title:
Simultaneous Transmission and Reflection Reconfigurable Intelligent
  Surface Assisted Full-Duplex Communications

abstract:
  This work demonstrates the effectiveness of a novel simultaneous transmission
and reflection reconfigurable intelligent surface (STAR-RIS) in Full-Duplex
(FD) aided communication system. The objective is to minimize the total
transmit power by jointly designing the transmit power and the transmitting and
reflecting (T&R) coefficients of the STAR-RIS. To solve the nonconvex problem,
an efficient algorithm is proposed by utilizing the alternating optimization
framework to iteratively optimize variables. Specifically, in each iteration,
we drive the closed-form expression for the optimal power design. The
successive convex approximation (SCA) method and semidefinite program (SDP) are
used to solve the passive beamforming optimization problem. Numerical results
verify the convergence and effectiveness of the proposed algorithm, and further
reveal in which scenarios STAR-RIS assisted FD communication defeats the
Half-Duplex and conventional RIS.


title: OneRel:Joint Entity and Relation Extraction with One Module in One Step

abstract:
  Joint entity and relation extraction is an essential task in natural language
processing and knowledge graph construction. Existing approaches usually
decompose the joint extraction task into several basic modules or processing
steps to make it easy to conduct. However, such a paradigm ignores the fact
that the three elements of a triple are interdependent and indivisible.
Therefore, previous joint methods suffer from the problems of cascading errors
and redundant information. To address these issues, in this paper, we propose a
novel joint entity and relation extraction model, named OneRel, which casts
joint extraction as a fine-grained triple classification problem. Specifically,
our model consists of a scoring-based classifier and a relation-specific horns
tagging strategy. The former evaluates whether a token pair and a relation
belong to a factual triple. The latter ensures a simple but effective decoding
process. Extensive experimental results on two widely used datasets demonstrate
that the proposed method performs better than the state-of-the-art baselines,
and delivers consistent performance gain on complex scenarios of various
overlapping patterns and multiple triples.


title:
A Self-Tuning Impedance-based Interaction Planner for Robotic Haptic
  Exploration

abstract:
  This paper presents a novel interaction planning method that exploits
impedance tuning techniques in response to environmental uncertainties and
unpredictable conditions using haptic information only. The proposed algorithm
plans the robot's trajectory based on the haptic interaction with the
environment and adapts planning strategies as needed. Two approaches are
considered: Exploration and Bouncing strategies. The Exploration strategy takes
the actual motion of the robot into account in planning, while the Bouncing
strategy exploits the forces and the motion vector of the robot. Moreover,
self-tuning impedance is performed according to the planned trajectory to
ensure stable contact and low contact forces. In order to show the performance
of the proposed methodology, two experiments with a torque-controller robotic
arm are carried out. The first considers a maze exploration without obstacles,
whereas the second includes obstacles. The proposed method performance is
analyzed and compared against previously proposed solutions in both cases.
Experimental results demonstrate that: i) the robot can successfully plan its
trajectory autonomously in the most feasible direction according to the
interaction with the environment, and ii) a stable interaction with an unknown
environment despite the uncertainties is achieved. Finally, a scalability
demonstration is carried out to show the potential of the proposed method under
multiple scenarios.


title:
Synthesis and Characterization of a LiFe0.6Mn0.4PO4 Olivine Cathode for
  Application in a New Lithium Polymer Battery

abstract:
  A LiFe0.6Mn0.4PO4 (LFMP) cathode exploiting the olivine structure is herein
synthesized and characterized in terms of structure, morphology, and
electrochemical features in a lithium cell. The material shows reversibility of
the electrochemical process which evolves at 3.5 and 4 V versus Li+/Li due to
the Fe+2/Fe+3 and Mn+2/Mn+3 redox couples, respectively, as determined by
cyclic voltammetry. The LFMP has a well-defined olivine structure revealed by
X-ray diffraction, a morphology consisting of submicron particle aggregated
into micrometric clusters as indicated by scanning and transmission electron
microscopy, with a carbon weight ratio of about 4% as suggested by
thermogravimetry. The electrode is used in lithium cells subjected to
galvanostatic cycling with a conventional liquid electrolyte, and demonstrates
a maximum capacity of 130 mAh g-1, satisfactory rate capability, excellent
efficiency, and a stable trend. Therefore, the material is studied in a lithium
metal polymer cell exploiting an electrolyte based on polyethylene glycol
dimethyl ether with a solid configuration. The cell reveals very promising
features in terms of capacity, efficiency, and retention, and suggests the LFMP
material as a suitable electrode for polymer batteries characterized by
increased energy density and remarkable safety.


title:
Effect of electric interaction on the deflection and gravitational
  lensing in the strong field limit

abstract:
  The deflection angle $\Delta\phi$ of charged signals in general charged
spacetime in the strong field limit is analyzed in this work using a
perturbative method generalized from the neutral signal case. The solved
$\Delta\phi$ naturally contains the finite distance effect and takes a
quasi-power series form with a logarithmic divergence at the leading order. The
coefficients of the series contain both the gravitational and electric
contributions. Using the Reissner-Nordstr\"{o}m spacetime as an example, we
found that an electric repulsion (or attraction) tends to decrease (or
increase) the critical impact parameter $b_c$. If the repulsion is strong
enough, then $b_c$ can shrink to zero and the critical particle sphere $r_{0c}$
will disappear. These results are applied to the gravitational lensing of
charge signal, from which we solved the image positions, their magnifications
and time delays. It is found that in general, the electric repulsion (or
attraction) will decrease (or increase) the image apparent angles, the black
hole shadow size as well as their magnifications but increase (or decrease) the
time delay.


title:
Optical selection bias and projection effects in stacked galaxy cluster
  weak lensing

abstract:
  Cosmological constraints from current and upcoming galaxy cluster surveys are
limited by the accuracy of cluster mass calibration. In particular, optically
identified galaxy clusters are prone to selection effects that can bias the
weak lensing mass calibration. We investigate the selection bias of the stacked
cluster lensing signal associated with optically selected clusters, using as
case study clusters identified by the redMaPPer algorithm in the Buzzard
simulations. We find that at a given cluster halo mass, the residuals of
redMaPPer richness and weak lensing signal are positively correlated. As a
result, for a given richness selection, the stacked lensing signal is biased
high compared with what we would expect from the underlying halo mass
probability distribution. The cluster lensing selection bias can thus lead to
overestimated mean cluster mass and biased cosmology results. We show that this
selection bias largely originates from spurious member galaxies within +/-20 to
60 Mpc/h along the line of sight, highlighting the importance of quantifying
projection effects associated with the broad redshift distribution of member
galaxies in photometric cluster surveys. While our results qualitatively agree
with those in the literature, precise quantitative modelling of selection bias
is needed to achieve the goals of cluster lensing cosmology. An accurate
calibration of the cluster lensing selection bias will require synthetic
catalogues covering a wide range of galaxy-halo connection models.


title: Deep Regression Ensembles

abstract:
  We introduce a methodology for designing and training deep neural networks
(DNN) that we call "Deep Regression Ensembles" (DRE). It bridges the gap
between DNN and two-layer neural networks trained with random feature
regression. Each layer of DRE has two components, randomly drawn input weights
and output weights trained myopically (as if the final output layer) using
linear ridge regression. Within a layer, each neuron uses a different subset of
inputs and a different ridge penalty, constituting an ensemble of random
feature ridge regressions. Our experiments show that a single DRE architecture
is at par with or exceeds state-of-the-art DNN in many data sets. Yet, because
DRE neural weights are either known in closed-form or randomly drawn, its
computational cost is orders of magnitude smaller than DNN.


title:
On a generalized Aviles-Giga functional: compactness, zero-energy
  states, regularity estimates and energy bounds

abstract:
  Given any strictly convex norm $\|\cdot\|$ on $\mathbb{R}^2$ that is $C^1$ in
$\mathbb{R}^2\setminus\{0\}$, we study the generalized Aviles-Giga functional
\[I_{\epsilon}(m):=\int_{\Omega} \left(\epsilon \left|\nabla m\right|^2 +
\frac{1}{\epsilon}\left(1-\|m\|^2\right)^2\right) \, dx,\] for
$\Omega\subset\mathbb R^2$ and $m\colon\Omega\to\mathbb R^2$ satisfying
$\nabla\cdot m=0$. Using, as in the euclidean case $\|\cdot\|=|\cdot|$, the
concept of entropies for the limit equation $\|m\|=1$, $\nabla\cdot m=0$, we
obtain the following. First, we prove compactness in $L^p$ of sequences of
bounded energy. Second, we prove rigidity of zero-energy states (limits of
sequences of vanishing energy), generalizing and simplifying a result by
Bochard and Pegon. Third, we obtain optimal regularity estimates for limits of
sequences of bounded energy, in terms of their entropy productions. Fourth, in
the case of a limit map in $BV$, we show that lower bound provided by entropy
productions and upper bound provided by one-dimensional transition profiles are
of the same order. The first two points are analogous to what is known in the
euclidean case $\|\cdot\|=|\cdot|$, and the last two points are sensitive to
the anisotropy of the norm $\|\cdot\|$.


title:
New method for Earth neutral atmospheric density retrieval based on
  energy spectrum fitting during occultation with LE/\emph{Insight}-HXMT

abstract:
  We propose a new method for retrieving the atmospheric number density profile
in the lower thermosphere, based on the X-ray Earth occultation of the Crab
Nebula with the Hard X-ray Modulation Telescope (\emph{Insight}-HXMT)
Satellite. The absorption and scattering of X-rays by the atmosphere result in
changes in the X-ray energy, and the Earth's neutral atmospheric number density
can be directly retrieved by fitting the observed spectrum and spectrum model
at different altitude ranges during the occultation process. The pointing
observations from LE/\emph{Insight}-HXMT on 16 November 2017 are analyzed to
obtain high-level data products such as lightcurve, energy spectrum and
detector response matrix. The results show that the retrieved results based on
the spectrum fitting in the altitude range of 90--200 km are significantly
lower than the atmospheric density obtained by the NRLMSISE-00 model,
especially in the altitude range of 110--120 km, where the retrieved results
are 34.4\% lower than the model values. The atmospheric density retrieved by
the new method is qualitatively consistent with previous independent X-ray
occultation results (Determan et al., 2007; Katsuda et al., 2021), which are
also lower than empirical model predictions. In addition, the accuracy of
atmospheric density retrieved results decreases with the increase of altitude
in the altitude range of 150--200 km, and the accurate quantitative description
will be further analyzed after analyzing a large number of X-ray occultation
data in the future.


