October 2023 arXiv papers — page 173

Rhyan Barrett, Julia Westermayr

In recent years, deep learning has made remarkable strides, surpassing human capabilities in tasks like strategy games, and it has found applications in complex domains, including protein folding. In the realm of quantum chemistry, machine learning methods have primarily served as predictive tools or design aids using generative models, while reinforcement l

François De Keersmaeker, Ramin Sadre, Cristel Pelsser

Internet of Things devices can now be found everywhere, including in our households in the form of Smart Home networks. Despite their ubiquity, their security is unsatisfactory, as demonstrated by recent attacks. The IETF's MUD standard has as goal to simplify and automate the secure deployment of end devices in networks. A MUD file contains a device specifi

Darshan Kumar, Debajyoti Choudhury, Debottam Nandi

The simplest cosmological model ($\Lambda$CDM) is well-known to suffer from the Hubble tension, namely an almost $5 \sigma$ discrepancy between the (model-based) early-time determination of the Hubble constant $H_0$ and its late-time (and model-independent) determination. To circumvent this, we introduce an additional energy source that varies with the redsh

Emanuel Willert

Based on a potential theoretical approach, the subsurface stress field is calculated for an elastic-half space, which is subject to normal and uniaxial tangential surface tractions that - in the case of elastic decoupling - correspond to rigid normal and tangential translations of a circular surface domain. The stress fields are obtained explicitly and in cl

Antoine Scardigli, Lukas Cavigelli, Lorenz K. Müller

Monte-Carlo path tracing is a powerful technique for realistic image synthesis but suffers from high levels of noise at low sample counts, limiting its use in real-time applications. To address this, we propose a framework with end-to-end training of a sampling importance network, a latent space encoder network, and a denoiser network. Our approach uses rein

Michael A. Henning, Douglas F. Rall

A vertex $u$ in a graph $G$ totally dominates a vertex $v$ if $u$ is adjacent to $v$ in $G$. A total dominating set of $G$ is a set $S$ of vertices of $G$ such that every vertex of $G$ is totally dominated by a vertex in $S$. The indicated total domination game is played on a graph $G$ by two players, Dominator and Staller, who take turns making a move. In e

Alexander Mock, Martin Magnusson, Joachim Hertzberg

RadaRays allows for the accurate modeling and simulation of rotating FMCW radar sensors in complex environments, including the simulation of reflection, refraction, and scattering of radar waves. Our software is able to handle large numbers of objects and materials in real-time, making it suitable for use in a variety of mobile robotics applications. We demo

Michail Zampetakis, Fanouria Antoniou, Foteini Asvesta, Hannes Bartosik

The ion injectors of the CERN accelerator chain, in particular the Super Proton Synchrotron (SPS) and the Low Energy Ion Ring (LEIR), operate in a strong space charge (SC) and intrabeam scattering (IBS) regime, which can degrade beam quality. Optimizing the ion beam performance therefore requires studying the interplay of these two effects in tracking simula

Nicola Di Vittorio, Gabriele Lobbia

We prove a generalised interchange equality for 3-cells in a Gray-category, i.e. we show that it still holds modulo the unique isomorphism given by the Gray-categorical pasting theorem of Di Vittorio. This significantly simplifies many calculations in Gray-categories.

Anton Razzhigaev, Arseniy Shakhmatov, Anastasia Maltseva, Vladimir Arkhipkin

Text-to-image generation is a significant domain in modern computer vision and has achieved substantial improvements through the evolution of generative architectures. Among these, there are diffusion-based models that have demonstrated essential quality enhancements. These models are generally split into two categories: pixel-level and latent-level approach

Joshua C. Yang, Carina I. Hausladen, Dominik Peters, Evangelos Pournaras

Participatory Budgeting (PB) has evolved into a key democratic instrument for resource allocation in cities. Enabled by digital platforms, cities now have the opportunity to let citizens directly propose and vote on urban projects, using different voting input and aggregation rules. However, the choices cities make in terms of the rules of their PB have ofte

Ninon Lizé Masclef, T. Anderson Keller

A prominent theory of affective response to music revolves around the concepts of surprisal and expectation. In prior work, this idea has been operationalized in the form of probabilistic models of music which allow for precise computation of song (or note-by-note) probabilities, conditioned on a 'training set' of prior musical or cultural experiences. To da

Kai Jeggle, Mikolaj Czerkawski, Federico Serva, Bertrand Le Saux

Clouds containing ice particles play a crucial role in the climate system. Yet they remain a source of great uncertainty in climate models and future climate projections. In this work, we create a new observational constraint of regime-dependent ice microphysical properties at the spatio-temporal coverage of geostationary satellite instruments and the qualit

