December 2023 arXiv papers — page 63

Konstantinos A. Oikonomidis, Alexander Bodard, Emanuel Laude, Panagiotis Patrinos

In this paper we study an unconventional inexact Augmented Lagrangian Method (ALM) for convex optimization problems, as first proposed by Bertsekas, wherein the penalty term is a potentially non-Euclidean norm raised to a power between one and two. We analyze the algorithm through the lens of a nonlinear Proximal Point Method (PPM), as originally introduced

Jiawei Jiang, Yinwei Li, Shaowen Luo, Ping Li

Video synthetic aperture radar (SAR) is attracting more attention in recent years due to its abilities of high resolution, high frame rate and advantages in continuous observation. Generally, the polar format algorithm (PFA) is an efficient algorithm for spotlight mode video SAR. However, in the process of PFA, the wavefront curvature error (WCE) limits the

Kaipeng Fang, Jingkuan Song, Lianli Gao, Pengpeng Zeng

The goal of Universal Cross-Domain Retrieval (UCDR) is to achieve robust performance in generalized test scenarios, wherein data may belong to strictly unknown domains and categories during training. Recently, pre-trained models with prompt tuning have shown strong generalization capabilities and attained noteworthy achievements in various downstream tasks,

Lin Huian, Ling Liming

This paper delves into the study of multi-component derivative nonlinear Schrodinger (n-DNLS) equations featuring nonzero boundary conditions. Employing the Darboux transformation (DT) method, we derive higher-order vector rogue wave solutions for the n-DNLS equations. Specifically, we focus on the distinctive scenario where the (n + 1)-order characteristic

Claudio Bonanno, Massimo D'Elia, Lorenzo Verzichelli

We investigate, by means of numerical lattice simulations, the $\theta$-dependence of the critical deconfinement temperature of $\mathrm{SU}(N)$ gauge theories at large $N$: $T_c(\theta) = T_c(0)[1-R\theta^2+O(\theta^4)]$, with $R\sim O(1/N^2)$. We follow two different strategies to determine $R$, one based on the calculation of the latent heat of the transi

Emil Östberg, Emil Viñas Boström, Claudio Verdozzi

Magnetic skyrmions hold great promise for realizing compact and stable memory devices that can be manipulated at very low energy costs via electronic current densities. In this work, we extend a recently introduced method to describe classical skyrmion textures coupled to dynamical itinerant electrons. In this scheme, the electron dynamics is described via n

Kirill Boguslavski, Aleksi Kurkela, Tuomas Lappi, Florian Lindenbauer

In these proceedings, we compute the heavy quark momentum diffusion coefficient using QCD effective kinetic theory for a plasma going through the bottom-up thermalization scenario until approximate hydrodynamization. This transport coefficient describes heavy quark momentum diffusion in the quark-gluon plasma and is used in many phenomenological frameworks,

Zikang Dong, Yutong Song, Weijia Wang, Hao Zhang

We study the conditional upper bounds and extreme values of derivatives of the Riemann zeta function and Dirichlet $L$-functions near the 1-line. Let $\ell$ be a fixed natural number. We show that, if $|\sigma-1|\ll1/\log_2t$, then $|\zeta^{(\ell)}(\sigma+ it)|$ has the same maximal order (up to the leading coefficients) as $|\zeta^{(\ell)}(1+ it)|$ when $t\

Ben Snyder, Marius Moisescu, Muhammad Bilal Zafar

While large language models (LLMs) have taken great strides towards helping humans with a plethora of tasks, hallucinations remain a major impediment towards gaining user trust. The fluency and coherence of model generations even when hallucinating makes detection a difficult task. In this work, we explore if the artifacts associated with the model generatio

Yong Xien Chng, Henry Zheng, Yizeng Han, Xuchong Qiu

Referring Image Segmentation (RIS) is a challenging task that requires an algorithm to segment objects referred by free-form language expressions. Despite significant progress in recent years, most state-of-the-art (SOTA) methods still suffer from considerable language-image modality gap at the pixel and word level. These methods generally 1) rely on sentenc

L. Doubrawa, E. S. Cypriano, A. Finoguenov, P. A. A. Lopes

Galaxy clusters are an essential tool to understand and constrain the cosmological parameters of our Universe. Thanks to its multi-band design, J-PAS offers a unique group and cluster detection window using precise photometric redshifts and sufficient depths. We produce galaxy cluster catalogues from the miniJPAS, which is a pathfinder survey for the wider J

