October 2022 arXiv papers — page 116

Denis Anuprienko

Poroelasticity is an example of coupled processes which are crucial for many applications including safety assessment of radioactive waste repositories. Numerical solution of poroelasticity problems discretized with finite volume -- virtual element scheme leads to systems of algebraic equations, which may be solved simultaneously or iteratively. In this work

Balhae Kim, Jungwon Choi, Seanie Lee, Yoonho Lee

A Bayesian pseudocoreset is a small synthetic dataset for which the posterior over parameters approximates that of the original dataset. While promising, the scalability of Bayesian pseudocoresets is not yet validated in realistic problems such as image classification with deep neural networks. On the other hand, dataset distillation methods similarly constr

ATLAS Collaboration

The need for large-scale production of highly accurate simulated event samples for the extensive physics programme of the ATLAS experiment at the Large Hadron Collider motivates the development of new simulation techniques. Building on the recent success of deep learning algorithms, variational autoencoders and generative adversarial networks are investigate

Jing Gu, Kai Zhang

The restricted Boltzmann machine (RBM) is a two-layer energy-based model that uses its hidden-visible connections to learn the underlying distribution of visible units, whose interactions are often complicated by high-order correlations. Previous studies on the Ising model of small system sizes have shown that RBMs are able to accurately learn the Boltzmann

Pedro Sanchez, Xiao Liu, Alison Q O'Neil, Sotirios A. Tsaftaris

Discovering causal relations from observational data becomes possible with additional assumptions such as considering the functional relations to be constrained as nonlinear with additive noise (ANM). Even with strong assumptions, causal discovery involves an expensive search problem over the space of directed acyclic graphs (DAGs). \emph{Topological orderin

P. Van Rooy, M. Prokop, S. Kwon, P. Torrez

Incremental upgrades of the legacy low level RF (LLRF) equipment-50 years for the Los Alamos Neutron Science Center (LANSCE)-involves challenges and problems not seen with new and total replacement opportunities. The digital LLRF upgrade at LANSCE has deployed 30 of the 53 required systems as of September 2022. This paper describes the performance of the dig

Dariusz Chruściński, Samaneh Hesabi, Davide Lonigro

We provide a detailed discussion about the unitary and reduced evolution induced by family of Hamiltonian models describing a multilevel system, with a ground state and a possibly multilevel excited sector, coupled to a multimode boson field via a rotating-wave interaction. We prove explicitly that the system, in the limit in which the coupling is flat with

Chung-Hsien Wang, Yi-Cheng Wang, Chi-Chih Chen, Chun-Che Wang

Resolved sideband cooling provides a crucial step in subrecoil cooling the trapped atoms toward their motional ground state, which is essential in atom-based quantum technologies. Here we present an enhanced dark-state sideband cooling in trapped atoms utilizing photon-mediated dipole-dipole interactions among them. By placing the atoms at the magic interpar

Felicity F. Worsnop, Susannah L. M. Lea, Jan Ilavsky, David Rugg

Increasing attention is being paid to $\alpha$$_2$ Ti$_3$(Al,Sn) precipitation from the $\alpha$ phase of titanium alloys owing to its effect on slip band formation, localisation and the implications for fatigue performance in jet engine titanium. However, the early stages of $\alpha$$_2$ precipitation have historically been difficult to observe in TEM, neut

Olav Bunte, Louis C. M. van Gool, Tim A. C. Willemse

In a system of processes that communicate asynchronously by means of FIFO channels, there are many options in which these channels can be laid out. In this paper, we compare channel layouts in how they affect the behaviour of the system using an ordering based on splitting and merging channels. This order induces a simulation relation, from which the preserv

David Brizuela, Albert Duran-Cabacés

The Schr\"odinger-Newton model describes self-gravitating quantum particles, and it is often cited to explain the gravitational collapse of the wave function and the localization of macroscopic objects. However, this model is completely nonrelativistic. Thus, in order to study whether the relativistic effects may spoil the properties of this system, we deriv

Charles Badger, Katarina Martinovic, Alejandro Torres-Forné, Mairi Sakellariadou

The noise produced by the inspiral of millions of white dwarf binaries in the Milky Way may pose a threat to one of the main goals of the space-based LISA mission: the detection of massive black hole binary mergers. We present a novel study for reconstruction of merger waveforms in the presence of Galactic confusion noise using dictionary learning. We discus

