title:
Cloud-Edge Training Architecture for Sim-to-Real Deep Reinforcement
  Learning

abstract:
  Deep reinforcement learning (DRL) is a promising approach to solve complex
control tasks by learning policies through interactions with the environment.
However, the training of DRL policies requires large amounts of training
experiences, making it impractical to learn the policy directly on physical
systems. Sim-to-real approaches leverage simulations to pretrain DRL policies
and then deploy them in the real world. Unfortunately, the direct real-world
deployment of pretrained policies usually suffers from performance
deterioration due to the different dynamics, known as the reality gap. Recent
sim-to-real methods, such as domain randomization and domain adaptation, focus
on improving the robustness of the pretrained agents. Nevertheless, the
simulation-trained policies often need to be tuned with real-world data to
reach optimal performance, which is challenging due to the high cost of
real-world samples.
  This work proposes a distributed cloud-edge architecture to train DRL agents
in the real world in real-time. In the architecture, the inference and training
are assigned to the edge and cloud, separating the real-time control loop from
the computationally expensive training loop. To overcome the reality gap, our
architecture exploits sim-to-real transfer strategies to continue the training
of simulation-pretrained agents on a physical system. We demonstrate its
applicability on a physical inverted-pendulum control system, analyzing
critical parameters. The real-world experiments show that our architecture can
adapt the pretrained DRL agents to unseen dynamics consistently and
efficiently.


title:
OPAL: Occlusion Pattern Aware Loss for Unsupervised Light Field
  Disparity Estimation

abstract:
  Light field disparity estimation is an essential task in computer vision with
various applications. Although supervised learning-based methods have achieved
both higher accuracy and efficiency than traditional optimization-based
methods, the dependency on ground-truth disparity for training limits the
overall generalization performance not to say for real-world scenarios where
the ground-truth disparity is hard to capture. In this paper, we argue that
unsupervised methods can achieve comparable accuracy, but, more importantly,
much higher generalization capacity and efficiency than supervised methods.
Specifically, we present the Occlusion Pattern Aware Loss, named OPAL, which
successfully extracts and encodes the general occlusion patterns inherent in
the light field for loss calculation. OPAL enables: i) accurate and robust
estimation by effectively handling occlusions without using any ground-truth
information for training and ii) much efficient performance by significantly
reducing the network parameters required for accurate inference. Besides, a
transformer-based network and a refinement module are proposed for achieving
even more accurate results. Extensive experiments demonstrate our method not
only significantly improves the accuracy compared with the SOTA unsupervised
methods, but also possesses strong generalization capacity, even for real-world
data, compared with supervised methods. Our code will be made publicly
available.


title:
Impact of electron-electron interactions on the thermoelectric
  efficiency of graphene quantum point contacts

abstract:
  Thermoelectric materials open a way to harness dissipated energy and make
electronic devices less energy-demanding. Heat-to-electricity conversion
requires materials with a strongly suppressed thermal conductivity but still
high electronic conduction. This goal is largely achieved with the help of
nanostructured materials, even if the bulk counterpart is not highly efficient.
In this work, we investigate how thermoelectric efficiency is enhanced by
many-body effects in graphene nanoribbons at low temperature. To this end,
starting from the Kane-Mele-Hubbard model within a mean-field approximation, we
carry out an extensive numerical study of the impact of electron-electron
interactions on the thermoelectric efficiency of graphene nanoribbons with
armchair or zigzag edges. We consider two different regimes, namely trivial and
topological insulator. We find that electron-electron interactions are crucial
for the appearance of interference phenomena that give rise to an enhancement
of the thermoelectric efficiency of the nanoribbons. Lastly, we also propose an
experimental setup that would help to test the validity of our conclusions.


title: Empirical Structure Models of Uranus and Neptune

abstract:
  Uranus and Neptune are still poorly understood. Their gravitational fields,
rotation periods, atmosphere dynamics, and internal structures are not well
determined. In this paper we present empirical structure models of Uranus and
Neptune where the density profiles are represented by polytropes. By using
these models, that are set to fit the planetary gravity field, we predict the
higher order gravitational coefficients $J_6$ and $J_8$ for various assumed
rotation periods, wind depths, and uncertainty of the low-order harmonics. We
show that faster rotation and/or deep winds favour centrally concentrated
density distributions. We demonstrate that an accurate determination of $J_6$
or $J_8$ with a relative uncertainty no larger than $10\%$ could constrain wind
depths of Uranus and Neptune. We also confirm that the Voyager rotation periods
are inconsistent with the measured shapes of Uranus and Neptune. We next
demonstrate that more accurate determination of the gravity field can
significantly reduce the possible range of internal structures. Finally, we
suggest that an accurate measurement of the moment of inertia of Uranus and
Neptune with a relative uncertainty of $\sim1\%$ and $\sim0.1\%$, could
constrain their rotation periods and depths of the winds, respectively.


title: Cluster-Robust Estimators for Bivariate Mixed-Effects Meta-Regression

abstract:
  Meta-analyses frequently include trials that report multiple effect sizes
based on a common set of study participants. These effect sizes will generally
be correlated. Cluster-robust variance-covariance estimators are a fruitful
approach for synthesizing dependent effects. However, when the number of
studies is small, state-of-the-art robust estimators can yield inflated Type 1
errors. We present two new cluster-robust estimators, in order to improve small
sample performance. For both new estimators the idea is to transform the
estimated variances of the residuals using only the diagonal entries of the hat
matrix. Our proposals are asymptotically equivalent to previously suggested
cluster-robust estimators such as the bias reduced linearization approach. We
apply the methods to real world data and compare and contrast their performance
in an extensive simulation study. We focus on bivariate meta-regression,
although the approaches can be applied more generally.


title: Latent Unbalancedness in Three-Way Gravity Models

abstract:
  Many panel data sets used for pseudo-poisson estimation of three-way gravity
models are implicitly unbalanced because uninformative observations are
redundant for the estimation. We show with real data as well as simulations
that this phenomenon, which we call latent unbalancedness, amplifies the
inference problem recently studied by Weidner and Zylkin (2021).


title:
A Simplified Twin Pati-Salam Theory of Flavour with a TeV Scale Vector
  Leptoquark

abstract:
  In this talk, we discuss a simplified version of a recently proposed twin
Pati-Salam (PS) theory of flavour broken to the $G_{4321}$ gauge group at high
energies, then to the Standard Model at low energies, yielding a TeV scale
vector leptoquark $U^{\mu}_1(3,1,2/3)$ which may be used to address the lepton
universality anomalies $R_{K^{(*)}}$ and $R_{D^{(*)}}$ in $B$ decays. The model
also accounts for quark and lepton mass hierarchies, providing a link between
the flavour anomalies and a theory of flavour.


title: A note on recovering the Brownian motion component from a Levy process

abstract:
  Gonzalez Cazares and Ivanovs (2021) suggested a new method for "recovering"
the Brownian motion component from the trajectory of a Levy process that
required sampling from an independent Brownian motion process. We show that
such a procedure works equally well without any additional source of randomness
if one uses normal quantiles instead of the ordered increments of the auxiliary
Brownian motion process.


title: Graviton scattering in self-dual radiative space-times

abstract:
  We give formulae for all tree-level graviton scattering amplitudes in curved
self-dual radiative space-times; these are chiral, source-free, asymptotically
flat spaces determined by free characteristic data at null infinity. Such
space-times admit an elegant description in terms of twistor theory and
Penrose's non-linear graviton, which manifests their underlying integrability.
The tree-level S-matrix is written in terms of an integral over the moduli
space of holomorphic maps from the Riemann sphere to twistor space, with the
degree of the map corresponding to the helicity configuration of the external
gravitons. For the MHV sector, we derive the amplitude directly from general
relativity, while other helicity configurations arise from a natural family of
generating functionals and pass several consistency checks. The amplitudes in
self-dual radiative space-times exhibit many novel features which are absent in
Minkowski space, including tail effects. There are also residual integrals due
to the functional degrees of freedom in the background space-time, although our
formulae have fewer such integrals than expected from space-time perturbation
theory. In highly symmetric special cases, such as self-dual plane waves, the
number of residual integrals can be further reduced, resulting in even simpler
expressions for the scattering amplitudes.


title: Phase of quantum oscillation in Weyl semimetals

abstract:
  We consider the semiclassical quantization condition for the energy of an
electron in a magnetic field in the case when the electron orbit lies on a
Fermi-surface pocket surrounding the Weyl point of a topological semimetal and
analyze the constant $\gamma$ appearing in this condition. It is shown that
this constant has the universal value, $\gamma=0$, independent of the tilt of
the Weyl spectrum. Since the constant $\gamma$ for an extremal cross section of
the Fermi surface determines the phase of quantum oscillations, this result
explains why measurements of the phase permit one to find Weyl points in
crystals even though the extremal cross section of the pocket does not pass
through this point, and the appropriate Berry phase of the orbit differs from
$\pi$.


title: Chaos and ergodicity in entangled non-ideal Bohmian qubits

abstract:
  We study the Bohmian dynamics of a large class of bipartite systems of
non-ideal qubit systems, by modifying the basic physical parameters of an ideal
two-qubit system, made of coherent states of the quantum harmonic oscillator.
First we study the case of coherent states with truncated energy levels and
large amplitudes. Then we study non-truncated coherent states but with small
amplitudes and finally a combination of the above cases. In all cases we find
that the chaotic Bohmian trajectories are approximately ergodic. We also study
the number and the spatial arrangement of the nodal points of the wavefunction
and their role both in the formation of chaotic-ergodic trajectories, and in
the emergence of ordered trajectories. Our results have strong implications on
the dynamical establishment of Born's rule.


title: Undoing Seamlessness: Exploring Seams for Critical Visualization

abstract:
  While seamful design has been part of discourses and work within HCI contexts
for some time, it has not yet been fully explored in data visualization design.
At the same time, critics of visualization have been arguing that the
representation of data as contextual, contingent, relational, partial,
heterogeneous, and situated is currently lacking in visualization. Seamful
visualization promises a fresh perspective on visualization design as we seek
to find more expressive encodings and novel approaches to representing data
that acknowledge their wider qualities and limitations. By consulting seams in
other realms and exploring existing seams and seamfulness in visualization,
this paper offers a foundation for conceptualizing seamful visualization,
points towards the value of seams and seamfulness in critical visualization,
and proposes principles for engaging with seamful visualization in practice and
research.