David Johansson, Janne Nurminen, Mikko Salo

This article studies the inverse problem of recovering a nonlinearity in an elliptic equation $\Delta u + a(x,u) = 0$ from boundary measurements of solutions. Previous results based on first order linearization achieve this under a sign condition on $\partial_u a(x,u)$, and results based on higher order linearization recover the Taylor series of $a(x,u)$ wit

Lars Krupp, Steffen Steinert, Maximilian Kiefer-Emmanouilidis, Karina E. Avila

The increased presence of large language models (LLMs) in educational settings has ignited debates concerning negative repercussions, including overreliance and inadequate task reflection. Our work advocates moderated usage of such models, designed in a way that supports students and encourages critical thinking. We developed two moderated interaction method

Zhiqiang Yu

Let $\mathcal{A}$ be a near-group fusion category of type $\mathbb{Z}_3+6$. We show that there is a modular tensor equivalence $\mathcal{Z}(\mathcal{A})\cong\mathcal{C}(\mathbb{Z}_3,\eta)\boxtimes\mathcal{C}(\mathfrak{sl}_3,9)_{\mathbb{Z}_3}^0$. Moreover, we construct two non-trivial faithful extensions of $\mathcal{A}$ explicitly, whose Drinfeld centers can

Giuseppe Baccella

For every partially ordered sets I, having a finite cofinal subset, and every field K we build a unital, locally matricial and hence unit-regular K-algebra B(I) such that the lattice of all its ideals is order isomorphic to the lattice of all lower subsets of I. We show that the Grothendieck group of B(I), with its natural partial order, is order isomorphic

Dongwei Ye, Mengwu Guo

One of the pivotal tasks in scientific machine learning is to represent underlying dynamical systems from time series data. Many methods for such dynamics learning explicitly require the derivatives of state data, which are not directly available and can be approximated conventionally by finite differences. However, the discrete approximations of time deriva

Julius Bauß, Sophie N. Parragh, Michael Stiglmayr

Branch and bound methods which are based on the principle "divide and conquer" are a well established solution approach in single-objective integer programming. In multi-objective optimization branch and bound algorithms are increasingly attracting interest. However, the larger number of objectives raises additional difficulties for implicit enumeration appr

Chenyu Sun, Hangwei Qian, Chunyan Miao

Offline reinforcement learning (RL) aims to learn an effective policy from a pre-collected dataset. Most existing works are to develop sophisticated learning algorithms, with less emphasis on improving the data collection process. Moreover, it is even challenging to extend the single-task setting and collect a task-agnostic dataset that allows an agent to pe

Martín González-Soto, Rebeca P. Díaz-Redondo, Manuel Fernández-Veiga, Bruno Rodríguez-Castro

Decentralised machine learning has recently been proposed as a potential solution to the security issues of the canonical federated learning approach. In this paper, we propose a decentralised and collaborative machine learning framework specially oriented to resource-constrained devices, usual in IoT deployments. With this aim we propose the following const

Arnela Hadzic, Barbara Kirnbauer, Darko Stern, Martin Urschler

The localization of teeth and segmentation of periapical lesions in cone-beam computed tomography (CBCT) images are crucial tasks for clinical diagnosis and treatment planning, which are often time-consuming and require a high level of expertise. However, automating these tasks is challenging due to variations in shape, size, and orientation of lesions, as w

D. Li, K. G. Miller, J. R. Pierce, W. B. Mori

Spatiotemporal control encompasses a variety of techniques for producing laser pulses with dynamic intensity peaks that move independently of the group velocity. This controlled motion of the intensity peak offers a new approach to optimizing laser-based applications and enhancing signatures of fundamental phenomena. Here, we demonstrate spatiotemporal contr

Alexander C. Tyner, Sinéad M. Griffin, Alexander V. Balatsky

Recent reports of room-temperature, ambient pressure superconductivity in copper-substituted lead phosphate apatite, commonly referred to as LK99, have prompted numerous theoretical and experimental studies into its properties. As the electron-phonon interaction is a common mechanism for superconductivity, the electron-phonon coupling strength is an importan

Valentina Shumovskaia, Mert Kayaalp, Ali H. Sayed

Traditional social learning frameworks consider environments with a homogeneous state, where each agent receives observations conditioned on that true state of nature. In this work, we relax this assumption and study the distributed hypothesis testing problem in a heterogeneous environment, where each agent can receive observations conditioned on their own p

Xiao-Jin Liu, Zhi-Qiang You, Zu-Cheng Chen, Shen-Shi Du

Spin period distribution provides important clues to understand the formation of millisecond pulsars (MSPs). To uncover the intrinsic period distribution, we analyze three samples of radio MSPs in the Galactic field and in globular clusters. The selection bias due to pulse broadening has been corrected but turns out to be negligible. We find that all the sam