title:
Evaluating Elements of Web-based Data Enrichment for Pseudo-Relevance
  Feedback Retrieval

abstract:
  In this work, we analyze a pseudo-relevance retrieval method based on the
results of web search engines. By enriching topics with text data from web
search engine result pages and linked contents, we train topic-specific and
cost-efficient classifiers that can be used to search test collections for
relevant documents. Building upon attempts initially made at TREC Common Core
2018 by Grossman and Cormack, we address questions of system performance over
time considering different search engines, queries, and test collections. Our
experimental results show how and to which extent the considered components
affect the retrieval performance. Overall, the analyzed method is robust in
terms of average retrieval performance and a promising way to use web content
for the data enrichment of relevance feedback methods.


title: On freely-jointed chain models with flexible links

abstract:
  Analytical relations for the mechanical response of single polymer chains are
valuable for modeling purposes, on both the molecular and continuum scale.
These relations can be obtained using statistical thermodynamics and an
idealized single-chain model, such as the freely-jointed chain model. In order
to include bond stretching, the rigid links in the freely-jointed chain model
can be made flexible, but this almost always renders the model analytically
intractable. Here, an asymptotically-correct statistical thermodynamic theory
is used to develop analytic approximations for the single-chain mechanical
response of this model. The accuracy of these approximations is demonstrated
using several link potential energy functions. This approach can be applied to
other single-chain models, and to molecular stretching in general.


title: Eigenvalue-flipping Algorithm for Matrix Monte Carlo

abstract:
  Many physical systems can be described in terms of matrix models that we
often cannot solve analytically. Fortunately, they can be studied numerically
in a straightforward way. Many commonly used algorithms follow the Monte Carlo
method, which is efficient for small matrix sizes but cannot guarantee
ergodicity when working with large ones. In this paper, we propose an
improvement of the algorithm that, for a large class of matrix models, allows
to tunnel between various vacua in a proficient way, where sign change of
eigenvalues is proposed externally. We test the method on two models: the pure
potential matrix model and the scalar field theory on the fuzzy sphere.


title: Likelihood ratio tests under model misspecification in high dimensions

abstract:
  We investigate the likelihood ratio test for a large block-diagonal
covariance matrix with an increasing number of blocks under the null
hypothesis. While so far the likelihood ratio statistic has only been studied
for normal populations, we establish that its asymptotic behavior is invariant
under a much larger class of distributions. This implies robustness against
model misspecification, which is common in high-dimensional regimes.
Demonstrating the flexibility of our approach, we additionally establish
asymptotic normality of the log-likelihood ratio test for the equality of many
large sample covariance matrices under model uncertainty. A simulation study
emphasizes the usefulness of our findings.


title: Modelling Quintessential Inflation in Palatini Modified Gravity

abstract:
  We study a model of quintessential inflation constructed in $R^2$ modified
gravity with a non-minimally coupled scalar field, in the Palatini formalism.
Our non-minimal inflaton field is characterised by a simple exponential
potential. We find that successful quintessential inflation can be achieved
with no fine-tuning on the model parameters. Predictions on the characteristics
of dark energy will be tested by observations in the near future, while
contrast with existing observations provides insights on the modified gravity
background, such as the value of the non-minimal coupling and its running.


title: Semantic Norm Recognition and its application to Portuguese Law

abstract:
  Being able to clearly interpret legal texts and fully understanding our
rights, obligations and other legal norms has become progressively more
important in the digital society. However, simply giving citizens access to the
laws is not enough, as there is a need to provide meaningful information that
cater to their specific queries and needs. For this, it is necessary to extract
the relevant semantic information present in legal texts. Thus, we introduce
the SNR (Semantic Norm Recognition) system, an automatic semantic information
extraction system trained on a domain-specific (legal) text corpus taken from
Portuguese Consumer Law. The SNR system uses the Portuguese Bert (BERTimbau)
and was trained on a legislative Portuguese corpus. We demonstrate how our
system achieved good results (81.44\% F1-score) on this domain-specific corpus,
despite existing noise, and how it can be used to improve downstream tasks such
as information retrieval.


title: Integrability breaking in the Rule 54 cellular automaton

abstract:
  Cellular automata have recently attracted a lot of attention as testbeds to
explore the emergence of many-body quantum chaos and hydrodynamics. We consider
the Rule 54 model, one of the simplest interacting integrable models featuring
two species of quasiparticles (solitons), in the presence of an
integrability-breaking perturbation that allows solitons to backscatter. We
study the onset of thermalization and diffusive hydrodynamics in this model,
compute perturbatively the diffusion constant of tracer particles, and comment
on its relation to transport coefficients.

categories: cond-mat.stat-mech nlin.CG nlin.SI quant-ph


title:
Almost all alternating groups are invariably generated by two elements
  of prime order

abstract:
  We show that for all $n\leq X$ apart from $O(X\exp(-c(\log X)^{1/2}(\log \log
X)^{1/2}))$ exceptions, the alternating group $A_n$ is invariably generated by
two elements of prime order. This answers (in a quantitative form) a question
of Guralnick, Shareshian and Woodroofe.


title: IRS-enabled Breath Tracking with Colocated Commodity WiFi Transceivers

abstract:
  Intelligent reflecting surfaces (IRS) are a key enabler of various new
applications in 6G smart radio environments. By utilizing an IRS prototype
system, this paper aims to enhance self-interference (SI) cancellation for
breath tracking with commodity WiFi devices. SI suppression is a crucial
requirement for breath tracking with a single antenna site as the SI severely
limits the radio sensing range by shadowing the received signal with its own
transmit signal. To this end, we propose to assist SI cancellation by
exploiting an IRS to form a suitable cancellation signal in the analog domain.
Building upon a 256-element IRS prototype, we present results of breath
tracking with IRS-assisted SI cancellation from a practical testbed. We use
inexpensive WiFi hardware to extract the Channel State Information (CSI) in the
5~GHz band and analyze the phase change between a colocated transmitter and
receiver with added local oscillator (LO) synchronization. We are able to track
the breath of a test person regardless of the position in an indoor environment
in a room-level range. The presented case study shows promising performance in
both capturing the breath frequency as well as the breathing patterns.


title:
Customized anti-reflection structure for perfect transmission through
  complex media

abstract:
  Getting to grips with the detrimental influence of disordered environments on
wave propagation is an interdisciplinary endeavour spanning diverse research
areas ranging from telecommunications \cite{basar_wireless_2019} and
bio-medical imaging \cite{kubby_wavefront_2019} to seismology
\cite{Campillo2003} and material engineering \cite{Chen2010,Molesky2018}.
Wavefront shaping techniques are highly promising to overcome the effect of
wave scattering as even opaque media feature open channels for which the
incident light is fully transmitted
\cite{Dorokhov1984,Gerardin2014,Sarma2016,Jeong18}. With this feature being
restricted, however, to just a small subset of judiciously engineered states it
remains out of reach to render an opaque sample translucent for any incident
light field. Here we show that a structureless medium composed of randomly
assembled scattering elements can be made fully transmitting to all incoming
wavefronts by putting a customized complementary medium in front of it. This
special situation is achieved when the reflection matrices of the two media
surfaces facing each other satisfy a matrix generalization of the condition for
critical coupling. We implement this protocol both numerically and
experimentally for the design of electromagnetic waveguides with several dozen
scattering elements placed inside of them. The translucent scattering media we
introduce here also have the promising property of being able to store incident
radiation in their interior for remarkably long times.


title: Overview of LiLAS 2021 -- Living Labs for Academic Search

abstract:
  The Living Labs for Academic Search (LiLAS) lab aims to strengthen the
concept of user-centric living labs for academic search. The methodological gap
between real-world and lab-based evaluation should be bridged by allowing lab
participants to evaluate their retrieval approaches in two real-world academic
search systems from life sciences and social sciences. This overview paper
outlines the two academic search systems LIVIVO and GESIS Search, and their
corresponding tasks within LiLAS, which are ad-hoc retrieval and dataset
recommendation. The lab is based on a new evaluation infrastructure named
STELLA that allows participants to submit results corresponding to their
experimental systems in the form of pre-computed runs and Docker containers
that can be integrated into production systems and generate experimental
results in real-time. Both submission types are interleaved with the results
provided by the productive systems allowing for a seamless presentation and
evaluation. The evaluation of results and a meta-analysis of the different
tasks and submission types complement this overview.


title:
RACIMO@Bucaramanga: A Citizen Science Project on Data Science and
  Climate Awareness

abstract:
  This paper describes a collaborative experience to empower organized
communities to produce, curate and disseminate environmental data. A particular
emphasis is done on the description of open hardware & software architecture
and the processes of commissioning of the low cost Arduino-Raspberry-Pi weather
station which measures: atmospheric pressure, temperature, humidity,
precipitation, cloudiness, and illuminance/irradiance. The idea is to encourage
more people to replicate this open-science initiative. We have started this
experience training students & teachers from seven mid secondary schools
through a syllabus of 12 two-hours lectures with a web-based support which
exposes them to basic concepts and practices of Citizen Science and Open Data
Science.


title: Estimates for the largest critical value of $T_n^{(k)}$

abstract:
  Here we study the quantity $$
\tau_{n,k}:=\frac{|T_n^{(k)}(\omega_{n,k})|}{T_n^{(k)}(1)}\,, $$ where $T_n$ is
the $n$-th Chebyshev polynomial of the first kind and $\omega_{n,k}$ is the
largest zero of $T_n^{(k+1)}$. Since the absolute values of the local extrema
of $T_n^{(k)}$ increase monotonically towards the end-points of $[-1,1]$, the
value $\tau_{n,k}$ shows how small is the largest critical value of
$\,T_n^{(k)}\,$ relative to its global maximum $\,T_n^{(k)}(1)$. This is a
continuation of the recent paper \cite{NNS2018}, where upper bounds and
asymptotic formuae for $\tau_{n,k}$ have been obtained on the basis of Alexei
Shadrin's explicit form of the Schaeffer--Duffin pointwise majorant for
polynomials with absolute value not exceeding $1$ in $[-1,1]$.
  We exploit a result of Knut Petras \cite{KP1996} about the weights of the
Gaussian quadrature formulae associated with the ultraspherical weight function
$w_{\lambda}(x)=(1-x^2)^{\lambda-1/2}$ to find an explicit (modulo
$\omega_{n,k}$) formula for $\tau_{n,k}^2$. This enables us to prove a lower
bound and to refine the upper bounds for $\tau_{n,k}$ obtained in
\cite{NNS2018}. The explicit formula admits also a new derivation of the
assymptotic formula in \cite{NNS2018} approximating $\tau_{n,k}$ for
$n\to\infty$. The new approach is simpler, without using deep results about the
ordinates of the Bessel function, and allows to better analyze the sharpness of
the estimates.


