November 2022 arXiv papers — page 78

Lizhe Hu, Linming Zhou, Yuhui Huang, Sujit Das

The controllable phase transition and nanopatterning of topological states in a ferroelectric system under external stimuli are critical for realizing the potential applications in nanoelectronic devices such as logic, memory, race-track, etc. Herein, using the phase-field simulations, we demonstrate the mechanical manipulation of polar skyrmions in ferroele

Yaiza Canzani, Jeffrey Galkowski, Blake Keeler

Let $(M,g)$ be a Zoll manifold, i.e., a smooth, compact, Riemannian manifold without boundary all of whose geodesics are closed with a minimal common period $T$. The positive definite Laplace-Beltrami operator has eigenvalues $\{\lambda_j^2\}_j$ which cluster around $\nu^2_\ell$ for some sequence $\nu_\ell\to \infty$. This article is concerned with the numbe

Natalia Frumkin, Dibakar Gope, Diana Marculescu

When considering post-training quantization, prior work has typically focused on developing a mixed precision scheme or learning the best way to partition a network for quantization. In our work, CPT-V, we look at a general way to improve the accuracy of networks that have already been quantized, simply by perturbing the quantization scales. Borrowing the id

Angelina Brilliantova, Hannah Miller, Ivona Bezáková

Signed networks, i.e., networks with positive and negative edges, commonly arise in various domains from social media to epidemiology. Modeling signed networks has many practical applications, including the creation of synthetic data sets for experiments where obtaining real data is difficult. Influential prior works proposed and studied various graph topolo

Jack Hirschman, Randy Lemons, Minyang Wang, Peter Kroetz

Chirped pulse amplification (CPA) and subsequent nonlinear optical (NLO) systems constitute the backbone of myriad advancements in semiconductor and additive manufacturing, communication networks, biology and medicine, defense and national security, and a host of other sectors over the past decades. Accurately and efficiently modeling CPA and NLO-based laser

Benjamin L. Badger

Very large deep learning models trained using gradient descent are remarkably resistant to memorization given their huge capacity, but are at the same time capable of fitting large datasets of pure noise. Here methods are introduced by which models may be trained to memorize datasets that normally are generalized. We find that memorization is difficult relat

Daniel Aloni, Avital Dery

In the presence of extra neutrino states at high scales, the low-energy effective $3\times 3$ leptonic mixing matrix (LMM) is in general nonunitary. We revisit the question of what is our current knowledge of individual LMM matrix elements without assuming unitarity. We first demonstrate that a minimal set of experimental constraints suffices in bounding LMM

Michael E. Tobar, Catriona A. Thomson, Benjamin T. McAllister, Maxim Goryachev

Recently interactions between putative axions and magnetic monopoles have been revisited by two of us [arXiv:2205.02605 [hep-ph]]. It has been shown that significant modifications to conventional axion electrodynamics arise due to these interactions, so that the axion-photon coupling parameter space is expanded from one parameter $g_{a\gamma\gamma}$ to three

Matthijs H. J. de Jong, Andrea Cupertino, Dongil Shin, Simon Gröblacher

Mechanical resonators that possess coupled modes with harmonic frequency relations have recently sparked interest due to their suitability for controllable energy transfer and non-Hermitian dynamics. Here, we show coupling between high Q-factor ($>\!\!10^4$) resonances with a nearly 1:1 frequency relation in spatially-symmetric microresonators. We develop an

N. Jordana-Mitjans, C. G. Mundell, S. Kobayashi, R. J. Smith

Gamma-ray bursts (GRBs) are bright extragalactic flashes of gamma-ray radiation and briefly the most energetic explosions in the Universe. Their catastrophic origin (the merger of compact objects or the collapse of massive stars) drives the formation of a newborn compact remnant (black hole or magnetar) that powers two highly relativistic jets. To distinguis

Amit Daniely, Elad Granot

We investigate the sample complexity of bounded two-layer neural networks using different activation functions. In particular, we consider the class $$ \mathcal{H} = \left\{\textbf{x}\mapsto \langle \textbf{v}, \sigma \circ W\textbf{b} + \textbf{b} \rangle : \textbf{b}\in\mathbb{R}^d, W \in \mathbb{R}^{\mathcal{T}\times d}, \textbf{v} \in \mathbb{R}^{\mathca

Erhan Bayraktar, Nicole Bauerle, Ali Devran Kara

We study a multi-agent mean field type control problem in discrete time where the agents aim to find a socially optimal strategy and where the state and action spaces for the agents are assumed to be continuous. The agents are only weakly coupled through the distribution of their state variables. The problem in its original form can be formulated as a classi