Ruiqi Hu, Dai Q. Ho, Quang To, Garnett W. Bryant

Embedding rare-earth pnictide (RE-V) nanoparticles into III-V semiconductors enables unique optical, electrical, and thermal properties, with applications in THz photoconductive switches, tunnel junctions, and thermoelectric devices. Despite the high structural quality and control over growth, particle size, and density, the underlying electronic structure o

Yuecen Wei, Haonan Yuan, Xingcheng Fu, Qingyun Sun

Hierarchy is an important and commonly observed topological property in real-world graphs that indicate the relationships between supervisors and subordinates or the organizational behavior of human groups. As hierarchy is introduced as a new inductive bias into the Graph Neural Networks (GNNs) in various tasks, it implies latent topological relations for at

Vincenzo Morinelli, Karl-Hermann Neeb

Various aspects of the geometric setting of Algebraic Quantum Field Theory (AQFT) models related to representations of the Poincar\'e group can be studied for general Lie groups, whose Lie algebra contains an Euler element, i.e., ad h is diagonalizable with eigenvalues in {-1,0,1}. This has been explored by the authors and their collaborators during recent y

Xueyuan Chen, Xi Wang, Shaofei Zhang, Lei He

The expressive quality of synthesized speech for audiobooks is limited by generalized model architecture and unbalanced style distribution in the training data. To address these issues, in this paper, we propose a self-supervised style enhancing method with VQ-VAE-based pre-training for expressive audiobook speech synthesis. Firstly, a text style encoder is

Ara Basmajian, Jade Brisson, Asma Hassannezhad, Antoine Métras

We consider the Steklov eigenvalue problem on a compact pinched negatively curved manifold $M$ of dimension at least three with totally geodesic boundaries. We obtain a geometric lower bound for the first nonzero Steklov eigenvalue in terms of the total volume of $M$ and the volume of its boundary. We provide examples illustrating the necessity of these geom

Toni Gui

We consider a model of a population in which individuals are sampled from different species. The Yule-Kingman nested coalescent describes the genealogy of the sample when each species merges with another randomly chosen species with a constant rate $c$ and each pair of lineages belonging to the same species coalesces independently at rate 1. We study the dis

Megan Howarth, Tatiana Nagnibeda

This paper is devoted to the study of tessellations of the hyperbolic plane, especially the ones associated to hyperbolic triangle groups $\Delta(l,m,n)$. We give a full description of the cone types of these graphs and show that their number depends only on the defining parameters of the group. We then use the cone types structure to provide estimates of th

G. V. Demidenko, Z. Wang

The problems on the location of the matrix spectrum inside or outside domains bounded by ellipses or parabolas are studied. Special Lyapunov-type equations are connected with these problems. Theorems about the unique solvability of such equations are proved. Conditions for perturbations of matrix entries are obtained, which guarantee that the spectra of the

Jose L. Gómez, Manuel Silva, Antonio Seoane, Agnès Borrás

We introduce UrbanSyn, a photorealistic dataset acquired through semi-procedurally generated synthetic urban driving scenarios. Developed using high-quality geometry and materials, UrbanSyn provides pixel-level ground truth, including depth, semantic segmentation, and instance segmentation with object bounding boxes and occlusion degree. It complements GTAV

Radu Ioan Bot, Dang-Khoa Nguyen, Chunxiang Zong

We address the problem of finding the zeros of the sum of a maximally monotone operator and a cocoercive operator. Our approach introduces a modification to the forward-backward method by integrating an inertial/momentum term alongside a correction term. We demonstrate that the sequence of iterations thus generated converges weakly towards a solution for the

Mohsen Abdoli, Félix Henry, Gordon Clare

A transcoding scheme for the High Efficiency Video Coding (HEVC) is proposed that allows any partial frame modification to be followed by a partial re-compression of only the modified areas, while guaranteeing identical reconstruction of non-modified areas. To this end, first, syntax elements of all Coding Units (CU) in the frame are parsed and decoded accor

Tomonori Sadamoto, Fumiya Nakamata

We present a model-based globally convergent policy gradient method (PGM) for linear quadratic Gaussian (LQG) control. Firstly, we establish equivalence between optimizing dynamic output feedback controllers and designing a static feedback gain for a system represented by a finite-length input-output history (IOH). This IOH-based approach allows us to explor

