title: Generalized McVittie geometry in Horndeski gravity with matter

abstract:
  We investigate McVittie and generalized McVittie solutions for Horndeski
gravity with a spatially homogeneous gravitational scalar field, which is
stealth at small scales near the central object but, at large scales, sources
the FLRW universe in which the central inhomogeneity is embedded. Unlike
previous studies, we include matter and obtain generalized McVittie solutions
in the extended cuscuton model. The possible configurations are classified
according to the time-dependence of the gravitational coupling, the radial
energy flow, the accretion rate onto the central object, and the Hubble rate.


title: Is the $\bar \theta$ parameter of QCD constant?

abstract:
  Testing the variation of fundamental constants of Nature can provide valuable
insights into new physics scenarios. While many constraints have been derived
for Standard Model coupling constants and masses, the $\bar{\theta}$ parameter
of QCD has often been ignored in these studies. This letter discusses
potentially promising paths to investigate the time dependence of the
$\bar{\theta}$ parameter. While laboratory searches for CP-violating signals of
$\bar{\theta}$ yield the most robust bounds on today's value of $\bar{\theta}$,
we show that CP-conserving effects provide constraints on the variation of
$\bar{\theta}$ over cosmological time scales. We find no significant evidence
for a variation of $\bar{\theta}$ except for a mild hint around $z\sim 4$ which
would imply an "iron-deficient" Universe at high redshifts. Finally, we also
sketch an axion model which results in a varying $\bar{\theta}$ and could lead
to excess diffuse gamma ray background, from decays of axions produced in high
redshift supernova explosions.


title:
Ab initio guided minimal model for the "Kitaev" material
  BaCo$_2$(AsO$_4$)$_2$: Importance of direct hopping, third-neighbor exchange
  and quantum fluctuations

abstract:
  We present a simple three-parameter exchange model to describe the
interactions of the lowest doublet of the honeycomb cobaltate
BaCo$_2$(AsO$_4$)$_2$, which has been proposed as a possible candidate for
Kitaev physics. Remarkably, it is the third-neighbor interactions, both
isotropic and anisotropic, that are responsible for the unique ground state of
BaCo$_2$(AsO$_4$)$_2$, stabilized by quantum fluctuations. By considering two
{\it ab initio}-based complementary approaches, we analyze the electronic
structure of BaCo$_2$(AsO$_4$)$_2$ and extract effective spin models that
justify the minimal model. Both methods show that the dominant direct hopping
makes the bond-dependent Kitaev term negligible moving the material away from
the sought-after spin-liquid regime. Moreover, a significantly large
third-nearest neighbor hopping supports the observed importance of the
third-neighbor interactions in the stabilization of the standout double-zigzag
ground state of BaCo$_2$(AsO$_4$)$_2$.


title: Atmospheric Dynamics of a Near Tidally Locked Earth-Size Planet

abstract:
  The discovery and characterization of Earth-sized planets that are in, or
near, a tidally-locked state are of crucial importance to understanding
terrestrial planet evolution, and for which Venus is a clear analog.
Exoplanetary science lies at the threshold of characterizing hundreds of
terrestrial planetary atmospheres, thereby providing a statistical sample far
greater than the limited inventory of terrestrial planetary atmospheres within
the Solar System. However, the model-based approach for characterizing
exoplanet atmospheres relies on Solar System data, resulting in our limited
inventory being both foundational and critical atmospheric laboratories.
Present terrestrial exoplanet demographics are heavily biased toward
short-period planets, many of which are expected to be tidally locked, and also
potentially runaway greenhouse candidates, similar to Venus. Here we describe
the rise in the terrestrial exoplanet population and the study of tidal locking
on climate simulations. These exoplanet studies are placed within the context
of Venus, a local example of an Earth-sized, asynchronous rotator that is near
the tidal locking limit. We describe the recent lessons learned regarding the
dynamics of the Venusian atmosphere and how those lessons pertain to the
evolution of our sibling planet. We discuss the implications of these lessons
for exoplanet atmospheres, and outline the need for a full characterization of
the Venusian climate in order to achieve a full and robust interpretation of
terrestrial planetary atmospheres.


title:
Hyperfunction formulation of many body Green's functions and the
  Matsubara formalism

abstract:
  We show that the single-particle Green's functions used in many body theory
have an elegant description in the form of hyperfunctions. We summarize the
necessary hyperfunction concepts. We show that the analytical properties and
the relations between different Green's functions are natural within this
formulation. Important results from the standard formalism are recovered
straightforwardly. We argue that hyperfunctions could possibly provide a
powerful new tool for many body theory, if the formalism could be developed
beyond single-particle Green's functions.

categories: cond-mat.str-el cond-mat.stat-mech math-ph math.MP


title: CO Excitation and Line Energy Distributions in Gas-selected Galaxies

abstract:
  While emission-selected galaxy surveys are biased towards the most luminous
part of the galaxy population, absorption selection is a potentially unbiased
galaxy selection technique with respect to luminosity. However, the physical
properties of absorption-selected galaxies are not well characterised. Here we
study the excitation conditions in the interstellar medium (ISM) in damped
Ly$\alpha$ (DLA) absorption-selected galaxies. We present a study of the CO
spectral line energy distribution (SLED) in four high-metallicity
absorption-selected galaxies with previously reported CO detections at
intermediate ($z \sim 0.7$) and high ($z \sim 2$) redshifts. We find further
evidence for a wide variety of ISM conditions in these galaxies. Two out of the
four galaxies show CO SLEDs consistent with that of the Milky Way inner disk.
Interestingly, one of these galaxies is at $z \sim 2$ and has a CO SLED below
that of main-sequence galaxies at similar redshifts. The other two galaxies at
$z>2$ show more excited ISM conditions, with one of them showing thermal
excitation of the mid-$J$ (J$=3, 4$) levels, similar to that seen in two
massive main-sequence galaxies at these redshifts. Overall, we find that
absorption selection traces a diverse population of galaxies.


title:
Distances to Local Group Galaxies via Population II, Stellar Distance
  Indicators. II. The Fornax Dwarf Spheroidal

abstract:
  We determine three independent Population II distance moduli to the Fornax
dwarf spheroidal (dSph) galaxy, using wide-field, ground-based $VI$ imaging
acquired with the Magellan-Baade telescope at Las Campanas Observatory. After
subtracting foreground stars using Gaia EDR3 proper motions, we measure an
$I$-band tip of the red giant branch (TRGB) magnitude of $I_0^\mathrm{TRGB} =
16.753 \pm 0.03_\mathrm{stat} \pm 0.037_\mathrm{sys}$ mag, with a calibration
based in the LMC giving a distance modulus of $\mu_0^\mathrm{TRGB} = 20.80 \pm
0.037_\mathrm{stat} \pm 0.057_\mathrm{sys}$ mag. We determine an RR Lyrae (RRL)
distance from template mean magnitudes, with periods adopted from the
literature. Adopting a Gaia DR2 calibration of first overtone RRL
period-luminosity and period-Wesenheit relations, we find $\mu_0^\mathrm{PLZ} =
20.74 \pm 0.01_\mathrm{stat} \pm 0.12_\mathrm{sys}$ mag and $\mu_0^\mathrm{PWZ}
= 20.68 \pm 0.02_\mathrm{stat} \pm 0.07_\mathrm{sys}$ mag. Finally, we
determine a distance from Fornax's horizontal branch (HB) and two galactic
globular cluster calibrators, giving $\mu_0^\mathrm{HB} = 20.83 \pm
0.03_\mathrm{stat} \pm 0.09_\mathrm{sys}$ mag. These distances are each derived
from homogeneous IMACS photometry, are anchored to independent geometric
zero-points, and utilize different classes of stars. We therefore average over
independent uncertainties and report the combined distance modulus $\langle
\mu_0\rangle = 20.770 \pm 0.042_\mathrm{stat} \pm 0.024_\mathrm{sys}$ mag
(corresponding to a distance of $143\pm3$ kpc).


title:
A Massive Star is Born: How Feedback from Stellar Winds, Radiation
  Pressure, and Collimated Outflows Limits Accretion onto Massive Stars

abstract:
  Massive protostars attain high luminosities as they are actively accreting
and the radiation pressure exerted on the gas in the star's atmosphere may
launch isotropic high-velocity ($v_{\rm w} \gtrsim 10^3$ km/s) winds. These
winds will collide with the surrounding gas producing shock-heated ($T\sim
10^7$ K) tenuous gas that adiabatically expands and pushes on the dense gas
that may otherwise be accreted. We present a series of 3D
radiation-magnetohydrodynamic simulations of the collapse of massive prestellar
cores and include radiative feedback from the direct stellar and
dust-reprocessed radiation fields, collimated outflows, and, for the first
time, isotropic stellar winds to model how these processes affect the formation
of massive (proto)stars. We find that winds are initially launched when the
massive protostar is still accreting and the wind properties evolve as the star
contracts to the main sequence. Wind feedback drives asymmetric adiabatic wind
bubbles that have a bipolar morphology because the dense circumstellar material
pinches the expansion of the hot shock-heated gas, which preferentially expands
along low-density channels. We term this the "wind tunnel effect." For
unmagnetized cores, we find that wind feedback eventually quenches accretion
onto massive stars. For magnetized cores, we find that wind feedback is less
efficient at halting the accretion flow initially because magnetic tension
delays the growth of the wind-driven bubbles. Once winds become strong enough,
wind feedback launches adiabatic wind bubbles that eventually reduce accretion.
Additionally, we discuss the implications of observing adiabatic wind bubbles
with Chandra while the massive protostars are still highly embedded.


title:
Where are the magnetar binary companions? Candidates from a comparison
  with binary population synthesis predictions

abstract:
  It is well established that magnetars are neutron stars with extreme magnetic
fields and young ages, but the evolutionary pathways to their creation are
still uncertain. Since most massive stars are in binaries, if magnetars are a
frequent result of core-collapse supernovae, some fraction are expected to have
a bound companion at the time of observation. In this paper, we utilise
literature constraints, including deep Hubble Space Telescope imaging, to
search for bound stellar companions to magnetars. The magnitude and colour
measurements are interpreted in the context of binary population synthesis
predictions. We find two candidates for stellar companions associated with CXOU
J171405.7-381031 and SGR 0755-2933, based on their J-H colours and H-band
absolute magnitudes. Overall, the proportion of the Galactic magnetar
population with a plausibly stellar near-infrared counterpart candidate, based
on their magnitudes and colours, is between 5 and 10 per cent. This is
consistent with a population synthesis prediction of 5 per cent, for the
fraction of core-collapse neutron stars arising from primaries which remain
bound to their companion after the supernova. These results are therefore
consistent with magnetars being drawn in an unbiased way from the natal
core-collapse neutron star population, but some contribution from alternative
progenitor channels cannot be ruled out.