title:
Extended Reality (XR) over 5G and 5G-Advanced New Radio:
  Standardization, Applications, and Trends

abstract:
  Extended Reality (XR) is one of the major innovations to be introduced in
5G/5G-Advanced communication systems. A combination of augmented reality,
virtual reality, and mixed reality, supplemented by cloud gaming, revisits the
way how humans interact with computers, networks, and each other. However,
efficient support of XR services imposes new challenges for existing and future
wireless networks. This article presents a tutorial on integrating support for
the XR into the 3GPP New Radio (NR), summarizing a range of activities handled
within various 3GPP Services and Systems Aspects (SA) and Radio Access Networks
(RAN) groups. The article also delivers a case study evaluating the performance
of different XR services in state-of-the-art NR Release 17. The paper concludes
with a vision of further enhancements to better support XR in future NR
releases and outlines open problems in this area.


title:
Interplay of the Jahn--Teller Effect and Spin-Orbit Coupling: The Case
  of Trigonal Vibronic Modes

abstract:
  We study an interplay between the orbital degeneracy and spin-orbit coupling
giving rise to spin-orbital entangled states. As a specific example, we analyze
the interaction of electrons occupying triply degenerate single-ion $t_{2g}$
levels with trigonal vibronic modes (the $t\otimes T$ problem). A more general
problem of the electron-lattice interaction involving both tetragonal and
trigonal vibrations is also considered. It is shown that the result of such
interaction crucially depends on the occupation of $t_{2g}$ levels leading to
either the suppression or enhancement of the Jahn-Teller effect by the
spin-orbit coupling.


title:
IISERB Brains at SemEval 2022 Task 6: A Deep-learning Framework to
  Identify Intended Sarcasm in English

abstract:
  This paper describes the system architectures and the models submitted by our
team "IISERBBrains" to SemEval 2022 Task 6 competition. We contested for all
three sub-tasks floated for the English dataset. On the leader-board, wegot19th
rank out of43 teams for sub-taskA, the 8th rank out of22 teams for sub-task
B,and13th rank out of 16 teams for sub-taskC. Apart from the submitted results
and models, we also report the other models and results that we obtained
through our experiments after organizers published the gold labels of their
evaluation data


title: Unveiling the Enhancement of Spontaneous Emission at Exceptional Points

abstract:
  Exceptional points (EPs), singularities of non-Hermitian physics where
complex spectral resonances degenerate, are one of the most exotic features of
nonequilibrium open systems with unique properties. For instance, the emission
rate of quantum emitters placed near resonators with EPs is enhanced (compared
to the free-space emission rate) by a factor that scales quadratically with the
resonance quality factor. Here, we verify the theory of spontaneous emission at
EPs by measuring photoluminescence from photonic-crystal slabs that are
embedded with a high-quantum-yield active material. While our experimental
results verify the theoretically predicted enhancement, it also highlights the
practical limitations on the enhancement due to material loss. Our designed
structures can be used in applications that require enhanced and controlled
emission, such as quantum sensing and imaging.


title: Detecting GAN-generated Images by Orthogonal Training of Multiple CNNs

abstract:
  In the last few years, we have witnessed the rise of a series of deep
learning methods to generate synthetic images that look extremely realistic.
These techniques prove useful in the movie industry and for artistic purposes.
However, they also prove dangerous if used to spread fake news or to generate
fake online accounts. For this reason, detecting if an image is an actual
photograph or has been synthetically generated is becoming an urgent necessity.
This paper proposes a detector of synthetic images based on an ensemble of
Convolutional Neural Networks (CNNs). We consider the problem of detecting
images generated with techniques not available at training time. This is a
common scenario, given that new image generators are published more and more
frequently. To solve this issue, we leverage two main ideas: (i) CNNs should
provide orthogonal results to better contribute to the ensemble; (ii) original
images are better defined than synthetic ones, thus they should be better
trusted at testing time. Experiments show that pursuing these two ideas
improves the detector accuracy on NVIDIA's newly generated StyleGAN3 images,
never used in training.


title: Four-dimensional factorization of the fermion determinant in lattice QCD

abstract:
  In the last few years it has been proposed a one-dimensional factorization of
the fermion determinant in lattice QCD with Wilson-type fermions that leads to
a block-local action of the auxiliary bosonic fields. Here we propose a
four-dimensional generalization of this factorization. Possible applications
are more efficient parallelizations of Monte Carlo algorithms and codes, master
field simulations, and multi-level integration.


title:
Peeling dynamics of fluid membranes bridged by molecular bonds: moving
  or breaking

abstract:
  Biological adhesion is a critical mechanical function of complex organisms
operating at multiple scales. At the cellular scale, cell-cell adhesion is
remarkably tunable to enable both cohesion and malleability during development,
homeostasis and disease. Such adaptable adhesion is physically supported by
transient bonds between laterally mobile molecules embedded in fluid membranes.
Thus, unlike specific adhesion at solid-solid or solid-fluid interfaces,
peeling at fluid-fluid interfaces can proceed by breaking bonds, by moving
bonds, or by a combination of both. How the additional degree of freedom
provided by bond mobility changes the mechanics of peeling is not understood.
To address this, we develop a theoretical model coupling self-consistently
diffusion, reactions and mechanics. Lateral mobility and reaction rates
determine distinct peeling regimes. In a diffusion-dominated Stefan-like
regime, bond motion establishes self-stabilizing dynamics that increase the
effective adhesion fracture energy. A reaction-dominated regime exhibits
traveling peeling solutions where small-scale diffusion and marginal unbinding
control peeling speed. In a mixed reaction-diffusion regime, strengthening by
bond motion competes with weakening by bond breaking in a force-dependent
manner, defining the strength of the adhesion patch. In turn, patch strength
depends on molecular properties such as bond stiffness, force sensitivity, or
crowding. We thus establish the physical rules enabling tunable cohesion in
cellular tissues and in engineered biomimetic systems.


title:
Dependence structure for the product of bi-dimensional finite-variance
  VAR(1) model components. An application to the cost of electricity load
  prediction errors

abstract:
  In this paper we analyze the product of bi-dimensional VAR(1) model
components. For the introduced time series we derive general formulas for the
autocovariance function and study its properties for different cases of
cross-dependence between the VAR(1) model components. The theoretical results
are then illustrated in the simulation study for two types of bivariate
distributions of the residual series, namely the Gaussian and Student's t. We
also show a possible practical application of the obtained results based on the
data from the electricity market.


title: Patch Similarity Aware Data-Free Quantization for Vision Transformers

abstract:
  Vision transformers have recently gained great success on various computer
vision tasks; nevertheless, their high model complexity makes it challenging to
deploy on resource-constrained devices. Quantization is an effective approach
to reduce model complexity, and data-free quantization, which can address data
privacy and security concerns during model deployment, has received widespread
interest. Unfortunately, all existing methods, such as BN regularization, were
designed for convolutional neural networks and cannot be applied to vision
transformers with significantly different model architectures. In this paper,
we propose PSAQ-ViT, a Patch Similarity Aware data-free Quantization framework
for Vision Transformers, to enable the generation of "realistic" samples based
on the vision transformer's unique properties for calibrating the quantization
parameters. Specifically, we analyze the self-attention module's properties and
reveal a general difference (patch similarity) in its processing of Gaussian
noise and real images. The above insights guide us to design a relative value
metric to optimize the Gaussian noise to approximate the real images, which are
then utilized to calibrate the quantization parameters. Extensive experiments
and ablation studies are conducted on various benchmarks to validate the
effectiveness of PSAQ-ViT, which can even outperform the real-data-driven
methods.


title: Indirect Mechanism of Au adatom Diffusion on the Si(100) Surface

abstract:
  Calculations of the diffusion of a Au adatom on the dimer reconstructed
Si(100)-2x1 surface reveal an interesting mechanism that differs significantly
from a direct path between optimal binding sites, which are located in between
dimer rows. Instead, the active diffusion mechanism involves promotion of the
adatom to higher energy sites on top of a dimer row and then fast migration
along the row, visiting ca. a hundred sites at room temperature, before falling
back down into an optimal binding site. This top-of-row mechanism becomes more
important the lower the temperature is. The calculations are carried out by
finding minimum energy paths on the energy surface obtained from density
functional theory within the PBEsol functional approximation followed by
kinetic Monte Carlo simulations of the diffusion over a range of temperature
from 200 K to 900 K. While the activation energy for the direct diffusion
mechanism is calculated to be 0.84 eV, the effective activation energy for the
indirect mechanism is on average 0.56 eV.


title: Parametric/direct CAD integration

abstract:
  In the history of computer-aided design (CAD), feature-based parametric
modeling and boundary representation-based direct modeling are two of the most
important CAD paradigms, developed respectively in the late 1980s and the late
2000s. They have complementary advantages and limitations, thereby offering
huge potential for improvement towards an integrated CAD modeling scheme. Some
believe that their integration will be the key characteristic of next
generation CAD software. This paper provides a brief review on current
parametric/direct integration approaches. Their basic ideas, advantages, and
disadvantages will be discussed. The main result reads that existing
integration approaches are far from being completed if seamless
parametric/direct integration is desired. It is hoped that, by outlining what
has already been made possible and what still remains problematic, more
researchers will be attracted to work on this very important research topic of
parametric/direct integration.


title: Galton-Watson trees with first ancestor interaction

abstract:
  We consider the set of random Bienaym\'e-Galton-Watson trees with a bounded
number of offspring and bounded number of generations as a statistical
mechanics model: a random tree is a rooted subtree of the maximal tree; the
spin at a given node of the maximal tree is equal to the number of offspring if
the node is present in the random tree and equal to -1 otherwise. We introduce
nearest neighbour interactions favouring pairs of neighbours which both have a
relatively large offspring. We then prove (1) correlation inequalities and (2)
recursion relations for generating functions, mean number of leaves,
interaction energy and the corresponding variances. The resulting quadratic
dynamical system, in two dimensions or more depending on the desired number of
moments, yields almost exact numerical results. The balance between offspring
distribution and coupling constant leads to a phase diagram for the analogue of
the extinction probability. On the transition line the mean number of leaves in
generation $n$ is found numerically to scale as $n^{-2}$.


