title: Fast Sparse Classification for Generalized Linear and Additive Models

abstract:
  We present fast classification techniques for sparse generalized linear and
additive models. These techniques can handle thousands of features and
thousands of observations in minutes, even in the presence of many highly
correlated features. For fast sparse logistic regression, our computational
speed-up over other best-subset search techniques owes to linear and quadratic
surrogate cuts for the logistic loss that allow us to efficiently screen
features for elimination, as well as use of a priority queue that favors a more
uniform exploration of features. As an alternative to the logistic loss, we
propose the exponential loss, which permits an analytical solution to the line
search at each iteration. Our algorithms are generally 2 to 5 times faster than
previous approaches. They produce interpretable models that have accuracy
comparable to black box models on challenging datasets.


title: Cosmological constraints on heavy sterile neutrinos

abstract:
  We consider heavy sterile neutrinos $\nu_s$, with mass in the range 10 MeV
$\lesssim m_s \lesssim m_{\pi} \sim 135$ MeV, thermally produced in the early
universe and freezing out after the QCD phase transition. The existence of
these neutrinos may alter the value of the effective number of neutrino species
$N_{\rm eff}$, measured by the cosmic microwave background (CMB), and the
${}^4$He production during the BBN. We provide a detailed account of the
solution of the relevant Boltzmann equations and we identify the parameter
space constrained by current Planck satellite data and forecast the parameter
space probed by future Stage-4 ground-based CMB (CMB-S4) observations.


title: Status of the Fermilab Muon $g-2$ Experiment

abstract:
  The muon anomalous magnetic moment, $a_\mu = (g-2)/2$, is a low-energy
observable which can be both measured and computed with very high precision,
making it an excellent test of the Standard Model (SM) and a sensitive probe of
new physics. Recent efforts improved the precision of both the theoretical
prediction and the experimental measurement. On the theory side, the Muon $g-2$
Theory Initiative, an international team of more than 130 physicists, reached
in 2020 a consensus on the SM prediction for $a_\mu$. On the experimental side,
the E989 Muon $g-2$ Collaboration at Fermilab (FNAL) published in April 2021 a
new measurement of $a_\mu$ from the Run-1 dataset (2018) with 0.46 ppm
precision, corroborating the previous Brookhaven National Laboratory (BNL)
measurement and increasing the discrepancy with the SM value to 4.2 standard
deviations. In this paper, I will discuss the experimental setup and report on
the current status of the experiment.


title: The free field realisation of the BVW string

abstract:
  The symmetric orbifold of $\mathbb{T}^4$ was recently shown to be exactly
dual to string theory on ${\rm AdS}_3\times {\rm S}^3 \times \mathbb{T}^4$ with
minimal ($k=1$) NS-NS flux. The worldsheet theory is best formulated in terms
of the hybrid formalism of Berkovits, Vafa & Witten (BVW), in terms of which
the ${\rm AdS}_3\times {\rm S}^3$ factor is described by a
$\mathfrak{psu}(1,1|2)_k$ WZW model. At level $k=1$, $\mathfrak{psu}(1,1|2)_1$
has a free field realisation that is obtained from that of
$\mathfrak{u}(1,1|2)_1$ upon setting a $\mathfrak{u}(1)$ field, often called
$Z$, to zero. We show that the free field version of the ${\cal N}=2$
generators of BVW (whose cohomology defines the physical states) does not give
rise to an ${\cal N}=2$ algebra, but is rather contaminated by terms
proportional to the $Z$-field. We also show how to overcome this problem by
introducing additional ghost fields that implement the quotienting by $Z$.


title: Differential privacy for symmetric log-concave mechanisms

abstract:
  Adding random noise to database query results is an important tool for
achieving privacy. A challenge is to minimize this noise while still meeting
privacy requirements. Recently, a sufficient and necessary condition for
$(\epsilon, \delta)$-differential privacy for Gaussian noise was published.
This condition allows the computation of the minimum privacy-preserving scale
for this distribution. We extend this work and provide a sufficient and
necessary condition for $(\epsilon, \delta)$-differential privacy for all
symmetric and log-concave noise densities. Our results allow fine-grained
tailoring of the noise distribution to the dimensionality of the query result.
We demonstrate that this can yield significantly lower mean squared errors than
those incurred by the currently used Laplace and Gaussian mechanisms for the
same $\epsilon$ and $\delta$.


title:
Modave Lectures on Horizon-Size Microstructure, Fuzzballs and
  Observations

abstract:
  These lecture notes discuss various aspects of the fuzzball paradigm,
microstate geometries, and their role in gravitational phenomenology. We
briefly introduce the information paradox and discuss how the fuzzball paradigm
aims to resolve it. Then, some important families of fuzzball solutions in
supergravity, called microstate geometries, are explored: multi-centered
bubbling geometries and superstrata. Finally, we will review some very recent
developments of the phenomenology of fuzzballs and delineate the exciting
opportunities as well as the limitations of studying fuzzballs as alternatives
to black holes in current and future observations.


title:
Dimension approximation for diffeomorphisms preserving hyperbolic SRB
  measures

abstract:
  For a C^{1+\alpha} diffeomorphism f preserving a hyperbolic ergodic SRB
measure \mu, Katok's remarkable results assert that \mu can be approximated by
a sequence of hyperbolic sets \{\Lambda_n\}_{n\geq1}. In this paper, we prove
the Hausdorff dimension for \Lambda_n on the unstable manifold tends to the
dimension of the unstable manifold. Furthermore, if the stable direction is one
dimension, then the Hausdorff dimension of \mu can be approximated by the
Hausdorff dimension of \Lambda_n. To establish these results, we utilize the
u-Gibbs property of the conditional measure of the equilibrium measure of
-\psi^{s}(\cdot,f^n) and the properties of the uniformly hyperbolic dynamical
systems.


title:
Strain assisted magnetization switching in ordered nanomagnets of
  CoFe2O4/SrRuO3/PMNPT hetrostructures

abstract:
  We have explored the electric field controlled magnetization in the nanodot
CoFe2O4/SrRuO3/PMN-PT heterostructures. Ordered ferromagnetic CFO nanodots
(~300 nm lateral dimension) are developed on the PMN-PT substrate
(ferroelectric as well as piezoelectric) using a nanostencil-mask pattering
method during pulsed laser deposition. The nanostructures reveal electric field
induced magnetization reversal in the single domain CFO nanodots through
transfer of piezostrains from the piezoelectric PMN-PT substrate to the CFO.
Further, electric field modulated spin structure of CFO nanomagnets is analysed
by using X-ray magnetic circular dichroism (XMCD). The XMCD analysis reveals
cations (Fe3+/Co2+) redistribution on the octahedral and tetrahedral site in
the electric field poled CoFe2O4 nanodots, establishing the strain induced
magneto-electric coupling effects. The CoFe2O4/SrRuO3/PMN-PT nanodots structure
demonstrate multilevel switching of ME coupling coefficient ({\alpha}) by
applying selective positive and negative electric fields in a non-volatile
manner. The retention of two stable states of {\alpha} is illustrated for ~106
seconds, which can be employed to store the digital data in non-volatile memory
devices. Thus the voltage controlled magnetization in the nanodot structures
leads a path towards the invention of energy efficient high-density memory
devices.


title:
Model-Driven Generation of Microservice Interfaces: From LEMMA Domain
  Models to Jolie APIs

abstract:
  We formally define and implement a translation from domain models in the
LEMMA modelling framework to microservice APIs in the Jolie programming
language. Our tool enables a software development process whereby microservice
architectures can first be designed with the leading method of Domain-Driven
Design, and then corresponding data types and service interfaces (APIs) in
Jolie are automatically generated. Developers can extend and use these APIs as
guides in order to produce compliant implementations. Our tool thus contributes
to enhancing productivity and improving the design adherence of microservices.


title: On Cayley graphs over generalized dicyclic groups

abstract:
  Recently, several works by a number of authors have studied integrality,
distance integrality, and distance powers of Cayley graphs over some finite
groups, such as dicyclic groups and (generalized) dihedral groups. Our aim is
to generalize and/or to give analogues of these results for generalized
dicyclic groups. For example, we give a necessary and sufficient condition for
a Cayley graph over a generalized dicyclic group to be integral (i.e., all
eigenvalues of its adjacency matrix are in $\mathbb{Z}$). We also obtain
sufficient conditions for the integrality of all distance powers of a Cayley
graph over a given generalized dicyclic group. These results extend works on
dicyclic groups by Cheng--Feng--Huang and Cheng--Feng--Liu--Lu--Stevanovic,
respectively.


title: Measurement of the Interactions and Stability of MTDC Systems

abstract:
  The small-signal stability of multi-terminal HVDC systems, which is related
to the dynamic interactions among different VSCs through the coupling of DC and
AC networks, has become one of the important issues for the safety and stable
operation of modern power systems. On the other hand, the robust stability
theory with {\nu}-gap metric is an effective tool for the stability analysis
and synthesis of uncertain feedback systems. In this paper, we combine it with
the self-/en-stabilizing coefficients method to measure the relative stability
and analyze the stability influence of different paths of interactions in an
MTDC system. The stability index is defined to represent the stability margin
with respect to different paths of interactions in an MTDC system. A method for
calculating the range of uncertain parameters preserving the stability is
presented based on the stability criterion. The influence of control parameters
on robust stability through interactions among VSCs can be analyzed
quantitatively. Extensive examples are given to demonstrate the application and
the effectiveness of the proposed method.


title:
A Facile Strategy for the Growth of High-Quality Tungsten Disulfide
  Crystals Mediated by Oxygen-Deficient Oxide Precursors

abstract:
  Chemical vapor deposition (CVD) has been established as a versatile route for
the large-scale synthesis of transition metal dichalcogenides, such as tungsten
disulfide (WS2). Yet, the role of the precursor composition on the efficiency
of the CVD process remains largely unknown and yet to be explored. Here, we
employ Pulsed Laser Deposition (PLD) in a two-stage process to tune the oxygen
content in tungsten oxide (WO3-x) precursors and demonstrate that the presence
of oxygen vacancies in the precursor films leads to a more facile conversion
from WO3-x to WS2. Using a joint study based on ab initio density functional
theory (DFT) calculations and experiments, we unravel that the oxygen vacancies
in WO3-x can serve as niches through which sulfur atoms enters the lattice and
may facilitate an efficient growth of WS2 crystals. By solely modulating the
precursor stoichiometry, the photoluminescence emission of WS2 can be greatly
enhanced, while the size of WS2 domains increases significantly. Atomic
resolution scanning transmission electron microscopy (STEM) reveals that
tungsten vacancies are the dominant intrinsic defects in mono- and bilayers
WS2. Moreover, our data reveal that grain boundaries in bilayer WS2 emerge upon
the coalescence of AA' and AB-oriented crystals, while turbostatic moir\'e
patterns originate upon formation of distinct grain boundaries between the
bottom and bottom layers. The atomic resolution images show local strain
buildup in bilayer WS2 due to competing effects of complex grain boundaries.
Our study provides a means to tune the precursor composition in order to
control the lateral growth of TMDs, while revealing insights into the different
pathways for the formation of grain boundaries in bilayer WS2.