Alphonsus Adu-Bredu, Nikhil Devraj, Odest Chadwicke Jenkins

For robots to successfully execute tasks assigned to them, they must be capable of planning the right sequence of actions. These actions must be both optimal with respect to a specified objective and satisfy whatever constraints exist in their world. We propose an approach for robot task planning that is capable of planning the optimal sequence of grounded a

A. V. Plavin, Y. Y. Kovalev, Y. A. Kovalev, S. V. Troitsky

Evidence for bright radio blazars being high-energy neutrino sources was found in recent years. However, specifics of how and where these particles get produced still need to be determined. In this paper, we add 14 new IceCube events from 2020-2022 to update our analysis of the neutrino-blazars connection. We test and refine earlier findings by utilising the

Mark Andrea A. de Cataldo, Michael Groechenig, Siqing Zhang

The stack of relative splittings of a special Azumaya algebra plays a key role in the Non-Abelian Hodge Theory for curves in positive characteristics. In this paper, we define and study an open substack consisting of the so-called very good splittings. We show that, when using very good splittings, the Non-Abelian Hodge isomorphism preserves the semistable l

Julie Binard, Pierre Degond, Pascal Noble

In this paper, we consider a system of partial differential equations modeling the evolution of a landscape. A ground surface is eroded by the flow of water over it, either by sedimentation or dilution. The system is composed by three evolution equations on the elevation of the ground surface, the fluid height and the concentration of sediment in the fluid l

F. R. Donnan, D. Rigopoulou, I. García-Bernete, M. Pereira-Santaella

Context. Compact Obscured Nuclei (CONs) are an extreme phase of galaxy evolution where rapid supermassive black hole growth and$/$or compact star-forming activity is completely obscured by gas and dust. Aims. We investigate the properties of CONs in the mid-infrared and explore techniques aimed at identifying these objects such as through the equivalent widt

Nicolas Fournier, Milica Tomasevic

In this work, we study a stochastic system of N particles associated with the parabolic-parabolic Keller-Segel system. This particle system is singular and non Markovian in that its drift term depends on the past of the particles. When the sensitivity parameter is sufficiently small, we show that this particle system indeed exists for any $N\geq 2$, we show

Qiang Gao, Jinyu Hong, Xovee Xu, Ping Kuang

Deep neural networks have recently achieved considerable improvements in learning human behavioral patterns and individual preferences from massive spatial-temporal trajectories data. However, most of the existing research concentrates on fusing different semantics underlying sequential trajectories for mobility pattern learning which, in turn, yields a narr

Yeong Chyuan Chung, Diego Martínez, Nóra Szakács

Given any quasi-countable, in particular any countable inverse semigroup $S$, we introduce a way to equip $S$ with a proper and right subinvariant extended metric. This generalizes the notion of proper, right invariant metrics for discrete countable groups. Such a metric is shown to be unique up to bijective coarse equivalence of the semigroup, and hence dep

Haojun Jiang, Jianke Zhang, Rui Huang, Chunjiang Ge

Vision-language retrieval is an important multi-modal learning topic, where the goal is to retrieve the most relevant visual candidate for a given text query. Recently, pre-trained models, e.g., CLIP, show great potential on retrieval tasks. However, as pre-trained models are scaling up, fully fine-tuning them on donwstream retrieval datasets has a high risk

Kevin Du, Ian Gemp, Yi Wu, Yingying Wu

Reinforcement learning has recently been used to approach well-known NP-hard combinatorial problems in graph theory. Among these problems, Hamiltonian cycle problems are exceptionally difficult to analyze, even when restricted to individual instances of structurally complex graphs. In this paper, we use Monte Carlo Tree Search (MCTS), the search algorithm be

Cathal Maguire, Neale P. Gibson, Stevanus K. Nugroho, Swaetha Ramkumar

Recent progress in high-resolution transmission spectroscopy has offered new avenues in which to characterise the atmospheres of transiting exoplanets. High-resolution cross-correlation spectroscopy allows for the unambiguous detection of molecules/atoms. It has also been used to map both atmospheric dynamics and longitudinal variations in the abundance of s

Zhongying Deng, Yanqi Chen, Lihao Liu, Shujun Wang

Traffic flow analysis is revolutionising traffic management. Qualifying traffic flow data, traffic control bureaus could provide drivers with real-time alerts, advising the fastest routes and therefore optimising transportation logistics and reducing congestion. The existing traffic flow datasets have two major limitations. They feature a limited number of c