Nils Dabrock, Sascha Knüttel, Matthias Röger

We introduce new diffuse approximations of the Willmore functional and the Willmore flow. They are based on a corresponding approximation of the perimeter that has been studied by Amstutz-van Goethem [{\em Interfaces Free Bound. 14 (2012)}]. We identify the candidate for the $\Gamma$--convergence, prove the $\Gamma$--limsup statement and justify the converge

Michael Bonfert, Anke V. Reinschluessel, Susanne Putze, Yenchin Lai

During the Covid-19 pandemic, online meetings became common for daily teamwork in the home office. To understand the opportunities and challenges of meeting in virtual reality (VR) compared to video conferences, we conducted the weekly team meetings of our human-computer interaction research lab on five off-the-shelf online meeting platforms over four months

Elisa Iacomini

We consider traffic flow models at different scales of observation. Starting from the well known hierarchy between microscopic, kinetic and macroscopic scales, we will investigate the propagation of uncertainties through the models using the stochastic Galerkin approach. Connections between the scales will be presented in the stochastic scenario and numerica

Marc Dietrichstein, David Major, Martin Trapp, Maria Wimmer

Unsupervised anomaly detection models which are trained solely by healthy data, have gained importance in the recent years, as the annotation of medical data is a tedious task. Autoencoders and generative adversarial networks are the standard anomaly detection methods that are utilized to learn the data distribution. However, they fall short when it comes to

David Wagner, Nora Weickgenannt, Dirk H. Rischke

We revisit the derivation of the nonlocal collision term in the Boltzmann equation for spin-1/2 particles, using both the Wigner-function approach by de Groot, van Leeuwen, and van Weert, and the Kadanoff-Baym equation in $T$-matrix approximation. Contrary to previous calculations, our results maintain full Lorentz covariance of the nonlocal collision term.

Govind Mittal, Chinmay Hegde, Nasir Memon

With the rise of AI-enabled Real-Time Deepfakes (RTDFs), the integrity of online video interactions has become a growing concern. RTDFs have now made it feasible to replace an imposter's face with their victim in live video interactions. Such advancement in deepfakes also coaxes detection to rise to the same standard. However, existing deepfake detection tec

Takashi Goda

In this note, we prove that the following function space with absolutely convergent Fourier series \[ F_d:=\left\{ f\in L^2([0,1)^d)\:\middle| \: \|f\|:=\sum_{\boldsymbol{k}\in \mathbb{Z}^d}|\hat{f}(\boldsymbol{k})| \max\left(1,\min_{j\in \mathrm{supp}(\boldsymbol{k})}\log |k_j|\right) <\infty \right\}\] with $\hat{f}(\boldsymbol{k})$ being the $\boldsymbol{

Jun Ueki, Hyuga Yoshizaki

This article discusses variants of Weber's class number problem in the spirit of arithmetic topology to connect the results of Sinnott--Kisilevsky and Kionke. Let $p$ be a prime number. We first prove the $p$-adic convergence of class numbers in a $\mathbb{Z}_p$-extension of a global field and a similar result in a $\mathbb{Z}_p$-cover of a compact 3-manifol

Youssef Aserrar, Elhoucien Elqorachi

In this paper, we determine the complex-valued solutions of the following functional equations \[g(x\sigma (y)) = g(x)g(y)+f(x)f(y),\quad x,y\in S,\]\[f(x\sigma (y)) = f(x)g(y)+f(y)g(x),\quad x,y\in S,\]\[f(x\sigma (y)) = f(x)g(y)+f(y)g(x)-g(x)g(y),\quad x,y\in S,\]\[f(x\sigma(y))=f(x)g(y)+f(y)g(x)+\alpha g(x\sigma(y)),\quad x,y\in S,\]\[f(x\sigma(y))=f(x)g(

Aaron Chan, Osamu Iyama, Rene Marczinzik

We introduce the class of dominant Auslander-Gorenstein algebras as a generalisation of higher Auslander algebras and minimal Auslander-Gorenstein algebras, and give their basic properties. We also introduce mixed (pre)cluster tilting modules as a generalisation of (pre)cluster tilting modules, and establish an Auslander type correspondence by showing that d

Mark Hindmarsh, Jun'ya Kume

Nielsen-Olesen vortices in the Abelian-Higgs (AH) model are the simplest realisations of cosmic strings in a gauge field theory. Large-scale numerical solutions show that the dominant decay channel of a network of AH strings produced from random initial conditions is classical field radiation. However, they also show that with special initial conditions, loo

Ryu Makiya, Hiroyuki Hirashita

We investigate the cosmological evolution of interstellar dust with a semi-analytical galaxy formation model ($\nu^2$GC), focusing on the evolution of grain size distribution. The model predicts the statistical properties of dust mass and grain size distribution in galaxies across cosmic history. We confirm that the model reproduces the relation between dust