Raphaël Mothe, Cyril Branciard, Alastair A. Abbott

The quantum switch, the canonical example of a process with indefinite causal order, has been claimed to provide various advantages over processes with definite causal orders for some particular tasks in the field of quantum metrology. In this work, we argue that some of these advantages in fact do not hold if a fairer comparison is made. To this end, we con

Angxiu Ni, Yao Tong

We prove the equivariant divergence formula for the axiom A flow attractors, which is a recursive formula for perturbation of transfer operators of physical measures along center-unstable manifolds. Hence the linear response acquires an `ergodic theorem', which means that it can be sampled by recursively computing only $2u$ many vectors on one orbit, where $

Stanislav Sysala, Michal Béreš, Simona Bérešová, Jaroslav Haslinger

This paper is motivated by the limit load, limit analysis and shear strength reduction methods, which are commonly employed in geotechnical stability analysis or similar applications. The aim is to make these methods more approachable by introducing a unified framework based on abstract convex optimization and its parametric studies. We establish suitable as

Runduo Liang, Zhengyan Liu, Lei Lei, Wen Zhao

With the enhancement of sensitivity of Gravitational Wave (GW) detectors and capabilities of large survey facilities, such as Vera Rubin Observatory Legacy Survey of Space and Time (LSST) and 2.5-m Wide Field Survey Telescope (WFST), we now have the potential to detect an increasing number of distant kilonova (KN). However, distinguishing KN from the plethor

M. Bojer, J. Eckert, S. Karl, S. Richter

To obtain spatial information about an arbitrary object in x-ray structure analysis, the standard method is to measure the intensity in the far field, i.e., the first-order photon correlation function of the coherently scattered x-ray photons (coherent diffractive imaging). Recently, it was suggested to record alternatively the incoherently scattered photons

Shengli Huang

In this proceeding, we present the first measurements of azimuthal anisotropies, $v_2$ and $v_3$, in $^{16}$O+$^{16}$O collisions at 200 GeV as a function of transverse momentum and multiplicity, by using two- and four-particle correlation methods. We compare our measurements with STAR measurements of $v_n$ in \dau and \heau collisions to provide insight int

John Erik Fornaess, Mi Hu, Tuyen Trung Truong, Takayuki Watanabe

A new variant of Newton's method - named Backtracking New Q-Newton's method (BNQN) - which has strong theoretical guarantee, is easy to implement, and has good experimental performance, was recently introduced by the third author. Experiments performed previously showed some remarkable properties of the basins of attractions for finding roots of polynomials

O. M. Smirnov, B. W. Stappers, C. Tasse, H. L. Bester

We report on a radiopolarimetric observation of the Saturn-Jupiter Great Conjunction of 2020 using the MeerKAT L-band system, initially carried out for science verification purposes, which yielded a serendipitous discovery of a pulsar. The radiation belts of Jupiter are very bright and time variable: coupled with the sensitivity of MeerKAT, this necessitated

Juan Sánchez-Baena, Raúl Bombín, Jordi Boronat

We study the interplay between the anisotropy of the dipole-dipole interaction and confinement in a curved geometry by means of the extended Gross-Pitaevskii equation, which allows us to characterize the ground state of a dipolar Bose gas under the confinement of a bubble trapping potential. We do so in terms of the scattering length a and the number of part

Jan-Willem van Ittersum, Berend Ringeling

We count the number of zeros of the holomorphic odd weight Eisenstein series in all $\mathrm{SL}_2(\mathbb{Z})$-translates of the standard fundamental domain.

Qiyao Peng, Hongyan Xu, Yinghui Wang, Hongtao Liu

Finding experts is essential in Community Question Answering (CQA) platforms as it enables the effective routing of questions to potential users who can provide relevant answers. The key is to personalized learning expert representations based on their historical answered questions, and accurately matching them with target questions. There have been some pre

Tony Quertier, Grégoire Barrué

Malware detection is an important topic of current cybersecurity, and Machine Learning appears to be one of the main considered solutions even if certain problems to generalize to new malware remain. In the aim of exploring the potential of quantum machine learning on this domain, our previous work showed that quantum neural networks do not perform well on i

Irina V. Lebedeva, Joaquim Jornet-Somoza

N-heterocyclic carbene (NHC) iridium (III) complexes are considered as promising candidates for blue emitters in organic light-emitting diodes. They can play the roles of the emitter as well as of electron and hole transporters in the same emission layer. We investigate optical transitions in such complexes with account of geometry and electronic structure c