Elad Hazan, Karan Singh

This text presents an introduction to an emerging paradigm in control of dynamical systems and differentiable reinforcement learning called online nonstochastic control. The new approach applies techniques from online convex optimization and convex relaxations to obtain new methods with provable guarantees for classical settings in optimal and robust control

Simon Apers, Sander Gribling, Sayantan Sen, Dániel Szabó

We describe a simple algorithm for estimating the $k$-th normalized Betti number of a simplicial complex over $n$ elements using the path integral Monte Carlo method. For a general simplicial complex, the running time of our algorithm is $n^{O\left(\frac{1}{\sqrt{\gamma}}\log\frac{1}{\varepsilon}\right)}$ with $\gamma$ measuring the spectral gap of the combi

Zhuoqi Zhang, Yuuki Omori, Chihway Chang

While the probability density function (PDF) of the cosmic microwave background (CMB) convergence field approximately follows a Gaussian distribution, primordial non-Gaussianities and small contributions from structures at low redshifts make the overall distribution slightly non-Gaussian. Some of the late-time component can be modelled using the distribution

Carla Verdi, Luigi Ranalli, Cesare Franchini, Georg Kresse

We demonstrate an approach for calculating temperature-dependent quantum and anharmonic effects with beyond density-functional theory accuracy. By combining machine-learned potentials and the stochastic self-consistent harmonic approximation, we investigate the cubic to tetragonal transition in strontium titanate and show that the paraelectric phase is stabi

Karsten Balzer, Niclas Schlünzen, Hannes Ohldag, Jan-Philip Joost

Real-time nonequilibrium Green functions (NEGF) have been very successful to simulate the dynamics of correlated many-particle systems far from equilibrium. However, NEGF simulations are computationally expensive since the effort scales cubically with the simulation duration. Recently we have introduced the G1--G2 scheme that allows for a dramatic reduction

Shuheng Liu, Qiongyi He, Marcus Huber, Otfried Gühne

We consider the problem of detecting the dimensionality of entanglement with the use of correlations between measurements in randomized directions. First, exploiting the recently derived covariance matrix criterion for the entanglement dimensionality [S. Liu et al., arXiv:2208.04909], we derive an inequality that resembles well-known entanglement criteria, b

Miguel Angel Gutierrez-Estevez, Yiqun Wu, Chan Zhou

We propose a novel framework to learn how to communicate with intent, i.e., to transmit messages over a wireless communication channel based on the end-goal of the communication. This stays in stark contrast to classical communication systems where the objective is to reproduce at the receiver side either exactly or approximately the message sent by the tran

Marco Mussi, Gianmarco Genalti, Alessandro Nuara, Francesco Trovò

According to the main international reports, more pervasive industrial and business-process automation, thanks to machine learning and advanced analytic tools, will unlock more than 14 trillion USD worldwide annually by 2030. In the specific case of pricing problems-which constitute the class of problems we investigate in this paper-, the estimated unlocked

F. Osswald, E. Traykov, T. Durand, M. Heine

Due to increasing environmental and economic constraints, optimization of ion beam transport and equipment design becomes essential. The future should be equipped with planet-friendly facilities, that is, solutions that reduce environmental impact and improve economic competitiveness. The tendency to increase the intensity of the current and the power of the

Nikolai Wyderka, Andreas Ketterer

The generalized Bloch decomposition of a bipartite quantum state gives rise to a correlation matrix whose singular values provide rich information about non-local properties of the state, such as the dimensionality of entanglement. While some entanglement criteria based on the singular values exist, a complete understanding of the geometry of admissible corr

Seth Poulsen, Yael Gertner, Benjamin Cosman, Matthew West

Proof Blocks is a software tool that provides students with a scaffolded proof-writing experience, allowing them to drag and drop prewritten proof lines into the correct order instead of starting from scratch. In this paper we describe a randomized controlled trial designed to measure the learning gains of using Proof Blocks for students learning proof by in

Fanny Thomas, Cécile Gallea, Virginie Moulier, Noomane Bouaziz

Auditory verbal hallucinations (AVH) in schizophrenia (SZ) have been associated with abnormalities of the left arcuate fasciculus and transcallosal white matter projections linking homologous language areas of both hemispheres. While most studies have used a whole-tract approach, here we focused on analyzing local alterations of the above-mentioned pathways

Tim Keil

This thesis presents recent advances in model order reduction methods with the primary aim to construct online-efficient reduced surrogate models for parameterized multiscale phenomena and accelerate large-scale PDE-constrained parameter optimization methods. In particular, we present several different adaptive RB approaches that can be used in an error-awar

Gramoz Goranci, Monika Henzinger

We show an $(1+\epsilon)$-approximation algorithm for maintaining maximum $s$-$t$ flow under $m$ edge insertions in $m^{1/2+o(1)} \epsilon^{-1/2}$ amortized update time for directed, unweighted graphs. This constitutes the first sublinear dynamic maximum flow algorithm in general sparse graphs with arbitrarily good approximation guarantee.