Đorđe Dangić, Stephen Fahy, Ivana Savić

Experimental investigations of the phase transition in GeTe provide contradictory conclusions regarding the nature of the phase transition. Considering growing interest in technological applications of GeTe, settling these disputes is of great importance. To that end, we present a molecular dynamics study of the structural phase transition in GeTe using a ma

Carlo Alberto Mantica, Luca Guido Molinari

We study the geometric properties of certain Codazzi tensors for their own sake, and for their appearance in the recent theory of Cotton gravity. We prove that a perfect-fluid tensor is Codazzi if and only if the metric is a generalized Stephani universe. A trace condition restricts it to a warped space-time, as proven by Merton and Derdzinski. We also give

Florian Arbes, Øyvind Jensen, Kent-Andre Mardal, Jørgen S. Dokken

Advection driven problems are known to be difficult to model with a reduced basis because of a slow decay of the Kolmogorov $N$-width. This paper investigates how this challenge transfers to the context of solidification problems and tries to answer when and to what extend reduced order models (ROMs) work for solidification problems. In solidification proble

Barbara Perri, Blazej Kuzma, Michaela Brchnelova, Tinatin Baratashvili

This paper is dedicated to the new implicit unstructured coronal code COCONUT, which aims at providing fast and accurate inputs for space weather forecast as an alternative to empirical models. We use all 20 available magnetic maps of the solar photosphere covering the date of the 2nd of July 2019 which corresponds to a solar eclipse on Earth. We use the sam

Vera Provatorova, Simone Tedeschi, Svitlana Vakulenko, Roberto Navigli

Entity disambiguation (ED) is the task of mapping an ambiguous entity mention to the corresponding entry in a structured knowledge base. Previous research showed that entity overshadowing is a significant challenge for existing ED models: when presented with an ambiguous entity mention, the models are much more likely to rank a more frequent yet less context

Anne Hartebrodt, Richard Röttger

Federated learning (FL) is a privacy-aware data mining strategy keeping the private data on the owners' machine and thereby confidential. The clients compute local models and send them to an aggregator which computes a global model. In hybrid FL, the local parameters are additionally masked using secure aggregation, such that only the global aggregated stati

Marco Di Francesco, Simone Fagioli, Valeria Iorio

We study the mathematical theory of second order systems with two species, arising in the dynamics of interacting particles subject to linear damping, to nonlocal forces and to external ones, and resulting into a nonlocal version of the compressible Euler system with linear damping. Our results are limited to the $1$ space dimensional case but allow for init

Santiago Carrero Ibanez

We derive concentration inequalities for empirical means $\frac{1}{t} \int_0^t f(X_s) ds$ where $X_s$ is an irreducible Markov jump process on a finite state space and $f$ some observable. Using a Feynman-Kac semigroup we first derive a general concentration inequality. Then, based on this inequality we derive further concentration inequalities. Hereby we us

Kaiyuan Cui, Fuzhou Gong

Inspired by the idea of stochastic quantization proposed by Parisi and Wu, we construct the transition probability matrix which plays a central role in the renormalization group through a stochastic differential equation. By establishing the discrete time stochastic dynamics, the renormalization procedure can be characterized from the perspective of probabil

Qiming Peng, Yinxu Pan, Wenjin Wang, Bin Luo

Recent years have witnessed the rise and success of pre-training techniques in visually-rich document understanding. However, most existing methods lack the systematic mining and utilization of layout-centered knowledge, leading to sub-optimal performances. In this paper, we propose ERNIE-Layout, a novel document pre-training solution with layout knowledge e

Bart Cox, Lydia Y. Chen, Jérémie Decouchant

Federated Learning (FL) is a popular approach for distributed deep learning that prevents the pooling of large amounts of data in a central server. FL relies on clients to update a global model using their local datasets. Classical FL algorithms use a central federator that, for each training round, waits for all clients to send their model updates before ag

Marco Aymone

We consider the problem of $\Omega$ bounds for the partial sums of a modified character, \textit{i.e.}, a completely multiplicative function $f$ such that $f(p)=\chi(p)$ for all but a finite number of primes $p$, where $\chi$ is a primitive Dirichlet character. We prove that in some special circumstances, $\sum_{n\leq x}f(n)=\Omega((\log x)^{|S|})$, where $S

