November 2024 arXiv papers — page 62

Sanchar Palit, Biplab Banerjee, Subhasis Chaudhuri

We propose a Bayesian neural network-based continual learning algorithm using Variational Inference, aiming to overcome several drawbacks of existing methods. Specifically, in continual learning scenarios, storing network parameters at each step to retain knowledge poses challenges. This is compounded by the crucial need to mitigate catastrophic forgetting,

Hengxing Liu, Mingjia Li, Xiaojie Guo

Shadow, as a natural consequence of light interacting with objects, plays a crucial role in shaping the aesthetics of an image, which however also impairs the content visibility and overall visual quality. Recent shadow removal approaches employ the mechanism of attention, due to its effectiveness, as a key component. However, they often suffer from two issu

Jacob Abajian

We consider $\mathcal{N} = 2$ superconformal gauge theories in four dimensions. We explain how these quiver gauge theories arise as low-energy worldvolume theories of D3-branes on orientifolds. Then, we examine their associated chiral algebras, and propose novel examples of twisted holographic dualities arising in the large-N limit. These dualities involve t

Akari Asai, Jacqueline He, Rulin Shao, Weijia Shi

Scientific progress depends on researchers' ability to synthesize the growing body of literature. Can large language models (LMs) assist scientists in this task? We introduce OpenScholar, a specialized retrieval-augmented LM that answers scientific queries by identifying relevant passages from 45 million open-access papers and synthesizing citation-backed re

Catherine Arnett, Benjamin K. Bergen

Language models perform differently across languages. It has been previously suggested that morphological typology may explain some of this variability (Cotterell et al., 2018). We replicate previous analyses and find additional new evidence for a performance gap between agglutinative and fusional languages, where fusional languages, such as English, tend to

Sapta Sindhu Paul Chowdhury, Sourav Thapliyal, Santosh Mogurampelly

We report an anomalous temperature-induced transition in thermal conductivity in germanene monolayer around a critical temperature $T_c = 350 \, \text{K}$. Equilibrium molecular dynamics simulations reveal a transition from $\kappa \sim T^{-2}$ scaling below $T_c$ to $\kappa \sim T^{-1/2}$ above, contrasting with conventional $\kappa \sim T^{-1}$ behavior. T

Hengyuan Ma, Wenlian Lu, Jianfeng Feng

Humans possess a finely tuned sense of uncertainty that helps anticipate potential errors, vital for adaptive behavior and survival. However, the underlying neural mechanisms remain unclear. This study applies moment neural networks (MNNs) to explore the neural mechanism of uncertainty quantification in working memory (WM). The MNN captures nonlinear couplin

Davide Ravasini

For every integer $k\geq 2$ and every $R>1$ one can find a dimension $n$ and construct a symmetric convex body $K\subset\mathbb{R}^n$ with $\text{diam}\,Q_{k-1}(K)\geq R\cdot\text{diam}\,Q_k(K)$, where $Q_k(K)$ denotes the $k$-convex hull of $K$. The purpose of this short note is to show that this result due to E.\ Kopeck\'{a} is impossible to obtain if one

A. Mironov, A. Morozov, A. Popolitov

Macdonald symmetric polynomial at $t=q^{-m}$ reduces to a sum of much simpler complementary non-symmetric polynomials, which satisfy a simple system of the first order linear difference equations with constant coefficients, much simpler than those induced by the usual Ruijsenaars Hamiltonians of the cut-and-join type. We provide examples of explicit expressi

Dominik Sobania, Martin Briesch, Franz Rothlauf

Automatic image generation is no longer just of interest to researchers, but also to practitioners. However, current models are sensitive to the settings used and automatic optimization methods often require human involvement. To bridge this gap, we introduce ComfyGI, a novel approach to automatically improve workflows for image generation without the need f

Yuxuan Gu, Catherine Spurin, Gege Wen

Understanding the process of multiphase fluid flow through porous media is crucial for many climate change mitigation technologies, including CO$_2$ geological storage, hydrogen storage, and fuel cells. However, current numerical models are often incapable of accurately capturing the complex pore-scale physics observed in experiments. In this study, we addre