title: Percolation transition in phase separating active fluid

abstract:
  The motility-induced phase separation exhibited by active particles with
repulsive interactions is well known. We show that the interaction softness of
active particles destabilizes the highly ordered dense phase, leading to the
formation of a porous cluster which spans the system. This soft limit can also
be achieved if the particle motility is increased beyond a critical value, at
which the system clearly exhibits all the characteristics of a standard
percolation transition. We also show that in the athermal limit, active
particles exhibit similar transitions even at low motility. With these
additional new phases, the phase diagram of repulsive active particles is
revealed to be richer than what was previously conceived.


title:
Near-optimal Deep Reinforcement Learning Policies from Data for Zone
  Temperature Control

abstract:
  Replacing poorly performing existing controllers with smarter solutions will
decrease the energy intensity of the building sector. Recently, controllers
based on Deep Reinforcement Learning (DRL) have been shown to be more effective
than conventional baselines. However, since the optimal solution is usually
unknown, it is still unclear if DRL agents are attaining near-optimal
performance in general or if there is still a large gap to bridge.
  In this paper, we investigate the performance of DRL agents compared to the
theoretically optimal solution. To that end, we leverage Physically Consistent
Neural Networks (PCNNs) as simulation environments, for which optimal control
inputs are easy to compute. Furthermore, PCNNs solely rely on data to be
trained, avoiding the difficult physics-based modeling phase, while retaining
physical consistency. Our results hint that DRL agents not only clearly
outperform conventional rule-based controllers, they furthermore attain
near-optimal performance.


title: Cosh gradient systems and tilting

abstract:
  We review a class of gradient systems with dissipation potentials of
hyperbolic-cosine type. We show how such dissipation potentials emerge in large
deviations of jump processes, multi-scale limits of diffusion processes, and
more. We show how the exponential nature of the cosh derives from the
exponential scaling of large deviations and arises implicitly in cell problems
in multi-scale limits.
  We discuss in-depth the role of "tilting" of gradient systems. Certain
classes of gradient systems are "tilt-independent", which means that changing
the driving functional does not lead to changes of the dissipation potential.
Such tilt-independence separates the driving functional from the dissipation
potential, guarantees a clear modelling interpretation, and gives rise to
strong notions of gradient-system convergence.
  We show that although in general many gradient systems are tilt-independent,
certain cosh-type systems are not. We also show that this is inevitable, by
studying in detail the classical example of the Kramers high-activation-energy
limit, in which a diffusion converges to a jump process and the Wasserstein
gradient system converges to a cosh-type system. We show and explain how the
tilt-independence of the pre-limit system is lost in the limit system. This
same lack of independence can be recognized in classical theories of chemical
reaction rates in the chemical-engineering literature.
  We illustrate a similar lack of tilt-independence in a discrete setting. For
a class of "two-terminal" fast subnetworks, we give a complete characterization
of the dependence on the tilting, which strongly resembles the classical theory
of equivalent electrical networks.


title: A Twistorial Description of the IKKT-Matrix Model

abstract:
  We consider the fuzzy 4-sphere $S_N^4$ as a background in the IKKT matrix
model and explore the relation between $S_N^4$ and fuzzy twistor space in the
semi-classical limit. A novel description for the IKKT-matrix model in terms of
spinorial indices is given, which is reminiscent of $\mathcal{N}=4$
super-symmetric Yang-Mills (SYM) in $4d$. On fuzzy twistor space, the
interactions of the IKKT model are of gravitational type. The higher-spin (HS)
gauge theory emerging in this limit from the IKKT model, denoted as HS-IKKT, on
fuzzy twistor space is shown to be a higher-spin extension of $\mathcal{N}=4$
SYM, with vertices that have more than two derivatives. We obtain its
(Euclidean) spacetime action using the Penrose transform. Although this is a
gravitational theory, it shares many features with the higher-spin extensions
of Yang-Mills in $4d$ flat space obtained in arXiv:2105.12782,
arXiv:2107.04500. The tree-level amplitudes of the HS-IKKT are studied in the
semi-classical flat limit. The self-dual sector of the IKKT model is obtained
by dropping some parts of the cubic- and the quartic interactions, which is
shown to reduce to a BF-type action on commutative deformed projective twistor
space.


title:
IndicNLG Suite: Multilingual Datasets for Diverse NLG Tasks in Indic
  Languages

abstract:
  In this paper, we present the IndicNLG suite, a collection of datasets for
benchmarking Natural Language Generation (NLG) for 11 Indic languages. We focus
on five diverse tasks, namely, biography generation using Wikipedia infoboxes
(WikiBio), news headline generation, sentence summarization, question
generation and paraphrase generation. We describe the process of creating the
datasets and present statistics of the dataset, following which we train and
report a variety of strong monolingual and multilingual baselines that leverage
pre-trained sequence-to-sequence models and analyze the results to understand
the challenges involved in Indic language NLG. To the best of our knowledge,
this is the first NLG dataset for Indic languages and also the largest
multilingual NLG dataset. Our methods can also be easily applied to
modest-resource languages with reasonable monolingual and parallel corpora, as
well as corpora containing structured data like Wikipedia. We hope this dataset
spurs research in NLG on diverse languages and tasks, particularly for Indic
languages. The datasets and models are publicly available at
https://indicnlp.ai4bharat.org/indicnlg-suite.


title:
Deliberation in autonomous robotic surgery: a framework for handling
  anatomical uncertainty

abstract:
  Autonomous robotic surgery requires deliberation, i.e. the ability to plan
and execute a task adapting to uncertain and dynamic environments. Uncertainty
in the surgical domain is mainly related to the partial pre-operative knowledge
about patient-specific anatomical properties. In this paper, we introduce a
logic-based framework for surgical tasks with deliberative functions of
monitoring and learning. The DEliberative Framework for Robot-Assisted Surgery
(DEFRAS) estimates a pre-operative patient-specific plan, and executes it while
continuously measuring the applied force obtained from a biomechanical
pre-operative model. Monitoring module compares this model with the actual
situation reconstructed from sensors. In case of significant mismatch, the
learning module is invoked to update the model, thus improving the estimate of
the exerted force. DEFRAS is validated both in simulated and real environment
with da Vinci Research Kit executing soft tissue retraction. Compared with
state-of-the art related works, the success rate of the task is improved while
minimizing the interaction with the tissue to prevent unintentional damage.


title:
Spectral form factor in a minimal bosonic model of many-body quantum
  chaos

abstract:
  We study spectral statistics and especially the spectral form factor in
Floquet driven (kicked) bosonic chains. We consider a family of models where
free boson Hamiltonian with the nearest neighbor hopping and possibly pairing
terms is kicked with the terms diagonal in the Fock space basis, including
random chemical potentials and pair-wise interactions. It is shown that for
intermediate-range interactions, random phase approximation can be used to
rewrite the spectral form factor in terms of a bi-stochastic many-body process
generated by an effective bosonic Hamiltonian. In the particle-number
conserving case, i.e., when pairing terms are absent, the effective Hamiltonian
has a non-abelian $SU(1,1)$ symmetry, resulting in universal quadratic scaling
of the Thouless time with the system size, irrespective of the particle number.
This is a consequence of degenerate symmetry multiplets of the subleading
eigenvalue of the effective Hamiltonian and is broken by the particle number
breaking pairing terms. In the latter case, we numerically find a nontrivial
systematic dependence of the Thouless time on the system size, in contrast to a
related recent study for kicked fermionic chains.

categories: cond-mat.stat-mech math-ph math.MP nlin.CD physics.atom-ph quant-ph


title:
Observation of Fermi arcs and Weyl nodes in a non-centrosymmetric
  magnetic Weyl semimetal

abstract:
  Weyl semimetal (WSM), a novel state of quantum matter, hosts Weyl fermions as
emergent quasiparticles resulting from the breaking of either inversion or
time-reversal symmetry. Magnetic WSMs that arise from broken time-reversal
symmetry provide an exceptional platform to understand the interplay between
magnetic order and Weyl physics, but few WSMs have been realized. Here, we
identify CeAlSi as a new non-centrosymmetric magnetic WSM via angle-resolved
photoemission spectroscopy (ARPES) and first-principles, density-functional
theory based calculations. Our surface-sensitive vacuum ultraviolet ARPES data
confirms the presence of surface Fermi arcs as, the smoking gun evidence for
the existence of the Weyl semimetallic state in CeAlSi. We also observe bulk
Weyl cones in CeAlSi using bulk-sensitive soft-X-ray ARPES measurements. In
addition, Ce 4f at bands are found near the Fermi level, indicating that CeAlSi
is a unique platform for investigating exotic quantum phenomena resulting from
the interaction of topology, magnetism and electronic correlations.


title:
Electron-induced excitation, recombination and dissociation of molecular
  ions initiating the formation of complex organic molecules

abstract:
  We review the study of dissociative recombination and ro-vibrational
excitation of diatomic and small polyatomic molecular ions initiating complex
organic molecules formation. In particular, we show how Multichannel Quantum
Defect Theory (MQDT) and R-matrix methods are used to compute cross sections
and rate coefficients for cations in well defined ro-vibrational levels of the
ground electronic state, from sub-meV up to few eV collision energies.
  The most recent MQDT results are compared with either other theoretical data,
or with measured data obtained in storage-ring experiments.

categories: physics.chem-ph astro-ph.IM physics.atom-ph physics.plasm-ph


title:
Conics on Gushel-Mukai fourfolds, EPW sextics and Bridgeland moduli
  spaces

abstract:
  We identify the double dual EPW sextic $\widetilde{Y}_{A^{\perp}}$ and the
double EPW sextic $\widetilde{Y}_A$, associated with a very general
Gushel-Mukai fourfold $X$, with the Bridgeland moduli spaces of stable objects
of character $\Lambda_1$ and $\Lambda_2$ in the Kuznetsov component
$\mathcal{K}u(X)$. This provides an affirmative answer to a question of
Perry-Pertusi-Zhao. As an application, we prove a conjecture of Kuznetsov-Perry
for very general Gushel-Mukai fourfolds.