Megha Arya, Preeti Bhumla, Sajjan Sheoran, Suraj

Inorganic-organic lead halide perovskites, particularly methylammonium lead halide (MAPbI$_3$) perovskite, is perceived to be a promising material for optoelectronics and spintronics. However, lead toxicity and instability under air and moisture restrict its practical uses. Hence, it is essential to reduce lead extent by substituting appropriate alternatives

Petter Mæhlum, Andre Kåsen, Samia Touileb, Jeremy Barnes

Norwegian Twitter data poses an interesting challenge for Natural Language Processing (NLP) tasks. These texts are difficult for models trained on standardized text in one of the two Norwegian written forms (Bokm{\aa}l and Nynorsk), as they contain both the typical variation of social media text, as well as a large amount of dialectal variety. In this paper

Gal Barkai, Leonid Mirkin, Daniel Zelazo

We study internal stability in the context of diffusively-coupled control architectures, common in multi-agent systems (i.e. the celebrated consensus protocol), for linear time-invariant agents. We derive a condition under which the system can not be stabilized by any controller from that class. In the finite-dimensional case the condition states that diffus

Weihuan Huang, Nifei Lin, L. Jeff Hong

${\rm CoVaR}$ is one of the most important measures of financial systemic risks. It is defined as the risk of a financial portfolio conditional on another financial portfolio being at risk. In this paper we first develop a Monte-Carlo simulation-based batching estimator of CoVaR and study its consistency and asymptotic normality. We show that the optimal rat

Andrea Braides, Andrea Causin, Margherita Solci, Lev Truskinovsky

Physically motivated variational problems involving non-convex energies are often formulated in a discrete setting and contain boundary conditions. The long-range interactions in such problems, combined with constraints imposed by lattice discreteness, can give rise to the phenomenon of geometric frustration even in a one-dimensional setting. While non-conve

Sandro Mattarei, Roberto Tauraso

We produce congruences modulo a prime $p>3$ for sums $\sum_k\binom{3k}{k}x^k$ over ranges $0\le k<q$ and $0\le k<q/3$, where $q$ is a power of $p$. Here $x$ equals either $c^2/(1-c)^3$, or $4s^2/\bigl(27(s^2-1)\bigr)$, where $c$ and $s$ are indeterminates. In the former case we deal more generally with shifted binomial coefficients $\binom{3k+e}{k}$. Our met

Itai Gat, Yossi Adi, Alexander Schwing, Tamir Hazan

Generalization bounds which assess the difference between the true risk and the empirical risk, have been studied extensively. However, to obtain bounds, current techniques use strict assumptions such as a uniformly bounded or a Lipschitz loss function. To avoid these assumptions, in this paper, we follow an alternative approach: we relax uniform bounds assu

Petar Pavlović, Marko Sossich

In this work we demonstrate that wormholes can in principle be naturally created during the cosmological bounce without the need for the exotic matter or any kind of additional modifications of the gravitational sector, apart from the one enabling the cosmological bounce. This result is general and does not depend on the details of the modifications of gravi

Martin Cederwall

This is an overview of the method of pure spinor superfields, written for "Handbook of Quantum Gravity", eds. C. Bambi, L. Modesto and I. Shapiro. The main focus is on the use of the formalism in maximal supergravity on a flat background. The basics of pure spinor superfields, and their relation to standard superspace, is reviewed. The pure spinor superstrin

Zhanyu Wang, Guang Cheng, Jordan Awan

Differentially private (DP) mechanisms protect individual-level information by introducing randomness into the statistical analysis procedure. Despite the availability of numerous DP tools, there remains a lack of general techniques for conducting statistical inference under DP. We examine a DP bootstrap procedure that releases multiple private bootstrap est

David Cerezo Sánchez

Optimal simple rules for the monetary policy of the first stochastically dominant crypto-currency are derived in a Dynamic Stochastic General Equilibrium (DSGE) model, in order to provide optimal responses to changes in inflation, output, and other sources of uncertainty. The optimal monetary policy stochastically dominates all the previous crypto-currencies

Hongxiao Zhang, Siyu Lai, Songming Zhang, Hui Huang

Translation suggestion (TS) models are used to automatically provide alternative suggestions for incorrect spans in sentences generated by machine translation. This paper introduces the system used in our submission to the WMT'22 Translation Suggestion shared task. Our system is based on the ensemble of different translation architectures, including Transfor

Tengfang Kuang, Ran Huang, Wei Xiong, Yunlan Zuo

Phonon lasers, exploiting coherent amplifications of phonons, have been a cornerstone for exploring nonlinear phononics, imaging nanomaterial structures, and operating phononic devices. Very recently, by levitating a nanosphere in an optical tweezer, a single-mode phonon laser governed by dispersive optomechanical coupling has been demonstrated, assisted by