title: Mixed-Block Neural Architecture Search for Medical Image Segmentation

abstract:
  Deep Neural Networks (DNNs) have the potential for making various clinical
procedures more time-efficient by automating medical image segmentation. Due to
their strong, in some cases human-level, performance, they have become the
standard approach in this field. The design of the best possible medical image
segmentation DNNs, however, is task-specific. Neural Architecture Search (NAS),
i.e., the automation of neural network design, has been shown to have the
capability to outperform manually designed networks for various tasks. However,
the existing NAS methods for medical image segmentation have explored a quite
limited range of types of DNN architectures that can be discovered. In this
work, we propose a novel NAS search space for medical image segmentation
networks. This search space combines the strength of a generalised
encoder-decoder structure, well known from U-Net, with network blocks that have
proven to have a strong performance in image classification tasks. The search
is performed by looking for the best topology of multiple cells simultaneously
with the configuration of each cell within, allowing for interactions between
topology and cell-level attributes. From experiments on two publicly available
datasets, we find that the networks discovered by our proposed NAS method have
better performance than well-known handcrafted segmentation networks, and
outperform networks found with other NAS approaches that perform only topology
search, and topology-level search followed by cell-level search.


title:
A Differential Attention Fusion Model Based on Transformer for Time
  Series Forecasting

abstract:
  Time series forecasting is widely used in the fields of equipment life cycle
forecasting, weather forecasting, traffic flow forecasting, and other fields.
Recently, some scholars have tried to apply Transformer to time series
forecasting because of its powerful parallel training ability. However, the
existing Transformer methods do not pay enough attention to the small time
segments that play a decisive role in prediction, making it insensitive to
small changes that affect the trend of time series, and it is difficult to
effectively learn continuous time-dependent features. To solve this problem, we
propose a differential attention fusion model based on Transformer, which
designs the differential layer, neighbor attention, sliding fusion mechanism,
and residual layer on the basis of classical Transformer architecture.
Specifically, the differences of adjacent time points are extracted and focused
by difference and neighbor attention. The sliding fusion mechanism fuses
various features of each time point so that the data can participate in
encoding and decoding without losing important information. The residual layer
including convolution and LSTM further learns the dependence between time
points and enables our model to carry out deeper training. A large number of
experiments on three datasets show that the prediction results produced by our
method are favorably comparable to the state-of-the-art.


title: Chern characters for curved dg-algebras

abstract:
  We construct a quasi-inverse of the cochain map on the negative cyclic
complexes of the second kind induced from the quasi-Yoneda embedding on a
curved dg algebra. This gives an explicit formula for the Chern character of a
perfect module.


title: Exceptional sets for average conformal dynamical systems

abstract:
  Let $f: M \to M$ be a $C^{1+\alpha}$ map/diffeomorphism of a compact
Riemannian manifold $M$ and $\mu$ be an expanding/hyperbolic ergodic
$f$-invariant Borel probability measure on $M$. Assume $f$ is average conformal
expanding/hyperbolic on the support set $W$ of $\mu$ and $W$ is locally
maximal. For any subset $A\subset W$ with small entropy or dimension, we
investigate the topological entropy and Hausdorff dimensions of the
$A$-exceptional set and the limit $A$-exceptional set.


title: Stokes drift and its discontents

abstract:
  The Stokes velocity $\mathbf{u}^\mathrm{S}$, defined approximately by Stokes
(1847, Trans. Camb. Philos. Soc., 8, 441-455), and exactly via the Generalized
Lagrangian Mean, is divergent even in an incompressible fluid. We show that the
Stokes velocity can be naturally decomposed into a solenoidal component,
$\mathbf{u}^\mathrm{S}_\mathrm{sol}$, and a remainder that is small for waves
with slowly varying amplitudes. We further show that
$\mathbf{u}^\mathrm{S}_\mathrm{sol}$ arises as the sole Stokes velocity when
the Lagrangian mean flow is suitably redefined to ensure its exact
incompressibility. The construction is an application of Soward & Roberts's glm
theory (2010, J. Fluid Mech., 661, 45-72) which we specialise to surface
gravity waves and implement effectively using a Lie series expansion. We
further show that the corresponding Lagrangian-mean momentum equation is
formally identical to the Craik-Leibovich equation with
$\mathbf{u}^\mathrm{S}_\mathrm{sol}$ replacing $\mathbf{u}^\mathrm{S}$, and we
discuss the form of the Stokes pumping associated with both
$\mathbf{u}^\mathrm{S}$ and $\mathbf{u}^\mathrm{S}_\mathrm{sol}$.


title:
Non-Energetic Formation of Ethanol via CCH Reaction with Interstellar
  H2O Ices. A Computational Chemistry Study

abstract:
  Ethanol (CH$_3$CH$_2$OH) is a relatively common molecule, often found in star
forming regions. Recent studies suggest that it could be a parent molecule of
several so-called interstellar complex organic molecules (iCOMs). Yet, the
formation route of this species remains debated. In the present work, we study
the formation of ethanol through the reaction of CCH with one H$_2$O molecule
belonging to the ice, as a test case to investigate the viability of chemical
reactions based on a "radical + ice component" scheme as an alternative
mechanism for the synthesis of iCOMs, beyond the usual radical-radical
coupling. This has been done by means of DFT calculations adopting two clusters
of 18 and 33 water molecules as ice models. Results indicate that
CH$_3$CH$_2$OH can potentially be formed by this proposed reaction mechanism.
The reaction of CCH with H$_2$O on the water ice clusters can be barrierless
(thanks to the help of boundary icy water molecules acting as proton transfer
assistants) leading to the formation of vinyl alcohol precursors (H$_2$CCOH and
CHCHOH). Subsequent hydrogenation of vinyl alcohol yielding ethanol is the only
step presenting a low activation energy barrier. We finally discuss the
astrophysical implications of these findings.


title: Superhydrophobic surfaces reduce form drag in separated flows

abstract:
  The drag force acting on a body moving in a fluid has two components,
friction drag due to fluid viscosity and form drag due to flow separation
behind the body. When present, form drag is the most significant between the
two. In many applications, streamlining effectively prevents flow separation,
fast vehicle aerodynamics being the archetypal example. As shown here, when the
operating fluid is water, e.g. for large container ships or underwater
vehicles, a promising technique is to decorate the walls of the body with
superhydrophobic surfaces. These surfaces entrap gas bubbles in their
asperities, avoiding the direct contact of the liquid with the wall.
Superhydrophobic surfaces have been largely studied for reducing friction drag.
Rather unexpectedly, they are shown here to be also extremely effective in
reducing/preventing flow separation, thereby reducing the form drag. Their
conceptual effectiveness is demonstrated by exploiting numerical simulations of
turbulent flows over a bluff obstacle fixed over a wall. The approach envisaged
here could pave the way to new and powerful techniques for drag reduction on
large bluff bodies moving in the water.


title: Brezis--Kato Type Regularity Results for Higher Order Elliptic Operators

abstract:
  We prove a Brezis--Kato regularity type results for solutions of the higher
order nonlinear elliptic equation \[
  L u = g(x,u)\qquad\text{in }\Omega \] with an elliptic operator $L$ of $2m$
order with variable coefficients and a Carath\'eodory function $g:\Omega\times
\mathbb{C}\to\mathbb{C}$, where $\Omega\subset\mathbb{R}^N$ is an open set with
$N > 2m$.


title:
ScrawlD: A Dataset of Real World Ethereum Smart Contracts Labelled with
  Vulnerabilities

abstract:
  Smart contracts on Ethereum handle millions of U.S. Dollars and other
financial assets. In the past, attackers have exploited smart contracts to
steal these assets. The Ethereum community has developed plenty of tools to
detect vulnerable smart contracts. However, there is no standardized data set
to evaluate these existing tools, or any new tools developed. There is a need
for an unbiased standard benchmark of real-world Ethereum smart contracts. We
have created ScrawlD: an annotated data set of real-world smart contracts taken
from the Ethereum network. The data set is labelled using 5 tools that detect
various vulnerabilities in smart contracts, using majority voting.


title: The tropical analogues of reproducing kernels

abstract:
  Hilbertian kernel methods and their positive semidefinite kernels have known
an extensive use in various fields of applied mathematics and machine learning,
owing to their several equivalent characterizations. We here unveil an analogy
with concepts from tropical geometry, proving that tropical positive
semidefinite kernels are also endowed with equivalent viewpoints, stemming from
Fenchel-Moreau conjugations. We give a tropical analogue of Aronszajn theorem,
showing that these kernels correspond to a feature map, define monotonous
operators, and generate max-plus function spaces endowed with a reproducing
property. They furthermore include all the Hilbertian kernels classically
studied as well as Monge arrays. However, two relevant notions of tropical
reproducing kernels must be distinguished, based either on linear or
sesquilinear interpretations. The sesquilinear interpretation is the most
expressive one, since reproducing spaces then encompass classical max-plus
spaces, such as those of (semi)convex functions. In contrast, in the linear
interpretation, the reproducing kernels are characterized by a restrictive
condition, von Neumann regularity.


title: Morphisms between Grassmannians

abstract:
  Denote by $\mathbb G(k,n)$ the Grassmannian of linear subspaces of dimension
$k$ in $\mathbb P^n$. We show that if $n>m$ then every morphism $\varphi:
\mathbb G(k,n) \to \mathbb G(l,m)$ is constant.


title: The Modular Isomorphism Problem: a survey

abstract:
  The Modular Isomorphism Problem asks if an isomorphism of group algebras of
two finite p-groups G and H over a field of characteristic p, implies an
isomorhism of the groups G and H. We survey the history of the problem, explain
strategies which were developed to study it and present the recent negative
solution of the problem. The problem is also compared to other isomorphism
problems for group rings and various question remaining open are included.