title:
Bias-variance decomposition of overparameterized regression with random
  linear features

abstract:
  In classical statistics, the bias-variance trade-off describes how varying a
model's complexity (e.g., number of fit parameters) affects its ability to make
accurate predictions. According to this trade-off, optimal performance is
achieved when a model is expressive enough to capture trends in the data, yet
not so complex that it overfits idiosyncratic features of the training data.
Recently, it has become clear that this classic understanding of the
bias-variance must be fundamentally revisited in light of the incredible
predictive performance of "overparameterized models" -- models that avoid
overfitting even when the number of fit parameters is large enough to perfectly
fit the training data. Here, we present results for one of the simplest
examples of an overparameterized model: regression with random linear features
(i.e. a two-layer neural network with a linear activation function). Using the
zero-temperature cavity method, we derive analytic expressions for the training
error, test error, bias, and variance. We show that the linear random features
model exhibits three phase transitions: two different transitions to an
interpolation regime where the training error is zero, along with an additional
transition between regimes with large bias and minimal bias. Using random
matrix theory, we show how each transition arises due to small nonzero
eigenvalues in the Hessian matrix. Finally, we compare and contrast the phase
diagram of the random linear features model to the random nonlinear features
model and ordinary regression, highlighting the new phase transitions that
result from the use of linear basis functions.


title: Relative Regular Riemann-Hilbert correspondence II

abstract:
  We develop the theory of relative regular holonomic D-modules with a smooth
complex manifold S of arbitrary dimension as parameter space, together with
their main functorial properties. In particular, we establish in this general
setting the relative Riemann-Hilbert correspondence proved in a previous work
in the one-dimensional case.


title:
The topological inequivalence of Hall bar versus Corbino geometries in
  real space

abstract:
  This work discusses the effect of topology in the frame of direct Coulomb
interactions, considering two distinct geometries, namely the Hall bar and the
Corbino disc. In the mainstream approaches to the quantized Hall effect, the
consequences of interactions are usually underestimated. Here, we investigate
the electron number density, potential and current distributions within the
screening theory that considers electron-electron interactions. Inclusion of
direct Coulomb interaction and realistic boundary conditions result in local
metal-like compressible and (Topological) insulator-like incompressible
regions. Consequently, we show that the bulk of both geometries in coordinate
space is not incompressible throughout the quantized Hall plateau. Furthermore,
placing two inner contacts within the Hall bar geometry shows that the
quantization is unaffected by changing the genus number in real space. Finally,
we propose novel experiments which will enable us to distinguish the
topological properties of the two geometries in the configuration space.


title: Algorithms for the Maximum Eulerian Cycle Decomposition Problem

abstract:
  Given an Eulerian graph G, in the Maximum Eulerian Cycle Decomposition
problem, we are interested in finding a collection of edge-disjoint cycles
{E_1, E_2, ..., E_k} in G such that all edges of G are in exactly one cycle and
k is maximum. We present an algorithm to solve the pricing problem of a column
generation Integer Linear Programming (ILP) model introduced by Lancia and
Serafini (2016). Furthermore, we propose a greedy heuristic, which searches for
minimum size cycles starting from a random vertex, and a heuristic based on
partially solving the ILP model. We performed tests comparing the three
approaches in relation to the quality of solutions and execution time, using
distinct sets of Eulerian graphs, each set grouping graphs with different
numbers of vertices and edges. Our experimental results show that the ILP based
heuristic outperforms the other methods.


title:
Global uniform in $N$ estimates for solutions of a system of
  Hartree-Fock-Bogoliubov type in the case $\beta<1$

abstract:
  We extend the results of the 2019 paper by the third and fourth author
globally in time. More precisely, we prove uniform in $N$ estimates for the
solutions $\phi$, $\Lambda$ and $\Gamma$ of a coupled system of
Hartree-Fock-Bogoliubov type with interaction potential $V_N(x-y)=N^{3
\beta}v(N^{\beta}(x-y))$ with $\beta<1$. The potential satisfies some technical
conditions, but is not small. The initial conditions have finite energy and the
"pair correlation" part satisfies a smallness condition, but are otherwise
general functions in suitable Sobolev spaces, and the expected correlations in
$\Lambda$ develop dynamically in time. The estimates are expected to improve
the Fock space bounds from the 2021 paper of the first and fifth author. This
will be addressed in a different paper.


title: Symplectic non-convexity of toric domains

abstract:
  We investigate the convexity up to symplectomorphism (called symplectic
convexity) of star-shaped toric domains in $\mathbb R^4$. In particular, based
on the criterion from Chaidez-Edtmair via Ruelle invariant and systolic ratio
of the boundary of star-shaped toric domains, we provide elementary operations
on domains that can kill the symplectic convexity. These operations only result
in $C^0$-small perturbations in terms of domains' volume. Moreover, one of the
operations is a systematic way to produce examples of dynamically convex but
not symplectically convex toric domains. Finally, we are able to provide
concrete bounds for the constants that appear in Chaidez-Edtmair's criterion.


title:
Artificial Intelligence in Vehicular Wireless Networks: A Case Study
  Using ns-3

abstract:
  Artificial intelligence (AI) techniques have emerged as a powerful approach
to make wireless networks more efficient and adaptable. In this paper we
present an ns-3 simulation framework, able to implement AI algorithms for the
optimization of wireless networks. Our pipeline consists of: (i) a new
geometry-based mobility-dependent channel model for V2X; (ii) all the layers of
a 5G-NR-compliant protocol stack, based on the ns3-mmwave module; (iii) a new
application to simulate V2X data transmission, and (iv) a new intelligent
entity for the control of the network via AI. Thanks to its flexible and
modular design, researchers can use this tool to implement, train, and evaluate
their own algorithms in a realistic and controlled environment. We test the
behavior of our framework in a Predictive Quality of Service (PQoS) scenario,
where AI functionalities are implemented using Reinforcement Learning (RL), and
demonstrate that it promotes better network optimization compared to baseline
solutions that do not implement AI.


title:
The Magellanic Edges Survey III. Kinematics of the disturbed LMC
  outskirts

abstract:
  We explore the structural and kinematic properties of the outskirts of the
Large Magellanic Cloud (LMC) using data from the Magellanic Edges Survey
(MagES) and Gaia EDR3. Even at large galactocentric radii
($8^\circ<R<11^\circ$), we find the north-eastern LMC disk is relatively
unperturbed: its kinematics are consistent with a disk of inclination
~$36.5^\circ$ and line-of-nodes position angle ~$145^\circ$ east of north. In
contrast, fields at similar radii in the southern and western disk are
significantly perturbed from equilibrium, with non-zero radial and vertical
velocities, and distances significantly in front of the disk plane implied by
our north-eastern fields. We compare our observations to simple dynamical
models of the Magellanic/Milky Way system which describe the LMC as a
collection of tracer particles within a rigid potential, and the Small
Magellanic Cloud (SMC) as a rigid Hernquist potential. A possible SMC crossing
of the LMC disk plane ~400 Myr ago, in combination with the LMC's infall to the
Milky Way potential, can qualitatively explain many of the perturbations in the
outer disk. Additionally, we find the claw-like and arm-like structures south
of the LMC have similar metallicities to the outer LMC disk ([Fe/H]~-1), and
are likely comprised of perturbed LMC disk material. The claw-like substructure
is particularly disturbed, with out-of-plane velocities >60 km s$^{-1}$ and
apparent counter-rotation relative to the LMC's disk motion. More detailed
N-body models are necessary to elucidate the origin of these southern features,
potentially requiring repeated interactions with the SMC prior to ~1 Gyr ago.


title: On the binary digits of $n$ and $n^2$

abstract:
  Let $s(n)$ denote the sum of digits in the binary expansion of the integer
$n$. Hare, Laishram and Stoll (2011) studied the number of odd integers such
that $s(n)=s(n^2)=k$, for a given integer $k\geq 1$. The remaining cases that
could not be treated by theses authors were $k\in\{9,10,11,14,15\}$. In this
paper we show that there is only a finite number of solutions for
$k\in\{9,10,11\}$ and comment on the difficulties to settle the two remaining
cases $k\in\{14,15\}$. A related problem is to study the solutions of
$s(n^2)=4$ for odd integers. Bennett, Bugeaud and Mignotte (2012) proved that
there are only finitely many solutions and conjectured that $n=13,15,47,111$
are the only solutions. In this paper, we give an algorithm to find all
solutions with fixed sum of digits value, supporting this conjecture, as well
as show related results for $s(n^2)=5$.


title:
Invariant domain preserving high-order spectral discontinuous
  approximations of hyperbolic systems

abstract:
  We propose a limiting procedure to preserve invariant domains with time
explicit discrete high-order spectral discontinuous approximate solutions to
hyperbolic systems of conservation laws. Provided the scheme is discretely
conservative and satisfy geometric conservation laws at the discrete level, we
derive a condition on the time step to guaranty that the cell-averaged
approximate solution is a convex combination of states in the invariant domain.
These states are then used to define local bounds which are then imposed to the
full high-order approximate solution within the cell via an a posteriori
scaling limiter. Numerical experiments are then presented with modal and nodal
discontinuous Galerkin schemes confirm the robustness and stability enhancement
of the present approach.


title:
THA 15-31: Discovery with VLT/X-Shooter and Swift/UVOT of a new
  symbiotic star of the accreting-only variety

abstract:
  We report the discovery and characterization of a new symbiotic star of the
accreting-only variety, which we observed in the optical/near-infrared (NIR)
with VLT/X-Shooter and in the X-rays/ultraviolet with Swift/UVOT+XRT. The new
symbiotic star, THA 15-31, was previously described as a pre-main sequence star
belonging to the Lupus~3 association. Our observations, ancillary data, and
Gaia EDR3 parallax indicate that THA 15-31 is a symbiotic star composed of an
M6III red giant and an accreting companion, is subject to E(B-V)=0.38
reddening, and is located at a distance of ~12 kpc and at 1.8 kpc above the
Galactic plane in the outskirts of the Bulge. The luminosity of the accreting
companion is ~100 Lsun, placing THA 15-31 among the symbiotic stars accreting
at a high rate (2.5e-08 Msun/yr if the accretion is occurring on a white dwarf
of 1 Msun). The observed emission lines originate primarily from HI, HeI, and
FeII, with no HeII or other high-excitation lines observed; a sharp central
absorption superimposed on the Balmer emission lines is observed, while all
other lines have a simple Gaussian-like profile. The emission from the
companion dominates over the M6III red giant at $U$ and $B$-band wavelengths,
and is consistent with an origin primarily in an optically thick accretion
disk. No significant photometric variability is observed at optical or NIR
wavelengths, suggesting either a face-on orbital orientation and/or that the
red giant is far from Roche-lobe filling conditions. The profile of emission
lines supports a low orbital inclination if they form primarily in the
accretion disk. An excess emission is present in AllWISE W3 (12 micron) and W4
(22 micron) data, radiating a luminosity ~35 Lsun, consistent with thermal
emission from optically thin circumstellar dust.