title: A real variable calculus for planar orthogonal polynomials

abstract:
  This note is part of a project in which we aim to obtain a global calculus
for polynomial Bergman kernels in the plane. We aim to find a characterization
of the diagonal restriction of the kernel as the unique solution to a certain
non-linear soft Riemann-Hilbert problem. It is well known that the diagonal
restriction of the polynomial Bergman kernel equals a sum of the squared moduli
of the normalized orthogonal polynomials. Here, we characterize these squared
moduli in terms of a real variable non-linear soft Riemann-Hilbert problem for
the Laplacian (in place of the $\bar\partial$-operator), and find a direct
algorithm to produce suitable approximants. The appearance of squared moduli
creates a non-linear effect which was not present in earlier work.


title:
Observational constraints on the origin of the elements. IV: The
  standard composition of the Sun

abstract:
  The chemical composition of the Sun is requested in the context of various
studies in astrophysics, among them in the calculation of the standard solar
models (SSMs), which describe the evolution of the Sun from the
pre-main-sequence to its present age. In this work, we provide a critical
re-analysis of the solar chemical abundances and corresponding SSMs. For the
photospheric values, we employ new high-quality solar observational data
collected with the IAG facility, state-of-the art non-equilibrium modelling,
new oscillator strengths, and different atmospheric models, including the MARCS
model, but also averages based on Stagger and CO5BOLD 3D
radiation-hydrodynamics simulations of stellar convection. We perform new
calculations of oscillator strengths for transitions in O I and N I. For O I -
the critical element for the interior models - calculations are carried out
using several independent methods. We find unprecedented agreement between the
new estimates of transition probabilities, thus supporting our revised solar
oxygen abundance. We also provide new estimates of the noble gas Ne abundance.
We investigate our results in comparison with the previous estimates. We
discuss the consistency of our photospheric measurements with meteoritic values
taking into account systematic and correlated errors. Finally, we provide
revised chemical abundances, leading to a new value of the solar photospheric
present-day metallicity $Z/X = 0.0225$, and employ them in the calculations of
the SSM. We find that the puzzling mismatch between the helioseismic
constraints on the solar interior structure and the model is resolved with the
new chemical composition.


title:
Global existence and analyticity of $L^p$ solutions to the compressible
  fluid model of Korteweg type

abstract:
  We are concerned with a system of equations in $\mathbb{R}^{d}(d\geq2)$
governing the evolution of isothermal, viscous and compressible fluids of
Korteweg type, that can be used as a phase transition model. In the case of
zero sound speed $P'(\rho^{\ast})=0$, it is found that the linearized system
admits the \textit{purely} parabolic structure, which enables us to establish
the global-in-time existence and Gevrey analyticity of strong solutions in
hybrid Besov spaces of $L^p$-type. Precisely, if the full viscosity coefficient
and capillary coefficient satisfy $\bar{\nu}^2\geq4\bar{\kappa}$, then the
acoustic waves are not available in compressible fluids. Consequently, the
prior $L^2$ bounds on the low frequencies of density and velocity could be
improved to the general $L^p$ version with $1\leq p\leq d$ if $d\geq2$. The
proof mainly relies on new nonlinear Besov (-Gevrey) estimates for product and
composition of functions.


title:
New Solar Flare Calcium Abundances with no Surprises: Results from the
  SMM Bent Crystal Spectrometer

abstract:
  The calcium abundance in flare plasmas is estimated using X-ray spectra from
the Solar Maximum Mission Bent Crystal Spectrometer (BCS) during the decays of
194 flares (GOES classifications from B6.4 to X13) occurring between 1980 and
1989. Previous work by Sylwester et al. found that the abundance varied from
flare to flare. That analysis is improved on here using updated instrument
parameters and by including all calcium lines viewed by the BCS instead of only
the resonance line, so greatly enhancing the photon count statistics. The
abundance variations are confirmed with the average abundance, $A({\rm Ca})$
(expressed logarithmically with $A({\rm H}) = 12$), equal to $6.77 \pm 0.20$
for 194 flares (141 of which are new in this study). This range corresponds to
factors of between 1.7 and 7.2 larger than the photospheric abundance and so
our results are in line with a ``FIP" (first ionization potential) effect
whereby low-FIP elements like Ca (FIP = 6.11~eV) have enhanced coronal
abundances. The Ca flare abundance is uncorrelated with solar activity indices,
but weak correlations are suggested with GOES flare class and duration (larger
$A({\rm Ca})$ for smaller and shorter flares). The ponderomotive force theory
of Laming explaining the FIP effect gives a range of parameters within which
our estimates of $A({\rm Ca})$ agree with the theory. However, this then gives
rise to disagreements with previous estimates of the flare silicon and sulfur
abundances, although those of argon and iron are in good agreement. Small
adjustments of the theory may thus be necessary.


title: Air Quality in the New Delhi Metropolis under COVID-19 Lockdown

abstract:
  Air pollution has been on continuous rise with increase in industrialization
in metropolitan cities of the world. Several measures including strict climate
laws and reduction in the number of vehicles were implemented by several
nations. The COVID-19 pandemic provided a great opportunity to understand the
daily human activities effect on air pollution. Majority nations restricted
industrial activities and vehicular traffic to a large extent as a measure to
restrict COVID-19 spread. In this paper, we analyzed the impact of such
COVID19-induced lockdown on the air quality of the city of New Delhi, India. We
analyzed the average concentration of common gaseous pollutants viz. sulfur
dioxide (SO$_2$), ozone (O$_3$), nitrogen dioxide (NO$_2$), and carbon monoxide
(CO). These concentrations were obtained from the tropospheric column of
Sentinel-5P (an earth observation satellite of European Space Agency) data. We
observed that the city observed a significant drop in the level of atmospheric
pollutant's concentration for all the major pollutants as a result of strict
lockdown measures. Such findings are also validated with pollutant data
obtained from ground-based monitoring stations. We observed that near-surface
pollutant concentration dropped significantly by 50% for PM$_{2.5}$, 71.9% for
NO$_2$, and 88% for CO, after the lockdown period. Such studies would pave the
path for implementing future air pollution control measures by
environmentalists.


title: Information retrieval and structural complexity of legal trees

abstract:
  We introduce a model for the retrieval of information hidden in legal texts.
These are typically organised in a hierarchical (tree) structure, which a
reader interested in a given provision needs to explore down to the "deepest"
level (articles, clauses,...). We assess the structural complexity of legal
trees by computing the mean first-passage time a random reader takes to
retrieve information planted in the leaves. The reader is assumed to skim
through the content of a legal text based on their interests/keywords, and be
drawn towards the sought information based on keywords affinity, i.e. how well
the Chapters/Section headers of the hierarchy seem to match the informational
content of the leaves. Using randomly generated keyword patterns, we
investigate the effect of two main features of the text -- the horizontal and
vertical coherence -- on the searching time, and consider ways to validate our
results using real legal texts. We obtain numerical and analytical results, the
latter based on a mean-field approximation on the level of patterns, which lead
to an explicit expression for the complexity of legal trees as a function of
the structural parameters of the model. Policy implications of our results are
briefly discussed.


title:
Defect-based characterization of the fatigue behavior of additively
  manufactured titanium aluminides

abstract:
  The additively manufactured titanium aluminide alloy TNM-B1 was characterized
microstructurally and mechanically in the as-built and hot isostatically
pressed (HIP) condition. Tensile and constant amplitude tests were performed at
room temperature and 800 {\deg}C. Using fractographic SEM images, the
fracture-inducing defect was identified. With the HIP, defect number and size
could be reduced, increasing fatigue strength by 43% to 500 MPa. Using the
model approaches of Murakami and Shiozawa, the fatigue life was correlated with
the local stress intensity factor and could be described as function of the
stress amplitude as well as the size and location of fracture-inducing defects.


title: Class-Aware Contrastive Semi-Supervised Learning

abstract:
  Pseudo-label-based semi-supervised learning (SSL) has achieved great success
on raw data utilization. However, its training procedure suffers from
confirmation bias due to the noise contained in self-generated artificial
labels. Moreover, the model's judgment becomes noisier in real-world
applications with extensive out-of-distribution data. To address this issue, we
propose a general method named Class-aware Contrastive Semi-Supervised Learning
(CCSSL), which is a drop-in helper to improve the pseudo-label quality and
enhance the model's robustness in the real-world setting. Rather than treating
real-world data as a union set, our method separately handles reliable
in-distribution data with class-wise clustering for blending into downstream
tasks and noisy out-of-distribution data with image-wise contrastive for better
generalization. Furthermore, by applying target re-weighting, we successfully
emphasize clean label learning and simultaneously reduce noisy label learning.
Despite its simplicity, our proposed CCSSL has significant performance
improvements over the state-of-the-art SSL methods on the standard datasets
CIFAR100 and STL10. On the real-world dataset Semi-iNat 2021, we improve
FixMatch by 9.80% and CoMatch by 3.18%. Code is available
https://github.com/TencentYoutuResearch/Classification-SemiCLS.


title: Gromov hyperbolicity in the free quasiworld. I

abstract:
  With the aid of a Gromov hyperbolic characterization of uniform domains, we
first give an affirmative answer to an open question arisen by V\"ais\"al\"a
under weaker assumption. Next, we show that the three-point condition
introduced by V\"ais\"al\"a is necessary to obtain quasisymmetry for
quasim\"obius maps between bounded connected spaces in a quantitative way.
Based on these two results, we investigate the boundary behavior of freely
quasiconformal and quasihyperbolic mappings on uniform domains of Banach spaces
and partially answer another question raised by V\"ais\"al\"a in different
ways.


title:
PercepNet+: A Phase and SNR Aware PercepNet for Real-Time Speech
  Enhancement

abstract:
  PercepNet, a recent extension of the RNNoise, an efficient, high-quality and
real-time full-band speech enhancement technique, has shown promising
performance in various public deep noise suppression tasks. This paper proposes
a new approach, named PercepNet+, to further extend the PercepNet with four
significant improvements. First, we introduce a phase-aware structure to
leverage the phase information into PercepNet, by adding the complex features
and complex subband gains as the deep network input and output respectively.
Then, a signal-to-noise ratio (SNR) estimator and an SNR switched
post-processing are specially designed to alleviate the over attenuation (OA)
that appears in high SNR conditions of the original PercepNet. Moreover, the
GRU layer is replaced by TF-GRU to model both temporal and frequency
dependencies. Finally, we propose to integrate the loss of complex subband
gain, SNR, pitch filtering strength, and an OA loss in a multi-objective
learning manner to further improve the speech enhancement performance.
Experimental results show that, the proposed PercepNet+ outperforms the
original PercepNet significantly in terms of both PESQ and STOI, without
increasing the model size too much.