Alexandre Salas-Bernardez, Juan J. Sanz-Cillero, Felipe J. Llanes-Estrada, Raquel Gomez-Ambrosio

The Standard Model Effective Field Theory (SMEFT) is the parametrization chosen to interpret many modern measurements. We have recently discussed, building on the work of other groups, that its overall framework can be experimentally tested, beyond simply constraining its parameters. This is because the Higgs Effective Field Theory (HEFT) is somewhat more ge

James A. Duffy, Sophocles Mavroeidis, Sam Wycherley

In the literature on nonlinear cointegration, a long-standing open problem relates to how a (nonlinear) vector autoregression, which provides a unified description of the short- and long-run dynamics of a vector of time series, can generate 'nonlinear cointegration' in the profound sense of those series sharing common nonlinear stochastic trends. We consider

Fedor V. Fomin, Petr A. Golovach, Tanmay Inamdar, Saket Saurabh

The problem of packing of equal disks (or circles) into a rectangle is a fundamental geometric problem. (By a packing here we mean an arrangement of disks in a rectangle without overlapping.) We consider the following algorithmic generalization of the equal disk packing problem. In this problem, for a given packing of equal disks into a rectangle, the questi

Julia Linhart, Alexandre Gramfort, Pedro L. C. Rodrigues

Building on the recent trend of new deep generative models known as Normalizing Flows (NF), simulation-based inference (SBI) algorithms can now efficiently accommodate arbitrary complex and high-dimensional data distributions. The development of appropriate validation methods however has fallen behind. Indeed, most of the existing metrics either require acce

Ivan Chi-Ho Ip

We give an algebraic proof of the independence of Coxeter moves involved in the construction of positive representations of split-real quantum groups, thus completing a gap in the original construction. To do this, we propose a new quantized version of Lusztig's Injectivity Lemma in the language of quantum cluster algebra, the proof of which by Tits' Lemma r

Simon Brandhorst, Giacomo Mezzedimi

Let $L$ be an even, hyperbolic lattice with infinitely many simple $(-2)$-roots. We call $L$ a Borcherds lattice if it admits an isotropic vector with bounded inner product with all the simple $(-2)$-roots. We show that this is the case if and only if $L$ has zero entropy, or equivalently if and only if all symmetries of $L$ preserve some isotropic vector. W

Sara Willhammar, Liesbet Van der Perre, Fredrik Tufvesson

One of the use cases for 5G systems and beyond is ultra-reliability low-latency communication (URLLC). An enabling technology for URLLC is massive multiple-input multiple-output (MIMO), which can increase reliability due to improved user separation, array gain and the channel hardening effect. Measurements have been performed in an operating factory environm

Jean Cappello, Javier Rivero-Rodrìguez, Youen Vitry, Adrien Dewandre

Understand and predict the dynamics of dispersed micro-objects in microfluidics is crucial in numerous natural, industrial and technological situations. In this paper, we experimentally characterized the equilibrium velocity $V$ and lateral position $\varepsilon$ of various dispersed micro-objects such as beads, bubbles and drops, in a cylindrical microchann

Utsav Akhaury, Jean-Luc Starck, Pascale Jablonka, Frédéric Courbin

With the onset of large-scale astronomical surveys capturing millions of images, there is an increasing need to develop fast and accurate deconvolution algorithms that generalize well to different images. A powerful and accessible deconvolution method would allow for the reconstruction of a cleaner estimation of the sky. The deconvolved images would be helpf

J. Yu. Panteleeva, E. Epelbaum, J. Gegelia, U. -G. Meißner

We work out details of defining the spatial densities corresponding to the gravitational form factors of spin-0 and spin-1/2 systems using spherically symmetric sharply localized wave packets. The expressions for the spatial densities are provided in the frames with both zero and non-zero expectation values of the momentum operator.