Nataliya Vasylyeva

For $\nu\in[0,1]$ and a complex parameter $\sigma,$ $Re\, \sigma>0,$ we discuss a linear inhomogeneous functional difference equation with variable coefficients on a complex plane $z\in\mathbb{C}$: \[ (a_{1}\sigma+a_{2}\sigma^{\nu})\mathcal{Y}(z+\beta,\sigma)-\Omega(z)\mathcal{Y}(z,\sigma)=\mathbb F(z,\sigma), \quad\beta\in\mathbb{R},\, \beta\neq 0, \] where

Jonathan Mui

This paper considers strongly continuous semigroups of operators on Banach lattices which are locally eventually positive, a property that was first investigated in the context of concrete fourth-order evolution equations. We construct a simple example to show that the typical assumptions on the spectrum of the semigroup generator considered currently in the

Hua Xuan Qin, Yuyang Wang, Pan Hui

With the boom in metaverse-related projects in major areas of the public's life, the safety of users becomes a pressing concern. We believe that an international legal framework should be established to promote collaboration among nations, facilitate crime investigation, and support democratic governance. In this paper, we discuss the legal concerns of ident

Hamid Reza Naeij

The use of rotational degrees of freedom of quantum systems in quantum technologies is limited by environmental effects under decoherence mechanism. Here, we study the mechanism of decoherence based on a new formalism of elastic scattering for a nonspherical quantum system prepared in a superposition of rotational degrees of freedom. We show that for a diele

Jaskaran Singh Bhatia, Parthasarathy P D, Snigdha Tiwari, Dhruv Nagpal

The growing interest in accessible software reflects in computing educators' and education researchers' efforts to include accessibility in core computing education. We integrated accessibility in a junior/senior-level Android app development course at a large private university in India. The course introduced three accessibility-related topics using various

Paolo Gidoni, Alessandro Margheri, Carlota Rebelo

We study the asymptotic behaviour of a family of dynamic models of crawling locomotion, with the aim of characterizing a gait as a limit property. The locomotors, which might have a discrete or continuous body, move on a line with a periodic prescribed shape change, and might possibly be subject to external forcing (e.g., crawling on a slope). We discuss how

Yan-Xia Ren, Renming Song, Rui Zhang

In this paper, we study the weak convergence of the extremes of supercritical branching L\'evy processes $\{\mathbb{X}_t, t \ge0\}$ whose spatial motions are L\'evy processes with regularly varying tails. The result is drastically different from the case of branching Brownian motions. We prove that, when properly renormalized, $\mathbb{X}_t$ converges weakly

Daiyu Geng, Hui Zhou, Shaosheng Yue, Zhenyu Sun

The Su-Schrieffer-Heeger (SSH) model in a two-dimensional rectangular lattice features gapless or gapped Dirac cones with topological edge states along specific peripheries. While such a simple model has been recently realized in photonic/acoustic lattices and electric circuits, its material realization in condensed matter systems is still lacking. Here, we

Gregor Cerar, Blaž Bertalanič, Carolina Fortuna

Location based services, already popular with end users, are now inevitably becoming part of new wireless infrastructures and emerging business processes. The increasingly popular Deep Learning (DL) artificial intelligence methods perform very well in wireless fingerprinting localization based on extensive indoor radio measurement data. However, with the inc

Herondy F. S. Mota, Celio R. Muniz, Valdir B. Bezerra

In the present paper we investigate thermal fluctuation corrections to the vacuum energy at zero temperature of a conformally coupled massless scalar field whose modes propagate in the Einstein universe with a spherical boundary, characterized by both Dirichlet and Neumann boundary conditions. Thus, we generalize the results found in literature in this scena

Adèle L. C. Mackowiak, Christopher W. Roy, Jérôme Yerly, Mariana B. L. Falcão

PURPOSE To develop free-running multi-echo GRE for cardiac- and respiratory-motion-resolved whole-heart fat fraction quantification. METHODS Multi-echo readouts optimized for water-fat separation and quantification were integrated within a non-ECG-triggered free-breathing 3D radial GRE acquisition. Pilot Tone navigation was used to extract cardiac and respir

Hongyuan Yu, Ting Li, Weichen Yu, Jianguo Li

Multivariate time-series forecasting is a critical task for many applications, and graph time-series network is widely studied due to its capability to capture the spatial-temporal correlation simultaneously. However, most existing works focus more on learning with the explicit prior graph structure, while ignoring potential information from the implicit gra