title: Phonon transport properties of particulate physical gels

abstract:
  Particulate physical gels are sparse, low-density amorphous materials in
which clusters of glasses are connected to form a heterogeneous network
structure. This structure is characterized by two length scales, $\xi_s$ and
$\xi_G$: $\xi_s$ measures the length of heterogeneities in the network
structure, and $\xi_G$ is the size of glassy clusters. Accordingly, the
vibrational states of such a material also exhibit a multiscale nature with two
characteristic frequencies, $\omega_\ast$ and $\omega_G$, which are associated
with $\xi_s$ and $\xi_G$, respectively: (i) phonon-like vibrations in the
homogeneous medium at $\omega < \omega_\ast$, (ii) phonon-like vibrations in
the heterogeneous medium at $\omega_\ast < \omega < \omega_G$, and (iii)
disordered vibrations in the glassy clusters at $\omega > \omega_G$. Here, we
demonstrate that the multiscale characteristics seen in the static structures
and vibrational states also extend to the phonon transport properties. Phonon
transport exhibits two distinct crossovers at the frequencies $\omega_\ast$ and
$\omega_G$~(or at wavenumbers of $\sim \xi_s^{-1}$ and $\sim \xi_G^{-1}$). In
particular, both transverse and longitudinal phonons cross over between
Rayleigh scattering at $\omega < \omega_\ast$ and diffusive damping at
$\omega>\omega_\ast$. Remarkably, the Ioffe--Regel limit is located at the very
low frequency of $\omega_\ast$. Thus, phonon transport is localized above
$\omega_\ast$, even where phonon-like vibrational states persist. This markedly
strong scattering behavior is caused by the sparse, porous structure of the
gel.


title:
Combined active-passive heat transfer enhancement for a partial
  superhydrophobic oscillating cylinder

abstract:
  Numerical simulation of convective heat transfer over a stationary and
transversely oscillating partial super-hydrophobic cylinder has been performed
using OpenFOAM libraries. Superhydrophobicity of the cylinder surface has been
addressed by means of a partial slip boundary condition. Applying the slip
condition to the surface of the stationary cylinder causes the drag and the rms
lift coefficients to reduce by 46 and 75 percent, respectively. It also
augments the average Nusselt number by 55 percent accompanied by a 21 percent
increase of the natural shedding frequency. The partially superhydrophobic
cylinder has also been investigated and the effects of slip on different
sections of the cylinder surface have been analyzed. Considering the reduction
of force coefficients, it is shown that the application of slip over a 135
segment of the surface is an optimum case, resulting in a 47 and 85 percent
decrease of the drag and the rms lift coefficients, respectively. However, the
fully superhydrophobic cylinder provides higher heat transfer rates. Regarding
the transversely oscillating cylinder, superhydrophobicity extends the primary
synchronization region, and also exhibits different wake dynamics behavior
compared to the no-slip case. The slip over surfaces also causes the average
Nusselt number to become nearly 6 times greater than the no-slip oscillating
cylinder at the lock-in condition. Further analysis based on thermal
performance index (TPI) proves that a high value of TPI = 6 can be reached for
the superhydrophobic cylinder.


title: Law of Large Numbers for Random Quantum Dynamical Semigroups

abstract:
  We present a Law of Large Numbers principle for uniformly continuous random
quantum dynamical semigroups. Random iterates of independent copies of these
semigroups are shown to be Chernoff equivalent to the quantum dynamical
semigroup by the average generator.


title:
Attainable set for rank 3 step 2 free Carnot group with positive
  controls

abstract:
  We find the attainable set for a control system on the free Carnot group of
rank $3$ and step $2$ with positive controls. This kind of control systems is
connected with the theory of free Lie semigroups; with some estimates for
probabilities of inequalities for independent random variables; with the
nilpotent approximation of robotic control systems and with contour recovering
without cusps in image processing. We investigate the boundary of the
attainable set with the help of the Pontryagin maximum principle for the
time-optimal control problem. We study extremal trajectories that correspond to
bang-bang, singular and mixed controls. We obtain upper bounds for the number
of switchings for optimal controls. This implies a parametrization of the
boundary faces of the attainable set.


title: Variance Reduction for Metropolis-Hastings Samplers

abstract:
  We introduce a general framework that constructs estimators with reduced
variance for random walk Metropolis and Metropolis-adjusted Langevin
algorithms. The resulting estimators require negligible computational cost and
are derived in a post-process manner utilising all proposal values of the
Metropolis algorithms. Variance reduction is achieved by producing control
variates through the approximate solution of the Poisson equation associated
with the target density of the Markov chain. The proposed method is based on
approximating the target density with a Gaussian and then utilising accurate
solutions of the Poisson equation for the Gaussian case. This leads to an
estimator that uses two key elements: (i) a control variate from the Poisson
equation that contains an intractable expectation under the proposal
distribution, (ii) a second control variate to reduce the variance of a Monte
Carlo estimate of this latter intractable expectation. Simulated data examples
are used to illustrate the impressive variance reduction achieved in the
Gaussian target case and the corresponding effect when target Gaussianity
assumption is violated. Real data examples on Bayesian logistic regression and
stochastic volatility models verify that considerable variance reduction is
achieved with negligible extra computational cost.


title: Do Explanations Explain? Model Knows Best

abstract:
  It is a mystery which input features contribute to a neural network's output.
Various explanation (feature attribution) methods are proposed in the
literature to shed light on the problem. One peculiar observation is that these
explanations (attributions) point to different features as being important. The
phenomenon raises the question, which explanation to trust? We propose a
framework for evaluating the explanations using the neural network model
itself. The framework leverages the network to generate input features that
impose a particular behavior on the output. Using the generated features, we
devise controlled experimental setups to evaluate whether an explanation method
conforms to an axiom. Thus we propose an empirical framework for axiomatic
evaluation of explanation methods. We evaluate well-known and promising
explanation solutions using the proposed framework. The framework provides a
toolset to reveal properties and drawbacks within existing and future
explanation solutions.


title:
Feature Transformation for Cross-domain Few-shot Remote Sensing Scene
  Classification

abstract:
  Effectively classifying remote sensing scenes is still a challenge due to the
increasing spatial resolution of remote imaging and large variances between
remote sensing images. Existing research has greatly improved the performance
of remote sensing scene classification (RSSC). However, these methods are not
applicable to cross-domain few-shot problems where target domain is with very
limited training samples available and has a different data distribution from
source domain. To improve the model's applicability, we propose the
feature-wise transformation module (FTM) in this paper. FTM transfers the
feature distribution learned on source domain to that of target domain by a
very simple affine operation with negligible additional parameters. Moreover,
FTM can be effectively learned on target domain in the case of few training
data available and is agnostic to specific network structures. Experiments on
RSSC and land-cover mapping tasks verified its capability to handle
cross-domain few-shot problems. By comparison with directly finetuning, FTM
achieves better performance and possesses better transferability and
fine-grained discriminability. \textit{Code will be publicly available.}


title: Data-driven MPC of descriptor systems: A case study for power networks

abstract:
  Recently, data-driven predictive control of linear systems has received
wide-spread research attention. It hinges on the fundamental lemma by Willems
et al. In a previous paper, we have shown how this framework can be applied to
predictive control of linear time-invariant descriptor systems. In the present
paper, we present a case study wherein we apply data-driven predictive control
to a discrete-time descriptor model obtained by discretization of the
power-swing equations for a nine-bus system. Our results shows the efficacy of
the proposed control scheme and they underpin the prospect of the data-driven
framework for control of descriptor systems.


title: Direct URCA process in light of PREX-2

abstract:
  We study the implications of the recent development in nuclear symmetry
energy constraints from PREX-2 data on dense matter equation of state and its
impact on dURCA threshold density. In this work, we construct the equation of
state within the framework of covariant density functional theory implementing
coupling schemes of non-linear and density-dependent models and exploring the
coupling parameter space of isovector-vector meson to baryons constrained by
the isospin asymmetry parameter values deduced from recent PREX-2 data. The
modified parameter sets are applied to evaluate the dense matter properties. We
find that the updated data suggests the occurrence of dURCA process within
neutron star even with mass as low as one solar mass.


title:
The eigenvector-eigenvalue identity for the quaternion matrix with its
  algorithm and computer program

abstract:
  Peter Denton, Stephen Parker, Terence Tao and Xining Zhang [arxiv 2019]
presented a basic and important identity in linear commutative algebra,
so-called {\bf the eigenvector-eigenvalue identity} (formally named in [BAMS,
2021]), which is a convenient and powerful tool to succinctly determine
eigenvectors from eigenvalues. The identity relates the eigenvector component
to the eigenvalues of $A$ and the minor $M_j$, which is formulated in an
elegant form as \[ \lvert v_{i,j} \rvert^2\prod_{k=1;k\ne
i}^{n-1}({\lambda_i}(A)-{\lambda_k}(A))=\prod_{k=1}^{n-1}({\lambda_i}(A)-{\lambda_k}(M_j)).
\,\,\,%\mbox{(\cite{tao-eig,D-P-T-Z})} \]
  In fact, it has been widely applied in various fields such as numerical
linear algebra, random matrix theory, inverse eigenvalue problem, graph theory,
neutrino physics and so on. In this paper, we extend the eigenvector-eigenvalue
identity to the quaternion division ring, which is non-commutative. A version
of eigenvector-eigenvalue identity for the quaternion matrix is established.
Furthermore, we give a new method and algorithm to compute the eigenvectors
from the right eigenvalues for the quaternion Hermitian matrix. A program is
designed to realize the algorithm to compute the eigenvectors. An open problem
ends the paper. Some examples show a good performance of the algorithm and the
program.


title: Some Counterexamples in Ring Theory

abstract:
  In this note we provide counterexamples related to an important result on
weakly tripotent rings.


title:
Speech watermarking: an approach for the forensic analysis of digital
  telephonic recordings

abstract:
  In this article, the authors discuss the problem of forensic authentication
of digital audio recordings. Although forensic audio has been addressed in
several articles, the existing approaches are focused on analog magnetic
recordings, which are less prevalent because of the large amount of digital
recorders available on the market (optical, solid state, hard disks, etc.). An
approach based on digital signal processing that consists of spread spectrum
techniques for speech watermarking is presented. This approach presents the
advantage that the authentication is based on the signal itself rather than the
recording format. Thus, it is valid for usual recording devices in
police-controlled telephone intercepts. In addition, our proposal allows for
the introduction of relevant information such as the recording date and time
and all the relevant data (this is not always possible with classical systems).
Our experimental results reveal that the speech watermarking procedure does not
interfere in a significant way with the posterior forensic speaker
identification.