Marie-Sophie Hartig, Sarah Paczkowski, Martin Hewitson, Gerhard Heinzel

The Laser Interferometer Space Antenna (LISA) will be the first space-based gravitational wave (GW) observatory. It will measure gravitational wave signals in the frequency regime from 0.1 mHz to 1 Hz. The success of these measurements will depend on the suppression of the various instrument noises. One important noise source in LISA will be tilt-to-length (

Maryam Saberi, Shahin Jafarzadeh, Sven Wedemeyer, Ricardo Gafeira

Magnetohydrodynamic (MHD) waves, playing a crucial role in transporting energy through the solar atmosphere, manifest in various chromospheric structures. Here, we investigated MHD waves in a long-lasting dark fibril using high-temporal-resolution (2~s cadence) Atacama Large Millimeter/submillimeter Array (ALMA) observations in Band 6 (centered at 1.25~mm).

Ye-Huang Pang, Xue Zhang, Qing-Guo Huang

$H_0$ tension in the spatially flat $\Lambda$CDM model is reevaluated by employing three sets of non-Planck CMB data, namely WMAP, WMAP+ACT, and WMAP+SPT, in conjunction with DESI BAO data and non-DESI BAO datasets including 6dFGS, SDSS DR7, and SDSS DR16. Our analysis yields $H_0 = 68.86\pm 0.68~\mathrm{km\ s^{-1} Mpc^{-1}}$ with WMAP+DESI BAO, $H_0 = 68.72

Heng Chen, Rong Ma, Tuoping Du

We introduce the relationship between congruent numbers and elliptic curves, and compute the conductor of the elliptic curve $y^2 = x^3 - n^2 x$ associated with it. Furthermore, we prove that its $L$-series coefficient $a_m = 0$ when $m \equiv 3 \mod 4$.By using the invariants of the elliptic curve introduced above, we calculate Heegner points to quickly ver

V. Volkov, M. Golubeva, F. Guber, A. Izvestnyy

The performance of the scintillation wall (ScWall) has been studied in the first physics run at the Baryonic Matter at Nuclotron (BM@N) in Xe+CsI reaction at a xenon beam energy of 3.8 and 3.0 AGeV. The design and functionality of the ScWall emphasizing its ability to detect charged spectator fragments produced in nucleus-nucleus interactions are shown. The

Marco Badran

In a closed, oriented ambient manifold $(M^n,g)$ we consider the problem of finding $\mathbb{S}^1$-valued harmonic maps with prescribed singular set. We show that the boundary of any oriented $(n-1)$-submanifold can be realised as the singular set of an $\mathbb{S}^1$-valued map, which is classically harmonic away from the singularity and distributionally ha

Nan Zheng, Noel Cadigan, James T. Thorson

We propose two methods to evaluate the conditional Akaike information (cAI) for nonlinear mixed-effects models with no restriction on cluster size. Method 1 is designed for continuous data and includes formulae for the derivatives of fixed and random effects estimators with respect to observations. Method 2, compatible with any type of observation, requires

Samiha Islam, Muhammad Zawad Mahmud, Shahran Rahman Alve, Md. Mejbah Ullah Chowdhury

The goal of the present study is to analyze an application of deep learning models in order to augment the diagnostic performance of oral squamous cell carcinoma (OSCC) with a longitudinal cohort study using the Histopathological Imaging Database for oral cancer analysis. The dataset consisted of 5192 images (2435 Normal and 2511 OSCC), which were allocated

Paolo Giani, Arlene M. Fiore, Glenn Flierl, Raffaele Ferrari

Climate models exhibit an approximately invariant surface warming pattern in typical end-of-century projections. This observation has been used extensively in climate impact assessments for fast calculations of local temperature anomalies, with a linear procedure known as pattern scaling. At the same time, emerging research has also shown that time-varying w