Anargyros Chrysanthou, Yorgos Pantis, Constantinos Patsakis

In an era dominated by digital interactions, phishing campaigns have evolved to exploit not just technological vulnerabilities but also human traits. This study takes an unprecedented deep dive into large-scale phishing campaigns aimed at Meta's users, offering a dual perspective on the technical mechanics and human elements involved. Analysing data from ove

X. Carvajal, P. Gamboa, R. Santos

We consider the initial value problem (IVP) associated to a higher order nonlinear Schr\"odinger (h-NLS) equation $ \partial_{t}u+ia \partial^{2}_{x}u+ b\partial^{3}_{x}u+ic_1|u|^{2}u+c_2 |u|^{2}\partial_{x}u=0, \quad x,t \in \mathbb{R}, $ for given data in the modulation space $M_s^{2,p}(\mathbb{R})$. Using ideias of Killip, Visan, Zhang, Oh, Wang, we prove

Elena Apresyan, Gor Sarkissian

In this paper we calculate matrix of modular transformations of the one-point toric conformal blocks in the Neveu-Schwarz sector of $N=1$ super Liouville field theory. For this purpose we use explicit expression for this matrix as integral of product of certain elements of fusion matrix. This integral is computed using the chain of integral identities for su

Mathieu Lewin, Phan Thành Nam

We consider the nonlinear Gross-Pitaevskii equation at positive density, that is, for a bounded solution not tending to 0 at infinity. We focus on infinite ground states, which are by definition minimizers of the energy under local perturbations. When the Fourier transform of the interaction potential takes negative values we prove the existence of a phase t

Saifullah Saifullah, Stefan Agne, Andreas Dengel, Sheraz Ahmed

In this paper, we introduce strategies for developing private Key Information Extraction (KIE) systems by leveraging large pretrained document foundation models in conjunction with differential privacy (DP), federated learning (FL), and Differentially Private Federated Learning (DP-FL). Through extensive experimentation on six benchmark datasets (FUNSD, CORD

Samuel Garcin, James Doran, Shangmin Guo, Christopher G. Lucas

A key limitation preventing the wider adoption of autonomous agents trained via deep reinforcement learning (RL) is their limited ability to generalise to new environments, even when these share similar characteristics with environments encountered during training. In this work, we investigate how a non-uniform sampling strategy of individual environment ins

Felix Finster, Magdalena Lottner, Alexander V. Sobolev

We consider the fermionic entanglement entropy for the free Dirac field in a bounded spatial region of Minkowski spacetime. In order to make the system ultraviolet finite, a regularization is introduced. An area law is proven in the limiting cases where the volume tends to infinity and/or the regularization length tends to zero. The technical core of the pap

Tony Lelièvre, Thomas Pigeon, Gabriel Stoltz, Wei Zhang

Finding collective variables to describe some important coarse-grained information on physical systems, in particular metastable states, remains a key issue in molecular dynamics. Recently, machine learning techniques have been intensively used to complement and possibly bypass expert knowledge in order to construct collective variables. Our focus here is on

Washington Cunha, Celso França, Leonardo Rocha, Marcos André Gonçalves

There is a niche of companies responsible for intermediating the purchase of large batches of varied products for other companies, for which the main challenge is to perform product description standardization, i.e., matching an item described by a client with a product described in a catalog. The problem is complex since the client's product description may

S. D. Solanki, S. B. Dhotre

Splitting operation in Matroid Theory does not preserve graphicness, connectedness, cographicness, etc. Also, the splitting of binary gammoid does not necessarily be binary gammoid after splitting. We have characterized a class of graphic matroids that gives binary gammoids after splitting. We have obtained prohibited minors for graphic and cographic matroid

Constantin Schuster, Sebastian Kempf

Cryogenic microcalorimeters are outstanding tools for X-ray spectroscopy due to their unique combination of excellent energy resolution and close to 100% detection efficiency. While well-established microcalorimeter concepts have already proven impressive performance, their energy resolution has yet to improve to be competitive with cutting-edge wavelength-d

Andrea Ninarello, José Ruiz-Franco, Emanuela Zaccarelli

Low-connectivity polymer networks were recently found to behave auxetically when subjected to small tensions, that is, their Poisson's ratio $\nu$ becomes negative. In addition, for specific state points, numerical simulations revealed that diamond-like networks reach the limit of mechanical stability, exhibiting values of $\nu = -1$, a condition that we def