title:
Large gaps between primes in arithmetic progressions -- an empirical
  approach

abstract:
  An overview of the results of new exhaustive computations of gaps between
primes in arithmetic progressions is presented. We also give new numerical
results for exceptionally large least primes in arithmetic progressions.


title: Genuine vs. na\"ive symmetric monoidal G-categories

abstract:
  We prove that through the eyes of equivariant weak equivalences the genuine
symmetric monoidal $G$-categories of arXiv:1809.03017 are equivalent to just
ordinary symmetric monoidal categories with $G$-action. Along the way, we give
an operadic model of global infinite loop spaces and provide an equivalence
between the equivariant category theory of genuine symmetric monoidal
$G$-categories and the $G$-parsummable categories studied in arXiv:1912.08872,
arXiv:2009.07004.


title:
Analytic expressions for some Mellin transforms with their application
  to prime counting function and interpolation formulas for the zeta function

abstract:
  The aim of our present work here is to present few results in the theory of
Mellin transforms using the method that S. Ramanujan used in proving his Master
Theorem. Further applications of our results for some number-theoretic
functions such as the prime counting function and the zeta function are
established.


title: On geometry of p-adic polynomials

abstract:
  An analogue of the Gauss-Lucas theorem for polynomials over the algebraic
closure $\mathbb C_p$ of the field of $p$-adic numbers is considered.


title: Postcertificates for Revocation Transparency

abstract:
  The modern Internet is highly dependent on trust communicated via
certificates. However, in some cases, certificates become untrusted, and it is
necessary to revoke them. In practice, the problem of secure revocation is
still open. Furthermore, the existing procedures do not leave a transparent and
immutable revocation history. We propose and evaluate a new revocation
transparency protocol that introduces postcertificates and utilizes the
existing Certificate Transparency (CT) logs. The protocol is practical, has a
low deployment cost, provides an immutable history of revocations, enables
delegation, and helps to detect revocation-related misbehavior by certificate
authorities (CAs). With this protocol, a holder of a postcertificate can bypass
the issuing CA and autonomously initiate the revocation process via submission
of the postcertificate to a CT log. The CAs are required to monitor CT logs and
proceed with the revocation upon detection of a postcertificate. Revocation
status delivery is performed independently and with an arbitrary status
protocol. Postcertificates can increase the accountability of the CAs and
empower the certificate owners by giving them additional control over the
status of the certificates. We evaluate the protocol, measure log and monitor
performance, and conclude that it is possible to provide revocation
transparency using existing CT logs.


title:
A Comprehensive Review of Computer Vision in Sports: Open Issues, Future
  Trends and Research Directions

abstract:
  Recent developments in video analysis of sports and computer vision
techniques have achieved significant improvements to enable a variety of
critical operations. To provide enhanced information, such as detailed complex
analysis in sports like soccer, basketball, cricket, badminton, etc., studies
have focused mainly on computer vision techniques employed to carry out
different tasks. This paper presents a comprehensive review of sports video
analysis for various applications high-level analysis such as detection and
classification of players, tracking player or ball in sports and predicting the
trajectories of player or ball, recognizing the teams strategies, classifying
various events in sports. The paper further discusses published works in a
variety of application-specific tasks related to sports and the present
researchers views regarding them. Since there is a wide research scope in
sports for deploying computer vision techniques in various sports, some of the
publicly available datasets related to a particular sport have been provided.
This work reviews a detailed discussion on some of the artificial
intelligence(AI)applications in sports vision, GPU-based work stations, and
embedded platforms. Finally, this review identifies the research directions,
probable challenges, and future trends in the area of visual recognition in
sports.


title:
On the equivalence between rotation and gravity: "Gravitational" and
  "cosmological" redshifts in the laboratory

abstract:
  The M\"ossbauer rotor effect recently gained a renewed interest due to the
discovery and explanation of an additional effect of clock synchronization
which has been missed for about 50 years, i.e. starting from a famous book of
Pauli, till some recent experimental analyses. The theoretical explanation of
such an additional effect is due to some recent papers in both the general
relativistic and the special relativistic frameworks. In the first case
(general relativistic framework) the key point of the approach is the
Einstein's equivalence principle (EEP), which, in the words of the same
Einstein, enables "the point of view to interpret the rotating system K' as at
rest, and the centrifugal field as a gravitational field". In this paper, we
analyse both the history of the M\"ossbauer rotor effect and its interpretation
from the point of view of Einstein's general theory of relativity (GTR) by
adding some new insight. In particular, it will be shown that, if on one hand
the "traditional" effect of redshift has a strong analogy with the
gravitational redshift, on the other hand the additional effect of clock
synchronization has an intriguing analogy with the cosmological redshift.
Finally, we show that a recent claim in the literature that the second effect
of clock synchronization does not exist is not correct.


title: An attack on Zarankiewicz's problem through SAT solving

abstract:
  The Zarankiewicz function gives, for a chosen matrix and minor size, the
maximum number of ones in a binary matrix not containing an all-one minor.
Tables of this function for small arguments have been compiled, but errors are
known in them. We both correct the errors and extend these tables in the case
of square minors by expressing the problem of finding the value at a specific
point as a series of Boolean satisfiability problems, exploiting permutation
symmetries for a significant reduction in the work needed. When the ambient
matrix is also square we also give all non-isomorphic examples of matrices
attaining the maximum, up to the aforementioned symmetries; it is found that
most maximal matrices have some form of symmetry.


title:
Nuclei instance segmentation and classification in histopathology images
  with StarDist

abstract:
  Instance segmentation and classification of nuclei is an important task in
computational pathology. We show that StarDist, a deep learning based nuclei
segmentation method originally developed for fluorescence microscopy, can be
extended and successfully applied to histopathology images. This is
substantiated by conducting experiments on the Lizard dataset, and through
entering the Colon Nuclei Identification and Counting (CoNIC) challenge 2022.
At the end of the preliminary test phase of CoNIC, our approach ranked first on
the leaderboard for the segmentation and classification task.


title:
A photonic chip-based machine learning approach for the prediction of
  molecular properties

abstract:
  Machine learning methods have revolutionized the discovery process of new
molecules and materials. However, the intensive training process of neural
networks for molecules with ever increasing complexity has resulted in
exponential growth in computation cost, leading to long simulation time and
high energy consumption. Photonic chip technology offers an alternative
platform for implementing neural network with faster data processing and lower
energy usage compared to digital computers. Here, we demonstrate the capability
of photonic neural networks in predicting the quantum mechanical properties of
molecules. Additionally, we show that multiple properties can be learned
simultaneously in a photonic chip via a multi-task regression learning
algorithm, which we believe is the first of its kind, as most previous works
focus on implementing a network for the task of classification. Photonics
technology are also naturally capable of implementing complex-valued neural
networks at no additional hardware cost and we show that such neural networks
outperform conventional real-valued networks for molecular property prediction.
Our work opens the avenue for harnessing photonic technology for large-scale
machine learning applications in molecular sciences such as drug discovery and
materials design.


title: Semi-parametric Makeup Transfer via Semantic-aware Correspondence

abstract:
  The large discrepancy between the source non-makeup image and the reference
makeup image is one of the key challenges in makeup transfer. Conventional
approaches for makeup transfer either learn disentangled representation or
perform pixel-wise correspondence in a parametric way between two images. We
argue that non-parametric techniques have a high potential for addressing the
pose, expression, and occlusion discrepancies. To this end, this paper proposes
a \textbf{S}emi-\textbf{p}arametric \textbf{M}akeup \textbf{T}ransfer (SpMT)
method, which combines the reciprocal strengths of non-parametric and
parametric mechanisms. The non-parametric component is a novel
\textbf{S}emantic-\textbf{a}ware \textbf{C}orrespondence (SaC) module that
explicitly reconstructs content representation with makeup representation under
the strong constraint of component semantics. The reconstructed representation
is desired to preserve the spatial and identity information of the source image
while "wearing" the makeup of the reference image. The output image is
synthesized via a parametric decoder that draws on the reconstructed
representation. Extensive experiments demonstrate the superiority of our method
in terms of visual quality, robustness, and flexibility. Code and pre-trained
model are available at \url{https://github.com/AnonymScholar/SpMT.


title:
Quasars physical properties study based on the medium-band photometric
  survey

abstract:
  The study is about the quasars cosmological evolution. We used the
medium-band photometric survey at the 1-m Schmidt telescope of the Byurakan
Astrophysical Observatory. The HS47-22 field with an area of 2.38 square
degrees has been selected. We have classified objects and composed a sample of
quasars using broadband photometric data and morphological classification from
the DECaLS survey, infrared photometry from the WISE survey, spectroscopy from
the SDSS survey, ROSAT X-ray data, FIRST radio data and stellar parallax data
from the GAIA survey. We have compiled a sample of 682 quasars, determined
their photometric redshifts from the medium-band photometric data, and
calculated the absolute stellar magnitudes. The space density of quasars was
calculated for different luminosity ranges at different redshifts using the
$\lambda$-CDM model with $\Omega_m = 0.3$ and $\Omega_\lambda = 0.7$. In this
paper, we present the comparison of our results with other works.


title:
Integrating Statistical Uncertainty into Neural Network-Based Speech
  Enhancement

abstract:
  Speech enhancement in the time-frequency domain is often performed by
estimating a multiplicative mask to extract clean speech. However, most neural
network-based methods perform point estimation, i.e., their output consists of
a single mask. In this paper, we study the benefits of modeling uncertainty in
neural network-based speech enhancement. For this, our neural network is
trained to map a noisy spectrogram to the Wiener filter and its associated
variance, which quantifies uncertainty, based on the maximum a posteriori (MAP)
inference of spectral coefficients. By estimating the distribution instead of
the point estimate, one can model the uncertainty associated with each
estimate. We further propose to use the estimated Wiener filter and its
uncertainty to build an approximate MAP (A-MAP) estimator of spectral
magnitudes, which in turn is combined with the MAP inference of spectral
coefficients to form a hybrid loss function to jointly reinforce the
estimation. Experimental results on different datasets show that the proposed
method can not only capture the uncertainty associated with the estimated
filters, but also yield a higher enhancement performance over comparable models
that do not take uncertainty into account.