title: Quantum edge correspondences and quantum Cuntz-Krieger algebras

abstract:
  Given a quantum graph $\mathcal{G}=(B,\psi,A)$, we define a C*-correspondence
$E_\mathcal{G}$ over the noncommutative vertex C*-algebra $B$, called the
quantum edge correspondence. For a classical graph $\mathcal{G}$,
$E_\mathcal{G}$ is the usual graph correspondence spanned by the edges of
$\mathcal{G}$. When the quantum adjacency matrix $A\colon B\to B$ is completely
positive, we show that $E_\mathcal{G}$ is faithful if and only if $\ker(A)$
does not contain a central summand of $B$. In this case, we show that the
Cuntz-Pimsner algebra $\mathcal{O}_{E_\mathcal{G}}$ is isomorphic to a quotient
of the quantum Cuntz-Krieger algebra $\mathcal{O}(\mathcal{G})$ defined by
Brannan, Eifler, Voigt, and Weber. Moreover, the kernel of the quotient map is
shown to be generated by "localized" versions of the quantum Cuntz-Krieger
relations, and $\mathcal{O}_{E_\mathcal{G}}$ is shown to be the universal
object associated to these local relations. We study in detail some concrete
examples and make connections with the theory of Exel crossed products.


title: Neutrino forces and the Sommerfeld enhancement

abstract:
  The Sommerfeld enhancement plays an important role in dark matter (DM)
physics, and can significantly enhance the annihilation cross section of
non-relativistic DM particles. In this paper, we study the effect of neutrino
forces, which are generated by the exchange of a pair of light neutrinos, on
the Sommerfeld enhancement. We demonstrate that in certain cases, a neutrino
force can cause a significant correction to the Sommerfeld enhancement. Models
that can realise DM-neutrino interactions and sizeable Sommerfeld enhancement
are also briefly discussed, together with the impacts on DM phenomenology of
neutrino forces.


title: End-to-end science operations in the era of extremely large telescopes

abstract:
  Observatory end-to-end science operations is the overall process starting
with a scientific question, represented by a proposal requesting observing
time, and ending with the analysis of observation data addressing that
question, and including all the intermediate steps needed to plan, schedule,
obtain, and process these observations. Increasingly complex observing
facilities demand a highly efficient science operations approach and at the
same time be user friendly to the astronomical user community and enable the
highest possible scientific return. Therefore, this process is supported by a
collection of tools. In this paper, we describe the overall end-to-end process
and its implementation for the three upcoming extremely large telescopes
(ELTs), ESO's ELT, the Thirty Meter Telescope (TMT), and the Giant Magellan
Telescope (GMT).


title:
Accelerated gradient methods combining Tikhonov regularization with
  geometric damping driven by the Hessian

abstract:
  In a Hilbert setting, for convex differentiable optimization, we consider
accelerated gradient dynamics combining Tikhonov regularization with
Hessian-driven damping. The Tikhonov regularization parameter is assumed to
tend to zero as time tends to infinity, which preserves equilibria. The
presence of the Tikhonov regularization term induces a strong convexity
property which vanishes asymptotically. To take advantage of the exponential
convergence rates attached to the heavy ball method in the strongly convex
case, we consider the inertial dynamic where the viscous damping coefficient is
taken proportional to the square root of the Tikhonov regularization parameter,
and therefore also converges towards zero. Moreover, the dynamic involves a
geometric damping which is driven by the Hessian of the function to be
minimized, which induces a significant attenuation of the oscillations. Under
an appropriate tuning of the parameters, based on Lyapunov's analysis, we show
that the trajectories have at the same time several remarkable properties: they
provide fast convergence of values, fast convergence of gradients towards zero,
and strong convergence to the minimum norm minimizer. This study extends a
previous paper by the authors where similar issues were examined but without
the presence of Hessian driven damping.


title: The H.E.S.S. transients follow-up system

abstract:
  Observations of astrophysical transients have brought many novel discoveries
and provided new insights into physical processes at work under extreme
conditions in the Universe. Multi-wavelength and multi-messenger observations
of variable objects require dedicated procedures and follow-up systems capable
of digesting and reacting to external alerts to execute coordinated follow-ups.
The main functions of such follow-up systems are the processing, filtering, and
ranking of incoming alerts, the fully automated rapid execution of the
observations according to an observation strategy tailored to the instrument,
and real-time data analysis with feedback to the operators and other
instruments. H.E.S.S. has been searching for transient phenomena since its
inauguration in 2003. In this paper, we describe the transients follow-up
system of H.E.S.S, which became operational in 2016. The transients follow-up
system allows H.E.S.S. to conduct a more versatile, optimised, and largely
autonomous transient follow-up program, combining all major functionalities in
one systematic approach. We describe the design, central functionalities, and
interfaces of the transients follow-up system in general and its three main
components in detail: the Target of Opportunity (ToO) alert system, the data
acquisition and central control system, and the real-time analysis. We
highlight architectural decisions and detailed features that enable fully
automatic ToO follow-up and indicate key performance metrics of the
sub-systems. We discuss the system's capabilities and highlight the need for a
fine-tuned interplay of the different sub-systems to react quickly and
reliably. Lessons learnt from the development, integration, and operation of
the H.E.S.S. transients follow-up system are reviewed in light of new and large
science infrastructures and associated challenges in this exciting new era of
interoperable astronomy.


title:
On the Einstein relation between mobility and diffusion coefficient in
  an active bath

abstract:
  An active bath, made of self-propelling units, is a nonequilibrium medium in
which the Einstein relation $D=\mu k_B T$ between the mobility $\mu$ and the
diffusivity $D$ of a tracer particle cannot be expected to hold a priori. We
consider here heavy tracers for which these coefficients can be related to
correlation functions which we estimate. We show that, to a good approximation,
an Einstein relation does hold in an active bath upon using a different
temperature which is defined mechanically, through the pressure exerted on the
tracer.


title: Stellar obliquities in exoplanetary systems

abstract:
  The rotation of a star and the revolutions of its planets are not necessarily
aligned. This article reviews the measurement techniques, key findings, and
theoretical interpretations related to the obliquities (spin-orbit angles) of
planet-hosting stars. The best measurements are for stars with short-period
giant planets, which have been found on prograde, polar, and retrograde orbits.
It seems likely that dynamical processes such as planet-planet scattering and
secular perturbations are responsible for tilting the orbits of close-in giant
planets, just as those processes are implicated in exciting orbital
eccentricities. The observed dependence of the obliquity on orbital separation,
planet mass, and stellar structure suggests that in some cases, tidal
dissipation damps a star's obliquity within its main-sequence lifetime. The
situation is not as clear for stars with smaller or wider-orbiting planets.
Although the earliest measurements of such systems tended to find low
obliquities, some glaring exceptions are now known in which the star's rotation
is misaligned with respect to the coplanar orbits of multiple planets. In
addition, statistical analyses based on projected rotation velocities and
photometric variability have found a broad range of obliquities for F-type
stars hosting compact multiple-planet systems. The results suggest it is unsafe
to assume that stars and their protoplanetary disks are aligned. Primordial
misalignments might be produced by neighboring stars or more complex events
that occur during the epoch of planet formation.


title:
Binary neutron star mergers as a probe of quark-hadron crossover
  equations of state

abstract:
  It is anticipated that the gravitational radiation detected in future
gravitational wave (GW) detectors from binary neutron star (NS) mergers can
probe the high density equation of state (EOS). We simulate binary NS mergers
which adopt various quark-hadron crossover (QHC) EOSs which are constructed
from combinations of a hardronic EOS ($n_{b} < 2~n_0$) and a quark-matter EOS
($n_{b} > 5~n_0$), where $n_{b}$ and $n_0$ are the baryon number density and
the nuclear saturation density, respectively. At the crossover densities ($2~
n_0 < n_{b} < 5~ n_0$), the QHC EOSs have a gradually increasing stiffness
reaching to the stiffness of the strongly correlated quark matter. This
enhanced stiffness leads to much longer lifetimes of the hypermassive NS than
that for a pure hadronic EOS. We find a dual nature of these EOSs such that
their maximum chirp GW frequencies $f_{max}$ fall into the category of a soft
EOS while the dominant peak frequencies ($f_{peak}$) of the postmerger stage
falls in between that of a soft and stiff hadronic EOSs. An observation of this
kind of dual nature in the characteristic GW frequencies will provide crucial
evidence for the existence of strongly interacting quark matter at the
crossover densities for QCD.


title: The Mg-K anti-correlation in Omega Centauri

abstract:
  We present [K/Fe] abundance ratios for a sample of 450 stars in Omega
Centauri, using high resolution spectra acquired with the multi-object
spectrograph FLAMES@VLT. Abundances for Fe, Na and Mg were also derived. We
detected intrinsic K variations in the analysed stars. Moreover, [K/Fe] shows a
significant correlation with [Na/Fe] and anti-correlation with [Mg/Fe]. The
presence of a clear-cut Mg-K anti-correlation makes Omega Centauri the third
stellar system, after NGC 2419 and NGC 2808, hosting a sub-population of stars
with [Mg/Fe]<0.0 dex, K-enriched in the case of Omega Centauri by ~0.3 dex with
respect to the Mg-rich stars ([Mg/Fe]>0.0 dex). The
correlation/anti-correlation between K and other light elements involved in
chemical anomalies supports the idea that the spread in [K/Fe] can be
associated to the same self-enrichment process typical of globular clusters. We
suggest that significant variations in K abundances perhaps can be found in the
most massive and/or metal-poor globular clusters as manifestation of an extreme
self-enrichment process. Theoretical models face problems to explain the K
production in globular clusters. Indeed, models where asymptotic giant branch
stars are responsible for the Mg-K anti-correlation only qualitatively agree
with the observations. Finally, we discovered a peculiar star with an
extraordinary K overabundance ([K/Fe]=+1.60 dex) with respect to the other
stars with similar [Mg/Fe]. We suggest that this K-rich star could be formed
from the pure ejecta of AGB stars before dilution with pristine material.