Victoria Borish, H. J. Lewandowski

As quantum information science and technology (QIST) is becoming more prevalent and occurring not only in research labs but also in industry, many educators are considering how best to incorporate learning about quantum mechanics into various levels of education. Although much of the focus has been on quantum concepts in non-lab courses, current work in QIST

Aleksandr Beknazaryan, Hailin Sang, Peter Adamic

Let $\{X_n: n\in \N\}$ be a linear process with density function $f(x)\in L^2(\R)$. We study wavelet density estimation of $f(x)$. Under some regular conditions on the characteristic function of innovations, we achieve, based on the number of nonzero coefficients in the linear process, the minimax optimal convergence rate of the integrated mean squared error

Zhongying Deng, Rihuan Ke, Carola-Bibiane Schonlieb, Angelica I Aviles-Rivero

Semi-Supervised Learning (SSL) aims to learn a model using a tiny labeled set and massive amounts of unlabeled data. To better exploit the unlabeled data the latest SSL methods use pseudo-labels predicted from a single discriminative classifier. However, the generated pseudo-labels are inevitably linked to inherent confirmation bias and noise which greatly a

R. R. S. Oliveira, G. Alencar, R. R. Landim

In this paper, we investigate the bound-state solutions of the noncommutative Dirac oscillator with a permanent electric dipole moment in the presence of an electromagnetic field in (2+1)-dimensions. We consider a radial magnetic field generated by anti-Helmholtz coils, and the uniform electric field of the Stark effect. Next, we determine the bound-state so

Tania Robens

The TRSM is a new physics model that extends the scalar sector of the Standard Model by two additional CP even scalars. It leads to a large variety of interesting signatures, some of which have not yet been explored by the LHC experiments. I will also discuss the option to explore the hhh final state within this model.

Zhiheng Yi, Xiaoli Chen

With the development of Internet technology, the issue of privacy leakage has attracted more and more attention from the public. In our daily life, mobile phone applications and identity documents that we use may bring the risk of privacy leakage, which had increasingly aroused public concern. The path of privacy protection in the digital age remains to be e

Yuxuan Zhou, Zhi-Qi Cheng, Chao Li, Yanwen Fang

Skeleton-based action recognition aims to recognize human actions given human joint coordinates with skeletal interconnections. By defining a graph with joints as vertices and their natural connections as edges, previous works successfully adopted Graph Convolutional networks (GCNs) to model joint co-occurrences and achieved superior performance. More recent

Wandrille Ruffenach, Luca Galantucci, Carlo F. Barenghi

Drain vortices are among the most common vortices observed in everyday life, yet their physics is complex due to the competition of vorticity's transport and diffusion, and the presence of viscous layers and a free surface. Recently, it has become possible to study experimentally drain vortices in superfluid liquid helium, a fluid in which the physics is sim

David Gontier, Adéchola Kouande, Eric Séré

We consider the Peierls model for closed polyactetylene chains with an even number of carbon atoms as well as infinite chains, in the presence of temperature. We prove the existence of a critical temperature below which the chain is dimerized, and above which it is 1-periodic. The chain behaves like an insulator below the critical temperature and like a meta

Inaam Ashraf, Luca Hermes, André Artelt, Barbara Hammer

We investigate the task of missing value estimation in graphs as given by water distribution systems (WDS) based on sparse signals as a representative machine learning challenge in the domain of critical infrastructure. The underlying graphs have a comparably low node degree and high diameter, while information in the graph is globally relevant, hence graph

Jean-François Jaulent

We show that the cyclotomic conjecture on the characteristic polynomial of T-ramified S-split Iwasawa modules introduced in a previous paper and satisfied by abelian fields governs the Z${\ell}$-rank of the submodule of fixed points for all finite disjoint sets S and T of places.Last, in the CM-case we prove that the weak and the strong versions of the cyclo

Rambabu Rajpoot, Amol R. Holkundkar

We investigated the high-order harmonic generation by interacting time-delayed, linearly polarized bi-chromatic laser pulses with the atomic target. The frequency ratio of secondary to primary fields ($\omega_2/\omega_1$), along with the relative carrier-envelope-phase (CEP) and respective time-delay between the two pulses, are very instrumental in controlli

Marcel Rodekamp, Christoph Gäntgen

Many fascinating systems suffer from a severe (complex action) sign problem preventing us from calculating them with Markov Chain Monte Carlo simulations. One promising method to alleviate the sign problem is the transformation of the integration domain towards Lefschetz Thimbles. Unfortunately, this suffers from poor scaling originating in numerically integ

Frederika Phipps, Sadegh Khochfar, Anna Lisa Varri, Claudio Dalla Vecchia

We investigate the formation of infant globular cluster (GC) candidates in high-resolution cosmological simulations from the First Billion Years (FiBY) project. By analysing the evolution of the systems in the energy and angular momentum plane, we identify the redshift at which the infant GCs first became gravitationally bound, and we find evidence of radial