Jun-Qian Jiang, Gen Ye, Yun-Song Piao

The spectral index $n_s$ of scalar perturbation is the significant initial condition set by inflation theory for our observable Universe. According to Planck results, current constraint is $n_s = 0.965\pm 0.004$, while an exact scale-invaiant Harrison-Zeldovich spectrum, i.e. $n_s=1$, has been ruled out at $8.4\sigma$ significance level. However, it is well-

Syed Rizvi, Akash Awasthi, Maria J. Peláez, Zhihui Wang

The COVID-19 pandemic has affected countries across the world, demanding drastic public health policies to mitigate the spread of infection, leading to economic crisis as a collateral damage. In this work, we investigated the impact of human mobility (described via international commercial flights) on COVID-19 infection dynamics at the global scale. For this

Peyman Mohammadzadeh germi, Mohsen Najarbashi

To produce important investment decisions, investors require financial records and economic information. However, most companies manipulate investors and financial institutions by inflating their financial statements. Fraudulent Financial Activities exist in any monetary or financial transaction scenario, whether physical or electronic. A challenging problem

Antoine Gagnebin

In this paper, we study the backward problem for the one-dimensional Vlasov-Poisson system with massless electrons, and we show the Landau damping by fixing the asymptotic behaviour of our solution.

O. Aslan, A. Popov

The self-force of the electromagnetic charge in the space-time of a wormhole with an infinitely short throat is calculated. It is assumed that the charge is a source of an electromagnetic field that is in non-minimal connection with the curvature of space-time.

Aron Zwaan

To warrant programmer productivity, type checker results should be correct and available quickly. Correctness can be provided when a type checker implementation corresponds to a declarative type system specification. Statix is a type system specification language which achieves this by automatically deriving type checker implementations from declarative typi

Kensei Morijiri, Kento Takehana, Takatomo Mihana, Kazutaka Kanno

Photonic accelerators have attracted increasing attention in artificial intelligence applications. The multi-armed bandit problem is a fundamental problem of decision making using reinforcement learning. However, the scalability of photonic decision making has not yet been demonstrated in experiments, owing to technical difficulties in physical realization.

Murad Banaji, Balázs Boros, Josef Hofbauer

We present a three-dimensional differential equation, which robustly displays a degenerate Andronov-Hopf bifurcation of infinite codimension, leading to a center, i.e., an invariant two-dimensional surface that is filled with periodic orbits surrounding an equilibrium. The system arises from a three-species bimolecular chemical reaction network consisting of

Nasrin Shabani

Creativity, i.e., the process of generating and developing fresh and original ideas or products that are useful or effective, is a valuable skill in a variety of domains. Creativity is called an essential 21st-century skill that should be taught in schools. The use of educational technology to promote creativity is an active study field, as evidenced by seve

Lea Fuß, Mathias Garny

Decaying Cold Dark Matter (DCDM) is a model that is currently under investigation regarding primarily the $S_8$ tension between cosmic microwave background (CMB) and certain large-scale structure measurements. The decay into one massive and one (or more) massless daughter particle(s) leads to a suppression of the power spectrum in the late universe that depe

Johanne Cohen, Laurence Pilard, François Pirot, Jonas Sénizergues

We analyze the impact of transient and Byzantine faults on the construction of a maximal independent set in a general network. We adapt the self-stabilizing algorithm presented by Turau `for computing such a vertex set. Our algorithm is self-stabilizing and also works under the more difficult context of arbitrary Byzantine faults. Byzantine nodes can prevent

Dong Zhao, Adriana-Simona Mihaita, Yuming Ou, Sajjad Shafiei

A multi-modal transport system is acknowledged to have robust failure tolerance and can effectively relieve urban congestion issues. However, estimating the impact of disruptions across multi-transport modes is a challenging problem due to a dis-aggregated modelling approach applied to only individual modes at a time. To fill this gap, this paper proposes a

Ranjeet Dalal, I. J. Douglas MacGregor

While the main features of atomic nuclei are well described by nuclear mean-field models, there is a large and growing body of evidence which indicates an important additional role played by spatially-correlated nucleon-nucleon structures. The role of nucleonic structures was first suggested by Heidmann in 1950 to explain pick-up reactions of energetic nucle

Andrea Lattuada, Frank McSherry

Distributed data processing systems have advanced through models that expose more and more opportunities for concurrency within a computation. The scheduling of these increasingly sophisticated models has become the bottleneck for improved throughput and reduced latency. We present a new coordination primitive for dataflow systems, the timestamp token, which