Federico Binda, Stefano Fedel, Santos Francisco Alvarado, Paul Noël

Topological insulators have attracted great interest as generators of spin-orbit torques (SOTs) in spintronic devices. Bi\textsubscript{1-x}Sb\textsubscript{x} is a prominent topological insulator that has a high charge-to-spin conversion efficiency. However, the origin and magnitude of the SOTs induced by current-injection in Bi\textsubscript{1-x}Sb\textsub

P B Jones

More than twenty papers on the development of this model have been published in Monthly Notices of the Royal Astronomical Society from 2010 to the present. Whilst some contain work that is essential for the development of the model, others are less so. This present paper is a summary, citing only the former set of papers and the observational phenomena to wh

Dimitrios Kollias, Karanjot Vendal, Priyanka Gadhavi, Solomon Russom

Brain tumors pose significant health challenges worldwide, with glioblastoma being one of the most aggressive forms. Accurate determination of the O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status is crucial for personalized treatment strategies. However, traditional methods are labor-intensive and time-consuming. This paper proposes

Takumi Fukushima, Nayuta Takemori, Shiro Sakai, Masanori Ichioka

We theoretically study the real-space distribution of the supercurrent that flows under a uniform vector potential in a two-dimensional quasiperiodic structure. This is done by considering the attractive Hubbard model on the quasiperiodic Ammann-Beenker structure and studying the superconducting phase within the Bogoliubov-de Gennes mean-field theory. Decomp

Piyush Kumar, Ignacio A. Reyes, Jakob Wintergerst

There is a well-known correspondence between the physics of black hole evaporation and that of moving mirrors in QFT. However, most analyses in this subject rely on prescribed mirror trajectories. Here, we study the flat-space dynamics of $1+1$-dimensional Conformal Field Theories interacting with a relativistic boundary particle of mass $m$ acting as a perf

Jonatan Vallin, Karl Larsson, Mats G. Larson

We formalize and interpret the geometric structure of $d$-dimensional fully connected ReLU layers in neural networks. The parameters of a ReLU layer induce a natural partition of the input domain, such that the ReLU layer can be significantly simplified in each sector of the partition. This leads to a geometric interpretation of a ReLU layer as a projection

Chiara Zappalá, Alessio Emanuele Biondo, Alessandro Pluchino, Andrea Rapisarda

Individual sports competitions provide a natural setting for examining the relative importance of talent and luck/chance in achieving success. The belief that success is primarily due to individual abilities and hard work rather than external factors is particularly strong in this context. In this study, we test this belief using tennis as a case study, due

Kirill Khrylchenko, Alexander Fritzler

Personalizing user experience with high-quality recommendations based on user activity is vital for e-commerce platforms. This is particularly important in scenarios where the user's intent is not explicit, such as on the homepage. Recently, personalized embedding-based systems have significantly improved the quality of recommendations and search in the e-co

Gerardo Roa Dabike, Michael A. Akeroyd, Scott Bannister, Jon Barker

This paper reports on the design and results of the 2024 ICASSP SP Cadenza Challenge: Music Demixing/Remixing for Hearing Aids. The Cadenza project is working to enhance the audio quality of music for those with a hearing loss. The scenario for the challenge was listening to stereo reproduction over loudspeakers via hearing aids. The task was to: decompose p

Kartick Adhikari, Arup Bose, Shambhu Nath Maurya

We investigate the joint convergence of independent random Toeplitz matrices with complex input entries that have a pair-correlation structure, along with deterministic Toeplitz matrices and the backward identity permutation matrix. Further, we study the joint convergence of independent generalized Toeplitz matrices along with other related matrices. The lim

Boshi An, Yiran Geng, Kai Chen, Xiaoqi Li

Robotic manipulation requires accurate perception of the environment, which poses a significant challenge due to its inherent complexity and constantly changing nature. In this context, RGB image and point-cloud observations are two commonly used modalities in visual-based robotic manipulation, but each of these modalities have their own limitations. Commerc

François Remy, Pieter Delobelle, Bettina Berendt, Kris Demuynck

Training monolingual language models for low and mid-resource languages is made challenging by limited and often inadequate pretraining data. In this study, we propose a novel model conversion strategy to address this issue, adapting high-resources monolingual language models to a new target language. By generalizing over a word translation dictionary encomp

Stephen W. Lovesey

Uranium ions in sesquinitride alpha-U2N3 occupy independent acentric and centrosymmetric sites according to conventional x-ray diffraction patterns [R. Tro\'c, J. Solid State Chem. 13, 14 (1975)]. We submit that polar uranium multipoles in acentric sites are revealed in resonant x-ray diffraction data recently published by Lawrence Bright et al. [Phys. Rev.