M. Andriamirado, A. B. Balantekin, C. D. Bass, D. E. Bergeron

This paper presents an energy calibration scheme for an upgraded reactor antineutrino detector for the Precision Reactor Oscillation and Spectrum Experiment (PROSPECT). The PROSPECT collaboration is preparing an upgraded detector, PROSPECT-II (P-II), to advance capabilities for the investigation of fundamental neutrino physics, fission processes and associat

Luigi Del Debbio, Alessandro Lupo, Marco Panero, Nazario Tantalo

We present a lattice study of the $SU(4)$ gauge theory with two Dirac fermions in the fundamental and two in the two-index antisymmetric representation, a model close to a theory of partial compositeness. Focus of this work are the methodologies behind the computation of the spectrum and the extrapolation of the chiral point for a theory with matter in multi

Eric Diehl, Moritz von Tresckow, Lou Scholtissek, Dimitrios Loukrezis

This work suggests to optimize the geometry of a quadrupole magnet by means of a genetic algorithm adapted to solve multi-objective optimization problems. To that end, a non-domination sorting genetic algorithm known as NSGA-III is used. The optimization objectives are chosen such that a high magnetic field quality in the aperture of the magnet is guaranteed

M. Yu. Khlopov, O. M. Lecian

The structure and evolution of Primordial Antimatter domains and Dark matter objects are analysed. Relativistic low-density antimatter domains are described. The Relativistic FRW perfect-fluid solution is found for the characterization of i) ultra-high density antimatter domains, ii) high-density antimatter domains, and iii) dense anti-matter domains. The po

Seth K. Asante, Bianca Dittrich, Sebastian Steinhaus

Spin foams provide path integrals for quantum gravity, which employ discretizations as regulator. To obtain regulator independent predictions, we must remove these fiducial structures in a suitable refinement limit. In this chapter we present the current state of research: We begin with a discussion on the role of diffeomorphism symmetries in discrete system

Theo van Uem

This paper studies asymmetric Ebert's Hat Problem with five players where the probability of the colors may be unequal. We obtain maximal winning probabilities and optimal winning strategies using the concept of adequate sets.

Naoya Iwahara, Liviu F. Chibotaru

The synergistic interplay of different interactions in materials leads to the emergence of novel quantum phenomena. Spin-orbit and vibronic couplings usually counteract each other, however, in cubic $d^1$ double perovskites they coexist and give rise to spin-orbit-lattice entanglement with unquenched dynamic Jahn-Teller effect on the metal sites. The correla

Florent Alexis, Sylvie Castagnet, Carole Nadot-Martin, Gilles Robert

The work deals with the fatigue lifetime estimation of Short Fiber Reinforced Thermoplastics (SFRP), with a focus on conjugated effects of thermal aging. Two materials containing 35% (V35) and 50% (V50) weight ratio of short glass fibers were aged for 500h at 200{\textdegree}C in air and compared to the same materials in a Dry-As-Molded (DAM) state. Monotoni

Greg Jackson

Electromagnetic radiation from the quark-gluon plasma (QGP) is an important observable to be considered in heavy ion collision experiments. I will provide an update on recent advancements from perturbation theory and quenched lattice simulations. The resummed next-to-leading order (NLO) emission rate has recently been decomposed into transverse and longitudi

G. Spada, L. Parisi, G. Pascual, N. G. Parker

We investigate the magnetic behavior of finite-temperature repulsive two-component Bose mixtures by means of exact path-integral Monte-Carlo simulations. Novel algorithms are implemented for the free energy and the chemical potential of the two components. Results on the magnetic susceptibility suggest that the conditions for phase separation are not modifie

D. Peralta-Salas, R. Slobodeanu

The 3D primitive equations are used in most geophysical fluid models to approximate the large scale oceanic and atmospheric dynamics. We prove that there do not exist smooth stationary solutions to the 3D primitive equations with compact support, independently of the presence of the Coriolis rotation term or the viscosity. This result is in strong contrast w

David Monniaux

Static analysis by abstract interpretation is generally designed to be "sound", that is, it should not claim to establish properties that do not hold-in other words, not provide "false negatives" about possible bugs. A rarer requirement is that it should be "complete", meaning that it should be able to infer certain properties if they hold. This paper descri

Felix Brandt, Martin Bullinger, Anaëlle Wilczynski

The formal study of coalition formation in multi-agent systems is typically realized in the framework of hedonic games, which originate from economic theory. The main focus of this branch of research has been on the existence and the computational complexity of deciding the existence of coalition structures that satisfy various stability criteria. The actual