title:
The Open Cluster Chemical Abundances and Mapping Survey: VII. APOGEE
  DR17 [C/N]-Age Calibration

abstract:
  Large scale surveys open the possibility to investigate Galactic evolution
both chemically and kinematically, however, reliable stellar ages remain a
major challenge. Detailed chemical information provided by high-resolution
spectroscopic surveys of the stars in clusters can be used as a means to
calibrate recently developed chemical tools for age-dating field stars. Using
data from the Open Cluster Abundances and Mapping (OCCAM) survey, based on the
SDSS/APOGEE-2 survey, we derive a new empirical relationship between open
cluster stellar ages and the carbon-to-nitrogen ([C/N]) abundance ratios for
evolved stars, primarily those on the red giant branch. With this calibration,
[C/N] can be used a chemical clock for evolved field stars to investigate the
formation and evolution of different parts of our Galaxy. We explore how mixing
effects at different stellar evolutionary phases, like the red clump, affect
the derived calibration. We have established the [C/N]-age calibration for
APOGEE DR17 giant star abundances to be $\log[Age({\rm yr})]_{\rm DR17} = 10.14
\, (\pm 0.08) + 2.23\,(\pm 0.19) \, {\rm [C/N]}$, usable for $8.62 \leq
\log(Age[{\rm yr}]) \leq 9.82$, derived from a uniform sample of 49 clusters
observed as part of APOGEE DR17 applicable primarily to metal-rich, thin and
thick disk giant stars. This measured [C/N]-age APOGEE DR17 calibration is also
shown to be consistent with astereoseismic ages derived from Kepler photometry.


title: A novel counterexample to the Nelson-Seiberg theorem

abstract:
  We present a new type of counterexample to the Nelson-Seiberg theorem. It is
a generic R-symmetric Wess-Zumino model with nine chiral superfields, including
one field of R-charge $2$ and no R-charge $0$ field. As in previous
counterexamples, the model gives a set of degenerate supersymmetric vacua with
a non-zero expectation value for a pair of oppositely R-charged fields.
However, one of these fields appears quadratically in the superpotential, and
many other fields with non-zero R-charges gain non-zero expectation values at
the vacuum, and so this model escapes the sufficient condition for
counterexamples established in previous literature. Thus there are still open
problems in the relation of R-symmetries to supersymmetry breaking in generic
models.


title:
LoopITR: Combining Dual and Cross Encoder Architectures for Image-Text
  Retrieval

abstract:
  Dual encoders and cross encoders have been widely used for image-text
retrieval. Between the two, the dual encoder encodes the image and text
independently followed by a dot product, while the cross encoder jointly feeds
image and text as the input and performs dense multi-modal fusion. These two
architectures are typically modeled separately without interaction. In this
work, we propose LoopITR, which combines them in the same network for joint
learning. Specifically, we let the dual encoder provide hard negatives to the
cross encoder, and use the more discriminative cross encoder to distill its
predictions back to the dual encoder. Both steps are efficiently performed
together in the same model. Our work centers on empirical analyses of this
combined architecture, putting the main focus on the design of the distillation
objective. Our experimental results highlight the benefits of training the two
encoders in the same network, and demonstrate that distillation can be quite
effective with just a few hard negative examples. Experiments on two standard
datasets (Flickr30K and COCO) show our approach achieves state-of-the-art dual
encoder performance when compared with approaches using a similar amount of
data.


title: Delocalized Photonic Deep Learning on the Internet's Edge

abstract:
  Advances in deep neural networks (DNNs) are transforming science and
technology. However, the increasing computational demands of the most powerful
DNNs limit deployment on low-power devices, such as smartphones and sensors --
and this trend is accelerated by the simultaneous move towards
Internet-of-Things (IoT) devices. Numerous efforts are underway to lower power
consumption, but a fundamental bottleneck remains due to energy consumption in
matrix algebra, even for analog approaches including neuromorphic, analog
memory and photonic meshes. Here we introduce and demonstrate a new approach
that sharply reduces energy required for matrix algebra by doing away with
weight memory access on edge devices, enabling orders of magnitude energy and
latency reduction. At the core of our approach is a new concept that
decentralizes the DNN for delocalized, optically accelerated matrix algebra on
edge devices. Using a silicon photonic smart transceiver, we demonstrate
experimentally that this scheme, termed Netcast, dramatically reduces energy
consumption. We demonstrate operation in a photon-starved environment with 40
aJ/multiply of optical energy for 98.8% accurate image recognition and <1
photon/multiply using single photon detectors. Furthermore, we show realistic
deployment of our system, classifying images with 3 THz of bandwidth over 86 km
of deployed optical fiber in a Boston-area fiber network. Our approach enables
computing on a new generation of edge devices with speeds comparable to modern
digital electronics and power consumption that is orders of magnitude lower.


title: Iitaka fibrations for dlt pairs polarized by a nef and log big divisor

abstract:
  We study lc pairs polarized by a nef and log big divisor. After proving the
minimal model theory for projective lc pairs polarized by a nef and log big
divisor, we prove the effectivity of the Iitaka fibrations and some boundedness
results for dlt pairs polarized by a nef and log big divisor.


title:
CoCo-FL: Communication- and Computation-Aware Federated Learning via
  Partial NN Freezing and Quantization

abstract:
  Devices participating in federated learning (FL) typically have heterogeneous
communication and computation resources. However, all devices need to finish
training by the same deadline dictated by the server when applying synchronous
FL, as we consider in this paper. Reducing the complexity of the trained neural
network (NN) at constrained devices, i.e., by dropping neurons/filters, is
insufficient as it tightly couples reductions in communication and computation
requirements, wasting resources. Quantization has proven effective to
accelerate inference, but quantized training suffers from accuracy losses. We
present a novel mechanism that quantizes during training parts of the NN to
reduce the computation requirements, freezes them to reduce the communication
and computation requirements, and trains the remaining parts in full precision
to maintain a high convergence speed and final accuracy. Using this mechanism,
we present the first FL technique that independently optimizes for specific
communication and computation constraints in FL: CoCo-FL. We show that CoCo-FL
reaches a much higher convergence speed than the state of the art and a
significantly higher final accuracy.


title: Prediction-Guided Distillation for Dense Object Detection

abstract:
  Real-world object detection models should be cheap and accurate. Knowledge
distillation (KD) can boost the accuracy of a small, cheap detection model by
leveraging useful information from a larger teacher model. However, a key
challenge is identifying the most informative features produced by the teacher
for distillation. In this work, we show that only a very small fraction of
features within a ground-truth bounding box are responsible for a teacher's
high detection performance. Based on this, we propose Prediction-Guided
Distillation (PGD), which focuses distillation on these key predictive regions
of the teacher and yields considerable gains in performance over many existing
KD baselines. In addition, we propose an adaptive weighting scheme over the key
regions to smooth out their influence and achieve even better performance. Our
proposed approach outperforms current state-of-the-art KD baselines on a
variety of advanced one-stage detection architectures. Specifically, on the
COCO dataset, our method achieves between +3.1% and +4.6% AP improvement using
ResNet-101 and ResNet-50 as the teacher and student backbones, respectively. On
the CrowdHuman dataset, we achieve +3.2% and +2.0% improvements in MR and AP,
also using these backbones. Our code is available at
https://github.com/ChenhongyiYang/PGD.


title:
Copolymeric stars adsorbed at a surface and subject to a force: a
  self-avoiding walk model

abstract:
  We consider a model of star copolymers, based on self-avoiding walks, where
the arms of the star can be chemically distinct. The copolymeric star is
attached to an impenetrable surface at a vertex of unit degree and the
different monomers constituting the star have different interaction strengths
with the surface. When the star is adsorbed at the surface it can be desorbed
by applying a force, either at a vertex of degree 1 or at the central vertex of
the star. We give some rigorous results about the free energy of the system and
use these to establish the general form of the phase diagrams, and the orders
of certain phase transitions in the system. We also consider the special case
of spiders, ie stars constrained to have all degree 1 vertices in the surface.


title:
A Full Dive into Realizing the Edge-enabled Metaverse: Visions, Enabling
  Technologies,and Challenges

abstract:
  Dubbed "the successor to the mobile Internet", the concept of the Metaverse
has grown in popularity. While there exist lite versions of the Metaverse
today, they are still far from realizing the full vision of an immersive,
embodied, and interoperable Metaverse. Without addressing the issues of
implementation from the communication and networking, as well as computation
perspectives, the Metaverse is difficult to succeed the Internet, especially in
terms of its accessibility to billions of users today. In this survey, we focus
on the edge-enabled Metaverse to realize its ultimate vision. We first provide
readers with a succinct tutorial of the Metaverse, an introduction to the
architecture, as well as current developments. To enable the ubiquitous,
seamless, and embodied access to the Metaverse, we discuss the communication
and networking challenges and survey cutting-edge solutions and concepts that
leverage next-generation communication systems for users to be telepresent and
teleoperate in the Metaverse. Moreover, given the high computation costs
required, e.g., to render immersive 3D worlds and run data hungry artificial
intelligence (AI) driven applications, we discuss the computation challenges
and cloud-edge-end computation framework driven solutions to realize the
Metaverse on resource-constrained edge devices. Next, we explore how blockchain
technologies can aid in the interoperable development of the Metaverse, not
just in terms of empowering the economic circulation of virtual user-generated
contents, but also to manage physical edge resources in a decentralized,
transparent, and tamper-proof manner. Finally, we discuss the future research
directions towards realizing the true vision of the edge-enabled Metaverse.


title:
Slow, ordinary and rapid points for Gaussian Wavelets Series and
  application to Fractional Brownian Motions

abstract:
  We study the H\"olderian regularity of Gaussian wavelets series and show that
they display, almost surely, three types of points: slow, ordinary and rapid.
In particular, this fact holds for the Fractional Brownian Motion. We also show
that this property is satisfied for a multifractal extension of Gaussian
wavelet series. Finally, we remark that the existence of slow points is
specific to these functions.


title:
Scale-free behavioral cascades and effective leadership in schooling
  fish

abstract:
  Behavioral contagion and the presence of behavioral cascades are natural
features in groups of animals showing collective motion, such as schooling fish
or grazing herbivores. Here we study empirical behavioral cascades observed in
fish schools defined as avalanches of consecutive large changes in the heading
direction of the trajectory of fish. In terms of a minimum turning angle
introduced to define a large change, avalanches are characterized by
distributions of size and duration showing scale-free signatures, reminiscent
of self-organized critical behavior. We observe that avalanches are generally
triggered by a small number of fish, which act as effective leaders that induce
large rearrangements of the group's trajectory. This observation motivates the
proposal of a simple model, based in the classical Vicsek model of collective
motion, in which a given individual acts as a leader subject to random heading
reorientations. The model reproduces qualitatively the empirical avalanche
behavior observed in real schools, and hints towards a connection between
effective leadership and avalanche behavior in collective movement.