Siyuan Guo, Jihong Guan, Shuigeng Zhou

In the past decade, Artificial Intelligence driven drug design and discovery has been a hot research topic, where an important branch is molecule generation by generative models, from GAN-based models and VAE-based models to the latest diffusion-based models. However, most existing models pursue only the basic properties like validity and uniqueness of the g

Sebastián A. Díaz, Jonas Nothhelfer, Kjetil M. D. Hals, Karin Everschor-Sitte

Vortices are point-like topological defects in superconductors whose motion dictates superconducting properties and controls device performance. In superconductor-ferromagnet heterostructures, vortices interact with topological defects in the ferromagnet such as line-like domain walls. While in previous heterostructure generations, vortex-domain wall interac

Xiaolin Bu, Zihao Li, Shengxin Liu, Jiaxin Song

We study the fair allocation of indivisible resources among agents. Most prior work focuses on fairness and/or efficiency among agents. However, the allocator, as the resource owner, may also be involved in many scenarios (e.g., government resource allocation, heritage division, company personnel assignment, etc). The allocator inclines to obtain a fair or e

Joshua F. Robinson, Patrick B. Warren, Matthew R. Turner, and Richard P. Sear

Aerosols are ubiquitous, and particle capture from particle-laden air as it flows past an obstacle is of widespread practical importance. Neglecting diffusion, previous work has shown that for a smooth curved surface in both Stokes flow and inviscid flow, only particles with inertia above a threshold value (quantified by the nondimensional Stokes number) col

Litton J Kurisinkel, Nancy F chen

Memory-efficient large language models are good at refining text input for better readability. However, controllability is a matter of concern when it comes to text generation tasks with long inputs, such as multi-document summarization. In this work, we investigate for a generic controllable approach for multi-document summarization that leverages the capab

Shunkai Shi, Yuqi Wang, Qihui Ye, Yanran Wang

In Traditional Chinese Medicine, the tooth marks on the tongue, stemming from prolonged dental pressure, serve as a crucial indicator for assessing qi (yang) deficiency, which is intrinsically linked to visceral health. Manual diagnosis of tooth-marked tongue solely relies on experience. Nonetheless, the diversity in shape, color, and type of tooth marks pos

Jing Zhang, Ze-Chun Hu, Wei Sun

Let ${\cal I}$ be the set of all infinitely divisible random variables\ with finite second moments, ${\cal I}_0=\{X\in{\cal I}:{\rm Var}(X)>0\}$, $P_{\cal I}=\inf_{X\in{\cal I}}P\{|X-E[X]|\le \sqrt{{\rm Var}(X)}\}$ and $P_{{\cal I}_0}=\inf_{X\in{\cal I}_0} P\{|X-E[X]|< \sqrt{{\rm Var}(X)}\}$. Firstly, we prove that $P_{{\cal I}}\ge P_{{\cal I}_0}>0$. Secondl

Hongwei Li, Tao Xiong

In this paper, we propose a method to estimate the exact location of a camera in a cyber-physical system using the exact geographic coordinates of four feature points stored in QR codes(Quick response codes) and the pixel coordinates of four feature points analyzed from the QR code images taken by the camera. Firstly, the P4P(Perspective 4 Points) algorithm

Tanmay Inamdar, Lawqueen Kanesh, Madhumita Kundu, M. S. Ramanujan

For numerous graph problems in the realm of parameterized algorithms, using the size of a smallest deletion set (called a modulator) into well-understood graph families as parameterization has led to a long and successful line of research. Recently, however, there has been an extensive study of structural parameters that are potentially much smaller than the

Robert Kindler, Johannes Handsteiner, Jaroslav Kysela, Kuntuo Zhu

We present an adaptive procedure for aligning quantum non-locality experiments without any knowledge of the two-qudit state shared by the participating parties. The quantum state produced by the source, its unitary evolution as well as the actual measurement bases remain unknown to both parties at all times. The entanglement of the quantum state helps establ

Fabio Natali, Gabriel E. Bittencourt Moraes

In this paper, we determine the transverse instability of periodic standing wave solutions for the generalized Schr\"odinger equation with fractional power nonlinearity. The existence of periodic waves is determined by using a constrained minimization problem in the complex setting, and it is shown that the corresponding real solution, depending on the power

Amir Hossein Akhavan Rahnama

The number of local model-agnostic explanation techniques proposed has grown rapidly recently. One main reason is that the bar for developing new explainability techniques is low due to the lack of optimal evaluation measures. Without rigorous measures, it is hard to have concrete evidence of whether the new explanation techniques can significantly outperfor