T. Rengneichuong Koireng, Pawan Bharadwaj

The receiver-function (RF) technique aims to recover receiver-side crustal and mantle structures by deconvolving either the radial or transverse component with the vertical component seismogram. Analysis of the variations of RFs along the backazimuth and slowness is the key in determining the geometry and anisotropic properties of the crustal structures. How

Victor Y. Wang, Max Wenqiang Xu

We prove that the average size of a mixed character sum $$\sum_{1\le n \le x} \chi(n) e(n\theta) w(n/x)$$ (for a suitable smooth function $w$) is on the order of $\sqrt{x}$ for all irrational real $\theta$ satisfying a weak Diophantine condition, where $\chi$ is drawn from the family of Dirichlet characters modulo a large prime $r$ and where $x\le r$. In con

Sushil Mario, Pavan Teja Pothamsetti, Louie Antony Thalakottor, Trisha Vishwanath

One of the most well-known problems in transportation and logistics is the Capacitated Vehicle Routing Problem (CVRP). It involves optimizing a set of truck routes to service a set of customers, subject to limits on truck capacity, to reduce travel costs. The biggest challenge faced whilst attempting to solve the issue is that the time complexity of the issu

Julian Wagner, Robin Bernhardt, Lukas Rieland, Omar Abdul-Aziz

We use helicity-resolved ultrafast transient absorption spectroscopy to study spin-valley polarization dynamics in a vertically stacked MoSe$_{2}$/WSe$_{2}$ heterostructure. The experimental findings reveal details of interlayer charge transfer on ultrafast timescales, showing that the spin-valley polarized state of photoexcited carriers is conserved during

Duanchu Wang, Jing Liu, Haoran Gong, Yinghui Quan

Transformer-based methods have become the dominant approach for 3D instance segmentation. These methods predict instance masks via instance queries, ranking them by classification confidence and IoU scores to select the top prediction as the final outcome. However, it has been observed that the current models employ a fixed and higher number of queries than

Aleksandr Kaplun, Boris Katsnelson

The following development of the well-known "vertical modes and horizontal rays" approach for acoustic waves propagation in shallow water, introduced in different works, is studied. In this approach we study so-called space-time horizontal rays, constructed on the base of decomposition of the sound field, depending on time, over adiabatic vertical modes (sol

Yongsheng Song

We first give a decomposition for a $T$-invariant sublinear expectation $\mathbb{E}=\sup_{P\in\Theta}\mathrm{E}_P$, and show that each component $\mathbb{E}^{(d)}=\sup_{P\in\Theta^{(d)}}\mathrm{E}_P$ of the decomposition has a finite period $p_d\in\mathbb{N}$, i.e., \[\mathbb{E}^{(d)}\left[f-f\circ T^{p_d}\right]=0, \quad f\in\mathcal{H}.\] Then we prove tha

Kimet Jusufi, Giuseppe Gaetano Luciano, Ahmad Sheykhi, Daris Samart

We explore the potential implications of Kaluza-Klein (KK) gravity in unifying the dark sector of the Universe. Through dimensional reduction in KK gravity, the 5D spacetime framework can be reformulated in terms of a 4D spacetime metric, along with additional scalar and vector fields. From the 4D perspective, this suggests the existence of a tower of partic

Olof Rubin

We present a survey of central developments in the theory of Chebyshev polynomials, introduced by P.~L.~Chebyshev and later extended to the complex plane by G.~Faber. Our primary focus is their defining extremal property: among all polynomials with a prescribed leading coefficient, they minimize the supremum norm on a given compact set. Although we do not pr

Ruishi Li, Bo Wang, Tianyu Li, Prateek Saxena

Rust aims to offer full memory safety for programs, a guarantee that untamed C programs do not enjoy. How difficult is it to translate existing C code to Rust? To get a complementary view from that of automatic C to Rust translators, we report on a user study asking humans to translate real-world C programs to Rust. Our participants are able to produce safe