title:
Galactic ArchaeoLogIcaL ExcavatiOns (GALILEO) I. An updated census of
  APOGEE N-rich giants across the Milky Way

abstract:
  (ABRIDGED) We use the 17th data release of the second phase of the Apache
Point Observatory Galactic Evolution Experiment (APOGEE-2) to provide a
homogenous census of N-rich red giant stars across the Milky Way (MW). We
report a total of 149 newly identified N-rich field giants toward the bulge,
metal-poor disk, and halo of our Galaxy. They exhibit significant enrichment in
their nitrogen abundance ratios ([N/Fe] $\gtrsim+0.5$), along with simultaneous
depletions in their [C/Fe] abundance ratios ([C/Fe] $< +0.15$), and they cover
a wide range of metallicities ($-1.8 < $ [Fe/H] $ <-0.7$). The final sample of
candidate N-rich red giant stars with globular-cluster-like (GC-like) abundance
patterns from the APOGEE survey includes a grand total of $\sim$ 412 unique
objects. These strongly N-enhanced stars are speculated to have been stripped
from GCs based on their chemical similarities with these systems. Even though
we have not found any strong evidence for binary companions or signatures of
pulsating variability yet, we cannot rule out the possibility that some of
these objects were members of binary systems in the past and/or are currently
part of a variable system. In particular, the fact that we identify such stars
among the field stars in our Galaxy provides strong evidence that the
nucleosynthetic process(es) producing the anomalous [N/Fe] abundance ratios
occurs over a wide range of metallicities. This may provide evidence either for
or against the uniqueness of the progenitor stars to GCs and/or the existence
of chemical anomalies associated with likely tidally shredded clusters in
massive dwarf galaxies such as "Kraken/Koala," \textit{Gaia}-Enceladus-Sausage,
among others, before or during their accretion by the MW. A dynamical analysis
reveals that the newly identified N-rich stars exhibit a wide range of
dynamical characteristics throughout the MW, ...


title:
APOGEE-2S Mg-Al anti-correlation of the Metal-Poor Globular Cluster NGC
  2298

abstract:
  We present detailed elemental abundances and radial velocities of stars in
the metal-poor globular cluster (GC) NGC 2298, based on near-infrared
high-resolution ($R\sim$ 22,500) spectra of twelve members obtained during the
second phase of the Apache Point Observatory Galactic Evolution Experiment
(APOGEE-2) at Las Campanas Observatory as part of the seventeenth Data Release
(DR 17) of the Sloan Digital Sky Survey IV (SDSS-IV). We employ the Brussels
Automatic Code for Characterizing High accuracy Spectra (\texttt{BACCHUS})
software to investigate abundances for a variety of species including
$\alpha$-elements (Mg, Si, and Ca), the odd-Z element Al, and iron-peak
elements (Fe and Ni) located in the innermost regions of NGC 2298. We find a
mean and median metallicity [Fe/H] $ = -1.76$ and $-1.75$, respectively, with a
star-to-star spread of 0.14 dex, compatible with the internal measurement
errors. Thus, we find no evidence for an intrinsic Fe abundance spread in NGC
2298. The typical $\alpha-$element enrichment in NGC 2298 is overabundant
relative to the Sun, and follows the trend of other metal-poor GCs. We confirm
the existence of an Al-enhanced population in this cluster, which is clearly
anti-correlated with Mg, indicating the prevalence of the multiple-population
phenomenon in NGC 2298.


title: The importance of X-ray frequency in driving photoevaporative winds

abstract:
  Photoevaporative winds are a promising mechanism for dispersing
protoplanetary discs, but so far theoretical models have been unable to agree
on the relative roles that the X-ray, Extreme Ultraviolet or Far Ultraviolet
play in driving the winds. This has been attributed to a variety of
methodological differences between studies, including their approach to
radiative transfer and thermal balance, the choice of irradiating spectrum
employed, and the processes available to cool the gas. We use the
\textsc{mocassin} radiative transfer code to simulate wind heating for a
variety of spectra on a static density grid taken from simulations of an
EUV-driven wind. We explore the impact of choosing a single representative
X-ray frequency on their ability to drive a wind by measuring the maximum
heated column as a function of photon energy. We demonstrate that for
reasonable luminosities and spectra, the most effective energies are at a few
$100~\mathrm{eV}$, firmly in the softer regions of the X-ray spectrum, while
X-rays with energies $\sim1000~\mathrm{eV}$ interact too weakly with disc gas
to provide sufficient heating to drive a wind. We develop a simple model to
explain these findings. We argue that further increases in the cooling above
our models - for example due to molecular rovibrational lines - may further
restrict the heating to the softer energies but are unlikely to prevent X-ray
heated winds from launching entirely; increasing the X-ray luminosity has the
opposite effect. The various results of photoevaporative wind models should
therefore be understood in terms of the choice of irradiating spectrum.


title:
The detection efficiency of type Ia supernovae from the Zwicky Transient
  Facility: Limits on the intrinsic rate of early flux excesses

abstract:
  Samples of young type Ia supernovae have shown `early excess' emission in a
few cases. Similar excesses are predicted by some explosion and progenitor
scenarios and hence can provide important clues regarding the origin of
thermonuclear supernovae. They are however, only predicted to last up to the
first few days following explosion. It is therefore unclear whether such
scenarios are intrinsically rare or if the relatively small sample size simply
reflects the difficulty in obtaining sufficiently early detections. To that
end, we perform toy simulations covering a range of survey depths and cadences,
and investigate the efficiency with which young type Ia supernovae are
recovered. As input for our simulations, we use models that broadly cover the
range of predicted luminosities. Based on our simulations, we find that in a
typical three day cadence survey, only $\sim$10% of type Ia supernovae would be
detected early enough to rule out the presence of an excess. A two day cadence
however, should see this increase to $\sim$15%. We find comparable results from
more detailed simulations of the Zwicky Transient Facility surveys. Using the
recovery efficiencies from these detailed simulations, we investigate the
number of young type Ia supernovae expected to be discovered assuming some
fraction of the population come from scenarios producing an excess at early
times. Comparing the results of our simulations to observations, we find the
intrinsic fraction of type Ia supernovae with early flux excesses is
$\sim28^{+13}_{-11}%$%.


title:
An H-alpha survey of the host environments of 77 type IIn supernovae
  within z<0.02

abstract:
  Type IIn supernovae (SNe\,IIn) are an uncommon and highly heterogeneous class
of SN where the SN ejecta interact with pre-existing circumstellar media (CSM).
Previous studies have found a mass ladder in terms of the association of the SN
location with H$\alpha$ emission and the progenitor masses of SN classes. In
this paper, we present the largest environmental study of SNe\,IIn. We analyse
the H$\alpha$ environments of 77 type IIn supernovae using continuum subtracted
H$\alpha$ images. We use the pixel statistics technique, normalised cumulative
ranking (NCR), to associate SN pixels with H$\alpha$ emission. We find that our
77 SNe\,IIn do not follow the H$\alpha$ emission. This is not consistent with
the proposed progenitors of SNe\,IIn, luminous blue variables (LBVs) as LBVs
are high mass stars that undergo dramatic episodic mass loss. However, a subset
of the NCR values follow the H$\alpha$ emission, suggesting a population of
high mass progenitors. This suggests there may be multiple progenitor paths
with $\sim$60\% having non-zero NCR values with a distribution consistent with
high mass progenitors such as LBVs and $\sim$40\% of these SNe not being
associated with H$\alpha$ emission. We discuss the possible progenitor routes
of SNe\,IIn, especially for the zero NCR value population. We also investigate
the radial distribution of the SNe in their hosts in terms of H$\alpha$ and
$r'$-band flux.


title: Smart Interference Management xApp using Deep Reinforcement Learning

abstract:
  Interference continues to be a key limiting factor in cellular radio access
network (RAN) deployments. Effective, data-driven, self-adapting radio resource
management (RRM) solutions are essential for tackling interference, and thus
achieving the desired performance levels particularly at the cell-edge. In
future network architecture, RAN intelligent controller (RIC) running with
near-real-time applications, called xApps, is considered as a potential
component to enable RRM. In this paper, based on deep reinforcement learning
(RL) xApp, a joint sub-band masking and power management is proposed for smart
interference management. The sub-band resource masking problem is formulated as
a Markov Decision Process (MDP) that can be solved employing deep RL to
approximate the policy functions as well as to avoid extremely high
computational and storage costs of conventional tabular-based approaches. The
developed xApp is scalable in both storage and computation. Simulation results
demonstrate advantages of the proposed approach over decentralized baselines in
terms of the trade-off between cell-centre and cell-edge user rates, energy
efficiency and computational efficiency.


title: Host Galaxies of Ultra Strong Mg II absorbers at z $\sim$ 0.5

abstract:
  From a sample of 109 candidate Ultra-Strong Mg II (USMgII; having rest
equivalent width of Mg II absorption, $W_{2796}>3.0$ Angstrom) systems at
z=0.4-0.6, we confirm 27 and identify host galaxies of 20 systems based on
associated nebular line emission from our SALT observations or from SDSS fiber
spectra. The measured impact parameter, [O II] luminosity, star formation rate,
B-band luminosity and stellar mass are in the ranges $7.3\le D[kpc]\le79$,
$0.2\le L_{[O II]}[ 10^{41}~erg s^{-1}]$ $\le 4.5$, $2.59\le SFR[M_\odot
yr^{-1} ]\le 33.51$, $0.15L_B^*\le L_B\le1.63L_B^*$ and $10.21\le
log[M_*/M_\odot]\le11.62$ respectively. The impact parameters found are larger
than that predicted by the $W_{2796}$ vs D relationship of the general
population of Mg II absorbers. At a given D, USMgII host galaxies are more
luminous and massive compared to typical Mg II absorbers. However, the measured
SFRs are slightly lower than that of main-sequence galaxies with the same
M$_\star$ at $z\sim0.5$. We report a correlation between $L_{[O II]}$ and
W$_{2796}$ for the full population of Mg II absorbers, driven mainly by the
host galaxies of weak Mg II absorbers that tend to have low $L_{[O II]}$ and
large impact parameters. We find at least $\sim$33% of the USMgII host galaxies
(with a limiting magnitude of $m_r<23.6$) are isolated and the large $W_{2796}$
in these cases may originate from gas flows (infall/outflow) in single halos of
massive but not starburst galaxies. We also find galaxy interactions could be
responsible for large velocity widths in at least $\sim$17% cases.