title:
Absolutely continuous edge spectrum of topological insulators with an
  odd time-reversal symmetry

abstract:
  We show that non-trivial two-dimensional topological insulators protected by
an odd time-reversal symmetry have absolutely continuous edge spectrum. The
proof employs a time-reversal symmetric version of the Wold decomposition that
singles out ballistic edge modes of the topological insulator.


title: Surprises in Lorentzian path-integral of Gauss-Bonnet gravity

abstract:
  In this paper we study the Lorentzian path-integral of Gauss-Bonnet gravity
in the mini-superspace approximation in four spacetime dimensions and
investigate the transition amplitude from one configuration to another. Past
studies motivate us on imposing Neumann boundary conditions on initial boundary
as they lead to stable behaviour of fluctuations. The transition amplitude is
computed exactly while incorporating the non-trivial contribution coming from
the Gauss-Bonnet sector of gravity. A saddle-point analysis involving usage of
Picard-Lefschetz methods allow us to gain further insight of the nature of
transition amplitude. Small-size Universe is Euclidean in nature which is shown
by the exponentially rising wave-function. It reaches a peak after which the
wave-function becomes oscillatory indicating an emergence of time and a
Lorentzian phase of the Universe. We also notice an interesting hypothetical
situation when the wave-function of Universe becomes independent of the initial
conditions completely, which happens when cosmological constant and
Gauss-Bonnet coupling have a particular relation. This however doesn't imply
that the initial momentum is left arbitrary as it needs to be fixed to a
particular value which is chosen by demanding regularity of Universe at an
initial time and the stability of fluctuations.


title: Propagators Beyond The Standard Model

abstract:
  In this paper, we explore one of the most important sorts of mathematical
tools within quantum field theory framework: the quantum field propagator. To
do so, we build such a quantity in its most general form and then we perform
some analyses for some theories within the ``Beyond the Standard Model''
context. We therefore define the general propagators for mass-dimension-one
fermions and spin-half bosons, such a task is accomplished investigating a
freedom on the spinorial dual structure, looking towards establish a
relationship among them.


title: Particles on Demand for flows with strong discontinuities

abstract:
  Particles on Demand formulation of kinetic theory [B. Dorschner, F. B\"{o}sch
and I. V. Karlin, {\it Phys. Rev. Lett.} {\bf 121}, 130602 (2018)] is used to
simulate a variety of compressible flows with strong discontinuities in
density, pressure and velocity. Two modifications are applied to the original
formulation of the Particles on Demand method. First, a regularization by
Grad's projection of particles populations is combined with the reference frame
transformations in order to enhance stability and accuracy. Second, a
finite-volume scheme is implemented which allows tight control of mass,
momentum and energy conservation. The proposed model is validated with an array
of challenging one- and two-dimensional benchmarks of compressible flows,
including hypersonic and near-vacuum situations, Richtmyer-Meshkov instability,
double Mach reflection and astrophysical jet. Excellent performance of the
modified Particles on Demand method is demonstrated beyond the limitations of
other lattice Boltzmann-like approaches to compressible flows.


title:
Tighter upper bounds on the critical temperature of two-dimensional
  superconductors and superfluids: Approaching the supremum

abstract:
  We discuss standard and tighter upper bounds on the critical temperature
$T_c$ of two-dimensional superconductors and superfluids versus particle
density n or filling factor $\nu$, under the assumption that the transition
from the normal to the superconducting (superfluid) phase is governed by the
Berezinskii-Kosterlitz-Thouless (BKT) mechanism of vortex-antivortex binding
and a direct relation between the superfluid density tensor and $T_c$ exists.
The standard critical temperature upper bound $T_c^{\rm up1}$ is obtained from
the Glover-Ferrell-Tinkham sum rule for the optical conductivity, which
constrains the superfluid density tensor components. However, we show that
$T_c^{\rm up1}$ is only useful in the limit of low particle/carrier density,
where it may be close to the critical temperature supremum $T_c^{\rm sup}$ .
For intermediate and high particle/carrier densities, $T_c^{\rm up1}$ is far
beyond $T_c^{\rm sup}$ for any given interaction strength. We demonstrate that
it is imperative to consider at least the full effects of phase fluctuations of
the order parameter for superconductivity (superfluidity) to establish tighter
bounds over a wide range of densities. Using the renormalization group, we
obtain the critical temperature supremum for phase fluctuations $T_c$ and show
that it is a much tighter upper bound to $T_c^{\rm sup}$ than $T_c^{\rm up1}$
for all particle/carrier densities. We conclude by indicating that if the $T_c$
is exceeded in experiments involving single band systems, then a non-BKT
mechanism must be invoked.


title: Summation-by-parts operators for general function spaces

abstract:
  Summation-by-parts (SBP) operators are popular building blocks for
systematically developing stable and high-order accurate numerical methods for
time-dependent differential equations. The main idea behind existing SBP
operators is that the solution is assumed to be well approximated by
polynomials up to a certain degree, and the SBP operator should therefore be
exact for them. However, polynomials might not provide the best approximation
for some problems, and other approximation spaces may be more appropriate. In
this paper, a theory for SBP operators based on general function spaces is
developed. We demonstrate that most of the established results for
polynomial-based SBP operators carry over to this general class of SBP
operators. Our findings imply that the concept of SBP operators can be applied
to a significantly larger class of methods than currently known. We exemplify
the general theory by considering trigonometric, exponential and radial basis
functions.


title:
Pair-density-wave and chiral superconductivity in twisted bilayer
  transition-metal-dichalcogenides

abstract:
  We theoretically explore possible unconventional superconductivity induced by
weak repulsive interactions in twisted bilayer TMD (e.g. WSe$_2$) in the
presence of an out-of-plane electric field. Using renormalization group (RG)
analysis, we show that topological chiral superconducting states with Chern
number $\mathcal{N}=1,2,4$ (namely $p+ip$, $d+id$, $g+ig$) appear over a large
parameter region with moire filling factor around $n=1$. At some special values
of applied electric field and in the presence of a weak out-of-plane Zeeman
field, spin-polarized pair density wave (PDW) superconductivity can emerge.
This spin-polarized PDW state can be probed by experiments such as
spin-polarized STM measuring spin-resolved pairing gap and quasi-particle
interference. Moreover, the spin-polarized PDW could lead to spin-polarized
superconducting diode effect.


title: Fully Adaptive Composition in Differential Privacy

abstract:
  Composition is a key feature of differential privacy. Well-known advanced
composition theorems allow one to query a private database quadratically more
times than basic privacy composition would permit. However, these results
require that the privacy parameters of all algorithms be fixed before
interacting with the data. To address this, Rogers et al. introduced fully
adaptive composition, wherein both algorithms and their privacy parameters can
be selected adaptively. The authors introduce two probabilistic objects to
measure privacy in adaptive composition: privacy filters, which provide
differential privacy guarantees for composed interactions, and privacy
odometers, time-uniform bounds on privacy loss. There are substantial gaps
between advanced composition and existing filters and odometers. First,
existing filters place stronger assumptions on the algorithms being composed.
Second, these odometers and filters suffer from large constants, making them
impractical. We construct filters that match the tightness of advanced
composition, including constants, despite allowing for adaptively chosen
privacy parameters. We also construct several general families of odometers.
These odometers can match the tightness of advanced composition at an
arbitrary, preselected point in time, or at all points in time simultaneously,
up to a doubly-logarithmic factor. We obtain our results by leveraging recent
advances in time-uniform martingale concentration. In sum, we show that fully
adaptive privacy is obtainable at almost no loss, and conjecture that our
results are essentially unimprovable (even in constants) in general.


title:
Model soups: averaging weights of multiple fine-tuned models improves
  accuracy without increasing inference time

abstract:
  The conventional recipe for maximizing model accuracy is to (1) train
multiple models with various hyperparameters and (2) pick the individual model
which performs best on a held-out validation set, discarding the remainder. In
this paper, we revisit the second step of this procedure in the context of
fine-tuning large pre-trained models, where fine-tuned models often appear to
lie in a single low error basin. We show that averaging the weights of multiple
models fine-tuned with different hyperparameter configurations often improves
accuracy and robustness. Unlike a conventional ensemble, we may average many
models without incurring any additional inference or memory costs -- we call
the results "model soups." When fine-tuning large pre-trained models such as
CLIP, ALIGN, and a ViT-G pre-trained on JFT, our soup recipe provides
significant improvements over the best model in a hyperparameter sweep on
ImageNet. As a highlight, the resulting ViT-G model attains 90.94% top-1
accuracy on ImageNet, a new state of the art. Furthermore, we show that the
model soup approach extends to multiple image classification and natural
language processing tasks, improves out-of-distribution performance, and
improves zero-shot performance on new downstream tasks. Finally, we
analytically relate the performance similarity of weight-averaging and
logit-ensembling to flatness of the loss and confidence of the predictions, and
validate this relation empirically.


title:
projUNN: efficient method for training deep networks with unitary
  matrices

abstract:
  In learning with recurrent or very deep feed-forward networks, employing
unitary matrices in each layer can be very effective at maintaining long-range
stability. However, restricting network parameters to be unitary typically
comes at the cost of expensive parameterizations or increased training runtime.
We propose instead an efficient method based on rank-$k$ updates -- or their
rank-$k$ approximation -- that maintains performance at a nearly optimal
training runtime. We introduce two variants of this method, named Direct
(projUNN-D) and Tangent (projUNN-T) projected Unitary Neural Networks, that can
parameterize full $N$-dimensional unitary or orthogonal matrices with a
training runtime scaling as $O(kN^2)$. Our method either projects low-rank
gradients onto the closest unitary matrix (projUNN-T) or transports unitary
matrices in the direction of the low-rank gradient (projUNN-D). Even in the
fastest setting ($k=1$), projUNN is able to train a model's unitary parameters
to reach comparable performances against baseline implementations. By
integrating our projUNN algorithm into both recurrent and convolutional neural
networks, our models can closely match or exceed benchmarked results from
state-of-the-art algorithms.


title:
Axion-Like Particles at High Energy Muon Colliders -- A White paper for
  Snowmass 2021

abstract:
  We study the discovery potential for heavy axion-like particles (ALPs) and
the perspectives for determining their coupling properties at a muon collider.
Focusing on their couplings to the Standard Model (SM) gauge bosons $\gamma, Z,
W^\pm$, we show that a high-energy muon collider can substantially extend the
mass coverage, essentially reaching the kinematic limit of the collider energy.
The unique kinematics allow for non-ambiguous determination of the individual
coupling strengths. The associated production via $\mu^+\mu^-$ annihilation and
the VBF processes with the tagged outgoing muons can be utilized to verify the
CP property of the ALPs. We illustrate our results for a muon collider running
at 3 TeV and 10 TeV.