title:
Excited-State Quantum Phase Transitions in the Anharmonic
  Lipkin-Meshkov-Glick Model I: Static Aspects

abstract:
  The basic Lipkin-Meshkov-Glick model displays a second order ground state
quantum phase transition and an excited state quantum phase transition (ESQPT).
The inclusion of an anharmonic term in the Hamiltonian implies a second ESQPT
of a different nature. We characterize this ESQPT using the mean field limit of
the model. The new ESQPT, associated with the changes in the boundary of the
finite Hilbert space of the system, can be properly described using the order
parameter of the ground state quantum phase transition, the energy gap between
adjacent states, the participation ratio, and the quantum fidelity
susceptibility.


title: Canonical Polyadic Decomposition via the generalized Schur decomposition

abstract:
  The canonical polyadic decomposition (CPD) is a fundamental tensor
decomposition which expresses a tensor as a sum of rank one tensors. In stark
contrast to the matrix case, with light assumptions, the CPD of a low rank
tensor is (essentially) unique. The essential uniqueness of CPD makes this
decomposition a powerful tool in many applications as it allows for extraction
of component information from a signal of interest.
  One popular algorithm for algebraic computation of a CPD is the generalized
eigenvalue decomposition (GEVD) which selects a matrix subpencil of a tensor,
then computes the generalized eigenvectors of the pencil. In this article, we
present a simplification of GEVD which improves the accuracy of the algorithm.
Surprisingly, the generalized eigenvector computation in GEVD is in fact
unnecessary and can be replaced by a QZ decomposition which factors a pair of
matrices as a product of unitary and upper triangular matrices. Computing a QZ
decomposition is a standard first step when computing generalized eigenvectors,
so our algorithm can been seen as a direct simplification of GEVD.


title: Privacy issues on biometric systems

abstract:
  In the XXIth century there is a strong interest on privacy issues. Technology
permits obtaining personal information without individuals consent, computers
make it feasible to share and process this information, and this can bring
about damaging implications. In some sense, biometric information is personal
information, so it is important to be conscious about what is true and what is
false when some people claim that biometrics is an attempt to individuals
privacy. In this paper, key points related to this matter are dealt with.


title: Price formation in financial markets: a game-theoretic perspective

abstract:
  We propose two novel frameworks to study the price formation of an asset
negotiated in an order book. Specifically, we develop a game-theoretic model in
many-person games and mean-field games, considering costs stemming from limited
liquidity. We derive analytical formulas for the formed price in terms of the
realized order flow. We also identify appropriate conditions that ensure the
convergence of the price we find in the finite population game to that of its
mean-field counterpart. We numerically assess our results with a large
experiment using high-frequency data from ten stocks listed in the NASDAQ, a
stock listed in B3 in Brazil, and a cryptocurrency listed in Binance.


title:
Impact of hadronic interactions and conservation laws on cumulants of
  conserved charges in a dynamical model

abstract:
  Understanding the phase diagram of QCD by measuring fluctuations of conserved
charges in heavy-ion collision is one of the main goals of the beam energy scan
program at RHIC. Within this work, we calculate the role of hadronic
interactions and momentum cuts on cumulants of conserved charges up to fourth
order in a system in equilibrium within a hadronic transport approach (SMASH).
In our model the net baryon, net charge and net strangeness is perfectly
conserved on an event-by-event basis and the cumulants are calculated as a
function of subvolume sizes and compared to analytic expectations. We find a
modification of the kurtosis due to charge annihilation processes in systems
with simplified degrees of freedom. Furthermore the result of the full SMASH
hadron gas for the net baryon and net proton number fluctuations is presented
for systems with zero and finite values of baryon chemical potential.
Additionally we find that due to dynamical correlations the cumulants of the
net baryon number cannot easily be recovered from the net protons. Finally the
influence of deuteron cluster formation on the net proton and net baryon
fluctuations in a simplified system is shown. This analysis is important to
better understand the relation between measurements of fluctuations in
heavy-ion collisions and theoretical calculation which are often performed in a
grand canonical ensemble.


title:
The Astrometric Performance Test of 80-cm Telescope at Yaoan Station and
  Precise CCD Positions of Apophis

abstract:
  The 80-cm azimuthal telescope is newly mounted at Yaoan Station, Purple
Mountain Observatory in 2018. The astrometric performance of the telescope is
tested in the following three aspects. (a) The geometric distortion of its CCD
attached. It is stable in both a single epoch and multi epochs. Eight
distortion solutions are derived over about one year. The maximum values range
from 0.75 to 0.79 pixel and the median values range from 0.14 to 0.16 pixel.
(b) The limit magnitude of stars. About 20.5 magnitude (Gaia-G) stars can be
detected with Johnson-V filter exposured in 300 seconds. The astrometric error
of about 20.5 magnitude stars is estimated at 0.14 arcsec using the fitted
sigmoidal function. (c) The astrometric accuracy and the precision of stacked
fast-moving faint object. 24 stacked frames of the potentially hazardous
asteroid (PHA) (99942) Apophis are derived on April 14 and 15, 2021 (fainter
than 18 mag) based on the ephemeris shifts. During data reduction, the newest
Gaia EDR3 Catalog and Jet Propulsion Laboratory Horizons ephemeris are
referenced as theoretical positions of stars and Apophis, respectively. Our
results show that the mean (O-C)s (observed minus computed) of Apophis are
-0.018 and 0.020 arcsec in right ascention and declination, and the dispersions
are estimated at 0.094 and 0.085 arcsec, respectively, which show the
consistency of the stacked results by Astrometrica.


title: Testing report of a fingerprint-based door-opening system

abstract:
  This paper describes the operational evaluation of a door-opening system
based on a low-cost inkless fingerprint sensor. This system has been developed
and installed for access control to one of our laboratories. Experimental
results reveal that the system is working fine and no special cleaning
requirements neither components replacement is needed. It can support more than
50 users, and an average of 74,5 access attempts per day in a 14-hour
5-day-per-week working. Emphasize is also given on some important facts to be
taken into consideration when comparing and evaluating different products from
different vendors.


title:
Sub-optimality of Gauss--Hermite quadrature and optimality of
  trapezoidal rule for functions with finite smoothness

abstract:
  A sub-optimality of Gauss--Hermite quadrature and an optimality of the
trapezoidal rule are proved in the weighted Sobolev spaces of square integrable
functions of order $\alpha$, where the optimality is in the sense of worst-case
error. For Gauss--Hermite quadrature, we obtain the matching lower and upper
bounds, which turns out to be merely of the order $n^{-\alpha/2}$ with $n$
function evaluations, although the optimal rate for the best possible linear
quadrature is known to be $n^{-\alpha}$. Our proof on the lower bound exploits
the structure of the Gauss--Hermite nodes; the bound is independent of the
quadrature weights, and changing the Gauss--Hermite weights cannot improve the
rate $n^{-\alpha/2}$. In contrast, we show that a suitably truncated
trapezoidal rule achieves the optimal rate up to a logarithmic factor.


title:
Effect of adhesive interaction on strain stiffening and dissipation in
  granular gels undergoing yielding

abstract:
  Stress induced yielding/fluidization in disordered solids, characterized by
irreversibility and enhanced dissipation, is important for a wide range of
industrial and geological processes. Although, such phenomena in thermal
systems have been extensively studied, they remain poorly understood for
granular solids. Here, using oscillatory shear rheology and in-situ optical
imaging, we study energy dissipation in a dense granular suspension of adhesive
particles that forms yield stress solids far below the isotropic jamming point
obtained in the limit of hard-sphere repulsion. We find interesting non-linear
flow regimes including intra-cycle strain stiffening and plasticity that
strongly depend on the applied strain amplitude ($\gamma_0$) and particle
volume fraction ($\phi$). We demonstrate that such nonlinearity over the entire
parameter range can be effectively captured by a dimensionless variable termed
as the normalized energy dissipation ($E_N$). Furthermore, in-situ optical
imaging reveals irreversible particle rearrangements correlating with the
spatiotemporal fluctuations in local velocity, the nature of which strikingly
varies across the yielding transition. By directly measuring the critical
jamming packing fractions using particle settling experiments, we propose a
detailed phase diagram that unravels the role of inter-particle interactions in
controlling the flow properties of the system for a wide range of $\gamma_0$
and $\phi$ values.


title:
Recycling of the first atmospheres of embedded planets: Dependence on
  core mass and optical depth

abstract:
  Recent observations found close-in planets with significant atmospheres of
hydrogen and helium in great abundance. These are the so-called super-Earths
and mini-Neptunes. Their atmospheric composition suggests that they formed
early during the gas-rich phase of the circumstellar disk and were able to
avoid becoming hot Jupiters. As a possible explanation, recent studies explored
the recycling hypothesis and showed that atmosphere-disk recycling is able to
fully compensate for radiative cooling and thereby halt Kelvin-Helmholtz
contraction to prevent runaway gas accretion.
  To understand the parameters that determine the efficiency of atmospheric
recycling, we extend our earlier studies by exploring the effects of the core
mass, the effect of circumstellar gas on sub-Keplerian orbits (headwind), and
the optical depth of the surrounding gas on the recycling timescale.
Additionally, we analyze their effects on the size and mass of the forming
atmosphere.
  For the explored parameter space, all simulations eventually reach an
equilibrium where heating due to hydrodynamic recycling fully compensates
radiative cooling. In this equilibrium, the atmosphere-to-core mass ratio stays
well below $10 \, \%$, preventing the atmosphere from becoming self-gravitating
and entering runaway gas accretion. Higher core masses cause the atmosphere to
become turbulent, which further enhances recycling.
  Even for our highest core mass of $10 \, M_\mathrm{Earth}$, atmosphere-disk
recycling is efficient enough to fully compensate for radiative cooling and
prevent the atmosphere from becoming self-gravitating. Hence, in-situ formation
of hot Jupiters is very unlikely, and migration of gas giants is a key process
required to explain their existence. Our findings imply that atmosphere-disk
recycling is the most natural explanation for the prevalence of close-in
super-Earths and mini-Neptunes.