title:
Tracing the environmental history of observed galaxies via extended fast
  action minimization method

abstract:
  We present a novel application of the extended Fast Action Minimization
method (eFAM) aimed at assessing the role of the environment in shaping galaxy
evolution. We validate our approach by testing eFAM predictions against the
Magneticum hydrodynamical simulation. We consider the z~0 snapshot of the
simulation as our observed catalogue and use the reconstructed trajectories of
galaxies to model the evolution of cosmic structures. At the statistical level,
the fraction of volume (VFF) occupied by voids, sheets, filaments, and clusters
in the reconstructed catalogues agrees within $1\sigma$ with the VFF estimated
from the high-redshift snapshots of the simulation. The local accuracy of eFAM
structures is evaluated by computing their purity with respect to the simulated
catalogues, P, at the cells of a regular grid. Up to z=1.2, clusters have
0.58<P<0.93, filaments vary in 0.90<P<0.99, sheets show 0.78<P<0.92, and voids
are best identified with 0.90<P<0.92. As redshift increases, comparing
reconstructed tracers and simulated galaxies becomes more difficult due to
their different biases and number densities and the purity decreases to P~0.6.
We retrieve the environmental history of individual galaxies by tracing their
trajectories through the cosmic web and relate their observed gas fraction,
$f_\mathrm{gas}$, with the time spent within different structures. For galaxies
in clusters and filaments, eFAM reproduces the variation of $f_\mathrm{gas}$ as
a function of the redshift of accretion/infall as traced by the simulations
with a 1.5 $\sigma$ statistical agreement (which decreases to 2.5 $\sigma$
statistical agreement for low-mass galaxies in filaments). These results
support the application of eFAM to observational data to study the
environmental dependence of observed galaxy properties, offering a
complementary approach to that based on light-cone observations.


title:
Complete identification of complex salt-geometries from inaccurate
  migrated images using Deep Learning

abstract:
  Delimiting salt inclusions from migrated images is a time-consuming activity
that relies on highly human-curated analysis and is subject to interpretation
errors or limitations of the methods available. We propose to use migrated
images produced from an inaccurate velocity model (with a reasonable
approximation of sediment velocity, but without salt inclusions) to predict the
correct salt inclusions shape using a Convolutional Neural Network (CNN). Our
approach relies on subsurface Common Image Gathers to focus the sediments'
reflections around the zero offset and to spread the energy of salt reflections
over large offsets. Using synthetic data, we trained a U-Net to use
common-offset subsurface images as input channels for the CNN and the correct
salt-masks as network output. The network learned to predict the salt
inclusions masks with high accuracy; moreover, it also performed well when
applied to synthetic benchmark data sets that were not previously introduced.
Our training process tuned the U-Net to successfully learn the shape of complex
salt bodies from partially focused subsurface offset images.


title: yosm: A new yoruba sentiment corpus for movie reviews

abstract:
  A movie that is thoroughly enjoyed and recommended by an individual might be
hated by another. One characteristic of humans is the ability to have feelings
which could be positive or negative. To automatically classify and study human
feelings, an aspect of natural language processing, sentiment analysis and
opinion mining were designed to understand human feelings regarding several
issues which could affect a product, a social media platforms, government, or
societal discussions or even movies. Several works on sentiment analysis have
been done on high resource languages while low resources languages like Yoruba
have been sidelined. Due to the scarcity of datasets and linguistic
architectures that will suit low resource languages, African languages "low
resource languages" have been ignored and not fully explored. For this reason,
our attention is placed on Yoruba to explore sentiment analysis on reviews of
Nigerian movies. The data comprised 1500 movie reviews that were sourced from
IMDB, Rotten Tomatoes, Letterboxd, Cinemapointer and Nollyrated. We develop
sentiment classification models using the state-of-the-art pre-trained language
models like mBERT and AfriBERTa to classify the movie reviews.


title:
The low redshift Lyman-$\alpha$ Forest as a constraint for models of AGN
  feedback

abstract:
  We study the low redshift Lyman-$\alpha$ Forest in the Illustris and
IllustrisTNG (TNG) cosmological simulations to demonstrate their utility in
constraining aspects of sub-grid models of feedback from active galactic nuclei
(AGN). The two simulations share an identical Ultraviolet Background
prescription and similar cosmological parameters, but TNG features an entirely
reworked AGN feedback model. Therefore a comparison of these simulations is
useful to assess the effects of an altered AGN sub-grid model on the low
redshift Lyman-$\alpha$ Forest. We find significant differences in the IGM
temperature-density relation between the two simulations due to changes in the
gas heating rate due to AGN. We investigate Lyman-$\alpha$ Forest observables
such as the column density distribution function, flux PDF, and Doppler width
($b$-parameter) distribution. Due to the AGN radio mode model, the original
Illustris simulations have a factor of 2-3 fewer absorbers than TNG at column
densities $N_{\rm HI}< 10^{15.5}$ cm$^{-2}$. We show that TNG is in much better
agreement with the observed $z=0.1$ flux power spectrum than Illustris. The
differences in the amplitude and shape of the flux PDF and power spectrum
between Illustris and TNG cannot be attributed to simple changes in the
photoheating rate. We also compare the simulated Forest statistics to UV data
from the Cosmic Origins Spectrograph (COS) and find that neither simulation can
reproduce the slope of the absorber distribution. Both Illustris and TNG also
produce significantly smaller $b$-parameter distributions than observed in the
COS data, possibly due to unresolved or missing sources of turbulence.


title: Thawing k-essence dark energy in the PAge space

abstract:
  A broad class of dark energy models can be written in the form of k-essence,
whose Lagrangian density is a two-variable function of a scalar field $\phi$
and its kinetic energy $X\equiv \frac{1}{2}\partial^\mu\phi \partial_\mu\phi$.
In the thawing scenario, the scalar field becomes dynamic only when the Hubble
friction drops below its mass scale in the late universe. Thawing k-essence
dark energy models can be randomly sampled by generating the Taylor expansion
coefficients of its Lagrangian density from random matrices \cite{thaws}. Ref.
\cite{thaws} points out that the non-uniform distribution of effective equation
of state parameters $(w_0, w_a)$ of thawing k-essence model can be used to
improve the statistics of model selection. The present work studies the
statistics of thawing k-essence in a more general framework that is
Parameterized by the Age of the universe (PAge) \cite{PAge}. For fixed matter
fraction $\Omega_m$, the random thawing k-essence models cluster in a narrow
band in the PAge parameter space, providing a strong theoretical prior. We
simulate cosmic shear power spectrum data for the Chinese Space Station
Telescope optical survey, and compare the fisher forecast with and without the
theoretical prior of thawing k-essence. For an optimal tomography binning
scheme, the theoretical prior improves the figure of merit in PAge space by a
factor of $3.3$.


title: Generative Pre-Trained Transformers for Biologically Inspired Design

abstract:
  Biological systems in nature have evolved for millions of years to adapt and
survive the environment. Many features they developed can be inspirational and
beneficial for solving technical problems in modern industries. This leads to a
novel form of design-by-analogy called bio-inspired design (BID). Although BID
as a design method has been proven beneficial, the gap between biology and
engineering continuously hinders designers from effectively applying the
method. Therefore, we explore the recent advance of artificial intelligence
(AI) for a computational approach to bridge the gap. This paper proposes a
generative design approach based on the pre-trained language model (PLM) to
automatically retrieve and map biological analogy and generate BID in the form
of natural language. The latest generative pre-trained transformer, namely
GPT-3, is used as the base PLM. Three types of design concept generators are
identified and fine-tuned from the PLM according to the looseness of the
problem space representation. Machine evaluators are also fine-tuned to assess
the correlation between the domains within the generated BID concepts. The
approach is then tested via a case study in which the fine-tuned models are
applied to generate and evaluate light-weighted flying car concepts inspired by
nature. The results show our approach can generate BID concepts with good
performance.


title: Scaling Language Model Size in Cross-Device Federated Learning

abstract:
  Most studies in cross-device federated learning focus on small models, due to
the server-client communication and on-device computation bottlenecks. In this
work, we leverage various techniques for mitigating these bottlenecks to train
larger language models in cross-device federated learning. With systematic
applications of partial model training, quantization, efficient transfer
learning, and communication-efficient optimizers, we are able to train a $21$M
parameter Transformer that achieves the same perplexity as that of a similarly
sized LSTM with $\sim10\times$ smaller client-to-server communication cost and
$11\%$ lower perplexity than smaller LSTMs commonly studied in literature.


title:
Domain Specific Fine-tuning of Denoising Sequence-to-Sequence Models for
  Natural Language Summarization

abstract:
  Summarization of long-form text data is a problem especially pertinent in
knowledge economy jobs such as medicine and finance, that require continuously
remaining informed on a sophisticated and evolving body of knowledge. As such,
isolating and summarizing key content automatically using Natural Language
Processing (NLP) techniques holds the potential for extensive time savings in
these industries. We explore applications of a state-of-the-art NLP model
(BART), and explore strategies for tuning it to optimal performance using data
augmentation and various fine-tuning strategies. We show that our end-to-end
fine-tuning approach can result in a 5-6\% absolute ROUGE-1 improvement over an
out-of-the-box pre-trained BART summarizer when tested on domain specific data,
and make available our end-to-end pipeline to achieve these results on finance,
medical, or other user-specified domains.


title: LSTM-RASA Based Agri Farm Assistant for Farmers

abstract:
  The application of Deep Learning and Natural Language based ChatBots are
growing rapidly in recent years. They are used in many fields like customer
support, reservation system and as personal assistant. The Enterprises are
using such ChatBots to serve their customers in a better and efficient manner.
Even after such technological advancement, the expert advice does not reach the
farmers on timely manner. The farmers are still largely dependent on their
peers knowledge in solving the problems they face in their field. These
technologies have not been effectively used to give the required information to
farmers on timely manner. This project aims to implement a closed domain
ChatBot for the field of Agriculture Farmers Assistant. Farmers can have
conversation with the Chatbot and get the expert advice in their field. Farmers
Assistant is based on RASA Open Source Framework. The Chatbot identifies the
intent and entity from user utterances and retrieve the remedy from the
database and share it with the user. We tested the Bot with existing data and
it showed promising results.


