and lifetime performance
remain uncertain. These aspects highlight the technological readiness of a new
segment of transportation.


Abstract:
  Ivrii's conjecture asserts that the Cauchy problem is $C^{\infty}$ well-posed
for any lower order term if every critical point of the principal symbol is
effectively hyperbolic. Effectively hyperbolic critical point is at most triple
characteristic. If every characteristic is at most double this conjecture has
been proved in 1980's. In this paper we prove the conjecture for the remaining
cases, that is for operators with triple effectively hyperbolic
characteristics.


Abstract:
  Presentation slides have become a common addition to the teaching material.
Emphasizing strong leading words in presentation slides can allow the audience
to direct the eye to certain focal points instead of reading the entire slide,
retaining the attention to the speaker during the presentation. Despite a large
volume of studies on automatic slide generation, few studies have addressed the
automation of design assistance during the creation process. Motivated by this
demand, we study the problem of Emphasis Selection (ES) in presentation slides,
i.e., choosing candidates for emphasis, by introducing a new dataset containing
presentation slides with a wide variety of topics, each is annotated with
emphasis words in a crowdsourced setting. We evaluate a range of
state-of-the-art models on this novel dataset by organizing a shared task and
inviting multiple researchers to model emphasis in this new domain. We present
the main findings and compare the results of these models, and by examining the
challenges of the dataset, we provide different analysis components.


Abstract:
  The baryon acoustic oscillations (BAO) have proven to be an invaluable tool
in constraining the expansion history of the Universe at late times and are
characterized by the comoving sound horizon at the baryon drag epoch
$r_\mathrm{s}(z_\mathrm{d})$. The latter quantity can be calculated either
numerically using recombination codes or via fitting functions, such as the one
by Eisenstein and Hu (EH), made via grids of parameters of the recombination
history. Here we quantify the accuracy of these expressions and show that they
can strongly bias the derived constraints on the cosmological parameters using
BAO data. Then, using a machine learning approach, called the genetic
algorithms, we proceed to derive new analytic expressions for
$r_\mathrm{s}(z_\mathrm{d})$ which are accurate at the $\sim0.003\%$ level in a
range of $10\sigma$ around the Planck 2018 best-fit or $\sim0.018\%$ in a much
broader range, compared to $\sim 2-4\%$ for the EH expression, thus obtaining
an improvement of two to three orders of magnitude. Moreover, we also provide
fits that include the effects of massive neutrinos and an extension to the
concordance cosmological model assuming variations of the fine structure
constant. Finally, we note that our expressions can be used to ease the
computational cost required to compute $r_\mathrm{s}(z_\mathrm{d})$ with a
Boltzmann code when deriving cosmological constraints using BAO data from
current and upcoming surveys.