title:
ProFormer: Learning Data-efficient Representations of Body Movement with
  Prototype-based Feature Augmentation and Visual Transformers

abstract:
  Automatically understanding human behaviour allows household robots to
identify the most critical needs and plan how to assist the human according to
the current situation. However, the majority of such methods are developed
under the assumption that a large amount of labelled training examples is
available for all concepts-of-interest. Robots, on the other hand, operate in
constantly changing unstructured environments, and need to adapt to novel
action categories from very few samples. Methods for data-efficient recognition
from body poses increasingly leverage skeleton sequences structured as
image-like arrays and then used as input to convolutional neural networks. We
look at this paradigm from the perspective of transformer networks, for the
first time exploring visual transformers as data-efficient encoders of skeleton
movement. In our pipeline, body pose sequences cast as image-like
representations are converted into patch embeddings and then passed to a visual
transformer backbone optimized with deep metric learning. Inspired by recent
success of feature enhancement methods in semi-supervised learning, we further
introduce ProFormer -- an improved training strategy which uses soft-attention
applied on iteratively estimated action category prototypes used to augment the
embeddings and compute an auxiliary consistency loss. Extensive experiments
consistently demonstrate the effectiveness of our approach for one-shot
recognition from body poses, achieving state-of-the-art results on multiple
datasets and surpassing the best published approach on the challenging NTU-120
one-shot benchmark by 1.84%. Our code will be made publicly available at
https://github.com/KPeng9510/ProFormer.


title: Towards Speaker Age Estimation with Label Distribution Learning

abstract:
  Existing methods for speaker age estimation usually treat it as a multi-class
classification or a regression problem. However, precise age identification
remains a challenge due to label ambiguity, \emph{i.e.}, utterances from
adjacent age of the same person are often indistinguishable. To address this,
we utilize the ambiguous information among the age labels, convert each age
label into a discrete label distribution and leverage the label distribution
learning (LDL) method to fit the data. For each audio data sample, our method
produces a age distribution of its speaker, and on top of the distribution we
also perform two other tasks: age prediction and age uncertainty minimization.
Therefore, our method naturally combines the age classification and regression
approaches, which enhances the robustness of our method. We conduct experiments
on the public NIST SRE08-10 dataset and a real-world dataset, which exhibit
that our method outperforms baseline methods by a relatively large margin,
yielding a 10\% reduction in terms of mean absolute error (MAE) on a real-world
dataset.


title: Multi-view Intent Disentangle Graph Networks for Bundle Recommendation

abstract:
  Bundle recommendation aims to recommend the user a bundle of items as a
whole. Nevertheless, they usually neglect the diversity of the user's intents
on adopting items and fail to disentangle the user's intents in
representations. In the real scenario of bundle recommendation, a user's intent
may be naturally distributed in the different bundles of that user (Global
view), while a bundle may contain multiple intents of a user (Local view). Each
view has its advantages for intent disentangling: 1) From the global view, more
items are involved to present each intent, which can demonstrate the user's
preference under each intent more clearly. 2) From the local view, it can
reveal the association among items under each intent since items within the
same bundle are highly correlated to each other. To this end, we propose a
novel model named Multi-view Intent Disentangle Graph Networks (MIDGN), which
is capable of precisely and comprehensively capturing the diversity of the
user's intent and items' associations at the finer granularity. Specifically,
MIDGN disentangles the user's intents from two different perspectives,
respectively: 1) In the global level, MIDGN disentangles the user's intent
coupled with inter-bundle items; 2) In the Local level, MIDGN disentangles the
user's intent coupled with items within each bundle.
  Meanwhile, we compare the user's intents disentangled from different views
under the contrast learning framework to improve the learned intents. Extensive
experiments conducted on two benchmark datasets demonstrate that MIDGN
outperforms the state-of-the-art methods by over 10.7% and 26.8%, respectively.


title: Open5x: Accessible 5-axis 3D printing and conformal slicing

abstract:
  The common layer-by-layer deposition of regular, 3-axis 3D printing
simplifies both the fabrication process and the 3D printer's mechanical design.
However, the resulting 3D printed objects have some unfavourable
characteristics including visible layers, uneven structural strength and
support material. To overcome these, researchers have employed robotic arms and
multi-axis CNCs to deposit materials in conformal layers. Conformal deposition
improves the quality of the 3D printed parts through support-less printing and
curved layer deposition. However, such multi-axis 3D printing is inaccessible
to many individuals due to high costs and technical complexities. Furthermore,
the limited GUI support for conformal slicers creates an additional barrier for
users. To open multi-axis 3D printing up to more makers and researchers, we
present a cheap and accessible way to upgrade a regular 3D printer to 5 axes.
We have also developed a GUI-based conformal slicer, integrated within a
popular CAD package. Together, these deliver an accessible workflow for
designing, simulating and creating conformally-printed 3D models.


title: Quasi 1D electronic transport in a 2D magnetic semiconductor

abstract:
  We investigate electronic transport through exfoliated multilayers of CrSBr,
a 2D semiconductor that is attracting attention because of its magnetic
properties. We find an extremely pronounced anisotropy that manifests itself in
qualitative and quantitative differences of all quantities measured along the
in-plane \textit{a} and \textit{b} crystallographic directions. In particular,
we observe a qualitatively different dependence of the conductivities
$\sigma_a$ and $\sigma_b$ on temperature and gate voltage, accompanied by
orders of magnitude differences in their values ($\sigma_b$/$\sigma_a \approx
3\cdot10^2-10^5$ at low temperature and large negative gate voltage). We also
find a different behavior of the longitudinal magnetoresistance in the two
directions, and the complete absence of the Hall effect in transverse
resistance measurements. These observations appear not to be compatible with a
description in terms of conventional band transport of a 2D doped
semiconductor. The observed phenomenology -- together with unambiguous
signatures of a 1D van Hove singularity that we detect in energy resolved
photocurrent measurements -- indicate that electronic transport through CrSBr
multilayers is better interpreted by considering the system as formed by weakly
and incoherently coupled 1D wires, than by conventional 2D band transport. We
conclude that CrSBr is the first 2D semiconductor to show distinctly quasi 1D
electronic transport properties.


title:
Linear Programming Fictitious Play algorithm for Mean Field Games with
  optimal stopping and absorption

abstract:
  We develop the fictitious play algorithm in the context of the linear
programming approach for mean field games of optimal stopping and mean field
games with regular control and absorption. This algorithm allows to approximate
the mean field game population dynamics without computing the value function by
solving linear programming problems associated with the distributions of the
players still in the game and their stopping times/controls. We show the
convergence of the algorithm using the topology of convergence in measure in
the space of subprobability measures, which is needed to deal with the lack of
continuity of the flows of measures. Numerical examples are provided to
illustrate the convergence of the algorithm.


title:
A Novel Self-Supervised Cross-Modal Image Retrieval Method In Remote
  Sensing

abstract:
  Due to the availability of multi-modal remote sensing (RS) image archives,
one of the most important research topics is the development of cross-modal RS
image retrieval (CM-RSIR) methods that search semantically similar images
across different modalities. Existing CM-RSIR methods require annotated
training images (which is time-consuming, costly and not feasible to gather in
large-scale applications) and do not concurrently address intra- and
inter-modal similarity preservation and inter-modal discrepancy elimination. In
this paper, we introduce a novel self-supervised cross-modal image retrieval
method that aims to: i) model mutual-information between different modalities
in a self-supervised manner; ii) retain the distributions of modal-specific
feature spaces similar; and iii) define most similar images within each
modality without requiring any annotated training images. To this end, we
propose a novel objective including three loss functions that simultaneously:
i) maximize mutual information of different modalities for inter-modal
similarity preservation; ii) minimize the angular distance of multi-modal image
tuples for the elimination of inter-modal discrepancies; and iii) increase
cosine similarity of most similar images within each modality for the
characterization of intra-modal similarities. Experimental results show the
effectiveness of the proposed method compared to state-of-the-art methods. The
code of the proposed method is publicly available at
https://git.tu-berlin.de/rsim/SS-CM-RSIR.


title:
Understanding the Sunyaev-Zeldovich decrement versus halo mass using the
  SIMBA and TNG Simulations

abstract:
  The relation between the integrated Sunyaev-Zeldovich (SZ) $y$-decrement
versus halo mass ($Y$-$M$) can potentially constrain galaxy formation models,
if theoretical and observational systematics can be properly assessed. We
investigate the $Y-M$ relation in the SIMBA and IllustrisTNG-100 cosmological
hydrodynamic simulations, quantifying the effects of feedback, line-of-sight
projection, and beam convolution. We find that SIMBA's AGN jet feedback
generates strong deviations from self-similar expectations for the $Y-M$
relation, especially at $M_{500}<10^{13}M_{\odot}$. In SIMBA this is driven by
suppressed in-halo $y$ contributions owing to lowered halo baryon fractions.
IllustrisTNG results more closely resemble SIMBA without jets. Projection of
line-of-sight structures weakens these model differences slightly, but they
remain significant at mostly group and lower halo masses. In contrast, beam
smearing at $\textit{Planck}$ resolution makes the models indistinguishable,
and both models appear to agree well with $\textit{Planck}$ data down to the
lowest masses probed. We show that the arcminute resolution expected from
forthcoming facilities would retain the differences between model predictions,
and thereby provide strong constraints on AGN feedback.


title:
DL-SLOT: Dynamic Lidar SLAM and Object Tracking Based On Graph
  Optimization

abstract:
  Ego-pose estimation and dynamic object tracking are two key issues in an
autonomous driving system. Two assumptions are often made for them, i.e. the
static world assumption of simultaneous localization and mapping (SLAM) and the
exact ego-pose assumption of object tracking, respectively. However, these
assumptions are difficult to hold in highly dynamic road scenarios where SLAM
and object tracking become correlated and mutually beneficial. In this paper,
DL-SLOT, a dynamic Lidar SLAM and object tracking method is proposed. This
method integrates the state estimations of both the ego vehicle and the static
and dynamic objects in the environment into a unified optimization framework,
to realize SLAM and object tracking (SLOT) simultaneously. Firstly, we
implement object detection to remove all the points that belong to potential
dynamic objects. Then, LiDAR odometry is conducted using the filtered point
cloud. At the same time, detected objects are associated with the history
object trajectories based on the time-series information in a sliding window.
The states of the static and dynamic objects and ego vehicle in the sliding
window are integrated into a unified local optimization framework. We perform
SLAM and object tracking simultaneously in this framework, which significantly
improves the robustness and accuracy of SLAM in highly dynamic road scenarios
and the accuracy of objects' states estimation. Experiments on public datasets
have shown that our method achieves better accuracy than A-LOAM.