Satyajit Puhan, Harleen Dahiya

We have presented the leading twist quark transverse momentum-dependent parton distribution functions (TMDs) for the spin-1 heavy vector mesons $J/\psi$-meson and $\Upsilon$-meson using the overlap of the light-front wave functions. We have computed their TMDs in the light-front holographic model (LFHM) as well as the light-front quark model (LFQM) and furth

Satyajit Puhan, Shubham Sharma, Navpreet Kaur, Narinder Kumar

We have investigated the pseudo-scalar meson structure in the form of transverse momentum-dependent parton distribution functions (TMDs) in the light-front based holographic model and quark model. Starting from leading order, we have calculated all the time-reversal even TMDs for pion and kaon up to twist-$4$ in these models. We have shown the 3-dimensional

Shubham Sharma, Harleen Dahiya

In this work, we delve into the realm of quantum chromodynamics (QCD) by calculating twist-4 chiral-even generalized parton distributions (GPDs), within the context of the light-front quark-diquark model (LFQDM), focusing specifically on the intriguing case of zero skewness. To shed light on the behavior of twist-4 chiral-even GPDs, we present comprehensive

Navpreet Kaur, Harleen Dahiya

We have presented a pathway to map the internal structure of lowest-lying octet baryons by using one-loop quantum fluctuations of a fermion state in Yukawa theory. The structural interpretation of baryons carrying different amount of strange content has been exemplified by employing a quark-scalar diquark model for studying the Generalized Parton Distributio

Yan Sun, Li Shen, Dacheng Tao

As two mainstream frameworks in federated learning (FL), both centralized and decentralized approaches have shown great application value in practical scenarios. However, existing studies do not provide sufficient evidence and clear guidance for analysis of which performs better in the FL community. Although decentralized methods have been proven to approach

Christopher J. Inman, Cristina C. Popescu, Mark T. Rushton, David Murphy

A quantitative derivation of the intrinsic properties of galaxies related to their fundamental building blocks, gas, dust and stars is essential for our understanding of galaxy evolution. A fully self-consistent derivation of these properties can be achieved with radiative transfer (RT) methods that are constrained by panchromatic imaging observations. Here

Samantha Fairchild, Jiyoung Han

We develop the theory and properties of primitive unimodular $S$-arithmetic lattices in $\mathbb{Q}_S^d$ by giving integral formulas in the spirit of Siegel's primitive mean value formula and Rogers' and Schmidt's second moment formulas. When $d=2$, unlike in the real case, functions arising from the $S$-primitive Siegel transform are unbounded, requiring a

Marcus Olofsson, André Berg Niklas L. P. Lundström

We use a dynamic programming approach to construct management strategies for a hydropower plant with a dam and a continuously adjustable unit. Along the way, we estimate unknown variables via simple models using historical data and forecasts. Our suggested scheme achieves on average 97.1 % of the theoretical maximum using small computational effort. We also

Aleksandra Urman, Aniko Hannak, Mykola Makhortykh

Internet users highly rely on and trust web search engines, such as Google, to find relevant information online. However, scholars have documented numerous biases and inaccuracies in search outputs. To improve the quality of search results, search engines employ various content moderation practices such as interface elements informing users about potentially

Kwanseok Oh, Da-Woon Heo, Ahmad Wisnu Mulyadi, Wonsik Jung

Deep learning (DL) for predicting Alzheimer's disease (AD) has provided timely intervention in disease progression yet still demands attentive interpretability to explain how their DL models make definitive decisions. Recently, counterfactual reasoning has gained increasing attention in medical research because of its ability to provide a refined visual expl

Edward Fish, Jon Weinbren, Andrew Gilbert

Temporal Action Localization (TAL) aims to identify actions' start, end, and class labels in untrimmed videos. While recent advancements using transformer networks and Feature Pyramid Networks (FPN) have enhanced visual feature recognition in TAL tasks, less progress has been made in the integration of audio features into such frameworks. This paper introduc

Francesca Ronchini, Romain Serizel

In recent years, deep learning systems have shown a concerning trend toward increased complexity and higher energy consumption. As researchers in this domain and organizers of one of the Detection and Classification of Acoustic Scenes and Events challenges tasks, we recognize the importance of addressing the environmental impact of data-driven SED systems. I

F. Dell'Agli, S. Tosi, D. Kamath, L. Stanghellini

We present a novel approach to address dust production by low- and intermediate-mass stars. We study the asymptotic giant branch (AGB) phase, during which the formation of dust takes place, from the perspective of post-AGB and planetary nebula (PN) evolutionary stage. Using results from stellar evolution and dust formation modelling, we interpret the spectra