Iñaki García Etxebarria, Nabil Iqbal

We study systems with an Adler-Bell-Jackiw anomaly in terms of non-invertible symmetry. We present a new kind of non-invertible charge defect where a key role is played by a local current operator localized on the defect. The charge defects are now labeled by elements of a continuous $U(1)$. We use this construction to prove an analogue of Goldstone's theore

Jeroen Bertels, David Robben, Robin Lemmens, Dirk Vandermeulen

We know that both the CNN mapping function and the sampling scheme are of paramount importance for CNN-based image analysis. It is clear that both functions operate in the same space, with an image axis $\mathcal{I}$ and a feature axis $\mathcal{F}$. Remarkably, we found that no frameworks existed that unified the two and kept track of the spatial origin of

Cristian Assaiante, Daniele Cono D'Elia, Giuseppe Antonio Di Luna, Leonardo Querzoni

The availability of debug information for optimized executables can largely ease crucial tasks such as crash analysis. Source-level debuggers use this information to display program state in terms of source code, allowing users to reason on it even when optimizations alter program structure extensively. A few recent endeavors have proposed effective methodol

Atsuki Yoshinaga, Yuichiro Matsuzaki, Ryusuke Hamazaki

We propose an entanglement-enhanced sensing scheme that is robust against spatially inhomogeneous always-on Ising interactions. Our strategy is to tailor coherent quantum dynamics employing the Hilbert-space fragmentation (HSF), a recently recognized mechanism that evades thermalization in kinetically constrained many-body systems. Specifically, we analytica

Varsha Ramachandran

Massive stars have far-reaching feedback effects that alter the surrounding environment on local, global, and cosmic scales. Spectral analyses of massive stars with adequate stellar-atmosphere models are important to study massive star feedback in detail. We discuss the most recent UV and optical studies of massive metal-poor stars, including those with meta

Guillaume Balezo, Christof A. Bertram, Cyprien Tilmant, Stéphanie Petit

In histology, the presence of collagen in the extra-cellular matrix has both diagnostic and prognostic value for cancer malignancy, and can be highlighted by adding Saffron (S) to a routine Hematoxylin and Eosin (HE) staining. However, Saffron is not usually added because of the additional cost and because pathologists are accustomed to HE, with the exceptio

Daria Botvynko, Carlos Granero-Belinchon, Simon Van Gennip, Abdesslam Benzinou

We address Lagrangian drift simulation in geophysical dynamics and explore deep learning approaches to overcome known limitations of state-of-the-art model-based and Markovian approaches in terms of computational complexity and error propagation. We introduce a novel architecture, referred to as DriftNet, inspired from the Eulerian Fokker-Planck representati

Zhengyu Zhao, Hanwei Zhang, Renjue Li, Ronan Sicre

Transfer adversarial attacks raise critical security concerns in real-world, black-box scenarios. However, the actual progress of this field is difficult to assess due to two common limitations in existing evaluations. First, different methods are often not systematically and fairly evaluated in a one-to-one comparison. Second, only transferability is evalua

Andrius Popovas, Åke Nordlund, Mikolaj Szydlarski

Solar modelling has long been split into ''internal'' and ''surface'' modelling, because of the lack of tools to connect the very different scales in space and time, as well as the widely different environments and dominating physical effects involved. Significant efforts have recently been put into resolving this disconnect. We address the outstanding bottl

Niko Jokela, Arttu Pönni, Kari Rummukainen, Tobias Rindlisbacher

Entanglement entropy is a notoriously difficult quantity to compute in strongly interacting gauge theories. Existing lattice replica methods have suffered from a severe signal-to-noise ratio problem, making high-precision studies prohibitively expensive. Our improved lattice method mitigates this situation and allows us to probe holographic predictions for t

Jeroen Bertels, David Robben, Robin Lemmens, Dirk Vandermeulen

In this article, we look into some essential aspects of convolutional neural networks (CNNs) with the focus on medical image segmentation. First, we discuss the CNN architecture, thereby highlighting the spatial origin of the data, voxel-wise classification and the receptive field. Second, we discuss the sampling of input-output pairs, thereby highlighting t

Yumeng Xu, Eleanor Hamilton

Gravitational wave detections offer insights into the astrophysical populations of black holes in the universe and their formation processes. Detections of binaries consisting of black holes lying outside the bulk distribution of the astrophysical population are particularly intriguing. In this study, we perform an injection analysis within the intermediate-

Masahiro Kadosawa, Masaaki Nakamura, Yukinori Ohta, Satoshi Nishimoto

We propose an efficient numerical method to obtain local order parameter in two-dimensional systems using spiral boundary conditions. As a benchmark, we first estimate the magnitude of staggered magnetization for the $S=1/2$ XXZ Heisenberg model on a square lattice in the whole range of the XXZ anisotropy by density-matrix renormalization group technique. Th