title:
Extension of Dynamic Mode Decomposition for dynamic systems with
  incomplete information based on t-model of optimal prediction

abstract:
  The Dynamic Mode Decomposition has proved to be a very efficient technique to
study dynamic data. This is entirely a data-driven approach that extracts all
necessary information from data snapshots which are commonly supposed to be
sampled from measurement. The application of this approach becomes problematic
if the available data is incomplete because some dimensions of smaller scale
either missing or unmeasured. Such setting occurs very often in modeling
complex dynamical systems such as power grids, in particular with reduced-order
modeling. To take into account the effect of unresolved variables the optimal
prediction approach based on the Mori-Zwanzig formalism can be applied to
obtain the most expected prediction under existing uncertainties. This
effectively leads to the development of a time-predictive model accounting for
the impact of missing data. In the present paper we provide a detailed
derivation of the considered method from the Liouville equation and finalize it
with the optimization problem that defines the optimal transition operator
corresponding to the observed data. In contrast to the existing approach, we
consider a first-order approximation of the Mori-Zwanzig decomposition, state
the corresponding optimization problem and solve it with the gradient-based
optimization method. The gradient of the obtained objective function is
computed precisely through the automatic differentiation technique. The
numerical experiments illustrate that the considered approach gives practically
the same dynamics as the exact Mori-Zwanzig decomposition, but is less
computationally intensive.


title: On moment map and bigness of tangent bundles of $G$-varieties

abstract:
  Let $G$ be a connected algebraic group and let $X$ be a smooth projective
$G$-variety. In this paper, we prove a sufficient criterion to determine the
bigness of the tangent bundle $TX$ using the moment map
$\Phi_X^G:T^*X\rightarrow \mathfrak{g}^*$. As an application, the bigness of
the tangent bundles of certain quasi-homogeneous varieties are verified,
including symmetric varieties, horospherical varieties and equivariant
compactifications of commutative linear algebraic groups. Finally, we study in
details the Fano manifolds $X$ with Picard number $1$ which is an equivariant
compactification of a vector group $\mathbb{G}_a^n$. In particular, we will
determine the pseudoeffective cone of $\mathbb{P}(T^*X)$ and show that the
image of the projectivised moment map along the boundary divisor $D$ of $X$ is
projectively equivalent to the dual variety of the VMRT of $X$.


title:
On the number of fixed edges of automorphisms of vertex-transitive
  graphs of small valency

abstract:
  We prove that, if $\Gamma$ is a finite connected $3$-valent
vertex-transitive, or $4$-valent vertex- and edge-transitive graph, then either
$\Gamma$ is part of a well-understood family of graphs, or every non-identity
automorphism of $\Gamma$ fixes at most $1/3$ of the edges. This answers a
question proposed by Primo\v{z} Poto\v{c}nik and the third author.


title: Data-Driven Decision Making in COVID-19 Response: A Survey

abstract:
  COVID-19 has spread all over the world, having an enormous effect on our
daily life and work. In response to the epidemic, a lot of important decisions
need to be taken to save communities and economies worldwide. Data clearly
plays a vital role in effective decision making. Data-driven decision making
uses data related evidence and insights to guide the decision making process
and to verify the plan of action before it is committed. To better handle the
epidemic, governments and policy making institutes have investigated abundant
data originating from COVID-19. These data include those related to medicine,
knowledge, media, etc. Based on these data, many prevention and control
policies are made. In this survey paper, we summarize the progress of
data-driven decision making in the response to COVID-19, including COVID-19
prevention and control, psychological counselling, financial aid, work
resumption, and school re-opening. We also propose some current challenges and
open issues in data-driven decision making, including data collection and
quality, complex data analysis, and fairness in decision making. This survey
paper sheds light on current policy making driven by data, which also provides
a feasible direction for further scientific research.


title:
Fine structure splitting analysis of cavity-enhanced telecom-wavelength
  InAs quantum dots grown on a GaAs(111)A vicinal substrate

abstract:
  The effcient generation of entangled photons at telecom wavelength is crucial
for the success of many quantum communication protocols and the development of
fiber-based quantum networks. Entangled light can be generated by solid state
quantum emitters with naturally low fine structure splitting, such as highly
symmetric InAs quantum dots (QDs) grown on (111)-oriented surfaces.
Incorporating this kind of QDs into optical cavities is critical to achieve
sufficient signal intensitiesfor applications, but has so far shown major
complications. In this work we present droplet epitaxy of telecom-wavelength
InAs QDs within an optical cavity on a vicinal (2{\deg} miscut) GaAs(111)A
substrate. We show a remarkable enhancement of the photon extraction efficiency
compared to previous reports together with a reduction of the density that
facilitates the isolation of single spectral lines. Moreover, we characterise
the exciton fine structure splitting and employ numerical simulations under the
framework of the empirical pseudopotential and configuration interaction
methods to study the impact of the miscut on the optical properties of the QDs.
We demonstrate that the presence of miscut steps influences the polarisation of
the excitonic states and introduces a preferential orientation in the $C_{3v}$
symmetry of the surface.


title: Dirac operator spectrum on a nilmanifold

abstract:
  We obtain the spectrum of the Dirac operator on the three-dimensional
Heisenberg nilmanifold $\mathcal{M}_3$, and its complete dependence on the
metric moduli. As an application, we construct the four-dimensional low-energy
effective action obtained by compactification of a seven-dimensional
gauge-fermion theory on $\mathcal{M}_3$.


title:
Unexpected advantages of exploitation for target searches in complex
  networks

abstract:
  Exploitation universally emerges in various decision-making contexts, e.g.,
animals foraging, web surfing, the evolution of scientists' research topics,
and our daily lives. Despite its ubiquity, exploitation, which refers to the
behavior of revisiting previous experiences, has often been considered to delay
the search process of finding a target. In this paper, we investigate how
exploitation affects search performance by applying a non-Markovian random walk
model, where a walker randomly revisits a previously visited node using
long-term memory. We analytically study two broad forms of network structures,
namely (i) clique-like networks and (ii) lollipop-like networks, and find that
exploitation can significantly improve search performance in lollipop-like
networks whereas it hinders target search in clique-like networks. Moreover, we
numerically verify that exploitation can reduce the time needed to fully
explore the underlying networks by using $550$ diverse real-world networks.
Based on the analytic result, we define the lollipop-likeness of a network and
observe a positive relationship between the advantage of exploitation and
lollipop-likeness.


title:
GCM-Motivated Multidimensional Temperature Parametrization Scheme for
  Phasecurve Retrieval

abstract:
  We present a novel physically-motivated parametrized temperature model for
phasecurve retrieval, able to self-consistently assess the variation in the
thermal structure in multidimensions. To develop this approach we drew
motivation from both full three-dimensional general circulation models and
analytic formulations, accounting for the dominant dynamical feature of
tidally-locked planets, the planetary jet. Our formulation shows notable
flexibility. It can generate planetary jets of various characteristics and
redistribution efficiencies seen in the literature, including both standard
eastward and unusual westward offset hotspots, as well as more exotic
configurations for potential future observations. In our modelling scheme we
utilize a tractable set of parameters efficient enough to enable future
Bayesian analysis and, in addition to the resolved temperature structure, we
return physical insights not yet derived from retrievals: the amplitude and the
phase offset, and the location and the extent of the equatorial jet.


title: Toeplitz operators on non-reflexive Fock spaces

abstract:
  We generalize several results on Toeplitz operators over Fock spaces to the
case of non-reflexive Fock spaces. Among these results are the characterization
of compactness and the Fredholm property of such operators, a well-known
representation of the Toeplitz algebra, a characterization of the essential
centre of the Toeplitz algebra. Further, we improve several results related to
correspondence theory, e.g. we improve previous results on the correspondence
of algebras and we give a correspondence theoretic version of the well-known
Berger-Coburn estimates.


title:
Understanding How Older Adults Comprehend COVID-19 Interactive
  Visualizations via Think-Aloud Protocol

abstract:
  Older adults have been hit disproportionally hard by the COVID-19 pandemic.
One critical way for older adults to minimize the negative impact of COVID-19
and future pandemics is to stay informed about its latest information, which
has been increasingly presented through online interactive visualizations
(e.g., live dashboards and websites). Thus, it is imperative to understand how
older adults interact with and comprehend online COVID-19 interactive
visualizations and what challenges they might encounter to make such
visualizations more accessible to older adults. We adopted a user-centered
approach by inviting older adults to interact with COVID-19 interactive
visualizations while at the same time verbalizing their thought processes using
a think-aloud protocol. By analyzing their think-aloud verbalizations, we
identified four types of thought processes representing how older adults
comprehended the visualizations and uncovered the challenges they encountered.
Furthermore, we also identified the challenges they encountered with seven
common types of interaction techniques adopted by the visualizations. Based on
the findings, we present design guidelines for making interactive
visualizations more accessible to older adults.


title:
The Standard Quantized Matrix Algebra $M_q(n)$ is A Solvable Polynomial
  Algebra

abstract:
  Let $M_q(n)$ be the standard quantized matrix algebra, introduced by Faddeev,
Reshetikhin, and Takhtajan. It is shown, by constructing an appropriate
monomial ordering $\prec$ on its PBW $K$-basis ${\cal B}$ , that $M_q(n)$ is a
solvable polynomial algebra. Consequently, further structural properties of
$M_q(n)$ and their modules may be established and realized in a
constructive-computational way.


title: Hybrid Quantum-Classical Search Algorithms

abstract:
  Search is one of the most commonly used primitives in quantum algorithm
design. It is known that quadratic speedups provided by Grover's algorithm are
optimal, and no faster quantum algorithms for Search exist. While it is known
that at least some quantum computation is required to achieve these speedups,
the existing bounds do not rule out the possibility of an equally fast hybrid
quantum-classical algorithm where most of the computation is classical. In this
work, we study such hybrid algorithms and we show that classical computation,
unless it by itself can solve the Search problem, cannot assist quantum
computation. In addition, we generalize this result to algorithms with
subconstant success probabilities.