Paloma Laguarta, Robin van der Laag, Melissa Lopez, Tom Dooney

Gravitational-wave (GW) interferometers are able to detect a change in distance of $\sim$ 1/10,000th the size of a proton. Such sensitivity leads to large appearance rates of non-Gaussian transient noise bursts in the main detector strain, also known as glitches. These glitches come in a wide range of frequency-amplitude-time morphologies and are caused by e

P. Dyke, S. Musolino, H. Kurkjian, D. J. M. Ahmed-Braun

Symmetry-breaking phase transitions are central to our understanding of states of matter. When a continuous symmetry is spontaneously broken, new excitations appear that are tied to fluctuations of the order parameter. In superconductors and fermionic superfluids, the phase and amplitude can fluctuate independently, giving rise to two distinct collective bra

Mateo Galdeano, Daniel Platt, Yuuji Tanaka, Luya Wang

We construct $Spin(7)$-instantons on one of Joyce's compact $Spin(7)$-manifolds. The underlying compact $Spin(7)$-manifold given by Joyce is the same as in Lewis' construction of $Spin(7)$-instantons. However, our construction method and the resulting instantons are new. The compact $Spin(7)$-manifold is constructed by gluing a $Spin(7)$-orbifold and certain

V. M. Aynutdinov, V. A. Allakhverdyan, A. D. Avrorin, A. V. Avrorin

Reconstructed tracks of muons produced in neutrino interactions provide the precise probe for the neutrino direction. Therefore, track-like events are a powerful tool to search for neutrino point sources. Recently, Baikal-GVD has demonstrated the first sample of low-energy neutrino candidate events extracted from the data of the season 2019 in a so-called si

Thomas Berger, Achim Ilchmann, Eugene P. Ryan

The methodology of funnel control was introduced in the early 2000s, and it has developed since then in many respects achieving a level of mathematical maturity balanced by practical applications. Its fundamental tenet is the attainment of prescribed transient and asymptotic behaviour for continuous-time controlled dynamical processes encompassing linear and

Szanna Zsíros, Tamás Szalai, Ilse De Looze, Arkaprabha Sarangi

We present mid-infrared (mid-IR) imaging of the Type IIL supernova (SN) 1980K with the James Webb Space Telescope (JWST) more than 40 yr post-explosion. SN 1980K, located in the nearby ($D\approx7$ Mpc) "SN factory" galaxy NGC 6946, was serendipitously captured in JWST/MIRI images taken of the field of SN 2004et in the same galaxy. SN 1980K serves as a promi

Samuel Maddock, Graham Cormode, Carsten Maple

Preserving individual privacy while enabling collaborative data sharing is crucial for organizations. Synthetic data generation is one solution, producing artificial data that mirrors the statistical properties of private data. While numerous techniques have been devised under differential privacy, they predominantly assume data is centralized. However, data

X. Lin, M. T. Hartman, S. Zhang, S. Seidelin

The agile generation and control of multiple optical frequency modes combined with the realtime processing of multi-mode data provides access to experimentation in domains such as optomechanical systems, optical information processing, and multi-mode spectroscopy. The latter, specifically spectroscopy of spectral-hole burning (SHB), has motivated our develop

Ezra Schoen, Jade Master, Clemens Kupke

We show how the relatively initial or relatively terminal fixed points for a well-behaved functor $F$ form a pair of adjoint functors between $F$-coalgebras and $F$-algebras. We use the language of locally presentable categories to find sufficient conditions for existence of this adjunction. We show that relative fixed points may be characterized as (co)equa

Frederik Bous, Axel Roebel

The information bottleneck auto-encoder is a tool for disentanglement commonly used for voice transformation. The successful disentanglement relies on the right choice of bottleneck size. Previous bottleneck auto-encoders created the bottleneck by the dimension of the latent space or through vector quantization and had no means to change the bottleneck size

Li-Wei Chen, Kai-Chen Cheng, Hung-Shin Lee

This report provides a concise overview of the proposed North system, which aims to achieve automatic word/syllable recognition for Taiwanese Hakka (Sixian). The report outlines three key components of the system: the acquisition, composition, and utilization of the training data; the architecture of the model; and the hardware specifications and operational

Charles Collot, Elena Danesi, Anne-Sophie de Suzzoni, Cyril Malézé

The Hartree-Fock equation admits homogeneous states that model infinitely many particles at equilibrium. We prove their asymptotic stability in large dimensions, under assumptions on the linearised operator. Perturbations are moreover showed to scatter to linear waves. We obtain this result for the equivalent formulation of the Hartree-Fock equation in the f

Zhaoyang Cheng, Guanpu Chen, Yiguang Hong

This paper focuses on the performance of equalizer zero-determinant (ZD) strategies in discounted repeated Stackerberg asymmetric games. In the leader-follower adversarial scenario, the strong Stackelberg equilibrium (SSE) deriving from the opponents' best response (BR), is technically the optimal strategy for the leader. However, computing an SSE strategy m