Sze-Man Ngai, Meng-Ke Zhang, Wen-Quan Zhao

Let $\mu$ be a compactly supported positive finite Borel measure on $\R^{d}$. Let $0<\lambda_{1}\leq\lambda_{2}\leq\ldots$ be eigenvalues of the Kre$\breve{{\i}}$n-Feller operator $\Delta_{\mu}$. We prove that, on a bounded domain, the nodal set of a continuous $\lambda_{n}$-eigenfunction of a Kre$\breve{{\i}}$n-Feller operator divides the domain into at lea

Xinyan Liu, Huihong Shi, Yang Xu, Zhongfeng Wang

Transformer-based diffusion models, dubbed Diffusion Transformers (DiTs), have achieved state-of-the-art performance in image and video generation tasks. However, their large model size and slow inference speed limit their practical applications, calling for model compression methods such as quantization. Unfortunately, existing DiT quantization methods over

Horia D. Cornean, Bernard Helffer, Radu Purice

We consider periodic (pseudo)differential {elliptic operators of Schr\"odinger type} perturbed by weak magnetic fields not vanishing at infinity, and extend our previous analysis in \cite{CIP,CHP-2,CHP-4} to the case {of a semimetal having a finite family of Bloch eigenvalues whose range may overlap with the other Bloch bands but remains isolated at each fix

Lewis Dean

We investigate the Demazure product in a double affine setting. Work by Muthiah and Pusk\'as gives a conjectural way to define this in terms of the $q=0$ specialisation of these Hecke algebras. We instead take a different approach generalising work by Felix Schremmer, who gave an equivalent formula for the (single) affine Demazure product in terms of the qua

Jingyi Xu, Xieyuanli Chen, Junyi Ma, Jiawei Huang

The task of occupancy forecasting (OCF) involves utilizing past and present perception data to predict future occupancy states of autonomous vehicle surrounding environments, which is critical for downstream tasks such as obstacle avoidance and path planning. Existing 3D OCF approaches struggle to predict plausible spatial details for movable objects and suf

Richard Banach

Event-B is a well known methodology for the verified design and development of systems that can be characterised as discrete transition systems. Hybrid Event-B is a conservative extension that interleaves the discrete transitions of Event-B (assumed to be temporally isolated) with episodes of continuously varying state change. While a single Hybrid Event-B m

Francesco Foggetti, Peter M. Oppeneer

In spintronic terahertz emitters, THz radiation is generated by exciting an ultrafast spin current through femtosecond laser excitation of a ferromagnetic-nonmagnetic metallic heterostructure. Although an extensive phenomenological knowledge has been built up during the last decade, a solid theoretical modeling that connects the generated THz signal to the l

Shuchen Zhu, Boao Kong, Songtao Lu, Xinmeng Huang

This paper studies decentralized bilevel optimization, in which multiple agents collaborate to solve problems involving nested optimization structures with neighborhood communications. Most existing literature primarily utilizes gradient tracking to mitigate the influence of data heterogeneity, without exploring other well-known heterogeneity-correction tech

Serena S. Serbinowska, Preston Robinette, Gabor Karsai, Taylor T. Johnson

Behavior Trees (BTs) are high-level controllers that are useful in a variety of planning tasks and are gaining traction in robotic mission planning. As they gain popularity in safety-critical domains, it is important to formalize their syntax and semantics, as well as verify properties for them. In this paper, we formalize a class of BTs we call Stateful Beh

Lei Jiang, Weizhe Huang, Tongxuan Liu, Yuting Zeng

Large Vision-Language Models (LVLMs) represent a significant advancement toward achieving superior multimodal capabilities by enabling powerful Large Language Models (LLMs) to understand visual input. Typically, LVLMs utilize visual encoders, such as CLIP, to transform images into visual tokens, which are then aligned with textual tokens through projection l

Syed Ali Asadullah Bukhari, Thomas Flinkow, Medet Inkarbekov, Barak A. Pearlmutter

The increased reliance of self-driving vehicles on neural networks opens up the challenge of their verification. In this paper we present an experience report, describing a case study which we undertook to explore the design and training of a neural network on a custom dataset for vision-based autonomous navigation. We are particularly interested in the use