title: Enabling arbitrary translation objectives with Adaptive Tree Search

abstract:
  We introduce an adaptive tree search algorithm, that can find high-scoring
outputs under translation models that make no assumptions about the form or
structure of the search objective. This algorithm -- a deterministic variant of
Monte Carlo tree search -- enables the exploration of new kinds of models that
are unencumbered by constraints imposed to make decoding tractable, such as
autoregressivity or conditional independence assumptions. When applied to
autoregressive models, our algorithm has different biases than beam search has,
which enables a new analysis of the role of decoding bias in autoregressive
models. Empirically, we show that our adaptive tree search algorithm finds
outputs with substantially better model scores compared to beam search in
autoregressive models, and compared to reranking techniques in models whose
scores do not decompose additively with respect to the words in the output. We
also characterise the correlation of several translation model objectives with
respect to BLEU. We find that while some standard models are poorly calibrated
and benefit from the beam search bias, other often more robust models
(autoregressive models tuned to maximize expected automatic metric scores, the
noisy channel model and a newly proposed objective) benefit from increasing
amounts of search using our proposed decoder, whereas the beam search bias
limits the improvements obtained from such objectives. Thus, we argue that as
models improve, the improvements may be masked by over-reliance on beam search
or reranking based methods.


title:
SMGO-$\Delta$: Balancing Caution and Reward in Global Optimization with
  Black-Box Constraints

abstract:
  In numerous applications across all science and engineering areas, there are
optimization problems where both the objective function and the constraints
have no closed-form expression or are too complex to be managed analytically,
that they can only be evaluated through experiments. To address such issues, we
design a global optimization technique for problems with black-box objective
and constraints. Assuming Lipschitz continuity of the cost and constraint
functions, a Set Membership framework is adopted to build a surrogate model of
the optimization program, that is used for exploitation and exploration
routines. The resulting algorithm, named Set Membership Global Optimization
With Black-Box Constraints (SMGO-$\Delta$), features one tunable risk
parameter, which the user can intuitively adjust to trade-off safety,
exploitation, and exploration. The theoretical properties of the algorithm are
derived, and the optimization performance is compared with representative
techniques from the literature in several benchmarks. Lastly, it is tested and
compared with constrained Bayesian optimization in a case study pertaining to
model predictive control tuning for a servomechanism with disturbances and
plant uncertainties, addressing practically-motivated task-level constraints.


title:
On the Cahn-Hilliard-Darcy system with mass source and strongly
  separating potential

abstract:
  We study an evolutionary system of Cahn-Hilliard-Darcy type including mass
source and transport effects. The system may arise in a number of physical
situations related to phase separation phenomena with convection, with the main
and most specific application being related to tumoral processes, where the
variations of the mass may correspond to growth, or shrinking, of the tumor. We
prove existence of weak solutions in the case when the configuration potential
for the order parameter $\varphi$ is designed in such a way to keep $\varphi$
in between the reference interval $(-1,1)$ despite the occurrence of mass
source effects. Moreover, in the two-dimensional case, we obtain existence and
uniqueness of strong (i.e., more regular) solutions.


title:
Reconstruction of observed mechanical motions with Artificial
  Intelligence tools

abstract:
  The goal of this paper is to determine the laws of observed trajectories
assuming that there is a mechanical system in the background and using these
laws to continue the observed motion in a plausible way. The laws are
represented by neural networks with a limited number of parameters. The
training of the networks follows the Extreme Learning Machine idea. We
determine laws for different levels of embedding, thus we can represent not
only the equation of motion but also the symmetries of different kinds. In the
recursive numerical evolution of the system, we require the fulfillment of all
the observed laws, within the determined numerical precision. In this way, we
can successfully reconstruct both integrable and chaotic motions, as we
demonstrate in the example of the gravity pendulum and the double pendulum.


title: Subsystem distances between quasiparticle excited states

abstract:
  We investigate the subsystem Schatten distance, trace distance and fidelity
between the quasiparticle excited states of the free and the nearest-neighbor
coupled fermionic and bosonic chains and the ferromagnetic phase of the
spin-1/2 XXX chain. The results support the scenario that in the scaling limit
when one excited quasiparticle has a large energy it decouples from the ground
state and when two excited quasiparticles have a large momentum difference they
decouple from each other. From the quasiparticle picture, we get the universal
subsystem distances that are valid when both the large energy condition and the
large momentum difference condition are satisfied, by which we mean each of the
excited quasiparticles has a large energy and the momentum difference of each
pair of the excited quasiparticles is large. In the free fermionic and bosonic
chains, we use the subsystem mode method and get efficiently the subsystem
distances, which are also valid in the coupled fermionic and bosonic chains if
the large energy condition is satisfied. Moreover, under certain limit the
subsystem distances from the subsystem mode method are even valid in the XXX
chain. We expect that the results can be also generalized for other integrable
models.


title:
S-PLUS: Exploring wide field properties of multiple populations in
  galactic globular clusters at different metallicities

abstract:
  The presence of Multiple Stellar Populations (MSPs) in Galactic Globular
Clusters (GCs) is a poorly understood phenomenon. By probing different spectral
ranges that are affected by different absorption lines using the multi-band
photometric survey S-PLUS, we study four GCs -- NGC 104, NGC 288, NGC 3201 and
NGC 7089 -- that span a wide range in metallicities. With the combination of
broad and narrow-band photometry in 12 different filters from 3485A (u) to
9114A (z), we identified MSPs along the rectified red-giant branch in
colour-magnitude diagrams (CMDs) and separated them using a K-means clustering
algorithm. Additionally, we take advantage of the large Field of View of the
S-PLUS detector to investigate radial trends in our sample. We report on six
colour combinations that can be used to successfully identify two stellar
populations in all studied clusters and show that they can be characterized as
Na-rich and Na-poor. For both NGC 288 and NGC 7089, their radial profiles show
a clear concentration of 2P. This directly supports the formation theories that
propose an enrichment of the intra-cluster medium and subsequent star formation
in the more dense central regions. However, in the case of NGC 3201, the trend
is reversed. The 1P is more centrally concentrated, in direct contradiction
with previous literature studies. NGC 104 shows a well-mixed population. We
also constructed radial profiles up to 1 half-light radius of the clusters with
HST data to highlight that radial differences are lost in the inner regions of
the GCs and that wide-field studies are essential when studying this.


title:
Topological phases of an interacting Majorana Benalcazar-Bernevig-Hughes
  model

abstract:
  We study the effects of Coulomb repulsive interactions on a Majorana
Benalcazar-Bernevig-Hughes (MBBH) model. The MBBH model belongs to the class of
second--order topological superconductors ($HOTSC_2$), featuring robust
Majorana corner modes. We consider an interacting strip of four chains of
length $L$ and perform a DMRG numerical analysis based on a tensor--network
approach. Study of the nonlocal fermionic correlations and of the degenerate
entanglement spectrum indicates that the topological phases are robust in the
presence of interactions, even in the strongly interacting regime.


title:
Zero-shot Cross-lingual Transfer of Prompt-based Tuning with a Unified
  Multilingual Prompt

abstract:
  Prompt-based tuning has been proven effective for pretrained language models
(PLMs). While most of the existing work focuses on the monolingual prompts, we
study the multilingual prompts for multilingual PLMs, especially in the
zero-shot cross-lingual setting. To alleviate the effort of designing different
prompts for multiple languages, we propose a novel model that uses a unified
prompt for all languages, called UniPrompt. Different from the discrete prompts
and soft prompts, the unified prompt is model-based and language-agnostic.
Specifically, the unified prompt is initialized by a multilingual PLM to
produce language-independent representation, after which is fused with the text
input. During inference, the prompts can be pre-computed so that no extra
computation cost is needed. To collocate with the unified prompt, we propose a
new initialization method for the target label word to further improve the
model's transferability across languages. Extensive experiments show that our
proposed methods can significantly outperform the strong baselines across
different languages. We will release data and code to facilitate future
research.


title: Deep Learning Reproducibility and Explainable AI (XAI)

abstract:
  The nondeterminism of Deep Learning (DL) training algorithms and its
influence on the explainability of neural network (NN) models are investigated
in this work with the help of image classification examples. To discuss the
issue, two convolutional neural networks (CNN) have been trained and their
results compared. The comparison serves the exploration of the feasibility of
creating deterministic, robust DL models and deterministic explainable
artificial intelligence (XAI) in practice. Successes and limitation of all here
carried out efforts are described in detail. The source code of the attained
deterministic models has been listed in this work. Reproducibility is indexed
as a development-phase-component of the Model Governance Framework, proposed by
the EU within their excellence in AI approach. Furthermore, reproducibility is
a requirement for establishing causality for the interpretation of model
results and building of trust towards the overwhelming expansion of AI systems
applications. Problems that have to be solved on the way to reproducibility and
ways to deal with some of them, are examined in this work.


title:
Bitwidth Heterogeneous Federated Learning with Progressive Weight
  Dequantization

abstract:
  In practical federated learning scenarios, the participating devices may have
different bitwidths for computation and memory storage by design. However,
despite the progress made in device-heterogeneous federated learning scenarios,
the heterogeneity in the bitwidth specifications in the hardware has been
mostly overlooked. We introduce a pragmatic FL scenario with bitwidth
heterogeneity across the participating devices, dubbed as Bitwidth
Heterogeneous Federated Learning (BHFL). BHFL brings in a new challenge, that
the aggregation of model parameters with different bitwidths could result in
severe performance degeneration, especially for high-bitwidth models. To tackle
this problem, we propose ProWD framework, which has a trainable weight
dequantizer at the central server that progressively reconstructs the
low-bitwidth weights into higher bitwidth weights, and finally into
full-precision weights. ProWD further selectively aggregates the model
parameters to maximize the compatibility across bit-heterogeneous weights. We
validate ProWD against relevant FL baselines on the benchmark datasets, using
clients with varying bitwidths. Our ProWD largely outperforms the baseline FL
algorithms as well as naive approaches (e.g. grouped averaging) under the
proposed BHFL scenario.


title: On $Z_{p^r}Z_{p^r}Z_{p^s}$-Additive Cyclic Codes

abstract:
  In this paper, we introduce
$\mathbb{Z}_{p^r}\mathbb{Z}_{p^r}\mathbb{Z}_{p^s}$-additive cyclic codes for
$r\leq s$. These codes can be identified as $\mathbb{Z}_{p^s}[x]$-submodules of
$\mathbb{Z}_{p^r}[x]/\langle x^{\alpha}-1\rangle \times
\mathbb{Z}_{p^r}[x]/\langle x^{\beta}-1\rangle\times
\mathbb{Z}_{p^s}[x]/\langle x^{\gamma}-1\rangle$. We determine the generator
polynomials and minimal generating sets for this family of codes. Some previous
works has been done for the case $p=2$ with $r=s=1$, $r=s=2$, and $r=1,s=2$.
However, we show that in these previous works the classification of these codes
were incomplete and the statements in this paper complete such classification.
We also discuss the structure of separable
$\mathbb{Z}_{p^r}\mathbb{Z}_{p^r}\mathbb{Z}_{p^s}$-additive cyclic codes and
determine their generator polynomials. Further, we also study the duality of
$\mathbb{Z}_{p^s}[x]$-submodules. As applications, we present some examples and
construct some optimal binary codes.