title: Matching Writers to Content Writing Tasks

abstract:
  Businesses need content. In various forms and formats and for varied
purposes. In fact, the content marketing industry is set to be worth $412.88
billion by the end of 2021. However, according to the Content Marketing
Institute, creating engaging content is the #1 challenge that marketers face
today. We under-stand that producing great content requires great writers who
understand the business and can weave their message into reader (and search
engine) friendly content. In this project, the team has attempted to bridge the
gap between writers and projects by using AI and ML tools. We used NLP
techniques to analyze thou-sands of publicly available business articles
(corpora) to extract various defining factors for each writing sample. Through
this project we aim to automate the highly time-consuming, and often biased
task of manually shortlisting the most suitable writer for a given content
writing requirement. We believe that a tool like this will have far reaching
positive implications for both parties - businesses looking for suitable talent
for niche writing jobs as well as experienced writers and Subject Matter
Experts (SMEs) wanting to lend their services to content marketing projects.
The business gets the content they need, the content writer/ SME gets a chance
to leverage his or her talent, while the reader gets authentic content that
adds real value.


title: Recent Progress in Conversational AI

abstract:
  Conversational artificial intelligence (AI) is becoming an increasingly
popular topic among industry and academia. With the fast development of neural
network-based models, a lot of neural-based conversational AI system are
developed. We will provide a brief review of the recent progress in the
Conversational AI, including the commonly adopted techniques, notable works,
famous competitions from academia and industry and widely used datasets.


title: Vehicle Models and Optimal Control on a Nonplanar Surface

abstract:
  We present a 10 DoF dynamic vehicle model for model-based control on
nonplanar road surfaces. A parametric surface is used to describe the road
surface, allowing the surface parameterization to describe the pose of the
vehicle. We use the proposed approach to compute minimum-time vehicle
trajectories on nonplanar surfaces and compare planar and nonplanar models.


title:
Pseudorapidity dependence of the $p_T$ spectra of charged hadrons in
  $pp$ collisions at $\sqrt{s}$ = 0.9 and 2.36 TeV

abstract:
  We report the predictions of different Monte Carlo event generators including
HIJING, Pythia, and QGSJETII in comparison with the experimental data measured
by the CMS Collaboration at CERN in proton-proton ($pp$) collisions at
center-of-mass energy $\sqrt{s}$ = 0.9 and 2.36 TeV. The CMS experimental
transverse momentum ($p_T$ or $p_{\perp}$) spectra of charged hadrons were
measured for pseudorapidity range 0 $\le$ $\eta$ $\le$ 2.4 with bin width of
$\eta$ = 0.2 (for $p_T$ from 0.1 to 2 GeV/$c$) and a single bin of $\eta$ for
$\lvert$$\eta$$\rvert$ $<$ 2.4 (for $p_T$ from 0.1 to 4 GeV/$c$). Pythia
reproduced the $p_T$ spectra with reasonable agreement for most of the $p_T$
range. It depicts better results in the case of the $|\eta|<$ 2.4 than HIJING
and QGSJETII which could reproduce the spectra in a limited $p_T$ range.
Furthermore, to analyze the $p_T$ spectra of charged hadrons measured by the
CMS Collaboration, we used a three component function (structured from the
Boltzmann distribution) and the $q$-dual function (from the $q$-dual
statistics) to extract parameter values relevant for the study of bulk
properties of hadronic matter at high energy. We have also applied the two
analytic functions over the model predictions. The values extracted by the
functions from the HIJING and Pythia models are closer to the experimental data
than the QGSJETII model. Although the models could reproduce the $p_T$ spectra
of all charged particles in some of the $p_T$ range but none of them could
reproduce the distributions over the entire $p_T$ range and in all the
pseudorapidity regions.


title:
When Does Syntax Mediate Neural Language Model Performance? Evidence
  from Dropout Probes

abstract:
  Recent causal probing literature reveals when language models and syntactic
probes use similar representations. Such techniques may yield "false negative"
causality results: models may use representations of syntax, but probes may
have learned to use redundant encodings of the same syntactic information. We
demonstrate that models do encode syntactic information redundantly and
introduce a new probe design that guides probes to consider all syntactic
information present in embeddings. Using these probes, we find evidence for the
use of syntax in models where prior methods did not, allowing us to boost model
performance by injecting syntactic information into representations.


title: An entropy functional bounded from above by one

abstract:
  Shannon entropy is widely used for quantifying uncertainty in discrete random
variables. But when normalized to the unit interval, as is often done in
practice, it fails to convey the alphabet size of the random variable under
study. This work introduces an entropy functional based on Jensen-Shannon
divergence that is naturally bounded from above by one. Unlike normalized
Shannon entropy, this new functional is strictly increasing in alphabet size
under uniformity and is thus well suited to the characterization of discrete
random variables.


title:
Generating arbitrary laser beam shapes through phase-mapped designed
  beam splitting

abstract:
  We describe here a method to generate high-definition arbitrary laser beam
shapes and profiles useful to many applications, ranging from optical
patterning and lithography to optical trapping of microscopic particles and
ultracold atoms. The phase contrast between a binary grating and a targeted
intensity distribution is encoded on a spatial light modulator to control light
diffraction, producing very sharp, speckles-free, and smooth images. Besides
simplicity, not requiring additional phase-plates, the method provides
straightforward encoding of images onto phase-only masks by a direct pixel
mapping, allowing simpler feedback schemes to correct and control light
distributions and optical potentials in real-time.

categories: physics.optics cond-mat.soft physics.app-ph physics.ins-det


title: Volumetric Benchmarking of Error Mitigation with Qermit

abstract:
  The detrimental effect of noise accumulates as quantum computers grow in
size. In the case where devices are too small or noisy to perform error
correction, error mitigation may be used. Error mitigation does not increase
the fidelity of quantum states, but instead aims to reduce the approximation
error in quantities of concern, such as expectation values of observables.
However, it is as yet unclear which circuit types, and devices of which
characteristics, benefit most from the use of error mitigation. Here we develop
a methodology to assess the performance of quantum error mitigation techniques.
Our benchmarks are volumetric in design, and are performed on different
superconducting hardware devices. Extensive classical simulations are also used
for comparison. We use these benchmarks to identify disconnects between the
predicted and practical performance of error mitigation protocols, and to
identify the situations in which their use is beneficial. To perform these
experiments, and for the benefit of the wider community, we introduce Qermit -
an open source python package for quantum error mitigation. Qermit supports a
wide range of error mitigation methods, is easily extensible and has a modular
graph-based software design that facilitates composition of error mitigation
protocols and subroutines.


title:
Coverage Control for a Multi-robot Team with Heterogeneous Capabilities
  using Block Coordinate Descent (BCD) Method

abstract:
  In this paper, we propose a coverage control system for a multi-robot team
with heterogeneous capabilities to patrol or monitor a bounded environment. The
capability could be defined as any criterion of robots like remaining power or
mobile speed, depending on the purpose. The proposed control system aims to
allocate different portions of the environment to the robots according to their
capabilities, i.e., the robot with higher capability takes a larger portion of
the environment while the robot with lower capability takes a smaller one. We
use the block coordinate descent (BCD) method to optimize the location of
portions and the partitioning method alternately. A centralized machine is used
to synchronize the robots and the gradient of each robot can be computed in a
distributed manner. Simulation results are provided to illustrate the
performance of the proposed control system.


title: Optical observations and dust modelling of comet 156P/Russell-LINEAR

abstract:
  Comet 156P/Russell-LINEAR is a short period Jupiter family comet with an
orbital period of 6.44 years. The results from spectroscopic, photometric,
polarimetric observations and dust modelling studies are presented here. From
the spectroscopic study, strong emissions from $CN (\Delta \nu = 0)$, $C_3
(\lambda 4050$ \AA), $C_2 (\Delta \nu = +1)$ and $C_2 (\Delta \nu = 0)$ can be
observed during both the epochs of our observations. The Q($C_2$)/Q(CN) ratio
classifies the comet as a typical comet. The imaging data reveals the presence
of jets. The dust emission from the comet is observed to have a non-steady
state outflow due to the presence of these strong jets which subside in later
epochs, resulting in a steady state outflow. Polarimetric study at two
different phase angles reveals the degree of polarization to be comparable to
Jupiter family comets at similar phase angles. Localized variations in
polarization values are observed in the coma. The dust modelling studies
suggest the presence of high amount of silicate/low absorbing material and
indicate the coma to be dominated by higher amount of large size grains with
low porosity having power law size distribution index = 2.4. The observed
activity and dust properties points to a similarity to another Jupiter family
comet, 67P/Churyumov-Gerasimenko.


title: Explaining the winds of AGB stars: Recent progress

abstract:
  The winds observed around asymptotic giant branch (AGB) stars are generally
attributed to radiation pressure on dust, which is formed in the extended
dynamical atmospheres of these pulsating, strongly convective stars. Current
radiation-hydrodynamical models can explain many of the observed features, and
they are on the brink of delivering a predictive theory of mass loss. This
review summarizes recent results and ongoing work on winds of AGB stars,
discussing critical ingredients of the driving mechanism, and first results of
global 3D RHD star-and-wind-in-a-box simulations. With such models it becomes
possible to follow the flow of matter, in full 3D geometry, all the way from
the turbulent, pulsating interior of an AGB star, through its atmosphere and
dust formation zone into the region where the wind is accelerated by radiation
pressure on dust. Advanced instruments, which can resolve the stellar
atmospheres, where the winds originate, provide essential data for testing the
models.


title: GRB Prompt Emission: Observed Correlations and Their Interpretations

abstract:
  The prompt emission of Gamma Ray Bursts (GRBs) is still an outstanding
question in the study of these cataclysmic events. Part of what makes GRBs
difficult to study is how unique each event seems to be. However, aggregating
many GRB observations and analyzing the population allows us to obtain a better
understanding of the emission mechanism that produces the observed prompt
emission. In this review, we outline some of the most prevalent correlations
that have emerged from GRB prompt emission observations and how these
correlations are interpreted in relation to GRB physical properties and prompt
emission models.