Serena S. Serbinowska, Nicholas Potteiger, Anne M. Tumlin, Taylor T. Johnson

Behavior Trees (BTs) are high level controllers that have found use in a wide range of robotics tasks. As they grow in popularity and usage, it is crucial to ensure that the appropriate tools and methods are available for ensuring they work as intended. To that end, we created a new methodology by which to create Runtime Monitors for BTs. These monitors can

Nikola Sadovek, Baylee Schutte

We study linearly independent complex line fields on almost-complex manifolds, which is a topic of long-standing interest in differential topology and complex geometry. A necessary condition for the existence of such fields is the vanishing of appropriate virtual Chern classes. We prove that this condition is also sufficient for the existence of one, two, or

Camilo Jose Castro, Ignacio Ortega-Piwonka, Boris A. Malomed, Deterlino Urzagasti

We report the results of systematic investigation of localized dynamical states in the model of a one-dimensional magnetic wire, which is based on the Landau-Lifshitz-Gilbert (LLG) equation. The dissipative term in the LLG equation is compensated by the parametric drive imposed by the external AC magnetic field, which is uniformly applied perpendicular to th

D. A. Head

Graph neural networks can accurately predict the chemical properties of many molecular systems, but their suitability for large, macromolecular assemblies such as gels is unknown. Here, graph neural networks were trained and optimised for two large-scale classification problems: the rigidity of a molecular network, and the connectivity percolation status whi

Wenqiang Xu, Wenrui Dai, Duoduo Xue, Ziyang Zheng

Due to limitations in acquisition equipment, noise perturbations often corrupt 3-D point clouds, hindering down-stream tasks such as surface reconstruction, rendering, and further processing. Existing 3-D point cloud denoising methods typically fail to reliably fit the underlying continuous surface, resulting in a degradation of reconstruction performance. T

Ryu Ueno

The tension field of the identity map from a statistical manifold to a Riemannian statistical manifold, which shares the same Riemannian metric, is the Tchevychev vector field multiplied by negative one. We derive a new class of statistical manifolds that satisfy the semi-equiaffine condition based on the statistical biharmonicity of the identity map. Furthe

Tri Cao, Minh-Huy Trinh, Ailin Deng, Quoc-Nam Nguyen

Anomaly detection (AD) is a machine learning task that identifies anomalies by learning patterns from normal training data. In many real-world scenarios, anomalies vary in severity, from minor anomalies with little risk to severe abnormalities requiring immediate attention. However, existing models primarily operate in a binary setting, and the anomaly score

Kevin Leahy, Hamid Asgari, Louise A. Dennis, Martin S. Feather

Autonomous systems use independent decision-making with only limited human intervention to accomplish goals in complex and unpredictable environments. As the autonomy technologies that underpin them continue to advance, these systems will find their way into an increasing number of applications in an ever wider range of settings. If we are to deploy them to

Tonghua Liu, Shengjia Wang, Hengyu Wu, Jieci Wang

We present an improved model-independent method for determining the cosmic curvature using the observations of Baryon Acoustic Oscillations (BAOs) and the Hubble parameter. The purpose of this work is to provide insights into late-universe curvature measurements using available observational data and techniques. Thus, we use two sources of BAO data sets, BOS

Hengyi Hong, Qing Wang, Jun Du, Ruoyu Wei

Sound event localization and detection with source distance estimation (3D SELD) involves not only identifying the sound category and its direction-of-arrival (DOA) but also predicting the source's distance, aiming to provide full information about the sound position. This paper proposes a multi-stage video attention network (MVANet) for audio-visual (AV) 3D

Markus Pössel

A challenge in teaching about special relativity is that a number of the theory's effects are at odds with the intuition of classical physics, as well as student's everyday experience. The relativity of simultaneity, time dilation and length contraction are prominent examples. This article describes two additional, less well-known counter-intuitive propertie