title: On PAC-Bayesian reconstruction guarantees for VAEs

abstract:
  Despite its wide use and empirical successes, the theoretical understanding
and study of the behaviour and performance of the variational autoencoder (VAE)
have only emerged in the past few years. We contribute to this recent line of
work by analysing the VAE's reconstruction ability for unseen test data,
leveraging arguments from the PAC-Bayes theory. We provide generalisation
bounds on the theoretical reconstruction error, and provide insights on the
regularisation effect of VAE objectives. We illustrate our theoretical results
with supporting experiments on classical benchmark datasets.


title:
SLOGAN: Handwriting Style Synthesis for Arbitrary-Length and
  Out-of-Vocabulary Text

abstract:
  Large amounts of labeled data are urgently required for the training of
robust text recognizers. However, collecting handwriting data of diverse
styles, along with an immense lexicon, is considerably expensive. Although data
synthesis is a promising way to relieve data hunger, two key issues of
handwriting synthesis, namely, style representation and content embedding,
remain unsolved. To this end, we propose a novel method that can synthesize
parameterized and controllable handwriting Styles for arbitrary-Length and
Out-of-vocabulary text based on a Generative Adversarial Network (GAN), termed
SLOGAN. Specifically, we propose a style bank to parameterize the specific
handwriting styles as latent vectors, which are input to a generator as style
priors to achieve the corresponding handwritten styles. The training of the
style bank requires only the writer identification of the source images, rather
than attribute annotations. Moreover, we embed the text content by providing an
easily obtainable printed style image, so that the diversity of the content can
be flexibly achieved by changing the input printed image. Finally, the
generator is guided by dual discriminators to handle both the handwriting
characteristics that appear as separated characters and in a series of cursive
joins. Our method can synthesize words that are not included in the training
vocabulary and with various new styles. Extensive experiments have shown that
high-quality text images with great style diversity and rich vocabulary can be
synthesized using our method, thereby enhancing the robustness of the
recognizer.


title:
Duality of generalized twisted Reed-Solomon codes and Hermitian
  self-dual MDS or NMDS codes

abstract:
  Self-dual MDS and NMDS codes over finite fields are linear codes with
significant combinatorial and cryptographic applications. In this paper,
firstly, we investigate the duality properties of generalized twisted
Reed-Solomon (abbreviated GTRS) codes in some special cases. In what follows, a
new systematic approach is proposed to draw Hermitian self-dual (+)-GTRS codes.
The necessary and sufficient conditions of a Hermitian self-dual (+)-GTRS code
are presented.With this method, several classes of Hermitian self-dual MDS and
NMDS codes are constructed.


title: Initial data on big bang singularities in symmetric settings

abstract:
  In a recent article, we propose a general geometric notion of initial data on
big bang singularities. This notion is of interest in its own right. However,
it also serves the purpose of giving a unified perspective on many of the
results in the literature. In the present article, we give a partial
justification of this statement by rephrasing the results concerning Bianchi
class A orthogonal stiff solutions and solutions in the $\mathbb{T}^{3}$-Gowdy
symmetric vacuum setting in terms of our general geometric notion of initial
data on the big bang singularity.


title: Biometric security technology

abstract:
  This paper presents an overview of the main topics related to biometric
security technology, with the main purpose to provide a primer on this subject.
Biometrics can offer greater security and convenience than traditional methods
for people recognition. Even if we do not want to replace a classic method
(password or handheld token) by a biometric one, for sure, we are potential
users of these systems, which will even be mandatory for new passport models.
For this reason, to be familiarized with the possibilities of biometric
security technology is useful.


title:
Evacuation trials from a double-deck electric train unit: Experimental
  data and sensitivity analysis

abstract:
  Passenger trains represent a challenging environment in emergencies, with
specific evacuation conditions resulting from the typical layout and interior
design inherent to public transportation vehicles. This paper describes a
dataset obtained in a full-scale controlled experiment emulating the emergency
evacuation of a double-deck electric unit railcar carried out in Prague in
2018. 15 evacuation trials involving 91 participants were conducted under
various evacuation scenarios considering different compositions of passenger
crowd, exit widths, and exit types (e.g. egress to a high platform, to an open
rail line using stairs, and a 750 mm jump without any supporting equipment).
The study's main goals were to collect experimental data on the movement
conditions in the railcar and to study the impact of various boundary
conditions on evacuation process and total evacuation time. Movement
characteristics (exit flows, speeds) and human behaviour (pre-movement
activities, exiting behaviours) were also analysed.
  The data obtained was used to validate and adjust a Pathfinder model to
capture important aspects of evacuation from the railcar. Furthermore, a series
of simulations using this model was performed to provide sensitivity analysis
of the influence of crowd composition, exit width, and exit type on total
evacuation time. As a key finding, we can conclude that for the case of a
standard exit path (platform or stairs) the width of the main exit had the
greatest impact on total evacuation time, however, crowd composition played the
prevailing role in evacuation scenarios involving a jump.


title:
Exponential Tail Local Rademacher Complexity Risk Bounds Without the
  Bernstein Condition

abstract:
  The local Rademacher complexity framework is one of the most successful
general-purpose toolboxes for establishing sharp excess risk bounds for
statistical estimators based on the framework of empirical risk minimization.
Applying this toolbox typically requires using the Bernstein condition, which
often restricts applicability to convex and proper settings. Recent years have
witnessed several examples of problems where optimal statistical performance is
only achievable via non-convex and improper estimators originating from
aggregation theory, including the fundamental problem of model selection. These
examples are currently outside of the reach of the classical localization
theory.
  In this work, we build upon the recent approach to localization via offset
Rademacher complexities, for which a general high-probability theory has yet to
be established. Our main result is an exponential-tail excess risk bound
expressed in terms of the offset Rademacher complexity that yields results at
least as sharp as those obtainable via the classical theory. However, our bound
applies under an estimator-dependent geometric condition (the "offset
condition") instead of the estimator-independent (but, in general,
distribution-dependent) Bernstein condition on which the classical theory
relies. Our results apply to improper prediction regimes not directly covered
by the classical theory.


title: Thermal hand image segmentation for biometric recognition

abstract:
  In this paper we present a method to identify people by means of thermal (TH)
and visible (VIS) hand images acquired simultaneously with a TESTO 882-3
camera. In addition, we also present a new database specially acquired for this
work. The real challenge when dealing with TH images is the cold finger areas,
which can be confused with the acquisition surface. This problem is solved by
taking advantage of the VIS information. We have performed different tests to
show how TH and VIS images work in identification problems. Experimental
results reveal that TH hand image is as suitable for biometric recognition
systems as VIS hand images, and better results are obtained when combining this
information. A Biometric Dispersion Matcher has been used as a feature vector
dimensionality reduction technique as well as a classification task. Its
selection criteria helps to reduce the length of the vectors used to perform
identification up to a hundred measurements. Identification rates reach a
maximum value of 98.3% under these conditions, when using a database of 104
people.


title: Symmetry energy effects on the properties of hybrid stars

abstract:
  Symmetry energy is an important part of the equation of state of isospin
asymmetry matter. However, the huge uncertainties of symmetry energy remain at
suprasaturation densities, where the phase transitions of strongly interacting
matter and the quark matter symmetry energy are likely to be taken into
account. In this work, we investigate the properties of symmetry energy by
using a hybrid star with the hadron-quark phase transition. The interaction
among strange quark matter (SQM) in hybrid stars is based on a 3-flavor NJL
model with different vector and isovector channels, while the equation of state
(EOS) of the nuclear matter is obtained by considering the ImMDI-ST interaction
by varying the parameters x, y, and z. Our results indicate that the various
parameters and coupling constants of the interactions from the ImMDI-ST and NJL
model can lead to widely different trends for the symmetry energy in the
hadron-quark mixed phase and the different onsets of the hadron-quark phase
transition. In addition, it has been found that the radii and tidal
deformabilities of hybrid stars constrain mostly the density dependence of
symmetry energy while the observed maximum masses of hybrid stars constrain
mostly the EOS of symmetric nuclear and quark matter.


title:
The Tiny-Tasks Granularity Trade-Off: Balancing overhead vs. performance
  in parallel systems

abstract:
  Models of parallel processing systems typically assume that one has $l$
workers and jobs are split into an equal number of $k=l$ tasks. Splitting jobs
into $k > l$ smaller tasks, i.e. using ``tiny tasks'', can yield performance
and stability improvements because it reduces the variance in the amount of
work assigned to each worker, but as $k$ increases, the overhead involved in
scheduling and managing the tasks begins to overtake the performance benefit.
We perform extensive experiments on the effects of task granularity on an
Apache Spark cluster, and based on these, developed a four-parameter model for
task and job overhead that, in simulation, produces sojourn time distributions
that match those of the real system. We also present analytical results which
illustrate how using tiny tasks improves the stability region of split-merge
systems, and analytical bounds on the sojourn and waiting time distributions of
both split-merge and single-queue fork-join systems with tiny tasks. Finally we
combine the overhead model with the analytical models to produce an analytical
approximation to the sojourn and waiting time distributions of systems with
tiny tasks which include overhead. Though no longer strict analytical bounds,
these approximations matched the Spark experimental results very well in both
the split-merge and fork-join cases.


title:
Personalized PPG Normalization based on Subject Heartbeat in Resting
  State Condition

abstract:
  Physiological responses are nowadays widely used to recognize the affective
state of subjects in real-life scenarios. However, these data are intrinsically
subject-dependent, making machine learning techniques for data classification
not easily applicable due to inter-subject variability. In this work, the
reduction of inter-subject heterogeneity is considered in the case of
PhotoPlethysmoGraphy (PPG), which is successfully used to detect stress and
evaluate experienced cognitive load. To face the inter-subject heterogeneity, a
novel personalized PPG normalization is here proposed. A subject-normalized
discrete domain where the PPG signals are properly re-scaled is introduced,
considering the subject's heartbeat frequency in resting state conditions. The
effectiveness of the proposed normalization is evaluated in comparison with
other normalization procedures in a binary classification task, where cognitive
load and relaxing state are considered. The results obtained on two different
datasets available in the literature confirm that applying the proposed
normalization strategy permits to increase classification performance.