abstract:
  Cross-modal image-recipe retrieval has gained significant attention in recent
years. Most work focuses on improving cross-modal embeddings using unimodal
encoders, that allow for efficient retrieval in large-scale databases, leaving
aside cross-attention between modalities which is more computationally
expensive. We propose a new retrieval framework, T-Food (Transformer Decoders
with MultiModal Regularization for Cross-Modal Food Retrieval) that exploits
the interaction between modalities in a novel regularization scheme, while
using only unimodal encoders at test time for efficient retrieval. We also
capture the intra-dependencies between recipe entities with a dedicated recipe
encoder, and propose new variants of triplet losses with dynamic margins that
adapt to the difficulty of the task. Finally, we leverage the power of the
recent Vision and Language Pretraining (VLP) models such as CLIP for the image
encoder. Our approach outperforms existing approaches by a large margin on the
Recipe1M dataset. Specifically, we achieve absolute improvements of 8.1 % (72.6
R@1) and +10.9 % (44.6 R@1) on the 1k and 10k test sets respectively. The code
is available here:https://github.com/mshukor/TFood


title:
Magnetic field strength from turbulence theory (I): Using differential
  measure approach (DMA)

abstract:
  The mean plane-of-sky magnetic field strength is traditionally obtained from
the combination of polarization and spectroscopic data using the
Davis-Chandrasekhar-Fermi (DCF) technique. However, we identify the major
problem of the DCF to be its disregard of the anisotropic character of MHD
turbulence. On the basis of the modern MHD turbulence theory we introduce a new
way of obtaining magnetic field strength from observations. Unlike the DCF, the
new technique uses not the dispersion of the polarization angle and line of
sight velocities, but increments of these quantities given by the structure
functions. To address the variety of the astrophysical conditions for which our
technique can be applied, we consider the turbulence in both media with
magnetic pressure larger than the gas pressure corresponding e.g. to molecular
and the gas pressure larger than the magnetic pressure corresponding to the
warm neutral medium. We provide general expressions for arbitrary admixture of
Alfv\'en, slow and fast modes in these media and consider in detail the
particular cases relevant to diffuse media and molecular clouds. We
successfully test our results using synthetic observations obtained from MHD
turbulence simulations. We demonstrate that our Differential Measure Approach
(DMA), unlike the DCF, can be used to measure the distribution of magnetic
field strengths, can provide magnetic field measurements with limited data and
is much more stable in the presence of large scale variations induces of
non-turbulent nature. In parallel, our study uncover the deficiencies of the
earlier DCF research.


title: Semicontinuity of capacity under pointed intrinsic flat convergence

abstract:
  The concept of the capacity of a compact set in $\mathbb R^n$ generalizes
readily to noncompact Riemannian manifolds and, with more substantial work, to
metric spaces (where multiple natural definitions of capacity are possible).
Motivated by analytic and geometric considerations, and in particular
Jauregui's definition of capacity-volume mass and Jauregui and Lee's results on
the lower semicontinuity of the ADM mass and Huisken's isoperimetric mass, we
investigate how the capacity functional behaves when the background spaces
vary. Specifically, we allow the background spaces to consist of a sequence of
local integral current spaces converging in the pointed Sormani--Wenger
intrinsic flat sense. For the case of volume-preserving ($\mathcal{VF}$)
convergence, we prove two theorems that demonstrate an upper semicontinuity
phenomenon for the capacity: one version is for balls of a fixed radius
centered about converging points; the other is for Lipschitz sublevel sets. Our
approach is motivated by Portegies' investigation of the semicontinuity of
eigenvalues under $\mathcal{VF}$ convergence. We include examples to show the
semicontinuity may be strict, and that the volume-preserving hypothesis is
necessary. Finally, there is a discussion on how capacity and our results may
be used towards understanding the general relativistic total mass in non-smooth
settings.


title:
Spectral Analysis of Scattering Resonances with Application on High
  Contrast Nanospheres

abstract:
  In this paper we provide further spectral analysis of the general asymptotic
scattering resonances formula of small high contrast 3D dielectrics of
arbitrary shape, initially derived to a first order approximation. To
investigate the components of a full expansion of such resonances, a breakdown
is presented for the case of high contrast nanospheres. We also derive, for
radially symmetric fields, an exact resonance formula for a spherical scatterer
in terms of its radius, not necessarily small, and dielectric susceptibility
coefficient, not necessarily high. Formula that is useful in imaging
applications to identify objects' properties from frequency measurements. The
latter formula is further developed and simplified in the case of high contrast
nanospheres.


title:
An updated view and perspectives on high-energy gamma-ray emission from
  SGR J1935+2154 and its environment

abstract:
  SGR J1935+2154 was discovered in 2016 and is currently one of the most
burst-active Soft Gamma-ray Repeaters (SGR), having emitted several X-ray
bursts in recent years. In one of our previous articles, we investigated the
contribution to high-energy and very high-energy gamma-ray emission (VHE, $E >
100$ GeV) due to cosmic-ray acceleration of SNR G57.2+0.8 hosting SGR
J1935+2154 using the GALPROP propagation code. However, follow-up observations
of SGR 1935+2154 were made for 2 hours on April 28, 2020, using the High Energy
Stereoscopic System (H.E.S.S.). The observations coincide with X-ray bursts
detected by INTEGRAL and Fermi/Gamma-ray Burst Monitor (GBM). These are the
first high-energy gamma-ray observations of an SGR in a flaring state, and
upper limits on sustained and transient emission have been derived. Now that
new H.E.S.S. observations have been made, it is interesting to update our model
with respect to these new upper limits. We extend our previous results to a
more general situation using the new version of GALPROP. We obtain a hadronic
model that confirms the results discussed by H.E.S.S.. This leads to an
optimistic prospect that cosmic ray gamma rays from SGR J1935+2154 can
contribute to the overall gamma energy density distribution and in particular
to the diffusion gamma rays from the Galactic center.


title:
Persistence criteria for a chemostat with variable nutrient input and
  variable washout with delayed response in growth

abstract:
  We study a general chemostat model with a discrete-time delay between
consumption and growth. The goal of this article is to provide sufficient and
necessary conditions for persistence. This extends previous works in the
matter. Furthermore, in the particular case of periodic nutrient input and the
same periodic washout with delayed response in growth, the persistence criteria
are average criteria. We remark in no case we need to impose any restrictions
on the size of the delay.


title: On the Interpretation of Quantum Indistinguishability : a No-Go Theorem

abstract:
  Despite being the most fundamental object in quantum theory, physicists are
yet to reach a consensus on the interpretation of a quantum wavefunction. In
the broad class of realist approaches, quantum states are viewed as
Liouville-like probability distributions over some space of physical variables
where indistinguishabity of non-orthogonal states is attributed to overlaps
between these distributions. Here we argue that such an interpretation of
quantum indistinguishability is wrong. In particular, we show that quantum
mechanical prediction of maximal violation of Mermin inequality in certain
thought experiment is incompatible with all ontological interpretations for
quantum theory where indistinguishability of non-orthonal quantum states is
explained, even partially, in terms of overlap of their Liouville
distributions.


title:
ARLIF-IDS -- Attention augmented Real-Time Isolation Forest Intrusion
  Detection System

abstract:
  Distributed Denial of Service (DDoS) attack is a malicious attempt to disrupt
the normal traffic of a targeted server, service or network by overwhelming the
target or its surrounding infrastructure with a flood of Internet traffic.
Emerging technologies such as the Internet of Things and Software Defined
Networking leverage lightweight strategies for the early detection of DDoS
attacks. Previous literature demonstrates the utility of lower number of
significant features for intrusion detection. Thus, it is essential to have a
fast and effective security identification model based on low number of
features.
  In this work, a novel Attention-based Isolation Forest Intrusion Detection
System is proposed. The model considerably reduces training time and memory
consumption of the generated model. For performance assessment, the model is
assessed over two benchmark datasets, the NSL-KDD dataset & the KDDCUP'99
dataset. Experimental results demonstrate that the proposed attention augmented
model achieves a significant reduction in execution time, by 91.78%, and an
average detection F1-Score of 0.93 on the NSL-KDD and KDDCUP'99 dataset. The
results of performance evaluation show that the proposed methodology has low
complexity and requires less processing time and computational resources,
outperforming other current IDS based on machine learning algorithms.


title:
Res-CNN-BiLSTM Network for overcoming Mental Health Disturbances caused
  due to Cyberbullying through Social Media

abstract:
  Mental Health Disturbance has many reasons and cyberbullying is one of the
major causes that does exploitation using social media as an instrument. The
cyberbullying is done on the basis of Religion, Ethnicity, Age and Gender which
is a sensitive psychological issue. This can be addressed using Natural
Language Processing with Deep Learning, since social media is the medium and it
generates massive form of data in textual form. Such data can be leveraged to
find the semantics and derive what type of cyberbullying is done and who are
the people involved for early measures. Since deriving semantics is essential
we proposed a Hybrid Deep Learning Model named 1-Dimensional
CNN-Bidirectional-LSTMs with Residuals shortly known as Res-CNN-BiLSTM. In this
paper we have proposed the architecture and compared its performance with
different approaches of Embedding Deep Learning Algorithms.


title:
Discovery of 34 low-mass comoving systems using NOIRLab Source Catalog
  DR2

abstract:
  We present the discovery of 34 comoving systems containing an ultra-cool
dwarf found by means of the NOIRLab Source Catalog (NSC) DR2. NSC's angular
resolution of $\sim$1" allows for the detection of small separation binaries
with significant proper motions. We used the catalog's accurate proper motion
measurements to identify the companions by cross-matching a previously compiled
list of brown dwarf candidates with NSC DR2. The comoving pairs consist of
either a very low-mass star and an ultra-cool companion, or a white dwarf and
an ultra-cool companion. The estimated spectral types of the primaries are in
the K and M dwarf regimes, those of the secondaries in the M, L and T dwarf
regimes. We calculated angular separations between $\sim$2 and $\sim$56",
parallactic distances between $\sim$43 and $\sim$261 pc and projected physical
separations between $\sim$169 and $\sim$8487 AU. The lowest measured total
proper motion is 97 mas yr$^{-1}$, the highest 314 mas yr$^{-1}$. Tangential
velocities range from $\sim$23 to $\sim$187 km s$^{-1}$. We also determined
comoving probabilities, estimated mass ratios and calculated binding energies
for each system. We found no indication of possible binarity for any component
of the 34 systems in the published literature. The discovered systems can
contribute to the further study of the formation and evolution of low-mass
systems as well as to the characterization of cool substellar objects.


title: Joint state and parameter estimation based on constrained zonotopes

abstract:
  This note presents a new method for set-based joint state and parameter
estimation of discrete-time systems using constrained zonotopes. This is done
by extending previous set-based state estimation methods to include parameter
identification in a unified framework. Unlike in interval-based methods, the
existing dependencies between states and model parameters are maintained from
one time step to the next, thus providing a more accurate estimation scheme. In
addition, the enclosure of states and parameters is refined using measurements
through generalized intersections, which are properly captured by constrained
zonotopes. The advantages of the new approach are highlighted in two numerical
examples.