title:
On the Determination of the Solar Rotation Elements i, {\Omega} and
  Period using Sunspot Observations by Ru{\dj}er Bo\v{s}kovi\'c in 1777

abstract:
  In September 1777, Ru{\dj}er Bo\v{s}kovi\'c observed sunspots for six days.
Based on these measurements, he used his own methods to calculate the elements
of the solar rotation, the longitude of the node, the inclination of the solar
equator and the period. He published a description of the methods, the method
of observation and detailed instructions for calculations in the second chapter
of the fifth part of the Opera in 1785. In this paper, Bo\v{s}kovi\'c original
calculations and repeated calculations by his procedure are published. By
analysing the input quantities, procedures, and results, the input quantities
of the error, and the calculation results are discussed. The reproduction of
Bo\v{s}kovi\'c calculations is successfully reproduced and we obtained very
similar results. The conclusion proposes a relationship of Bo\v{s}kovi\'c
research with modern astronomy.


title:
A general class of linear unconditionally energy stable schemes for the
  gradient flows

abstract:
  This paper studies a class of linear unconditionally energy stable schemes
for the gradient flows. Such schemes are built on the SAV technique and the
general linear time discretization (GLTD) as well as the linearization based on
the extrapolation for the nonlinear term, and may be arbitrarily high-order
accurate and very general, containing many existing SAV schemes and new SAV
schemes. It is shown that the semi-discrete-in-time schemes are unconditionally
energy stable when the GLTD is algebraically stable, and are convergent with
the order of $\min\{\hat{q},\nu\}$ under the diagonal stability and some
suitable regularity and accurate starting values, where $\hat{q}$ is the
generalized stage order of the GLTD and $\nu$ denotes the number of the
extrapolation points in time. The energy stability results can be easily
extended to the fully discrete schemes, for example, if the Fourier spectral
method is employed in space when the periodic boundary conditions are
specified. Some numerical experiments on the Allen-Cahn, Cahn-Hilliard, and
phase field crystal models are conducted to validate those theories as well as
the effectiveness, the energy stability and the accuracy of our schemes.


title: Freeform Body Motion Generation from Speech

abstract:
  People naturally conduct spontaneous body motions to enhance their speeches
while giving talks. Body motion generation from speech is inherently difficult
due to the non-deterministic mapping from speech to body motions. Most existing
works map speech to motion in a deterministic way by conditioning on certain
styles, leading to sub-optimal results. Motivated by studies in linguistics, we
decompose the co-speech motion into two complementary parts: pose modes and
rhythmic dynamics. Accordingly, we introduce a novel freeform motion generation
model (FreeMo) by equipping a two-stream architecture, i.e., a pose mode branch
for primary posture generation, and a rhythmic motion branch for rhythmic
dynamics synthesis. On one hand, diverse pose modes are generated by
conditional sampling in a latent space, guided by speech semantics. On the
other hand, rhythmic dynamics are synced with the speech prosody. Extensive
experiments demonstrate the superior performance against several baselines, in
terms of motion diversity, quality and syncing with speech. Code and
pre-trained models will be publicly available through
https://github.com/TheTempAccount/Co-Speech-Motion-Generation.


title:
Broadening and redward asymmetry of H$\alpha$ line profiles observed by
  LAMOST during a stellar flare on an M-type star

abstract:
  Stellar flares are characterized by sudden enhancement of electromagnetic
radiation in stellar atmospheres. So far much of our understanding of stellar
flares comes from photometric observations, from which plasma motions in flare
regions could not be detected. From the spectroscopic data of LAMOST DR7, we
have found one stellar flare that is characterized by an impulsive increase
followed by a gradual decrease in the H$\alpha$ line intensity on an M4-type
star, and the total energy radiated through H${\alpha}$ is estimated to be on
the order of $10^{33}$ erg. The H$\alpha$ line appears to have a Voigt profile
during the flare, which is likely caused by Stark pressure broadening due to
the dramatic increase of electron density and/or opacity broadening due to the
occurrence of strong non-thermal heating. Obvious enhancement has been
identified at the red wing of the H$\alpha$ line profile after the impulsive
increase of the H$\alpha$ line intensity. The red wing enhancement corresponds
to plasma moving away from the Earth at a velocity of 100$-$200 km s$^{-1}$.
According to the current knowledge of solar flares, this red wing enhancement
may originate from: (1) flare-driven coronal rain, (2) chromospheric
condensation, or (3) a filament/prominence eruption that either with a
non-radial backward propagation or with strong magnetic suppression. The total
mass of the moving plasma is estimated to be on the order of $10^{15}$ kg.


title:
The THOR+HELIOS general circulation model: multi-wavelength radiative
  transfer with accurate scattering by clouds/hazes

abstract:
  General circulation models (GCMs) provide context for interpreting
multi-wavelength, multi-phase data of the atmospheres of tidally locked
exoplanets. In the current study, the non-hydrostatic THOR GCM is coupled with
the HELIOS radiative transfer solver for the first time, supported by an
equilibrium chemistry solver (FastChem), opacity calculator (HELIOS-K) and Mie
scattering code (LX-MIE). To accurately treat the scattering of radiation by
medium-sized to large aerosols/condensates, improved two-stream radiative
transfer is implemented within a GCM for the first time. Multiple scattering is
implemented using a Thomas algorithm formulation of the two-stream flux
solutions, which decreases the computational time by about 2 orders of
magnitude compared to the iterative method used in past versions of HELIOS. As
a case study, we present four GCMs of the hot Jupiter WASP-43b, where we
compare the temperature, velocity, entropy, and streamfunction, as well as the
synthetic spectra and phase curves, of runs using regular versus improved
two-stream radiative transfer and isothermal versus non-isothermal layers.
While the global climate is qualitatively robust, the synthetic spectra and
phase curves are sensitive to these details. A THOR+HELIOS WASP-43b GCM
(horizontal resolution of about 4 degrees on the sphere and with 40 radial
points) with multi-wavelength radiative transfer (30 k-table bins) running for
3000 Earth days (864,000 time steps) takes about 19-26 days to complete
depending on the type of GPU.


title:
Viterbo's conjecture for Lagrangian products in $\mathbb{R}^4$ and
  symplectomorphisms to the Euclidean ball

abstract:
  We analyze Viterbo's conjecture for the EHZ-capacity for convex Lagrangian
products in $\mathbb{R}^4$. We use the generalized Minkowski billiard
characterization of the EHZ-capacity in order to reprove that Viterbo's
conjecture holds for the Lagrangian products (any triangle/parallelogram in
$\mathbb{R}^2$)$\times$(any convex body in $\mathbb{R}^2$) and extend this fact
to the Lagrangian products (any trapezoid in $\mathbb{R}^2$)$\times$(any convex
body in $\mathbb{R}^2$). Based on this analysis, we classify equality cases of
Viterbo's conjecture and prove that most of them can be proven to be
symplectomorphic to Euclidean balls. As a by-product, we prove sharp Minkowski
billiard / worm problem inequalities. Finally, we discuss the Lagrangian
products (any convex quadrilateral in $\mathbb{R}^2$)$\times$(any convex body
in $\mathbb{R}^2$) for which we show that the truth of Viterbo's conjecture
would follow from the positive solution of a challenging Euclidean packing
problem.


title:
Evaluating Local Model-Agnostic Explanations of Learning to Rank Models
  with Decision Paths

abstract:
  Local explanations of learning-to-rank (LTR) models are thought to extract
the most important features that contribute to the ranking predicted by the LTR
model for a single data point. Evaluating the accuracy of such explanations is
challenging since the ground truth feature importance scores are not available
for most modern LTR models. In this work, we propose a systematic evaluation
technique for explanations of LTR models. Instead of using black-box models,
such as neural networks, we propose to focus on tree-based LTR models, from
which we can extract the ground truth feature importance scores using decision
paths. Once extracted, we can directly compare the ground truth feature
importance scores to the feature importance scores generated with explanation
techniques. We compare two recently proposed explanation techniques for LTR
models when using decision trees and gradient boosting models on the MQ2008
dataset. We show that the explanation accuracy in these techniques can largely
vary depending on the explained model and even which data point is explained.


title: On pairs of one prime, four prime cubes and powers of 2

abstract:
  In this paper, we consider the simultaneous representation of pairs of
sufficiently large integers. We prove that every pair of large positive odd
integers can be represented in the form of a pair of one prime, four cubes of
primes and 231 powers of 2.


title: The infrared behavior of tame two-field cosmological models

abstract:
  We study the first order infared behavior of tame hyperbolizable two-field
cosmological models, defined as those classical two-field models whose scalar
manifold is a connected, oriented and topologically finite hyperbolizable
Riemann surface $(\Sigma,\mathcal{G})$ and whose scalar potential $\Phi$ admits
a positive and Morse extension to the end compactification of $\Sigma$. We
achieve this by determining the universal forms of the asymptotic gradient flow
of the classical effective potential $V$ with respect to the uniformizing
metric $G$ near all interior critical points and ends of $\Sigma$, finding that
some of the latter act like fictitious but exotic stationary points of the
gradient flow. We also compare these results with numerical studies of
cosmological orbits. For critical cusp ends, we find that cosmological curves
have transient quasiperiodic behavior but are eventually attracted or repelled
by the cusp along principal geodesic orbits determined by the extended
effective potential. This behavior is approximated in the infrared by that of
gradient flow curves near the cusp.


title: Intrinsically-Motivated Reinforcement Learning: A Brief Introduction

abstract:
  Reinforcement learning (RL) is one of the three basic paradigms of machine
learning. It has demonstrated impressive performance in many complex tasks like
Go and StarCraft, which is increasingly involved in smart manufacturing and
autonomous driving. However, RL consistently suffers from the
exploration-exploitation dilemma. In this paper, we investigated the problem of
improving exploration in RL and introduced the intrinsically-motivated RL. In
sharp contrast to the classic exploration strategies, intrinsically-motivated
RL utilizes the intrinsic learning motivation to provide sustainable
exploration incentives. We carefully classified the existing intrinsic reward
methods and analyzed their practical drawbacks. Moreover, we proposed a new
intrinsic reward method via R\'enyi state entropy maximization, which overcomes
the drawbacks of the preceding methods and provides powerful exploration
incentives. Finally, extensive simulation demonstrated that the proposed module
achieve superior performance with higher efficiency and robustness.