Hao Liang, Yongfeng Zhu, Yuexin Wang, Yuzhi Che

To enhance the scientific discovery power of high-energy collider experiments, we propose and realize the concept of jet origin identification that categorizes jets into 5 quark species $(b,c,s,u,d)$, 5 anti-quarks $(\bar{b},\bar{c},\bar{s},\bar{u},\bar{d})$, and the gluon. Using state-of-the-art algorithms and simulated $\nu\bar{\nu}H, H\rightarrow jj$ even

Andreas Tiffeau-Mayer

Quantification of measurement uncertainty is crucial for robust scientific inference, yet accurate estimates of this uncertainty remain elusive for ecological measures of diversity. Here, we address this longstanding challenge by deriving a closed-form unbiased estimator for the sampling variance of Simpson's diversity index. In numerical tests the estimator

Jeroen S. W. Lamb, Martin Rasmussen, Wei Hao Tey

We consider invertible linear maps with additive spherical bounded noise. We show that minimal attractors of such random dynamical systems are unique, strictly convex and have a continuously differentiable boundary. Moreover, we present an auxiliary finite-dimensional deterministic boundary map for which the unit normal bundle of this boundary is globally at

Ion Nechita, Zikun Ouyang, Anna Szczepanek

We study a class of bistochastic matrices generalizing unistochastic matrices. Given a complex bipartite unitary operator, we construct a bistochastic matrix having as entries the normalized squares of Frobenius norm of the blocks. We show that the closure of the set of generalized unistochastic matrices is the whole Birkhoff polytope. We characterize the po

Martin Magris, Alexandros Iosifidis

The Bayesian estimation of GARCH-family models has been typically addressed through Monte Carlo sampling. Variational Inference is gaining popularity and attention as a robust approach for Bayesian inference in complex machine learning models; however, its adoption in econometrics and finance is limited. This paper discusses the extent to which Variational I

Debasmita Bhoumik, Susmita Sur-Kolay, Latesh Kumar K. J., Sundaraja Sitharama Iyengar

Machine learning in quantum computing and communication provides intensive opportunities for revolutionizing the field of Physics, Mathematics, and Computer Science. There exists an aperture of understanding behind this interdisciplinary domain and a lack of core understanding renders an opportunity to explore the machine learning techniques for this domain.

H. Witała, J. Golak, R. Skibiński

We propose a simplified approach to incorporate the long-range proton-proton (pp) Coulomb force in the three-nucleon (3N) scattering calculations, based on exact formulation presented in Eur. Phys. Journal A {\bf{41}}, 369 (2009) and {\bf{41}}, 385 (2009). It permits us to get elastic proton-deuteron (pd) scattering and breakup observables relatively simply

Sireesha Chamarthi, Katharina Fogelberg, Roman C. Maron, Titus J. Brinker

The potential of deep neural networks in skin lesion classification has already been demonstrated to be on-par if not superior to the dermatologists diagnosis. However, the performance of these models usually deteriorates when the test data differs significantly from the training data (i.e. domain shift). This concerning limitation for models intended to be

Fei Hou, Xuhui Chen, Wencheng Wang, Hong Qin

In this paper, we propose a new method, called DoubleCoverUDF, for extracting the zero level-set from unsigned distance fields (UDFs). DoubleCoverUDF takes a learned UDF and a user-specified parameter $r$ (a small positive real number) as input and extracts an iso-surface with an iso-value $r$ using the conventional marching cubes algorithm. We show that the

Karan Fernandes, Feng-Li Lin, Arpita Mitra

We investigate the celestial description of an eikonal amplitude for the scattering of massless scalars mediated by soft gravitons in the near-horizon region of a large eternal Schwarzschild black hole. Our construction thus provides a celestial conformal field theory on the horizon corresponding to a non-perturbative scattering process that accounts for eve

Matthijs H. S. de Buck, Peter Jezzard, Aaron T. Hess

Purpose: The DANTE-SPACE sequence facilitates three-dimensional intracranial vessel wall imaging with simultaneous suppression of blood and cerebrospinal fluid (CSF). However, the achieved image contrast depends closely on the selected sequence parameters, and the clinical use of the sequence is limited in vivo by observed signal variations in the vessel wal

G. Ejlali, R. Adam, P. Ade, H. Ajeddig

This study presents the first millimeter continuum mapping observations of two nearby galaxies, the starburst spiral galaxy NGC2146 and the dwarf galaxy NGC2976, at 1.15 mm and 2 mm using the NIKA2 camera on the IRAM 30m telescope, as part of the Guaranteed Time Large Project IMEGIN. These observations provide robust resolved information about the physical p