title:
A majorization-minimization algorithm for nonnegative binary matrix
  factorization

abstract:
  This paper tackles the problem of decomposing binary data using matrix
factorization. We consider the family of mean-parametrized Bernoulli models, a
class of generative models that are well suited for modeling binary data and
enables interpretability of the factors. We factorize the Bernoulli parameter
and consider an additional Beta prior on one of the factors to further improve
the model's expressive power. While similar models have been proposed in the
literature, they only exploit the Beta prior as a proxy to ensure a valid
Bernoulli parameter in a Bayesian setting; in practice it reduces to a uniform
or uninformative prior. Besides, estimation in these models has focused on
costly Bayesian inference. In this paper, we propose a simple yet very
efficient majorization-minimization algorithm for maximum a posteriori
estimation. Our approach leverages the Beta prior whose parameters can be tuned
to improve performance in matrix completion tasks. Experiments conducted on
three public binary datasets show that our approach offers an excellent
trade-off between prediction performance, computational complexity, and
interpretability.


title: Time-like Gravitational Formfactors and Shear Viscosity

abstract:
  The gravitational formfactor similar to shear viscosity is identified. In the
time-like region it corresponds to the contribution of exotic hybrid meson. The
exotic quantum numbers may be considered as a counterpart of dissipation in
crossed channel. The ratio of viscosity to entropy density is estimated. The
smallness due to holographic bound corresponds to the relative smallness of
coupling of hybrid meson and the intrinsic transverse momentum, being the
dynamical counterpart of temperature.


title:
Carleman inequality for a class of super strong degenerate parabolic
  operators and applications

abstract:
  In this paper, we present a new Carleman estimate for the adjoint equations
associated to a class of super strong degenerate parabolic linear problems. Our
approach considers a standard geometric imposition on the control domain, which
can not be removed in the general situations. Additionally, we also apply the
aformentioned main inequality in order to investigate the null controllability
of two nonlinear parabolic systems. The first application is concerned a global
null controllability result obtained for some semilinear equations, relying on
a fixed point argument. In the second one, a local null controllability for
some equations with nonlocal terms is also achieved, by using an inverse
function theorem.


title: A Framework for Topological Music Analysis (TMA)

abstract:
  In the present article we describe and discuss a framework for applying
different topological data analysis (TDA) techniques to a music fragment given
as a score in traditional Western notation. We first consider different sets of
points in Euclidean spaces of different dimensions that correspond to musical
events in the score, and obtain their persistent homology features. Then we
introduce two families of simplicial complexes that can be associated to chord
sequences, and calculate their main homological descriptors. These complexes
lead us to the definition of dynamical systems modeling harmonic progressions.
Finally, we show the results of applying the described methods to the analysis
and stylistic comparison of fragments from three Brandenburg Concertos by J.S.
Bach and two Graffiti by Mexican composer Armando Luna.


title:
ColorCode: A Bayesian Approach to Augmentative and Alternative
  Communication with Two Buttons

abstract:
  Many people with severely limited muscle control can only communicate through
augmentative and alternative communication (AAC) systems with a small number of
buttons. In this paper, we present the design for ColorCode, which is an AAC
system with two buttons that uses Bayesian inference to determine what the user
wishes to communicate. Our information-theoretic analysis of ColorCode
simulations shows that it is efficient in extracting information from the user,
even in the presence of errors, achieving nearly optimal error correction.
ColorCode is provided as open source software
(https://github.com/mrdaly/ColorCode).


title:
Federated Learning for Energy-limited Wireless Networks: A Partial Model
  Aggregation Approach

abstract:
  The limited communication resources, e.g., bandwidth and energy, and data
heterogeneity across devices are two of the main bottlenecks for federated
learning (FL). To tackle these challenges, we first devise a novel FL framework
with partial model aggregation (PMA), which only aggregates the lower layers of
neural networks responsible for feature extraction while the upper layers
corresponding to complex pattern recognition remain at devices for
personalization. The proposed PMA-FL is able to address the data heterogeneity
and reduce the transmitted information in wireless channels. We then obtain a
convergence bound of the framework under a non-convex loss function setting.
With the aid of this bound, we define a new objective function, named the
scheduled data sample volume, to transfer the original inexplicit optimization
problem into a tractable one for device scheduling, bandwidth allocation,
computation and communication time division. Our analysis reveals that the
optimal time division is achieved when the communication and computation parts
of PMA-FL have the same power. We also develop a bisection method to solve the
optimal bandwidth allocation policy and use the set expansion algorithm to
address the optimal device scheduling. Compared with the state-of-the-art
benchmarks, the proposed PMA-FL improves 2.72% and 11.6% accuracy on two
typical heterogeneous datasets, i.e., MINIST and CIFAR-10, respectively. In
addition, the proposed joint dynamic device scheduling and resource
optimization approach achieve slightly higher accuracy than the considered
benchmarks, but they provide a satisfactory energy and time reduction: 29%
energy or 20% time reduction on the MNIST; and 25% energy or 12.5% time
reduction on the CIFAR-10.


title: Conceptual structure and the growth of scientific knowledge

abstract:
  How does scientific knowledge grow? For generations, this question has
occupied a central place in the philosophy of science, stimulating heated
debates, and yielding no clear consensus. Many proposed explanations can be
understood in terms of whether and how they view the expansion of knowledge as
proceeding through the organization of scientific concepts into core/periphery
structures, wherein the core encompasses foundational knowledge and the
periphery consists of emergent ideas. Here, we examine these views empirically,
performing a large-scale analysis of the physical and social sciences, spanning
five decades. Using techniques from natural language processing, we create
semantic networks of concepts, wherein single- and multi-word noun phrases
become linked when they are used in the same paper abstract. For both the
physical and social sciences, we observe increasingly rigid cores accompanied
by the proliferation of periphery concepts. In the physical sciences, these
changes coincide with an increasing number of cores, while in the social
sciences, the number of cores is decreasing. In subsequent analyses, we examine
the relationship between core/periphery organization and the growth of
scientific knowledge, finding that scientific works are less innovative in
fields with smaller cores, cores with less conceptual churn, and an overall
larger number of cores, the latter of which is also associated with less
scientific consensus. Overall, our findings suggest that while the organization
of scientific concepts is important for the growth of knowledge, the mechanisms
vary across fields and time.


title:
Inferring ice sheet damage models from limited observations using
  CRIKit: the Constitutive Relation Inference Toolkit

abstract:
  We examine the prospect of learning ice sheet damage models from
observational data. Our approach, implemented in CRIKit (the Constitutive
Relation Inference Toolkit), is to model the material time derivative of damage
as a frame-invariant neural network, and to optimize the parameters of the
model from simulations of the flow of an ice dome. Using the model of Albrecht
and Levermann as the ground truth to generate synthetic observations, we
measure the difference of optimized neural network models from that model to
try to understand how well this process generates models that can then transfer
to other ice sheet simulations.
  The use of so-called "deep-learning" models for constitutive equations,
equations of state, sub-grid-scale processes, and other pointwise relations
that appear in systems of PDEs has been successful in other disciplines, yet
our inference setting has some confounding factors. The first is the type of
observations that are available: we compare the quality of the inferred models
when the loss of the numerical simulations includes observation misfits
throughout the ice, which is unobtainable in real settings, to losses that
include only combinations of surface and borehole observations. The second
confounding factor is the evolution of damage in an ice sheet, which is
advection dominated. The non-local effect of perturbations in a damage models
results in loss functions that have both many local minima and many parameter
configurations for which the system is unsolvable.
  Our experience suggests that basic neural networks have several deficiencies
that affect the quality of the optimized models. We suggest several approaches
to incorporating additional inductive biases into neural networks which may
lead to better performance in future work.


title: Gravitational orbits, double-twist mirage, and many-body scars

abstract:
  We explore the implications of stable gravitational orbits around an AdS
black hole for the boundary conformal field theory. The orbits are long-lived
states that eventually decay due to gravitational radiation and tunneling. They
appear as narrow resonances in the heavy-light OPE when the spectrum becomes
effectively continuous due to the presence of the black hole horizon.
Alternatively, they can be identified with quasi-normal modes with small
imaginary part in the thermal two-point function. The two pictures are related
via the eigenstate thermalisation hypothesis. When the decay effects can be
neglected the orbits appear as a discrete family of double-twist operators. We
investigate the connection between orbits, quasi-normal modes, and double-twist
operators in detail. Using the corrected Bohr-Sommerfeld formula for
quasi-normal modes, we compute the anomalous dimension of double-twist
operators. We compare our results to the prediction of the light-cone
bootstrap, finding perfect agreement where the results overlap. We also compute
the orbit decay time due to scalar radiation and compare it to the tunneling
rate. Perturbatively in spin, in the light-cone bootstrap framework
double-twist operators appear as a small fraction of the Hilbert space which
violate the eigenstate thermalization hypothesis, a phenomenon known as
many-body scars. Nonperturbatively in spin, the double-twist operators become
long-lived states that eventually thermalize. We briefly discuss the connection
between perturbative scars in holographic theories and known examples of scars
in the condensed matter literature.

categories: hep-th cond-mat.quant-gas cond-mat.stat-mech gr-qc quant-ph


title:
Multiplicity Statistics of Stars in the Sagittarius Dwarf Spheroidal
  Galaxy: Comparison to the Milky Way

abstract:
  We use time-resolved spectra from the Apache Point Observatory Galactic
Evolution Experiment (APOGEE) to examine the distribution of radial velocity
(RV) variations in 249 stars identified as members of the Sagittarius (Sgr)
dwarf spheroidal (dSph) galaxy by Hayes et al (2020). We select Milky Way (MW)
stars that have stellar parameters ($log(g)$, $T_{eff}$, and $[Fe/H]$) similar
to those of the Sagittarius members by means of a k-d tree of dimension 3. We
find that the shape of the distribution of RV shifts in Sgr dSph stars is
similar to that measured in their MW analogs, but the total fraction of RV
variable stars in the Sgr dSph is larger by a factor of $\sim 2$. After ruling
out other explanations for this difference, we conclude that the fraction of
close binaries in the Sgr dSph is intrinsically higher than in the MW. We
discuss the implications of this result for the physical processes leading to
the formation of close binaries in dwarf spheroidal and spiral galaxies.