title:
Stability analysis of non-thermal fixed points in longitudinally
  expanding kinetic theory

abstract:
  We use the Hamiltonian formulation of kinetic theory to perform a stability
analysis of non-thermal fixed points in a non-Abelian plasma. We construct a
perturbative expansion of the Fokker-Planck collision kernel in an adiabatic
approximation and show that the (next-to-)leading order solutions reproduce the
known non-thermal fixed point scaling exponents. Working at next-to-leading
order, we derive the stability equations for scaling exponents and find the
relaxation rate to the non-thermal fixed point. This approach provides the
basis for an understanding of the prescaling phenomena observed in QCD kinetic
theory and non-relativistic Bose gas systems.


title:
Mixed Reality Depth Contour Occlusion Using Binocular Similarity
  Matching and Three-dimensional Contour Optimisation

abstract:
  Mixed reality applications often require virtual objects that are partly
occluded by real objects. However, previous research and commercial products
have limitations in terms of performance and efficiency. To address these
challenges, we propose a novel depth contour occlusion (DCO) algorithm. The
proposed method is based on the sensitivity of contour occlusion and a
binocular stereoscopic vision device. In this method, a depth contour map is
combined with a sparse depth map obtained from a two-stage adaptive filter area
stereo matching algorithm and the depth contour information of the objects
extracted by a digital image stabilisation optical flow method. We also propose
a quadratic optimisation model with three constraints to generate an accurate
dense map of the depth contour for high-quality real-virtual occlusion. The
whole process is accelerated by GPU. To evaluate the effectiveness of the
algorithm, we demonstrate a time con-sumption statistical analysis for each
stage of the DCO algorithm execution. To verify the relia-bility of the
real-virtual occlusion effect, we conduct an experimental analysis on
single-sided, enclosed, and complex occlusions; subsequently, we compare it
with the occlusion method without quadratic optimisation. With our GPU
implementation for real-time DCO, the evaluation indicates that applying the
presented DCO algorithm can enhance the real-time performance and the visual
quality of real-virtual occlusion.


title: Composite nature of $Z_b$ states from data analysis

abstract:
  We use a near-threshold parameterization with explicit inclusion of the
Castillejo-Dalitz-Dyson poles, which is more general than the effective range
expansion, to study the bottomonium-like states $Z_b(10610)$ and $Z_b(10650)$.
In terms of the partial-wave amplitude, we fit the event number distribution of
$B^{(*)}\bar B^*$ system to the experimental data for these resonances from
Belle Collaboration. The data could be described very well in our method, which
supports the molecular interpretation. Then the relevant physical quantities
are obtained, including the $B^{(*)}\bar{B}^*$ scattering length ($a$),
effective range ($r$), and residue squared ($\gamma_s^2$) of the pole in the
complex plane. In particular, we find the compositeness can range from about
0.4 up to 1 for the $B\bar B^*$ ($B^*\bar B^*$) component in the resonance
$Z_b(10610)$ ($Z_b(10650)$).


title:
The method of solving initial structure by Seidel aberration theory for
  extreme ultraviolet lithography objective

abstract:
  In this paper, a method for solving the initial structure of an off-axis
multi-mirror system applied to extreme ultraviolet (EUV) lithography using a
paraxial ray-tracing algorithm based on Seidel aberration theory is proposed.
By tracing the characteristic rays in the reflection system, the height and
paraxial angle on each surface can be obtained, then through the relationship
between the Seidel aberration coefficient and these parameters, the initial
structure with good aberration performance can be solved. We can obtain
different initial structures by adding different initial condition constraints.
In this paper, we have solved two different initial structures by assigning
different optical powers as different initial structures, and on this basis, we
have optimized two off-axis six-mirror systems with numerical aperture (NA) of
0.25. Their wavefront aberration RMS value is about 0.04 wavelength, and the
absolute distortion is less than 1.2nm, with good imaging quality. We believe
that this method can greatly improve the design efficiency and optimization
effect of complex multi-mirror systems.


title: Low Energy Event Reconstruction in IceCube DeepCore

abstract:
  The reconstruction of event-level information, such as the direction or
energy of a neutrino interacting in IceCube DeepCore, is a crucial ingredient
to many physics analyses. Algorithms to extract this high level information
from the detector's raw data have been successfully developed and used for high
energy events. In this work, we address unique challenges associated with the
reconstruction of lower energy events in the range of a few to hundreds of GeV
and present two separate, state-of-the-art algorithms. One algorithm focuses on
the fast directional reconstruction of events based on unscattered light. The
second algorithm is a likelihood-based multipurpose reconstruction offering
superior resolutions, at the expense of larger computational cost.

categories: hep-ex astro-ph.IM physics.data-an physics.ins-det


title:
Hitchhiker: A Quadrotor Aggressively Perching on a Moving Inclined
  Surface Using Compliant Suction Cup Gripper

abstract:
  Perching on surfaces of moving objects, like vehicles, could extend the
flight times and range of quadrotors. For surfaces attachment, suction cups are
usually adopted due to their durability and large adhesion force. To seal on
surfaces, suction cups are required to be aligned with surfaces and match to
the frictions on end faces induced by relative tangential velocity. However,
when the object surface is moving and inclined such that an aggressive maneuver
is required, the attitude and relative velocity errors of quadrotors would
become significant, which poses challenges to perch. To address the problem, we
proposed a real-time trajectory planning algorithm to alleviate the velocity
errors of quadrotors relative to moving surfaces. Multimodal search in dynamic
time-domain is developed in the algorithm and thus the time-optimal aggressive
trajectories can be efficiently generated. To further adapt to the residual
attitude and relative velocity errors, we design a compliant gripper using
self-sealing cups. Multiple cups in different directions are integrated into a
wheel-like mechanism to increase the tolerance to attitude errors. The wheel
mechanism in the gripper also eliminates the requirement of matching the
attitude and tangential velocity and thus increases the adaptability to
tangential velocity. Extensive tests are conducted, including comparison
experiments, to perch on static and moving surfaces at various inclinations.
Results demonstrate that our proposed system enables a quadrotor to reliably
perch on static and moving inclined (up to 1.18$m/s$ and 90$^\circ$) surfaces
with a success rate of 70\% or higher. The trajectory planner is valid and
efficient. Compared to conventional suction cup grippers in moving surface
perching, our gripper has larger adaptability to attitude errors and tangential
velocities, and the success rate increases by 45\%.


title: Global linear stability analysis of a flame anchored to a cylinder

abstract:
  The linear stability of a laminar premixed flame, anchored on a square
cylinder at Re = 500 and confined inside a channel, is investigated via global
eigenmode analysis, based on the reacting flow equations with a one-step
chemistry scheme. While the flow is unstable in the absence of reaction, flame
ignition leads to a stabilisation, as long as the wall temperature of the
cylinder is sufficiently low. When the mean flow fields, obtained from
nonlinear timestepping, are taken as the basic state for the linear analysis,
the leading eigenvalue accurately matches the oscillation frequency observed in
the simulation. The "wavemaker" region that controls the global flow dynamics
is localised in the shear layer at the rear of the recirculation zone, where
the stability or instability results from the balance of shear-derived
production and downstream convection of momentum perturbations. It is concluded
that instability in this configuration arises from hydrodynamic effects, not
fundamentally different from the non-reacting flow case, although the critical
parameters and the oscillation frequency are strongly modified by the presence
of the flame. This influence is attributed to the significant changes in the
base flow, principally due to thermal expansion.


title:
Batalin-Vilkovisky structure on Hochschild cohomology of zigzag algebra
  of type $\widetilde{\mathbf{A}}_{1}$

abstract:
  In this paper, we study the Batalin-Vilkovisky structure on the Hochschild
cohomology of quantum zigzag algebras $A_{q}$ of type
$\widetilde{\mathbf{A}}_{1}$. We first calculate the dimensions of Hochschild
homology groups and Hochschild cohomology groups of $A_{q}$. Based on these
computations, we determine the Hochschild cohomology ring of $A_{q}$, and give
the Batalin-Vilkovisky operator and the Gerstenhaber bracket on Hochschild
cohomology ring of $A_{q}$ explicitly.


title: The nilpotent genus of finitely generated residually nilpotent groups

abstract:
  If $G$ and $H$ are finitely generated residually nilpotent groups, then $G$
and $H$ are in the same nilpotent genus if they have the same lower central
quotients (up to isomorphism). A stronger condition is that $H$ is para-$G$ if
there exists a monomorphism of $G$ into $H$ which induces isomorphisms between
the corresponding quotients of their lower central series. We first consider
residually nilpotent groups and find sufficient conditions on the monomorphism
so that $H$ is para-$G.$ We then prove that for certain polycyclic groups, if
$H$ is para-$G$, then $G$ and $H$ have the same Hirsch length. We also prove
that the pro-nilpotent completions of these polycyclic groups are locally
polycyclic.


title:
Structural features of microvascular networks trigger blood-flow
  oscillations

abstract:
  We analyse mathematical models in order to understand how microstructural
features of vascular networks may affect blood-flow dynamics, and to identify
particular characteristics that promote the onset of self-sustained
oscillations. By focusing on a simple three-node motif, we predict that network
"redundancy", in the form of a redundant vessel connecting two main
flow-branches, together with differences in haemodynamic resistance in the
branches, can promote the emergence of oscillatory dynamics. We use existing
mathematical descriptions for blood rheology and haematocrit splitting at
vessel branch-points to construct our flow model; we combine numerical
simulations and stability analysis to study the dynamics of the three-node
network and its relation to the system's multiple steady-state solutions.
While, for the case of equal inlet-pressure conditions, a "trivial" equilibrium
solution with no flow in the redundant vessel always exists, we find that it is
not stable when other, stable, steady-state attractors exist. In turn, these
"nontrivial" steady-state solutions may undergo a Hopf bifurcation into an
oscillatory state. We use the branch diameter ratio, together with the inlet
haematocrit rate, to construct a two-parameter stability diagram that
delineates regimes in which such oscillatory dynamics exist. We show that flow
oscillations in this network geometry are only possible when the branch
diameters are sufficiently different to allow for a sufficiently large flow in
the redundant vessel, which acts as the driving force of the oscillations.
These microstructural properties, which were found to promote oscillatory
dynamics, could be used to explore sources of flow instability in biological
microvascular networks.