Corinne Steiner, Rebecca Rahmel, Frank Volmer, Rika Windisch

We perform photoluminescence measurements on vacancy-related emitters in hexagonal boron nitride (hBN) that are notorious for their low quantum yields. The gating of these emitters via few-layer graphene electrodes reveals a reproducible, gate-dependent brightening of the emitter, which coincides with a change in the direction of the simultaneously measured

Mengjia Bai, Jingrun Chen, Rui Du, Zhiwei Sun

This paper presents an a priori error analysis of the Deep Mixed Residual method (MIM) for solving high-order elliptic equations with non-homogeneous boundary conditions, including Dirichlet, Neumann, and Robin conditions. We examine MIM with two types of loss functions, referred to as first-order and second-order least squares systems. By providing boundedn

Yuzhou Tang, Dejun Xu, Yongjie Hou, Zhenzhong Wang

Photorealistic 3D reconstruction of unstructured real-world scenes remains challenging due to complex illumination variations and transient occlusions. Existing methods based on Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) struggle with inefficient light decoupling and structure-agnostic occlusion handling. To address these limitations, we

Xiao Guo, Qingjuan Yu, Youjun Lu

Massive black holes (MBHs) exist in the Galactic center (GC) and other nearby galactic nuclei. As natural outcome of galaxy mergers, some MBHs may have a black hole (BH) companion. In this paper, assuming that the MBHs in the GC and some nearby galaxies are in binaries with orbital periods ranging from months to years (gravitational-wave frequency $\sim1-100

V. M. A. Gómez-González, L. M. Oskinova, W. -R. Hamann, H. Todt

Massive stars lead the ionization and mechanical feedback within young star-forming regions. The Large Magellanic Cloud (LMC) is an ideal galaxy for studying individual massive stars and quantifying their feedback contribution to the environment. We analyze eight exemplary targets in LMC N11 B from the Hubble UV Legacy Library of Young Stars as Essential Sta

D. V. Grosman, G. K. Sizykh, E. O. Lazarev, G. V. Voloshin

Pairs of entangled vortex photons can promise new prospects of application in quantum computing and cryptography. We investigate the possibility of generating such states via two-level atom emission induced by a single photon wave packet with a definite total angular momentum (TAM). The entangled pair produced in this process possesses well-defined mean TAM

Katerina Maria Oikonomou, Vasiliki Balaska, Konstantinos A. Tsintotas, Christos N. Mavridis

Spiking neural networks (SNNs) have captured apparent interest over the recent years, stemming from neuroscience and reaching the field of artificial intelligence. However, due to their nature SNNs remain far behind in achieving the exceptional performance of deep neural networks (DNNs). As a result, many scholars are exploring ways to enhance SNNs by using

Joydeep Chakrabortty, Subhendra Mohanty

We compute the one loop effective action for a Quantum Field Theory at finite temperature, in the presence of background gauge fields, employing the Heat-Kernel method. This method enables us to compute the thermal corrections to the Wilson coefficients associated with effective operators up to arbitrary mass dimension, which emerge after integrating out hea

Thomas Karam, Peter Keevash

We prove that if $d \ge 2$ is an integer, $G$ is a finite abelian group, $Z_0$ is a subset of $G$ not contained in any strict coset in $G$, and $E_1,\dots,E_d$ are dense subsets of $G^n$ such that the sumset $E_1+\dots+E_d$ avoids $Z_0^n$ then $E_1, \dots, E_d$ essentially have bounded dimension. More precisely, they are almost entirely contained in sets $E_

Shaina Gandhi, Jayendra N. Bandyopadhyay

We study the effects of superconducting $p$-wave pairing on the non-Hermitian Aubry-Andr\'e-Harper model with power-law hopping. For the case of short-range hopping, weak pairing leads to oscillating quasi-Majorana zero modes, turning to edge-localized Majorana zero modes as pairing strength increases. For the case of long-range hopping, we observe the emerg

Xiaolei Zhang

Let $R$ be a commutative ring with identity and $S$ a multiplicative subset of $R$. In this paper, we first introduce and study the notions of $s$-pure exact sequences and $s$-absolutely pure modules which extend the classical notions of pure exact sequences and absolutely pure modules. And then, we give some new characterizations of $S$-coherent rings in te