title:
An Adaptive and Robust Method for Multi-trait Analysis of Genome-wide
  Association Studies Using Summary Statistics

abstract:
  Genome-wide association studies (GWAS) have identified thousands of genetic
variants associated with human traits or diseases in the past decade.
Nevertheless, much of the heritability of many traits is still unaccounted for.
Commonly used single-trait analysis methods are conservative, while multi-trait
methods improve statistical power by integrating association evidence across
multiple traits. In contrast to individual-level data, GWAS summary statistics
are usually publicly available, and thus methods using only summary statistics
have greater usage. Although many methods have been developed for joint
analysis of multiple traits using summary statistics, there are many issues,
including inconsistent performance, computational inefficiency, and numerical
problems when considering lots of traits. To address these challenges, we
propose a multi-trait adaptive Fisher method for summary statistics (MTAFS), a
computationally efficient method with robust power performance. We applied
MTAFS to two sets of brain image-derived phenotypes (IDPs) from the UK Biobank,
including a set of 58 Volumetric IDPs and a set of 212 Area IDPs. Together with
results from a simulation study, MTAFS shows its advantage over existing
multi-trait methods, with robust performance across a range of underlying
settings. It controls type 1 error well, and can efficiently handle a large
number of traits.


title:
Development of a water-based cooling system for the Muon Chamber
  detector system of the CBM experiment

abstract:
  A water-based cooling system is being investigated to meet the cooling
requirement of the Gas Electron Multiplier (GEM) based Muon Chamber (MuCh)
detector system of the Compressed Baryonic Matter (CBM) experiment at GSI,
Germany. The system is based on circulating cold water through the channels
inside an aluminium plate. The aluminium plate is attached to a GEM chamber. A
feasibility study is conducted on one small and two real-size prototype cooling
plates. A microcontroller based unit has been built and integrated into the
system to achieve automatic control and monitoring of temperature on plate
surface. The real-size prototypes have been used in a test beam experiment at
the CERN SPS (Super Proton Synchrotron) with the lead beam on a lead target. A
setup using three prototype modules has been prepared in the lab for testing in
a simulated real life environment. This paper discusses the working principle,
mechanical design, fabrication, and test results of the cooling prototypes in
detail.


title: Path Planning Algorithms for Robotic Aquaculture Monitoring

abstract:
  Aerial drones have great potential to monitor large areas quickly and
efficiently. Aquaculture is an industry that requires continuous water quality
data to successfully grow and harvest fish. The Hybrid Aerial Underwater
Robotic System (HAUCS) is designed to collect water quality data of aquaculture
ponds to reduce labor costs for farmers. The routing of drones to cover each
fish pond on an aquaculture farm can be reduced to the Vehicle Routing Problem.
A dataset is created to simulate the distribution of ponds on a farm and is
used to assess the HAUCS Path Planning Algorithm (HPP). Its performance is
compared with the Google Linear Optimization Package (GLOP) and a Graph
Attention Model (AM) for routing problems. GLOP is the most efficient solver
for 50 to 200 ponds at the expense of long run times, while HPP outperforms the
other methods in solution quality and run time for instances larger than 200
ponds.


title:
Closed form optimized transmission conditions for complex diffusion with
  many subdomains

abstract:
  Optimized transmission conditions in domain decomposition methods have been
the focus of intensive research efforts over the past decade. Traditionally,
transmission conditions are optimized for two subdomain model configurations,
and then used in practice for many subdomains. We optimize here transmission
conditions for the first time directly for many subdomains for a class of
complex diffusion problems. Our asymptotic analysis leads to closed form
optimized transmission conditions for many subdomains, and shows that the
asymptotic best choice in the mesh size only differs from the two subdomain
best choice in the constants, for which we derive the dependence on the number
of subdomains explicitly, including the limiting case of an infinite number of
subdomains, leading to new insight into scalability. Our results include both
Robin and Ventcell transmission conditions, and we also optimize for the first
time a two-sided Ventcell condition. We illustrate our results with numerical
experiments, both for situations covered by our analysis and situations that go
beyond.


title: Decoherence: From Interpretation to Experiment

abstract:
  I offer a few selected reflections on the decoherence program, with an
emphasis on Zeh's role and views. First, I discuss Zeh's commitment to a
realistic interpretation of the quantum state, which he saw as necessary for a
consistent understanding of the decoherence process. I suggest that this
commitment has been more fundamental than, and prior to, his support of an
Everett-style interpretation of quantum mechanics. Seen through this lens, both
his defense of Everett and the genesis of his ideas on decoherence emerge as
consequences of his realistic view of the quantum state. Second, I give an
overview of experiments on decoherence and describe, using the study of
collisional decoherence as an example, the close interplay between experimental
advances and theoretical modeling in decoherence research.


title:
A Generalized Distributed Analysis and Control Synthesis Approach for
  Networked Systems with Arbitrary Interconnections

abstract:
  We consider the problem of distributed analysis and control synthesis to
verify and ensure properties like stability and dissipativity of a large-scale
networked system comprised of linear subsystems interconnected in an arbitrary
topology. In particular, we design systematic networked system analysis and
control synthesis processes that can be executed in a distributed manner at the
subsystem level with minimal information sharing among the subsystems. Compared
to a recent work on the same topic, we consider a substantially more
generalized problem setup and develop distributed processes to verify and
ensure a broader range of networked system properties. We also show that
optimizing subsystems' indexing scheme used in such distributed processes can
substantially reduce the required information-sharing sessions between
subsystems. Moreover, the proposed networked system analysis and control
synthesis processes are compositional and thus allow them to conveniently and
efficiently handle situations where new subsystems are being added to an
existing network. We also provide significant insights into our approach so
that it can be quickly adopted to verify and ensure properties beyond the
stability and dissipativity of networked systems. Finally, we provide several
simulation results to demonstrate the proposed distributed analysis and control
synthesis processes.


title: Class group statistics for torsion fields generated by elliptic curves

abstract:
  For a prime $p$ and a rational elliptic curve $E_{/\mathbb{Q}}$, set
$K=\mathbb{Q}(E[p])$ to denote the torsion field generated by
$E[p]:=\operatorname{ker}\{E\xrightarrow{p} E\}$. The class group
$\operatorname{Cl}_K$ is a module over $\operatorname{Gal}(K/\mathbb{Q})$.
Given a fixed odd prime number $p$, we study the average non-vanishing of
certain Galois stable quotients of the mod-$p$ class group
$\operatorname{Cl}_K/p\operatorname{Cl}_K$. Here, $E$ varies over rational
elliptic curves, ordered according to \emph{height}. Our results are
conditional and rely on predictions made by Delaunay and Poonen-Rains for the
statistical variation of the $p$-primary parts of Tate-Shafarevich groups of
elliptic curves. We also prove results in the case when the elliptic curve
$E_{/\mathbb{Q}}$ is fixed and the prime $p$ is allowed to vary.


title:
Lowering Barriers to Application Development With Cloud-Native
  Domain-Specific Functions

abstract:
  Creating and maintaining a modern, heterogeneous set of client applications
remains an obstacle for many businesses and individuals. While simple
domain-specific graphical languages and libraries can empower a variety of
users to create application behaviors and logic, using these languages to
produce and maintain a set of heterogeneous client applications is a challenge.
Primarily because each client typically requires the developers to both
understand and embed the domain-specific logic. This is because application
logic must be encoded to some extent in both the server and client sides.
  In this paper, we propose an alternative approach, which allows the
specification of application logic to reside solely on the cloud. We have built
a system where reusable application components can be assembled on the cloud in
different logical chains and the client is largely decoupled from this logic
and is solely concerned with how data is displayed and gathered from users of
the application. In this way, the chaining of requests and responses is done by
the cloud and the client side has no knowledge of the application logic.
  An additional effect of our approach is that the client side developer is
able to immediately see any changes they make, while executing the logic
residing on the cloud. This further allows more novice programmers to perform
these customizations, as they do not need to `get the full application working'
and are able to see the results of their code as they go, thereby lowering the
obstacles to businesses and individuals to produce and maintain applications.
Furthermore, this decoupling enables the quick generation and customization of
a variety of application clients, ranging from web to mobile devices and
personal assistants, while customizing one or more as needed.


title:
The eta Aquilae System: Radial Velocities and Astrometry in Search of
  eta Aql B

abstract:
  The classical Cepheid eta Aql was not included in past Leavitt Law work
(Benedict et al. 2007) because of a presumed complicating orbit due to a known
B9.8V companion. To determine the orbit of eta Aql B, we analyze a significant
number of radial velocity measures (RV) from eight sources. With these we
establish the RV variation due to Cepheid pulsation, using a twelve Fourier
coefficient model, while solving for velocity offsets required to bring the RV
data sets into coincidence. RV residuals provide no evidence of orbital motion,
suggesting either nearly face-on orientation or very long period. Reanalysis of
Hubble Space Telescope Fine Guidance Sensor astrometry now includes reference
star parallax and proper motion priors from Gaia EDR3. As modeling
confirmation, we reanalyze zeta Gem in parallel, deriving zeta Gem parallax and
proper motion values consistent with Gaia EDR3, and consistent with the
Benedict 2007 Leavitt Law. In an effort to further characterize eta Aql B, we
hypothesize that eta Aql residuals larger than those of the associated
reference stars or a parallax inconsistent with EDR3 and the Benedict 2007
Leavitt Law indicate unmodeled orbital motion. Using the astrometric noise or
parallax mismatch with EDR3 we estimate possible periods and mass for eta Aql
B. Ascribing photocenter motion to the photometric variation of the Cepheid,
eta Aql A, yields a plausible separation, consistent with a long period,
explaining the lack of RV variation. None of these approaches yields an
unassailable characterization of the eta Aql A-B system


title:
Long-range propagation of indirect excitons in van der Waals
  heterostructure: $1/e$ decay distance reaches $\sim 100$ microns

abstract:
  A long-range propagation of indirect excitons (IXs), also known as interlayer
excitons, is observed in a van der Waals MoSe$_2$/WSe$_2$ heterostructure. The
$1/e$ decay distance of IX luminescence reaches $\sim 100$ $\mu$m. The
long-range IX propagation is realized using an optical excitation with the
energy close to the MoSe$_2$ or WSe$_2$ direct exciton energy. The range of
excitation powers and temperatures for the long-range IX propagation is
determined.


title:
Performance of the X-Calibur Hard X-Ray Polarimetry Mission during its
  2018/19 Long-Duration Balloon Flight

abstract:
  X-Calibur is a balloon-borne telescope that measures the polarization of
high-energy X-rays in the 15--50keV energy range. The instrument makes use of
the fact that X-rays scatter preferentially perpendicular to the polarization
direction. A beryllium scattering element surrounded by pixellated CZT
detectors is located at the focal point of the InFOC{\mu}S hard X-ray mirror.
The instrument was launched for a long-duration balloon (LDB) flight from
McMurdo (Antarctica) on December 29, 2018, and obtained the first constraints
of the hard X-ray polarization of an accretion-powered pulsar. Here, we
describe the characterization and calibration of the instrument on the ground
and its performance during the flight, as well as simulations of particle
backgrounds and a comparison to measured rates. The pointing system and
polarimeter achieved the excellent projected performance. The energy detection
threshold for the anticoincidence system was found to be higher than expected
and it exhibited unanticipated dead time. Both issues will be remedied for
future flights. Overall, the mission performance was nominal, and results will
inform the design of the follow-up mission XL-Calibur, which is scheduled to be
launched in summer 2022.