title:
A Next-Generation Liquid Xenon Observatory for Dark Matter and Neutrino
  Physics

abstract:
  The nature of dark matter and properties of neutrinos are among the most
pressing issues in contemporary particle physics. The dual-phase xenon
time-projection chamber is the leading technology to cover the available
parameter space for Weakly Interacting Massive Particles (WIMPs), while
featuring extensive sensitivity to many alternative dark matter candidates.
These detectors can also study neutrinos through neutrinoless double-beta decay
and through a variety of astrophysical sources. A next-generation xenon-based
detector will therefore be a true multi-purpose observatory to significantly
advance particle physics, nuclear physics, astrophysics, solar physics, and
cosmology. This review article presents the science cases for such a detector.

categories: physics.ins-det astro-ph.CO hep-ex nucl-ex


title: Poisson structures on sets of Maurer-Cartan elements

abstract:
  Given a differential graded Lie algebra (dgla) L satisfying certain
conditions, we construct Poisson structures on the gauge orbits of its set of
Maurer-Cartan (MC) elements, termed Maurer-Cartan-Poisson (MCP) structures.
They associate a compatible Batalin-Vilkovisky algebra to each MC element of L.
An MCP structure is shown to exist for a number of dglas associated to
commutative Frobenius algebras, deformations of Poisson and symplectic
structures, as well as the Chevally-Eilenberg complex. MCP structures yield a
notion of hamiltonian flow of MC elements, and also define Lie algebroids on
gauge orbits, whose isotropy algebras give invariants of MC elements. As an
example, this gives a finite-dimensional two-step nilpotent graded Lie algebra
associated to any closed symplectic manifold.


title:
Quantum Levenberg--Marquardt Algorithm for optimization in Bundle
  Adjustment

abstract:
  In this paper we develop a quantum optimization algorithm and use it to solve
the bundle adjustment problem with a simulated quantum computer. Bundle
adjustment is the process of optimizing camera poses and sensor properties to
best reconstruct the three-dimensional structure and viewing parameters. This
problem is often solved using some implementation of the Levenberg--Marquardt
algorithm. In this case we implement a quantum algorithm for solving the linear
system of normal equations that calculates the optimization step in
Levenberg--Marquardt. This procedure is the current bottleneck in the
algorithmic complexity of bundle adjustment. The proposed quantum algorithm
dramatically reduces the complexity of this operation with respect to the
number of points.
  We investigate 9 configurations of a toy-model for bundle adjustment, limited
to 10 points and 2 cameras. This optimization problem is solved both by using
the sparse Levenberg-Marquardt algorithm and our quantum implementation. The
resulting solutions are presented, showing an improved rate of convergence,
together with an analysis of the theoretical speed up and the probability of
running the algorithm successfully on a current quantum computer.
  The presented quantum algorithm is a seminal implementation of using quantum
computing algorithms in order to solve complex optimization problems in
computer vision, in particular bundle adjustment, which offers several avenues
of further investigations.


title:
Structural phase transitions and magnetic superexchange in MIAgIIF3
  perovskites at high pressure

abstract:
  Pressure induced phase transitions of MIAgIIF3 perovskites where M = K, Rb,
Cs, have been predicted theoretically for the first time for pressures up to
100 GPa. The sequence of phase transitions for M = K and Rb consists of an
orthorhombic to monoclinic and back to orthorhombic transition, associated with
progressive bending of infinite chains of corner sharing [AgF6]4 minus
octahedra and their mutual approaching via secondary Ag...F contacts. In stark
contrast, only a single phase transition i.e. tetragonal to triclinic, is
predicted for CsAgF3, associated with substantial deformation of the Jahn
Teller-distorted first coordination sphere of AgII and association of the
infinite [AgF6]4 minus chains into a polymeric sublattice. The phase
transitions markedly decrease the coupling strength of intra-chain
antiferromagnetic superexchange in MAgF3 hosts lattices.


title:
Multifunctional acoustic holography based on compact acoustic
  geometric-phase meta-array

abstract:
  Optical geometric-phase metasurface provides a robust and efficient means for
light control by simply manipulating the spatial orientations of the in-plane
anisotropic meta-atoms, where polarization conversion plays a vital role.
However, the concept of acoustic geometric-phase modulation for acoustic field
control remains unexplored because airborne acoustic waves lack a similar
optical polarization conversion process. In this work, a new type of acoustic
meta-atom with deep subwavelength feature size is theoretically investigated
and further applied to acoustic field engineering based on the so-called
acoustic geometric phase. Herein, tunable acoustic geometric-phase modulation
of designated order is obtained via the near-field coupled orbital angular
momentum transfer process, and the topological charge-multiplexed acoustic
geometric phase endows our meta-arrays with multiple functionalities. Our work
extends the capacity of acoustic meta-arrays in high-quality acoustic field
reconstruction and offers new possibilities in multifunctional acoustic
meta-holograms.


title: Constructive Post-Quantum Reductions

abstract:
  Is it possible to convert classical cryptographic reductions into
post-quantum ones? It is customary to argue that while this is problematic in
the interactive setting, non-interactive reductions do carry over. However,
when considering quantum auxiliary input, this conversion results in a
non-constructive post-quantum reduction that requires duplicating the quantum
auxiliary input, which is in general inefficient or even impossible. This
violates the win-win premise of provable cryptography: an attack against a
cryptographic primitive should lead to an algorithmic advantage.
  We initiate the study of constructive quantum reductions and present positive
and negative results for converting large classes of classical reductions to
the post-quantum setting in a constructive manner. We show that any
non-interactive non-adaptive reduction from assumptions with a polynomial
solution space (such as decision assumptions) can be made post-quantum
constructive. In contrast, assumptions with super-polynomial solution space
(such as general search assumptions) cannot be generally converted.
  Along the way, we make several additional contributions:
  1. We put forth a framework for reductions (or general interaction) with
stateful solvers for a computational problem, that may change their internal
state between consecutive calls. We show that such solvers can still be
utilized. This framework and our results are meaningful even in the classical
setting.
  2. A consequence of our negative result is that quantum auxiliary input that
is useful against a problem with a super-polynomial solution space cannot be
generically ``restored'' post-measurement. This shows that the novel rewinding
technique of Chiesa et al. (FOCS 2021) is tight in the sense that it cannot be
extended beyond a polynomial measurement space.


title: Characterization of tropical planar curves up to genus six

abstract:
  We provide new forbidden criterion for realizability of smooth tropical plane
curves. This in turn provides us a complete classification of smooth tropical
plane curves up to genus six.


title: Coloring closed Noetherian graphs

abstract:
  If G is a closed Noetherian graph on a sigma-compact Polish space without an
infinite clique, it is consistent with the choiceless set theory ZF+DC that G
is countably chromatic and there is no Vitali set.


title: Adaptive Discounting of Implicit Language Models in RNN-Transducers

abstract:
  RNN-Transducer (RNN-T) models have become synonymous with streaming
end-to-end ASR systems. While they perform competitively on a number of
evaluation categories, rare words pose a serious challenge to RNN-T models. One
main reason for the degradation in performance on rare words is that the
language model (LM) internal to RNN-Ts can become overconfident and lead to
hallucinated predictions that are acoustically inconsistent with the underlying
speech. To address this issue, we propose a lightweight adaptive LM discounting
technique AdaptLMD, that can be used with any RNN-T architecture without
requiring any external resources or additional parameters. AdaptLMD uses a
two-pronged approach: 1) Randomly mask the prediction network output to
encourage the RNN-T to not be overly reliant on it's outputs. 2) Dynamically
choose when to discount the implicit LM (ILM) based on rarity of recently
predicted tokens and divergence between ILM and implicit acoustic model (IAM)
scores. Comparing AdaptLMD to a competitive RNN-T baseline, we obtain up to 4%
and 14% relative reductions in overall WER and rare word PER, respectively, on
a conversational, code-mixed Hindi-English ASR task.


title:
Adaptive Semi-Supervised Inference for Optimal Treatment Decisions with
  Electronic Medical Record Data

abstract:
  A treatment regime is a rule that assigns a treatment to patients based on
their covariate information. Recently, estimation of the optimal treatment
regime that yields the greatest overall expected clinical outcome of interest
has attracted a lot of attention. In this work, we consider estimation of the
optimal treatment regime with electronic medical record data under a
semi-supervised setting. Here, data consist of two parts: a set of `labeled'
patients for whom we have the covariate, treatment and outcome information, and
a much larger set of `unlabeled' patients for whom we only have the covariate
information. We proposes an imputation-based semi-supervised method, utilizing
`unlabeled' individuals to obtain a more efficient estimator of the optimal
treatment regime. The asymptotic properties of the proposed estimators and
their associated inference procedure are provided. Simulation studies are
conducted to assess the empirical performance of the proposed method and to
compare with a fully supervised method using only the labeled data. An
application to an electronic medical record data set on the treatment of
hypotensive episodes during intensive care unit (ICU) stays is also given for
further illustration.


title:
Two-band model and RVB-type states: application to Kondo lattices,
  pyrochlores and Mn-based systems

abstract:
  An exotic fractionalized Fermi-liquid FL$^*$ theory of metallic systems,
which combines resonant-valence-bond (RVB) state and the band of current
carriers, is treated. An application of this theory to spin-liquid,
antiferromagnetic and nearly antiferromagnetic systems is proposed with the use
of various bosonic and fermionic representations, a comparison with
perturbation theory in the $s-d(f)$ exchange model being performed. The
topological aspects including formation of the small Fermi surface are treated.
In the case of narrow bands (strong correlations), the ground state is
considered as a direct product of RVB and dopon or Weng's fermion states.
Examples of Kondo lattices, doped pyrochlores, and metallic $\beta$-Mn,
YMn$_2$, Y$_{1-x}$Sc$_x$Mn$_2$ systems are discussed, analogies with
copper-oxide systems being treated.


title: Non-Transversal Multilinear Duality and Joints

abstract:
  We develop a framework for a duality theory for general multilinear operators
which extends that for transversal multilinear operators which has been
established in arXiv:1809.02449. We apply it to the setting of joints and
multijoints, and obtain a "factorisation" theorem which provides an analogue in
the discrete setting of results of Bourgain and Guth (arXiv:0811.2251 and
arXiv:1012.3760) from the Euclidean setting.