Denis Huseljic, Marek Herde, Lukas Rauch, Paul Hahn

Deep active learning (AL) selects batches of instances for annotation to avoid retraining deep neural networks (DNNs) after each new label. Employing a naive top-$b$ selection can result in a batch of redundant (similar) instances. To address this, various AL strategies employ clustering techniques that ensure diversity within a batch. We approach this issue

Martin Brešar, Pavle Boškoski

Inferring the coupling direction from measured time series of complex systems is challenging. We propose a new state space based causality measure obtained from cross-distance vectors for quantifying interaction strength. It is a model-free noise-robust approach that requires only a few parameters. The approach is applicable to bivariate time series and is r

Yu Zheng, Jinghan Peng, Miao Zhao, Yufeng Ma

This paper presents the system description of the THUEE team for the NIST 2020 Speaker Recognition Evaluation (SRE) conversational telephone speech (CTS) challenge. The subsystems including ResNet74, ResNet152, and RepVGG-B2 are developed as speaker embedding extractors in this evaluation. We used combined AM-Softmax and AAM-Softmax based loss functions, nam

Moritz Einfalt, Katja Ludwig, Rainer Lienhart

The state-of-the-art for monocular 3D human pose estimation in videos is dominated by the paradigm of 2D-to-3D pose uplifting. While the uplifting methods themselves are rather efficient, the true computational complexity depends on the per-frame 2D pose estimation. In this paper, we present a Transformer-based pose uplifting scheme that can operate on tempo

Panping Li, Qian-Qing Yin, Zhengwei Li, Lian Tao

In time-domain astronomy, a substantial number of transients will be discovered by multi-wavelength and multi-messenger observatories, posing a great challenge for follow-up capabilities. We have thus proposed an intelligent X-ray constellation, the Chasing All Transients Constellation Hunters (CATCH) space mission. Consisting of 126 micro-satellites in thre

Xuan Gao, Chenglai Zhong, Jun Xiang, Yang Hong

We present a novel semantic model for human head defined with neural radiance field. The 3D-consistent head model consist of a set of disentangled and interpretable bases, and can be driven by low-dimensional expression coefficients. Thanks to the powerful representation ability of neural radiance field, the constructed model can represent complex facial att

Juncheng Li, Pingzhong Tang

Most of the work in the auction design literature assumes that bidders behave rationally based on the information available for every individual auction, and the revelation principle enables designers to restrict their efforts to incentive compatible (IC) mechanisms. However, in today's online advertising markets, one of the most important real-life applicat

Anthony Knittel, Majd Hawasly, Stefano V. Albrecht, John Redford

Accurate prediction is important for operating an autonomous vehicle in interactive scenarios. Prediction must be fast, to support multiple requests from a planner exploring a range of possible futures. The generated predictions must accurately represent the probabilities of predicted trajectories, while also capturing different modes of behaviour (such as t

Piotr Kawa, Marcin Plata, Piotr Syga

Audio DeepFakes are utterances generated with the use of deep neural networks. They are highly misleading and pose a threat due to use in fake news, impersonation, or extortion. In this work, we focus on increasing accessibility to the audio DeepFake detection methods by providing SpecRNet, a neural network architecture characterized by a quick inference tim

Amir Hadifar, Semere Kiros Bitew, Johannes Deleu, Chris Develder

We introduce a high-quality dataset that contains 3,397 samples comprising (i) multiple choice questions, (ii) answers (including distractors), and (iii) their source documents, from the educational domain. Each question is phrased in two forms, normal and close. Correct answers are linked to source documents with sentence-level annotations. Thus, our versat

Muhammad Junaid Arshad, Christiaan Bekker, Ben Haylock, Krzysztof Skrzypczak

Characterising the time over which quantum coherence survives is critical for any implementation of quantum bits, memories and sensors. The usual method for determining a quantum system's decoherence rate involves a suite of experiments probing the entire expected range of this parameter, and extracting the resulting estimation in post-processing. Here we pr

Avioz Dagan, Yaniv Edery

In recent years, Darcy scale transport in porous media was characterized to be Fickian or non-Fickian due to the homogeneity or heterogeneity of the porous medium conductivity layout. Yet, evidence shows that preferential flows that funnel the transport occur in heterogeneous and homogenous cases. We model the Darcy scale transport using a 2D conductivity fi