Andrea Bonato, Dom Corbett, Sergey Kitaev, Davide Marenduzzo

The 3D folding of a mammalian gene can be studied by a polymer model, where the chromatin fibre is represented by a semiflexible polymer which interacts with multivalent proteins, representing complexes of DNA-binding transcription factors and RNA polymerases. This physical model leads to the natural emergence of clusters of proteins and binding sites, accom

Anthony Nixon, Bernd Schulze, Joseph Wall

A bar-joint framework $(G,p)$ is the combination of a finite simple graph $G=(V,E)$ and a placement $p:V\rightarrow \mathbb{R}^d$. The framework is rigid if the only edge-length preserving continuous motions of the vertices arise from isometries of the space. Motivated by applications where boundary conditions play a significant role, one may generalise and

Ishraq U. Ahmed, Mary R. Myerscough

Atherosclerotic plaques are accumulations of cholesterol-engorged macrophages in the artery wall. Plaque growth is initiated and sustained by the deposition of low density lipoproteins (LDL) in the artery wall. High density lipoproteins (HDL) counterbalance the effects of LDL by accepting cholesterol from macrophages and removing it from the plaque. In this

Jan Haskovec

We study hierarchical properties of optimal transportation networks with biological background. The networks are obtained as minimizers of an energy functional which involves a metabolic cost term of a power-law form with exponent $\gamma>0$. In the range $\gamma\in (0,1)$, most relevant for biological applications, the functional is non-convex and its local

Zhihang Liu, Jun Li, Hongtao Xie, Pandeng Li

Video Moment Retrieval (VMR) aims to retrieve temporal segments in untrimmed videos corresponding to a given language query by constructing cross-modal alignment strategies. However, these existing strategies are often sub-optimal since they ignore the modality imbalance problem, \textit{i.e.}, the semantic richness inherent in videos far exceeds that of a g

Andrea Bonato, Dom Corbett, Sergey Kitaev, Davide Marenduzzo

Polymer physics models suggest that chromatin spontaneously folds into loop networks with transcription units (TUs), such as enhancers and promoters, as anchors. Here we use combinatoric arguments to enumerate the emergent chromatin loop networks, both in the case where TUs are labelled and where they are unlabelled. We then combine these mathematical result

Fabian Ritter-Gutierrez, Kuan-Po Huang, Dianwen Ng, Jeremy H. M. Wong

Compared to large speech foundation models, small distilled models exhibit degraded noise robustness. The student's robustness can be improved by introducing noise at the inputs during pre-training. Despite this, using the standard distillation loss still yields a student with degraded performance. Thus, this paper proposes improving student robustness via d

Asier López-Gordón, Leonardo J. Colombo

A hybrid system is a system whose dynamics are controlled by a mixture of both continuous and discrete transitions. The integrability of Hamiltonian systems is often identified with complete integrability or Liouville integrability, that is, the existence of as many independent integrals of motion in involution as the dimension of the phase space. Under cert

Lydia A. Schoenpflug, Viktor H. Koelzer

Detecting and classifying cells in histopathology H\&E stained whole-slide images is a core task in computational pathology, as it provides valuable insight into the tumor microenvironment. In this work we investigate the impact of ground truth formats on the models performance. Additionally, cell-tissue interactions are considered by providing tissue segmen

Angeliki Katsenou, Xinyi Wang, Daniel Schien, David Bull

The environmental impact of video streaming services has been discussed as part of the strategies towards sustainable information and communication technologies. A first step towards that is the energy profiling and assessment of energy consumption of existing video technologies. This paper presents a comprehensive study of power measurement techniques in vi

Christine Allard, Éric Marchand

We study the problem of loss estimation that involves for an observable $X \sim f_{\theta}$ the choice of a first-stage estimator $\hat{\gamma}$ of $\gamma(\theta)$, incurred loss $L=L(\theta, \hat{\gamma})$, and the choice of a second-stage estimator $\hat{L}$ of $L$. We consider both: (i) a sequential version where the first-stage estimate and loss are fix

Lingling Xu, Haoran Xie, Si-Zhao Joe Qin, Xiaohui Tao

With the continuous growth in the number of parameters of transformer-based pretrained language models (PLMs), particularly the emergence of large language models (LLMs) with billions of parameters, many natural language processing (NLP) tasks have demonstrated remarkable success. However, the enormous size and computational demands of these models pose sign

Uwe M. Borghoff

LoKit is a toolkit based on the coordination language LO. It allows to build distributed collaborative applications by providing a set of generic tools. This paper briefly introduces the concept of the toolkit, presents a subset of the LoKit tools, and finally demonstrates its power by discussing a sample application built with the toolkit.