Bimalesh Giri, Dola Chakrabartty, S. S. P. Parkin, Ajaya K. Nayak

Interstitial topological objects, such as skyrmions, within a natural 1-D helix are predicted to be free from ambiguous 'skyrmion Hall effect'. The helical ambience precipitate an additional potential that counteract the Magnus force arising from the gyrotropic motion of skyrmion. Here, we present the observation of $\pm$ $\frac{1}{2}$ topological charge obj

Francesco Camilloni, Werner Becker

Context. G189.6+03.3 and IC443 are two examples of supernova remnants located in a region rich of gas and dust, spatially close to the HII region S249. So far, the actual shape of IC443 is believed to be given by the past action of multiple supernova explosions, while a third unrelated might have originated G189.6+03.3. Aims. If the IC443 nebula has been ext

Yiqi Geng, Mingqi Cao, Ruilin Zhu

To distinguish the low-lying vector beauty-charm meson, we systematically study the $B_c^*\to B_c+\gamma$, $B_c^*\to \ell+{\nu}_{\ell}$ and $B_c^{(*)}\to J/\psi+nh$ processes within effective theory by the helicity decomposition method. The significant difference of polarization asymmetry in $B_c^{(*)}\to J/\psi+nh$ indicates a general law in vector-to-vecto

Leonardo Emili, Thiago Fraga-Silva, Ernest Pusateri, Markus Nußbaum-Thom

We study model pruning methods applied to Transformer-based neural network language models for automatic speech recognition. We explore three aspects of the pruning frame work, namely criterion, method and scheduler, analyzing their contribution in terms of accuracy and inference speed. To the best of our knowledge, such in-depth analyses on large-scale reco

Matteo Paoluzzi, Demian Levis, Andrea Crisanti, Ignacio Pagonabarraga

Within the Landau-Ginzburg picture of phase transitions, scalar field theories develop phase separation because of a spontaneous symmetry-breaking mechanism. This picture works in thermodynamics but also in the dynamics of phase separation. Here we show that scalar non-equilibrium field theories undergo phase separation just because of non-equilibrium fluctu

Sushmita Yadav, Puneet Sharma

In this work, we investigate the dynamics of a general non-autonomous system generated by a commutative family of homeomorphisms. In particular, we investigate properties such as periodicity, equicontinuity, minimality and transitivity for a general non-autonomous dynamical system. In \cite{sk2}, the authors derive necessary and sufficient conditions for a s

Antonio Paolo Carlucci, Hossein Darvish, Domenico Laforgia

This study experimentally investigates the temperature distribution and behavior of a 48V Lithium-Ion (Li-ion) battery pack during two charge-discharge cycles using 25 thermocouples. Results indicate that better convective heat transfer occurs at the external surfaces of the pack, while middle cells reach maximum temperatures. Differences are also observed i

Haiping Wang, Yuan Liu, Bing Wang, Yujing Sun

Matching cross-modality features between images and point clouds is a fundamental problem for image-to-point cloud registration. However, due to the modality difference between images and points, it is difficult to learn robust and discriminative cross-modality features by existing metric learning methods for feature matching. Instead of applying metric lear

Ling Pan, Moksh Jain, Kanika Madan, Yoshua Bengio

Generative Flow Networks (GFlowNets) are amortized samplers that learn stochastic policies to sequentially generate compositional objects from a given unnormalized reward distribution. They can generate diverse sets of high-reward objects, which is an important consideration in scientific discovery tasks. However, as they are typically trained from a given e

Paul C. Bressloff

There are many processes in cell biology that can be modelled in terms of an actively switching particle. The continuous degrees of freedom evolve according to a hybrid stochastic differential equation (hSDE) whose drift term depends on a discrete internal or environmental state that switches according to a continuous time Markov chain. In this paper we deri

Gabriel Calvo, Carmen Armero, Bernd Grimm, Christophe Ley

Wheelchair basketball, regulated by the International Wheelchair Basketball Federation, is a sport designed for individuals with physical disabilities. This paper presents a data-driven tool that effectively determines optimal team line-ups based on past performance data and metrics for player effectiveness. Our proposed methodology involves combining a Baye

Shinji Hirano

We propose a Lorentzian derivation of the generalized entropy associated with the island formula for black holes as a Wald-like entropy without reference to the exterior non-gravitating region or field-theoretic von Neumann entropy of Hawking radiation in a fixed curved spacetime background. We illustrate this idea by studying two-dimensional black holes in