title: The Tur\'an number of the grid

abstract:
  For a positive integer $t$, let $F_t$ denote the graph of the $t\times t$
grid. Motivated by a 50-year-old conjecture of Erd\H{o}s about Tur\'{a}n
numbers of $r$-degenerate graphs, we prove that there exists a constant
$C=C(t)$ such that $\mathrm{ex}(n,F_t)\leq Cn^{3/2}$. This bound is tight up to
the value of $C$. One of the interesting ingredients of our proof is a novel
way of using the tensor power trick.


title: Electric Double Layer at the Metal-Oxide/Electrolyte Interface

abstract:
  Metal-oxide surfaces act as both Br{\o}nsted acids and bases, which allows
the exchange of protons with the electrolyte solution and generates either
positive or negative proton charges depending on the environmental pH. These
interfacial proton charges are then compensated by counter-ions from the
electrolyte solution, which leads to the formation of the electric double layer
(EDL). Because the EDL plays a crucial role in electrochemistry, geochemistry
and colloid science, understanding the structure-property relationship of the
EDL in metal-oxide systems from both experimental and theoretical approaches is
necessary. This chapter focuses on the physical chemistry of the protonic
double layer at the metal-oxide/electrolyte interface. In particular,
determinations of the EDL capacitance and the double-layer potential from
potentiometric titration experiments, electrochemical methods,
surface-sensitive vibrational spectroscopy and X-ray photoelectron spectroscopy
are summarized. This is followed by discussions from the atomistic modelling
aspect of the EDL, with an emphasis on the density-functional theory-based
molecular dynamics simulations. A conclusion and outlook for future works on
this topic are also given.


title: Constructible Graphs and Pursuit

abstract:
  A (finite or infinite) graph is called constructible if it may be obtained
recursively from the one-point graph by repeatedly adding dominated vertices.
In the finite case, the constructible graphs are precisely the cop-win graphs,
but for infinite graphs the situation is not well understood. One of our aims
in this paper is to give a graph that is cop-win but not constructible. This is
the first known such example. We also show that every countable ordinal arises
as the rank of some constructible graph, answering a question of Evron, Solomon
and Stahl. In addition, we give a finite constructible graph for which there is
no construction order whose associated domination map is a homomorphism,
answering a question of Chastand, Laviolette and Polat. Lehner showed that
every constructible graph is a weak cop win (meaning that the cop can
eventually force the robber out of any finite set). Our other main aim is to
investigate how this notion relates to the notion of `locally constructible'
(every finite graph is contained in a finite constructible subgraph). We show
that, under mild extra conditions, every locally constructible graph is a weak
cop win. But we also give an example to show that, in general, a locally
constructible graph need not be a weak cop win. Surprisingly, this graph may
even be chosen to be locally finite. We also give some open problems.


title:
Geometric and Topological Inference for Deep Representations of Complex
  Networks

abstract:
  Understanding the deep representations of complex networks is an important
step of building interpretable and trustworthy machine learning applications in
the age of internet. Global surrogate models that approximate the predictions
of a black box model (e.g. an artificial or biological neural net) are usually
used to provide valuable theoretical insights for the model interpretability.
In order to evaluate how well a surrogate model can account for the
representation in another model, we need to develop inference methods for model
comparison. Previous studies have compared models and brains in terms of their
representational geometries (characterized by the matrix of distances between
representations of the input patterns in a model layer or cortical area). In
this study, we propose to explore these summary statistical descriptions of
representations in models and brains as part of a broader class of statistics
that emphasize the topology as well as the geometry of representations. The
topological summary statistics build on topological data analysis (TDA) and
other graph-based methods. We evaluate these statistics in terms of the
sensitivity and specificity that they afford when used for model selection,
with the goal to relate different neural network models to each other and to
make inferences about the computational mechanism that might best account for a
black box representation. These new methods enable brain and computer
scientists to visualize the dynamic representational transformations learned by
brains and models, and to perform model-comparative statistical inference.


title:
Error mitigation increases the effective quantum volume of quantum
  computers

abstract:
  Quantum volume is a single-number metric which, loosely speaking, reports the
number of usable qubits on a quantum computer. While improvements to the
underlying hardware are a direct means of increasing quantum volume, the metric
is "full-stack" and has also been increased by improvements to software,
notably compilers. We extend this latter direction by demonstrating that error
mitigation, a type of indirect compilation, increases the effective quantum
volume of several quantum computers. Importantly, this increase occurs while
taking the same number of overall samples. We encourage the adoption of quantum
volume as a benchmark for assessing the performance of error mitigation
techniques.


title:
Reconciling nonlinear dissipation with the bilinear model of two
  Brownian particles

abstract:
  The Brownian motion of a single particle is a paradigmatic model of the
nonequilibrium dynamics of dissipative systems. In the system-plus-reservoir
approach, one can derive the particle's equations of motion from the reversible
dynamics of the system coupled to a bath of oscillators representing its
thermal environment. However, extending the system-plus-reservoir approach to
multiple particles in a collective environment is not straightforward, and
conflicting models have been proposed to that end. Here, we set out to
reconcile some aspects of the nonlinear and the bilinear models of two Brownian
particles. We show how the nonlinear dissipation originally derived from
exponential system-reservoir couplings can alternatively be obtained from the
bilinear Lagrangian, with a modified spectral function that explicitly depends
on the distance between the particles. As applications, we discuss how to avoid
the anomalous diffusion from the standard nonlinear model, as well as how to
phenomenologically model a hydrodynamic interaction between a pair of Brownian
particles in a viscous fluid.


title: Balanced Partial Entanglement in Flat Holography

abstract:
  We advance a construction for the balanced partial entanglement entropy (BPE)
for bipartite mixed states in a class of $(1+1)$-dimensional Galilean conformal
field theories dual to Einstein gravity and topologically massive gravity in
asymptotically flat spacetimes. We compare our results with the entanglement
wedge cross section (EWCS) in the dual geometries and find exact agreement.
Furthermore, utilizing a geometric picture, we demonstrate the holographic
duality between the EWCS and the BPE in the context of flat holography.


title: An Empirical Study of Low Precision Quantization for TinyML

abstract:
  Tiny machine learning (tinyML) has emerged during the past few years aiming
to deploy machine learning models to embedded AI processors with highly
constrained memory and computation capacity. Low precision quantization is an
important model compression technique that can greatly reduce both memory
consumption and computation cost of model inference. In this study, we focus on
post-training quantization (PTQ) algorithms that quantize a model to low-bit
(less than 8-bit) precision with only a small set of calibration data and
benchmark them on different tinyML use cases. To achieve a fair comparison, we
build a simulated quantization framework to investigate recent PTQ algorithms.
Furthermore, we break down those algorithms into essential components and
re-assembled a generic PTQ pipeline. With ablation study on different
alternatives of components in the pipeline, we reveal key design choices when
performing low precision quantization. We hope this work could provide useful
data points and shed lights on the future research of low precision
quantization.


title: Green's function formulation of quantum defect embedding theory

abstract:
  We present a Green's function formulation of the quantum defect embedding
theory (QDET) where a double counting scheme is rigorously derived within the
$G_0 W_0$ approximation. We then show the robustness of our methodology by
applying the theory with the newly derived scheme to several defects in
diamond. Additionally, we discuss a strategy to obtain converged results as a
function of the size and composition of the active space. Our results show that
QDET is a promising approach to investigate strongly correlated states of
defects in solids.

categories: quant-ph cond-mat.mtrl-sci cond-mat.str-el physics.comp-ph


title:
Out-of-time-order correlators of nonlocal block-spin and random
  observables in integrable and nonintegrable spin chains

abstract:
  Out-of-time-order correlators (OTOC) in the Ising Floquet system, that can be
both integrable and nonintegrable is studied. Instead of localized spin
observables, we study contiguous symmetric blocks of spins or random operators
localized on these blocks as observables. We find only power-law growth of OTOC
in both integrable and nonintegrable regimes. In the non-integrable regime,
beyond the scrambling time, there is an exponential saturation of the OTOC to
values consistent with random matrix theory. This motivates the use of
"pre-scrambled" random block operators as observables. A pure exponential
saturation of OTOC in both integrable and nonintegrable system is observed,
without a scrambling phase. Averaging over random observables from the Gaussian
unitary ensemble, the OTOC is found to be exactly same as the operator
entanglement entropy, whose exponential saturation has been observed in
previous studies of such spin-chains.


title: Widely Distributed Radar Imaging: Unmediated ADMM Based Approach

abstract:
  In this paper, we present a novel approach to reconstruct a unique image of
an observed scene with widely distributed radar sensors. The problem is posed
as a constrained optimization problem in which the global image which
represents the aggregate view of the sensors is a decision variable. While the
problem is designed to promote a sparse solution for the global image, it is
constrained such that a relationship with local images that can be
reconstructed using the measurements at each sensor is respected. Two problem
formulations are introduced by stipulating two different establishments of that
relationship. The proposed formulations are designed according to consensus
ADMM (CADMM) and sharing ADMM (SADMM), and their solutions are provided
accordingly as iterative algorithms. We drive the explicit variable updates for
each algorithm in addition to the recommended scheme for hybrid parallel
implementation on the distributed sensors and a central processing unit. Our
algorithms are validated and their performance is evaluated exploiting Civilian
Vehicles Dome data-set to realize different scenarios of practical relevance.
Experimental results show the effectiveness of the proposed algorithms,
especially in cases with limited measurements.


title: A Universal Triangulation for Flat Tori

abstract:
  A result due to Burago and Zalgaller states that every orientable polyhedral
surface, one that is obtained by gluing Euclidean polygons, has an isometric
piecewise linear (PL) embedding into Euclidean space $\mathbb{E}^3$. A flat
torus, resulting from the identification of the opposite sides of a Euclidean
parallelogram, is a simple example of polyhedral surface. In a first part, we
adapt the proof of Burago and Zalgaller, which is partially constructive, to
produce PL isometric embeddings of flat tori. In practice, the resulting
embeddings have a huge number of vertices, moreover distinct for every flat
torus. In a second part, based on another construction of Zalgaller and on
recent works by Arnoux et al., we exhibit a universal triangulation with 5974
triangles which can be embedded linearly on each triangle in order to realize
the metric of any flat torus.