Yi Han

Symmetric tridiagonal matrices appear ubiquitously in mathematical physics, serving as the matrix representation of discrete random Schr\"odinger operators. In this work we investigate the top eigenvalue of these matrices in the large deviation regime, assuming the random potentials are on the diagonal with a certain decaying factor $N^{-\alpha}$, and the pr

Jinyi Liu, Zhi Wang, Yan Zheng, Jianye Hao

In reinforcement learning, the optimism in the face of uncertainty (OFU) is a mainstream principle for directing exploration towards less explored areas, characterized by higher uncertainty. However, in the presence of environmental stochasticity (noise), purely optimistic exploration may lead to excessive probing of high-noise areas, consequently impeding e

Wenzhao Jiang, Hao Liu, Hui Xiong

Graph Neural Networks (GNNs) have emerged as powerful representation learning tools for capturing complex dependencies within diverse graph-structured data. Despite their success in a wide range of graph mining tasks, GNNs have raised serious concerns regarding their trustworthiness, including susceptibility to distribution shift, biases towards certain popu

Siran Chen, Yue Ma, Yu Qiao, Yali Wang

3D perception is a critical problem in autonomous driving. Recently, the Bird-Eye-View (BEV) approach has attracted extensive attention, due to low-cost deployment and desirable vision detection capacity. However, the existing models ignore a realistic scenario during the driving procedure, i.e., one or more view cameras may be failed, which largely deterior

Akshat Kishore Shrivastava, Tapan Kumar Gandhi

In this paper, we propose an novel methodology aimed at simulating the learning phenomenon of nystagmus through the application of differential blurring on datasets. Nystagmus is a biological phenomenon that influences human vision throughout life, notably by diminishing head shake from infancy to adulthood. Leveraging this concept, we address the issue of w

Zhenhua Yang, Dezhi Peng, Yuxin Kong, Yuyi Zhang

Automatic font generation is an imitation task, which aims to create a font library that mimics the style of reference images while preserving the content from source images. Although existing font generation methods have achieved satisfactory performance, they still struggle with complex characters and large style variations. To address these issues, we pro

Zeping Yu, Sophia Ananiadou

Identifying important neurons for final predictions is essential for understanding the mechanisms of large language models. Due to computational constraints, current attribution techniques struggle to operate at neuron level. In this paper, we propose a static method for pinpointing significant neurons. Compared to seven other methods, our approach demonstra

Wiktor Bednarczyk, Maria Wątroba, Grzegorz Cieślak, Marta Ciemiorek

Zinc alloys have emerged as promising candidates for biodegradable materials due to their remarkable biocompatibility and favorable mechanical characteristics. The incorporation of alloying elements plays an essential role in advancing the tensile strength of Zn alloys. Nevertheless, achieving uniform dispersion of these elements poses challenges due to chem

Francesca Biagini, Andrea Mazzon, Katharina Oberpriller

In this paper we introduce a definition of a multi-dimensional fractional Brownian motion of Hurst index $H \in (0, 1)$ under volatility uncertainty (in short G-fBm). We study the properties of such a process and provide first results about stochastic calculus with respect to a fractional G-Brownian motion for a Hurst index $H >\frac{1}{2}$ .

Xiao-Wu Chen, Zhengfang Wang

The singularity category of a ring detects the homological singularity of the given ring, and appears in many different contexts. We describe two different dg enhancements of the singularity category, that is, the Vogel dg category and the singular Yoneda dg category. These two dg enhancements turn out to be quasi-equivalent. We report some progress on the S

Po-An Wang, Ruo-Chun Tzeng, Alexandre Proutiere

We consider the problem of identifying the best arm in stochastic Multi-Armed Bandits (MABs) using a fixed sampling budget. Characterizing the minimal instance-specific error probability for this problem constitutes one of the important remaining open problems in MABs. When arms are selected using a static sampling strategy, the error probability decays expo

Muping Chen, Graciela B. Gelmini, Philip Lu, Volodymyr Takhistov

Sterile neutrinos ($\nu_s$s) are well-motivated and actively searched for hypothetical neutral particles that would mix with the Standard Model active neutrinos. They are considered prime warm dark matter (DM) candidates, typically when their mass is in the keV range, although they can also be hot or cold DM components. We discuss in detail the characteristi

Hadis Keshavarz, Hossein Sadr

In the era of digital medicine, medical imaging serves as a widespread technique for early disease detection, with a substantial volume of images being generated and stored daily in electronic patient records. X-ray angiography imaging is a standard and one of the most common methods for rapidly diagnosing coronary artery diseases. The notable achievements o