Yinghao Zhang, Yue Hu

Low-rank regularization-based deep unrolling networks have achieved remarkable success in various inverse imaging problems (IIPs). However, the singular value decomposition (SVD) is non-differentiable when duplicated singular values occur, leading to severe numerical instability during training. In this paper, we propose a differentiable SVD based on the Moo

Yue Lu, Jie Chen, Feng Zhou, Yong-Chang Lau

The angular dependence of magnetoresistance (MR) in antiferromagnetic half-Heusler HoAuSn single crystals have been systematically studied. Negative MR, as large as 99%, is observed at 9 T, is not restricted to the specific configuration of applied magnetics fields and current, and can persist up to 20 K, much higher than the Neel temperature (TN 1.9 K). Exp

Luiza Miranda, Isaque P. de Freitas, Francesco Toppan

The first-order L\'evy-Leblond differential equations (LLEs) are the non-relativistic analogous of the Dirac equation: they are the "square roots" of the Schr\"odinger equation in ($1+d$) dimensions and admit spinor solutions. In this paper we show how to extend to the L\'evy-Leblond spinors the real/complex/quaternionic classification of the relativistic sp

Fabian Burghart, Annika Heckel, Marc Kaufmann, Noela Müller

Let $F$ be a graph on $r$ vertices and let $G$ be a graph on $n$ vertices. Then an $F$-factor in $G$ is a subgraph of $G$ composed of $n/r$ vertex-disjoint copies of $F$, if $r$ divides $n$. In other words, an $F$-factor yields a partition of the $n$ vertices of $G$. The study of such $F$-factors in the Erd\H{o}s-R\'enyi random graph dates back to Erd\H{o}s

Heejeong Nam, Jinwoo Ahn, Keummin Ka, Jiwan Chung

Human communication often relies on visual cues to resolve ambiguity. While humans can intuitively integrate these cues, AI systems often find it challenging to engage in sophisticated multimodal reasoning. We introduce VAGUE, a benchmark evaluating multimodal AI systems' ability to integrate visual context for intent disambiguation. VAGUE consists of 1.6K a

Nidhin George Mathews, Matti Lindroos, Johann Michler, Gaurav Mohanty

The deformation behavior of single crystal and nanocrystalline nickel were studied using in situ micropillar compression experiments from quasi-static to high strain rates up to 10^3 s-1. Deformation occurred by dislocation slip activity in single crystal nickel whereas extensive grain boundary sliding was observed in nanocrystalline nickel, with a shift tow

Peilin Chen, Xiaohan Fang, Meng Wang, Shiqi Wang

The Human Visual System (HVS), with its intricate sophistication, is capable of achieving ultra-compact information compression for visual signals. This remarkable ability is coupled with high generalization capability and energy efficiency. By contrast, the state-of-the-art Versatile Video Coding (VVC) standard achieves a compression ratio of around 1,000 t

Lorenzo Restaino, Thomas Schnappinger, Markus Kowalewski

Benzophenone serves as a prototype chromophore for studying the photochemistry of aromatic ketones, with applications ranging from biochemistry to organic light-emitting diodes. In particular, its intersystem crossing from the first singlet excited state to triplet states has been extensively studied, but experimental or theoretical studies on the preceding

Advik Raj Basani, Xiao Zhang

LLMs have shown impressive capabilities across various natural language processing tasks, yet remain vulnerable to input prompts, known as jailbreak attacks, carefully designed to bypass safety guardrails and elicit harmful responses. Traditional methods rely on manual heuristics but suffer from limited generalizability. Despite being automatic, optimization

Kalel L. Rossi, Everton S. Medeiros, Peter Ashwin, Ulrike Feudel

In networked systems, the interplay between the dynamics of individual subsystems and their network interactions has been found to generate multistability in various contexts. Despite its ubiquity, the specific mechanisms and ingredients that give rise to multistability from such interplay remain poorly understood. In a network of coupled excitable units, we