title:
Effect of various particlization models on anisotropic flow and particle
  production using UrQMD hybrid model

abstract:
  We discuss the effect of various particlization models available in the
hybrid Ultra-relativistic Quantum Molecular Dynamics (UrQMD) event generator on
different observables in non-central ($b$ $=$ 5--9 $fm$) Au + Au collisions in
the beam energy range 1A-158A GeV. Particlization models are used to switch
fluid dynamic description to the transport description using various
hypersurface criteria. In addition to particlization models, various
equations-of-state (EoS) provided by UrQMD hybrid model were employed. The
observables examined in this paper include excitation function of anisotropic
coefficients such as directed ($v_{1}$) and elliptic flow ($v_{2}$), particle
ratios of the species and shape of net-proton rapidity spectra at mid-rapidity.
The results obtained here can be useful to predict as well as compare the
measurements provided by the future experiments at FAIR and NICA once the data
become available. We also make some comments on the best combination of
particlization model and EoS which describe the experimental measurements best.


title:
Crystal structure prediction of (quasi-)two-dimensional lead halide
  perovskites

abstract:
  Two-dimensional lead halide perovskites are promising materials for
optoelectronics due to the tunability of their properties with the number of
lead halide layers and the choice of an organic spacer. Physical understanding
for the rational design of materials primarily requires knowledge of crystal
structure. 2D lead halide perovskites are usually prepared in the form of films
complicating the experimental determination of structure. To enable theoretical
studies of experimentally unresolvable structures as well as high-throughput
virtual screening, we present an algorithm for crystal structure prediction of
lead halide perovskites. Using automatically prepared classical potential we
show that our algorithm enables fast access to a structure that can be used for
further first-principles studies.


title:
Delamination prediction in composite panels using unsupervised-feature
  learning methods with wavelet-enhanced guided wave representations

abstract:
  With the introduction of damage tolerance-based design philosophies, the
demand for reliable and robust structural health monitoring (SHM) procedures
for aerospace composite structures is increasing rapidly. The performance of
supervised learning algorithms for SHM depends on the amount of labeled and
balanced datasets. Apart from this, collecting datasets accommodating all
possible damage scenarios is cumbersome, costly, and inaccessible for aerospace
applications. In this paper, we have proposed two different
unsupervised-feature learning approaches where the algorithms are trained only
on the baseline scenarios to learn the distribution of baseline signals. The
trained unsupervised feature learner is used for delamination prediction with
an anomaly detection philosophy. In the first approach, we have combined
dimensionality reduction techniques (principal component analysis and
independent component analysis) with a one-class support vector machine. In
another approach, we have utilized deep learning-based deep convolutional
autoencoders (CAE). These state-of-the-art algorithms are applied on three
different guided wave-based experimental datasets. The raw guided wave signals
present in the datasets are converted into wavelet-enhanced higher-order
representations for training unsupervised feature-learning algorithms. We have
also compared different techniques, and it is seen that CAE generates better
reconstructions with lower mean squared error and can provide higher accuracy
on all the datasets.


title: 2-roots for simply laced Weyl groups

abstract:
  We introduce and study "2-roots", which are symmetrized tensor products of
orthogonal roots of Kac--Moody algebras. We concentrate on the case where $W$
is the Weyl group of a simply laced Y-shaped Dynkin diagram $Y_{a,b,c}$ having
$n$ vertices and with three branches of arbitrary finite lengths $a$, $b$ and
$c$; special cases of this include types $D_n$, $E_n$ (for arbitrary $n \geq
6$), and affine $E_6$, $E_7$ and $E_8$. We show that a natural codimension-$1$
submodule $M$ of the symmetric square of the reflection representation of $W$
has a remarkable canonical basis $\mathcal{B}$ that consists of 2-roots. We
conjecture that, with respect to $\mathcal{B}$, every element of $W$ is
represented by a column sign-coherent matrix in the sense of cluster algebras,
and we prove the conjecture in the finite and affine cases. If $W$ is a finite
simply laced Weyl group, each $W$-orbit of 2-roots has a highest element,
analogous to the highest root, and we calculate these elements explicitly. We
prove that if $W$ is not of affine type, the module $M$ is completely reducible
in characteristic zero and each of its nontrivial direct summands is spanned by
a $W$-orbit of 2-roots.


title:
Reflection in second-order set theory with abundant urelements
  bi-interprets a supercompact cardinal

abstract:
  After reviewing various natural bi-interpretations in urelement set theory,
including second-order set theories with urelements, we explore the strength of
second-order reflection in these contexts. Ultimately, we prove, second-order
reflection with the abundant atom axiom is bi-interpretable and hence also
equiconsistent with the existence of a supercompact cardinal. The proof relies
on a reflection characterization of supercompactness, namely, a cardinal
$\kappa$ is supercompact if and only if every $\Pi^1_1$ sentence true in a
structure $M$ (of any size) containing $\kappa$ in a language of size less than
$\kappa$ is also true in a substructure $m\prec M$ of size less than $\kappa$
with $m\cap\kappa\in\kappa$.


title: Classical results for alternating virtual links

abstract:
  We extend some classical results of Bankwitz, Crowell, and Murasugi to the
setting of virtual links. For instance, we show that an alternating virtual
link is split if and only if it is visibly split, and that the Alexander
polynomial of any almost classical alternating virtual link is alternating. The
first result is a consequence of an inequality relating the link determinant
and crossing number for any non-split alternating virtual link. The second is a
consequence of the matrix-tree theorem of Bott and Mayberry. We discuss the
Tait conjectures for virtual and welded links, and we note that Tait's second
conjecture is not true for alternating welded links.


title: Optimality of intercellular signaling: direct transport versus diffusion

abstract:
  Intercellular signaling has an important role in organism development, but
not all communication occurs using the same mechanism. Here, we analyze the
energy efficiency of intercellular signaling by two canonical mechanisms:
diffusion of signaling molecules and direct transport mediated by signaling
cellular protrusions. We show that efficient contact formation for direct
transport can be established by an optimal rate of projecting protrusions,
which depends on the availability of information about the location of the
target cell. The optimal projection rate also depends on how signaling
molecules are transported along the protrusion, in particular the ratio of the
energy cost for contact formation and molecule synthesis. Also, we compare the
efficiency of the two signaling mechanisms, under various model parameters. We
find that the direct transport is favored over the diffusion when transporting
a large amount of signaling molecules. There is a critical number of signaling
molecules at which the efficiency of the two mechanisms are the same. The
critical number is small when the distance between cells is far, which helps
explain why protrusion-based mechanisms are observed in long-range cellular
communications.


title:
The Harmonic GBC Function Map is a Bijection if the Target Domain is
  Convex

abstract:
  Harmonic generalized barycentric coordinates (GBC) functions have been used
for cartoon animation since an early work in 2006\cite{JMDGS06}. A
computational procedure was further developed in \cite{SH15} for deformation
between any two polygons. The bijectivity of the map based on harmonic GBC
functions is still murky in the literature. In this paper, we present an
elementary proof of the bijection of the harmonic GBC map transforming from one
arbitrary polygonal domain $V$ to a convex polygonal domain $W$. This result is
further extended to a more general harmonic map from one simply connected
domain $V$ to a convex domain $W$ if the harmonic map preserves the orientation
of the boundary of the domain $V$. In addition, we shall point out that the
harmonic GBC map is also a diffeomorphism over the interior of $V$ to the
interior of $W$. Finally, we remark on how to construct a harmonic GBC map from
$V$ to $W$ when the number of vertices of $V$ is different from the number of
vertices of $W$ and how to construct harmonic GBC functions over a polygonal
domain with a hole or holes. We also point out that it is possible to use the
harmonic GBC map to deform a nonconvex polygon $V$ to another nonconvex polygon
$W$ by a good arrangement of the boundary map between $\partial V$ and
$\partial W$. Several numerical deformations based on images are presented to
show the effectiveness of the map based on bivariate spline approximation of
the harmonic GBC functions.


title:
A Generalized Block-Iterative Projection Method for the Common Fixed
  Point Problem Induced by Cutters

abstract:
  The block-iterative projections (BIP) method of Aharoni and Censor
[Block-iterative projection methods for parallel computation of solutions to
convex feasibility problems, Linear Algebra and its Applications 120, (1989),
165--175] is an iterative process for finding asymptotically a point in the
nonempty intersection of a family of closed convex subsets. It employs
orthogonal projections onto the individual subsets in an algorithmic regime
that uses "blocks" of operators and has great flexibility in constructing
specific algorithms from it. We extend this algorithmic scheme to handle a
family of continuous cutter operators and to find a common fixed point of them.
Since the family of continuous cutters includes several important specific
operators, our generalized scheme, which ensures global convergence and retains
the flexibility of BIP, can handle, in particular, metric (orthogonal)
projectors and continuous subgradient projections, which are very important in
applications. We also allow a certain kind of adaptive perturbations to be
included, and along the way we derive a perturbed Fej\'er monotonicity lemma
which is of independent interest.


title:
Relativistic global solutions of neutrino-dominated accretion flows with
  magnetic coupling

abstract:
  A Kerr black hole (BH) surrounded by a neutrino-dominated accretion flow
(NDAF) is one of plausible candidates of the central engine in gamma-ray
bursts. The accretion material might inherit and restructure strong magnetic
fields from the compact object mergers or massive collapsars. The magnetic
coupling (MC) process between a rapid rotating BH and an accretion disc is one
of possible magnetic configurations that transfers the energy and angular
momentum from the BH to the disc. In this paper, we investigate one-dimensional
global solutions of NDAFs with MC (MCNDAFs), taking into account general
relativistic effects, detailed neutrino physics, different MC geometries, and
reasonable nucleosynthesis processes. Six cases with different accretion rates
and power-law indices of magnetic fields are presented and compared with NDAFs
without MC. Our results indict that the MC process can prominently impact the
structure, thermal properties, and microphysics of MCNDAFs, increase
luminosities of neutrinos and their annihilations, result in the changing of
radial distributions of nucleons, and push the region of heavy nuclei synthesis
to a larger radius than counterparts in NDAFs.