Pengwei Liu, Wenwei Wang, Bingqing Peng, Binqing Wu

While widely recognized as one of the most substantial weather forecasting methodologies, Numerical Weather Prediction (NWP) usually suffers from relatively coarse resolution and inevitable bias due to tempo-spatial discretization, physical parametrization process, and computation limitation. With the roaring growth of deep learning-based techniques, we prop

Lorenz Frühwirth, Michael Juhos, Joscha Prochno

In this paper we take a probabilistic look at Maclaurin's inequality, which is a refinement of the classical AM-GM inequality. In a natural randomized setting, we obtain limit theorems and show that a reverse inequality holds with high probability. The form of Maclaurin's inequality naturally relates it to U-statistics. More precisely, given $x_1, \ldots, x_

Wooju Lee, Dasol Hong, Hyungtae Lim, Hyun Myung

Single-domain generalization (S-DG) aims to generalize a model to unseen environments with a single-source domain. However, most S-DG approaches have been conducted in the field of classification. When these approaches are applied to object detection, the semantic features of some objects can be damaged, which can lead to imprecise object localization and mi

Jonathan P. Itcovitz, Auriol S. P. Rae, Thomas M. Davison, Gareth S. Collins

Large impacts onto young rocky planets may transform their compositions, creating highly reducing conditions at their surfaces and reintroducing highly siderophile metals to their mantles. Key to these processes is the availability of an impactor's chemically reduced core material (metallic iron). It is, therefore, important to constrain how much of an impac

Marija Mikic, Mihajlo Srbakoski

Protecting the privacy of blockchain transactions is extremely important for users. Stealth address protocols (SAP) allow users to receive assets via stealth addresses that they do not associate with their stealth meta-addresses. SAP can be generated using different cryptographic approaches. DKSAP uses an elliptic curve multiplication and hashing of the resu

Rajiv V. Gavai, Bedangadas Mohanty, Jaydev Singh Rao, Swati Saha

Theoretical considerations predict a specific hierarchy among ratios of net-baryon number cumulants ($\chi_n$, where $n$ is the order of cumulant) in the vicinity of the transition from the low-temperature hadronic phase to the high temperature quark-gluon plasma phase at small baryon chemical potential, $\mu_\mathrm{B}$, in the QCD phase diagram. This hiera

Giosuè Muratore

We say that a line in $\mathbb P^{n+1}_k$ is osculating to a hypersurface $Y$ if they meet with contact order $n+1$. When $k=\mathbb C$, it is known that through a fixed point of $Y$, there are exactly $n!$ of such lines. Under some parity condition on $n$ and $\mathrm{deg}(Y)$, we define a quadratically enriched count of these lines over any perfect field $

A. V. Bednyakov, A. I. Mukhaeva

We consider a four-dimensional $SU(N_c)$ gauge theory coupled to $N_f$ species of color fermions and $N_f^2$ colorless scalars. The quantum field theory possesses a weakly interacting ultraviolet fixed point that we determine from beta functions computed up to four-loop order in the gauge coupling, and up to three-loop order in the Yukawa and quartic scalar

Huan-Yu Wang, Zhen-Biao Yang, Wu-Ming Liu

Bulk-boundary correspondences (BBCs) remain the central topic in modern condensed matter physics, and are gaining increasing interests with the recent discovery of non-Hermitian skin effects. However, there still exist profound features of BBCs that are beyond the existing framework. Here, we report the unexpected behavior of BBC when the Hamiltonian contain

Simon Barazer

One of the versions of the wind-tree model of Boltzmann gas, suggested by Paul and Tatiana Ehrenfest more than a century ago, can be seen as a billiard in the plane endowed with $\mathbb{Z}\oplus\mathbb{Z}$-periodic rectangular obstacles. In the breakthrough paper by V. Delecroix, P. Hubert and S. Lelievre the authors proved, that the diffusion rate of traje

James Leftley, Romain Petrov, Niklas Moszczynski, Pierre Vermot

The Very Large Telescope Interferometer (VLTI) has been providing breakthrough images of the dust in the central parsecs of Active Galactic Nuclei (AGN), a key component of the AGN unification scheme and AGN host galaxy interaction. In single IR bands, the images can have multiple interpretations some of which could challenge the unification scheme. This is

P. Vemareddy, Jörn Warnecke, Ph. A. Bourdin

Coronal magnetic fields evolve quasi statically over long time scales and dynamically over short time scales. As of now there exists no regular measurements of coronal magnetic fields, and therefore generating the coronal magnetic field evolution using the observations of the magnetic field at the photosphere is of fundamental requirement to understand the o