Yatin Chaudhary, Pranav Rai, Matthias Schubert, Hinrich Schütze

In this work, we combine the two paradigms: Federated Learning (FL) and Continual Learning (CL) for text classification task in cloud-edge continuum. The objective of Federated Continual Learning (FCL) is to improve deep learning models over life time at each client by (relevant and efficient) knowledge transfer without sharing data. Here, we address challen

Ananda Hota, Pratik Dabhade, Sravani Vaddi, Chiranjib Konar

AGN feedback during galaxy merger has been the most favoured model to explain black hole-galaxy co-evolution. However, how the AGN-driven jet/wind/radiation is coupled with the gas of the merging galaxies, which leads to positive feedback, momentarily enhanced star formation, and subsequently negative feedback, a decline in star formation, is poorly understo

Priya Chakraborty, Ushasi Roy, Mohit K. Jolly, Sayantari Ghosh

Biological systems are majorly dependent on their property of bistability in order to exhibit nongenetic heterogeneity in terms of cellular morphology and physiology. Spatial patterns of phenotypically heterogeneous cells, arising due to underlying bistability, may play significant role in phenomena like biofilm development, adaptation, cell motility etc. Wh

Konstantin Hauch, Claudia Redenbach

We present canonical quantiles and depths for directional data following a distribution which is elliptically symmetric about a direction $\mu$ on the sphere $\mathcal{S}^{d-1}$. Our approach extends the concept of Ley et al. [1], which provides valuable geometric properties of the depth contours (such as convexity and rotational equivariance) and a Bahadur-

Michael L. Weber, Barbara Ercolano, Giovanni Picogna, Christian Rab

Disc winds and planet formation are considered to be two of the most important mechanisms that drive the evolution and dispersal of protoplanetary discs and in turn define the environment in which planets form and evolve. While both have been studied extensively in the past, we combine them into one model by performing three-dimensional radiation-hydrodynami

Xinyu Sun, Peihao Chen, Liangwei Chen, Changhao Li

How to learn discriminative video representation from unlabeled videos is challenging but crucial for video analysis. The latest attempts seek to learn a representation model by predicting the appearance contents in the masked regions. However, simply masking and recovering appearance contents may not be sufficient to model temporal clues as the appearance c

Pietro Di Gianantonio, Abbas Edalat, Ran Gutin

We present a simple functional programming language, called Dual PCF, that implements forward mode automatic differentiation using dual numbers in the framework of exact real number computation. The main new feature of this language is the ability to evaluate correctly up to the precision specified by the user -- in a simple and direct way -- the directional

Achraf Ben-Hamadou, Nour Neifar, Ahmed Rekik, Oussama Smaoui

Intraoral 3D scanning is now widely adopted in modern dentistry and plays a central role in supporting key tasks such as tooth segmentation, detection, labeling, and dental landmark identification. Accurate analysis of these scans is essential for orthodontic and restorative treatment planning, as it enables automated workflows and minimizes the need for man

Prabhanjan Ananth, Alex B. Grilo

The traditional definition of quantum zero-knowledge stipulates that the knowledge gained by any quantum polynomial-time verifier in an interactive protocol can be simulated by a quantum polynomial-time algorithm. One drawback of this definition is that it allows the simulator to consume significantly more computational resources than the verifier. We argue

Chuchu Chen, Jialin Hong, Lihai Ji, Ge Liang

In this paper, we propose a novel kind of numerical approximations to inherit the ergodicity of stochastic Maxwell equations. The key to proving the ergodicity lies in the uniform regularity estimates of the numerical solutions with respect to time, which are established by analyzing some important physical quantities. By introducing an auxiliary process, we

Avshalom Offner, Sam Manger, Jacques Vanneste

Positron Emission Particle Tracking (PEPT) is an imaging method for the visualization of fluid motion, capable of reconstructing three-dimensional trajectories of small tracer particles suspended in nearly any medium, including fluids that are opaque or contained within opaque vessels. The particles are labeled radioactively, and their positions are reconstr

Shuhao Deng, Chengfei Li, Jinfeng Bai, Qingqing Zhang

Code-switching automatic speech recognition becomes one of the most challenging and the most valuable scenarios of automatic speech recognition, due to the code-switching phenomenon between multilingual language and the frequent occurrence of code-switching phenomenon in daily life. The ISCSLP 2022 Chinese-English Code-Switching Automatic Speech Recognition

Oktay Karakuş

Marine plastic pollution is an emerging environmental problem since it pollutes the ocean, air and food whilst endangering the ocean wildlife via the ingestion and entanglements. During the last decade, an enormous effort has been spent on finding possible solutions to marine plastic pollution. Remote sensing imagery sits in a crucial place for these efforts