Manh Dan Pham, Cyprien Tilmant, Stéphanie Petit, Isabelle Salmon

The evaluation of the Human Epidermal growth factor Receptor-2 (HER2) expression is an important prognostic biomarker for breast cancer treatment selection. However, HER2 scoring has notoriously high interobserver variability due to stain variations between centers and the need to estimate visually the staining intensity in specific percentages of tumor area

Jiayi Shao, Xiaohan Wang, Yi Yang

In this report, we present the ReLER@ZJU1 submission to the Ego4D Moment Queries Challenge in ECCV 2022. In this task, the goal is to retrieve and localize all instances of possible activities in egocentric videos. Ego4D dataset is challenging for the temporal action localization task as the temporal duration of the videos is quite long and each video contai

Sarthak Gupta, Vassilis Kekatos, Spyros Chatzivasileiadis

Distribution grids are challenged by rapid voltage fluctuations induced by variable power injections from distributed energy resources (DERs). To regulate voltage, the IEEE Standard 1547 recommends each DER inject reactive power according to piecewise-affine Volt/VAR control rules. Although the standard suggests a default shape, the rule can be customized pe

Isaac A. Broudy, Sebastian Eterović

Given a subfield $F$ of $\mathbb{C}$, we study the linear disjointess of the field $E$ generated by iterated exponentials of elements of $\overline{F}$, and the field $L$ generated by iterated logarithms, in the presence of Schanuel's conjecture. We also obtain similar results replacing $\exp$ by the modular $j$-function, under an appropriate version of Scha

Zhiqing Wei, Mingyue Zhu, Ning Zhang, Lin Wang

Thanks to the advantages of flexible deployment and high mobility, unmanned aerial vehicles (UAVs) have been widely applied in the areas of disaster management, agricultural plant protection, environment monitoring and so on. With the development of UAV and sensor technologies, UAV assisted data collection for Internet of Things (IoT) has attracted increasin

Thomas Fel, Agustin Picard, Louis Bethune, Thibaut Boissin

Attribution methods, which employ heatmaps to identify the most influential regions of an image that impact model decisions, have gained widespread popularity as a type of explainability method. However, recent research has exposed the limited practical value of these methods, attributed in part to their narrow focus on the most prominent regions of an image

Alessandro Sola, Elena Olivetti, Luca Martino, Vittorio Basso

To assess the potential of polycrystalline MnBi as a transverse thermoelectric material, we have experimentally investigated its anomalous Nernst effect (ANE) by means of the heat flux method. We prepared MnBi samples by powder metallurgy; this technique allows the preparation of samples in arbitrary shapes with the possibility to tailor their magnetic prope

Kunchang Li, Yali Wang, Yinan He, Yizhuo Li

Learning discriminative spatiotemporal representation is the key problem of video understanding. Recently, Vision Transformers (ViTs) have shown their power in learning long-term video dependency with self-attention. Unfortunately, they exhibit limitations in tackling local video redundancy, due to the blind global comparison among tokens. UniFormer has succ

Amir Eshaghi Chaleshtori, Abdollah aghaie

In the Engineering discipline, predictive maintenance techniques play an essential role in improving system safety and reliability of industrial machines. Due to the adoption of crucial and emerging detection techniques and big data analytics tools, data fusion approaches are gaining popularity. This article thoroughly reviews the recent progress of data fus

Anuj Kumar Dubey, Tanay Ghosh

In the present work, we will derive the expression for the change in direction of the electric field using the Lorentz transformation for inertial frame or un-accelerated frame. The acceleration also influences the observed rate of a moving clock in addition to the influence due to its velocity. So we will also derive the expression for the change in directi

Zhiwei Huang, Sergey Sergeyev, Qing Wang, Hani Kbashi

Mode-locked lasers play the role of the ideal testbeds for studying self-coherent structures, dissipative solitons, with stable spatiotemporal profiles supported by the balance between dispersion and nonlinearity. However, under some conditions, the profile and energy of the solitons can oscillate (breath) periodically. Unlike the previous studies of differe

Suvankar Dutta, Taniya Mandal, Sanhita Parihar

We discuss two different approaches to synthesise holographic non-relativistic fluid from its relativistic counterpart. In the first approach we obtain the non-relativistic fluid by light-cone reduction of a relativistic conformal fluid. In the second approach we consider the bulk dual of the relativistic fluid, uplift the solution to 10 dimensions and perfo