Carl De Sousa Trias, Mihai Petru Mitrea, Attilio Fiandrotti, Marco Cagnazzo

Deep neural networks are characterized by multiple symmetrical, equi-loss solutions that are redundant. Thus, the order of neurons in a layer and feature maps can be given arbitrary permutations, without affecting (or minimally affecting) their output. If we shuffle these neurons, or if we apply to them some perturbations (like fine-tuning) can we put them b

Shuli Wang, Kun Gao, Lanfang Zhang, Yang Liu

Automated vehicles are envisioned to navigate safely in complex mixed-traffic scenarios alongside human-driven vehicles. To promise a high degree of safety, accurately predicting the maneuvers of surrounding vehicles and their future positions is a critical task and attracts much attention. However, most existing studies focused on reasoning about positional

Xiang Feng, Yongbo He, Yubo Wang, Chengkai Wang

Neural Radiance Fields (NeRF) have achieved great success in the task of synthesizing novel views that preserve the same resolution as the training views. However, it is challenging for NeRF to synthesize high-quality high-resolution novel views with low-resolution training data. To solve this problem, we propose a zero-shot super-resolution training framewo

Daniel Engelsman, Itzik Klein

Inertial navigation systems (INS) are widely used in both manned and autonomous platforms. One of the most critical tasks prior to their operation is to accurately determine their initial alignment while stationary, as it forms the cornerstone for the entire INS operational trajectory. While low-performance accelerometers can easily determine roll and pitch

Markus Steenbock

We arrange classical small cancellation constructions to produce left-orderable groups: we show that every finitely generated group is the quotient of a left-ordered small cancellation group by a finitely generated kernel (Rips construction). We give presentations of left-ordered hyperbolic small cancellation groups that are not locally indicable, and observ

Susanne Hindennach, Lei Shi, Filip Miletić, Andreas Bulling

When users perceive AI systems as mindful, independent agents, they hold them responsible instead of the AI experts who created and designed these systems. So far, it has not been studied whether explanations support this shift in responsibility through the use of mind-attributing verbs like "to think". To better understand the prevalence of mind-attributing

Erdem Eray Cil, Laurent Schmalen

We introduce an iteration-dependent scaled min-sum decoding for low-rate LDPC codes in CV-QKD, achieving near-sum product algorithm performance with reduced complexity, and facilitating CV-QKD hardware implementation.

Joaquin Espinosa-Garcia, Somnath Bhowmick

Temperature dependence of the thermal rate constants and kinetic isotope effects (KIE) of the CN + C2H6 gas-phase hydrogen abstraction reaction was theoretically determined within the 25-1000 K temperature range, i.e., from ultra-low to high-temperature regimes. Based on a recently developed full-dimensional analytical potential energy surface fitted to high

Larry A. Dunning

In 1969 J. Verhoeff provided the first examples of a decimal error detecting code using a single check digit to provide protection against all single, transposition, and adjacent twin errors. The three codes he presented are length 3-digit codes with 2 information digits. To date, the existence of a length 4-digit code with 3 information digits having these

Gwladys Kelodjou, Laurence Rozé, Véronique Masson, Luis Galárraga

Machine learning techniques, such as deep learning and ensemble methods, are widely used in various domains due to their ability to handle complex real-world tasks. However, their black-box nature has raised multiple concerns about the fairness, trustworthiness, and transparency of computer-assisted decision-making. This has led to the emergence of local pos

Yongliang Hao, Kamphamba Sokalao Nyirenda, Zhenwei Chen

In this work, we explore the possibility of the $n$-$\bar{n}$ oscillation accompanied by CP-violation in the presence of magnetic fields. The $n$-$\bar{n}$ oscillation, which violates the baryon number ($\mathcal{B}$) by two units ($|\Delta \mathcal{B}| = 2$), can be originated from the mixing between the neutron ($n$) and the neutral elementary particle ($\

Yuya Ohmichi

The conventional modal analysis techniques face difficulties in handling nonstationary phenomena, such as transient, nonperiodic, or intermittent phenomena. This paper presents a variational mode decomposition--based nonstationary coherent structure (VMD-NCS) analysis that enables the extraction and analysis of coherent structures in the case of nonstationar

Nabeel Seedat, Nicolas Huynh, Boris van Breugel, Mihaela van der Schaar

Machine Learning (ML) in low-data settings remains an underappreciated yet crucial problem. Hence, data augmentation methods to increase the sample size of datasets needed for ML are key to unlocking the transformative potential of ML in data-deprived regions and domains. Unfortunately, the limited training set constrains traditional tabular synthetic data g