title:
Magnetic moment of the $X_1(2900)$ state in the diquark-antidiquark
  picture

abstract:
  Motivated by the discovery of fully open-flavor tetraquark states $X_0(2900)$
and $X_1(2900)$ by the LHCb Collaboration, the magnetic dipole moment of the
$X_1(2900)$ state with the quantum numbers $ J^{P} = 1^{-}$ is determined in
the diquark-antidiquark model using the light-cone sum rules. The magnetic
moments of hadrons encompasses useful knowledge on the distributions of charge
and magnetization their inside, which can be used to better understand their
geometrical shapes and quark-gluon organizations. The observation of the
$X_0(2900)$ and $X_1(2900)$ as the first two fully open-flavor multiquark
states has opened a new window for investigation of the exotic states. The
obtained results in the present study may shed light on the future experimental
and theoretical searches on the properties of fully open-flavor multiquark
states.


title:
Effects of Mercury surface temperature on the sodium abundance in its
  exosphere

abstract:
  The link between the surface temperature of Mercury and the exosphere sodium
content has been investigated. Observations show that, along the orbit of
Mercury, two maxima of total Na content are present: one at aphelion and one at
perihelion. Previous models, based on a simple thermal map, were not able to
reproduce the aphelion peak. Here we introduce a new thermophysical model
giving soil temperatures as an input for the IAPS exospheric model already used
in the past with the input of a simple thermal map. By comparing the reference
model output with the new one, we show that such improved surface temperature
map is crucial to explain the temporal variability of Sodium along the orbit.


title: Bond Graph Modelling and Simulation of Pneumatic Soft Actuator

abstract:
  This paper presents the design and dynamic modelling of a soft pneumatic
actuator that can be used to mimic snake or worm-like locomotion. The bond
graph technique is used to derive the dynamics of the actuator. To validate the
accuracy of the derived dynamic model, we conduct numerical simulations using
20-sim software. Experimental results demonstrate that the soft actuator
achieves bi-directional bending and linear displacement, which is essential for
mimicking snake or worm-like locomotion


title: Integrating Dark Matter, Modified Gravity, and the Humanities

abstract:
  Editorial of a special issue on dark matter & modified gravity, distributed
across the journals Studies in History and Philosophy of Modern Physics and
Studies in History and Philosophy of Science. Published version of the open
access editorial (in SHPS) available here:
https://doi.org/10.1016/j.shpsa.2021.08.015. The six papers are collected here:
https://www.sciencedirect.com/journal/studies-in-history-and-philosophy-of-science-part-b-studies-in-history-and-philosophy-of-modern-physics/special-issue/10CR71RJLWM.

categories: physics.hist-ph astro-ph.CO astro-ph.GA gr-qc hep-th


title:
Gravity-driven coatings on curved substrates: a differential geometry
  approach

abstract:
  Although the drainage and spreading processes of thin liquid films on
substrates have received growing attention during the last decades, the study
of three-dimensional cases is limited to a few studies on flat and axisymmetric
substrates. In this work, we exploit differential geometry to study the
drainage and spreading of thin films on generic curved substrates. We initially
investigate the drainage and spreading processes on spheroidal and paraboloidal
substrates by employing an asymptotic expansion in the vicinity of the pole and
a self-similar approach, finding that the thickness distribution is set by the
substrate metric and tangential gravity force components. Spheroids with a
large ratio between height and equatorial radius are characterized by a growing
thickness moving away from the pole, and vice versa. The non-symmetric coating
on a toroidal substrate shows that larger thicknesses and a faster spreading
are attained on the inner region than on the outer region of the torus. An
ellipsoid with three different axes is chosen as a testing ground for
three-dimensional drainage and spreading. Modulations in the drainage solution
are observed, with a different variation of the thickness along the two axes.
By imposing the conservation of mass, an analytical solution for the average
spreading front is obtained. The analytical and numerical results are in good
agreement. The resulting drainage solutions show also a good agreement with
experimental measurements obtained from the coating of a curing polymer on
diverse substrates.


title:
Radiation hardness study on a CMOS pixel sensor for charged particle
  tracking

abstract:
  A CMOS pixel sensor, named Supix-1, is developed for a pixelated silicon
tracker for the Circular Electron-Positron Collider (CEPC) project. The sensor,
consisted of nine sectors varying in pixel sizes, diode sizes and geometries,
is fabricated with a 180 nm CMOS Image Sensor (CIS) process to study the
particle detection performance of enlarged pixels. In this work, the
radiation-induced effects on the charge collection of the sensor under the
fluence of 1 $\times$ 10^13 1 MeV neq/cm^2 are studied by the measurements with
the radioactive source of Fe-55 and the Technology Computer Aided Design (TCAD)
simulations, since the radiation hardness of 6.8 $\times$ 10^12 1 MeV neq/cm^2
per year for Non-Ionizing Energy Loss (NIEL) effects is required. In
measurements, the sensor gain has been calibrated using the k-$\alpha$ peak of
Fe-55 before and after irradiation. The pixel-wise equivalent noise charge
(ENC), charge collection efficiency (CCE) and signal-to-noise ratio (SNR) were
evaluated. The radiation-induced effects on cluster properties are studied
through a self-developed reconstruction algorithm. In TCAD simulations, charge
collections in 5 $\times$ 5 pixel matrixes for two typical impinging cases of
incident particles were simulated with and without irradiation. Both
measurements and simulations indicate that enlarged pixels with area of 21
$\mu$m $\times$ 84 $\mu$m, though suffering greater loss on sensor performance
than small pixels do, still have satisfactory noise and charge collection
performance after irradiation for particle tracking in the upcoming collider
detectors.


title:
J-PLUS: A catalogue of globular cluster candidates around the
  M81/M82/NGC3077 triplet of galaxies

abstract:
  Globular clusters (GCs) are proxies of the formation assemblies of their host
galaxies. However, few studies exist targeting GC systems of spiral galaxies up
to several effective radii. Through 12-band Javalambre Photometric Local
Universe Survey (J-PLUS) imaging, we study the point sources around the
M81/M82/NGC3077 triplet in search of new GC candidates. We develop a tailored
classification scheme to search for GC candidates based on their similarity to
known GCs via a principal components analysis (PCA) projection. Our method
accounts for missing data and photometric errors. We report 642 new GC
candidates in a region of 3.5 deg$^2$ around the triplet, ranked according to
their Gaia astrometric proper motions when available. We find tantalising
evidence for an overdensity of GC candidate sources forming a bridge connecting
M81 and M82. Finally, the spatial distribution of the GC candidates $(g-i)$
colours is consistent with halo/intra-cluster GCs, i.e. it gets bluer as they
get further from the closest galaxy in the field. We further employ a
regression-tree based model to estimate the metallicity distribution of the GC
candidates based on their J-PLUS bands. The metallicity distribution of the
sample candidates is broad and displays a bump towards the metal-rich end. Our
list increases the population of GC candidates around the triplet by 3-fold,
stresses the usefulness of multi-band surveys in finding these objects, and
provides a testbed for further studies analysing their spatial distribution
around nearby (spirals) galaxies.


title: 2021 Update on $\varepsilon_K$ with lattice QCD inputs

abstract:
  We present recent updates for $\varepsilon_K$ determined directly from the
standard model (SM) with lattice QCD inputs such as $\hat{B}_K$, $|V_{cb}|$,
$|V_{us}|$, $\xi_0$, $\xi_2$, $\xi_\text{LD}$, $f_K$, and $m_c$. We find that
the standard model with exclusive $|V_{cb}|$ and other lattice QCD inputs
describes only 66\% of the experimental value of $|\varepsilon_K|$ and does not
explain its remaining 34\%, which leads to a strong tension in
$|\varepsilon_K|$ at the $4.5\sigma \sim 3.7\sigma$ level between the SM theory
and experiment. We also find that this tension disappears when we use the
inclusive value of $|V_{cb}|$ obtained using the heavy quark expansion based on
the QCD sum rule approach.


title: Residual Bootstrap Exploration for Stochastic Linear Bandit

abstract:
  We propose a new bootstrap-based online algorithm for stochastic linear
bandit problems. The key idea is to adopt residual bootstrap exploration, in
which the agent estimates the next step reward by re-sampling the residuals of
mean reward estimate. Our algorithm, residual bootstrap exploration for
stochastic linear bandit (\texttt{LinReBoot}), estimates the linear reward from
its re-sampling distribution and pulls the arm with the highest reward
estimate. In particular, we contribute a theoretical framework to demystify
residual bootstrap-based exploration mechanisms in stochastic linear bandit
problems. The key insight is that the strength of bootstrap exploration is
based on collaborated optimism between the online-learned model and the
re-sampling distribution of residuals. Such observation enables us to show that
the proposed \texttt{LinReBoot} secure a high-probability $\tilde{O}(d
\sqrt{n})$ sub-linear regret under mild conditions. Our experiments support the
easy generalizability of the \texttt{ReBoot} principle in the various
formulations of linear bandit problems and show the significant computational
efficiency of \texttt{LinReBoot}.


title:
Wigner's approach enabled detection of genuine multipartite nonlocality
  and its finer characterisation using all different bipartitions

abstract:
  Distinct from Bell's approach, Wigner had derived a form of local realist
(LR) inequality which is quantum mechanically violated for a bipartite
maximally entangled state. Subsequently, this approach was generalized to
obtain a multipartite LR inequality. However, the violation of such generalised
Wigner's inequality does not signify what has been called genuine multipartite
nonlocality, meaning nonlocality between any one subsystem and all other
subsystems. In the present work, this limitation has been overcome by
formulating a further extension of Wigner's approach through the derivation of
a set of LR inequalities with respect to all different bipartitions of a
N-partite system. Quantum mechanical violations of the full set of such LR
inequalities would rigorously certify genuine multipartite nonlocality. An
additional significant feature of our scheme is that it also provides a finer
characterization of the nature of nonlocality embodied in a multipartite
quantum state in the following sense. In the absence of genuine multipartite
nonlocality, the multipartite LR inequalities such as the Svetlichny inequality
cannot be used to detect whether there is any particular bipartition which is
nonlocally correlated. On the other hand, the quantum violation of any given
inequality of our complete set of LR inequalities would enable identification
of the particular bipartition which exhibits nonlocality. The efficacy of the
scheme developed in this paper is illustrated for the tripartite and
quadripartite states.