Hongxin Li, Jingsheng Tang, Xuechao Xu, Wei Dai

In sensitive scenarios, such as meetings, negotiations, and team sports, messages must be conveyed without detection by non-collaborators. Previous methods, such as encrypting messages, eye contact, and micro-gestures, had problems with either inaccurate information transmission or leakage of interaction intentions. To this end, a novel gesture-free hand int

Jean-Pascal Capp, Benoît Aliaga, Vera Pancaldi

In cancer research, the term epigenetics was used in the 1970s in its modern sense encompassing non-genetic events modifying the chromatin state, mainly to oppose the emerging oncogene paradigm. However, starting from the establishment of this prominent concept, the importance of these epigenetic phenomena in cancer rarely led to questioning the causal role

Gyula Lakos

Assume that $\mathfrak A$ is a real Banach space of finite dimension $n\geq2$. Consider any Borel probability measure $\nu$ supported on the unit ball $K$ of $\mathfrak A$. We show that \[\Delta(\nu)=\int_{x \in K}\int_{ y\in K}|x-y|_{\mathfrak A} \,\,\,\nu(x)\,\nu(y)\leq 2(1-2^{-n}f(n)),\] where $f:\mathbb N\setminus \{0,1\}\rightarrow (0,1]$ is a concrete

Narcisa Guran, Florian Knauf, Man Ngo, Stefan Petrescu

Large language models have gained widespread popularity for their ability to process natural language inputs and generate insights derived from their training data, nearing the qualities of true artificial intelligence. This advancement has prompted enterprises worldwide to integrate LLMs into their services. So far, this effort is dominated by commercial cl

Jordan Gué

Ultralight dark matter (ULDM), as a class of low mass (< 1 eV) dark matter (DM) candidates, is a compelling alternative to historically dominant models such as WIMPs and has recently gained significant attention in the scientific community. In this thesis, we study various experimental schemes for the direct detection of ULDM, both on ground and in space. Mo

Leonardo Giusti, Davide Laudicina, Matteo Bresciani, Mattia Dalla Brida

We discuss a recently introduced strategy to study non-perturbatively thermal QCD up to temperatures of the order of the electro-weak scale, combining step scaling techniques and shifted boundary conditions. The former allow to renormalize the theory for a range of scales which spans several orders of magnitude with a moderate computational cost. Shifted bou

Anirban Kundu, Poulami Mondal, Gilbert Moultaka

Over the last few years, the CMS and ATLAS collaborations at the Large Hadron Collider (LHC) have reported excesses that could hint at several new scalar resonances. Although none of them has touched the discovery level, at least two of them, at about 95 GeV and 650 GeV, have been indicated by more than one experiments, and have reached statistical significa

Jiacheng Ying, Mushui Liu, Zhe Wu, Runming Zhang

Blind face restoration has made great progress in producing high-quality and lifelike images. Yet it remains challenging to preserve the ID information especially when the degradation is heavy. Current reference-guided face restoration approaches either require face alignment or personalized test-tuning, which are unfaithful or time-consuming. In this paper,

Bjorn Gustafsson, Mihai Putinar

Given a finite family of compact subsets of the complex plane we propose a certificate of mutual non-overlapping with respect to area measure. The criterion is stated as a couple of positivity conditions imposed on a four argument analytic/anti-analytic kernel defined in a neighborhood of infinity. In case the compact sets are closures of quadrature domains

Anjana B., Suman Maiti, Sunandan Adhikary, Soumyajit Dey

Smart grids are designed to efficiently handle variable power demands, especially for large loads, by real-time monitoring, distributed generation and distribution of electricity. However, the grid's distributed nature and the internet connectivity of large loads like Heating Ventilation, and Air Conditioning (HVAC) systems introduce vulnerabilities in the s

Viswanathan Ramachandran, Tobias J. Oechtering, Mikael Skoglund

A fundamental problem in decentralized networked systems is to coordinate actions of different agents so that they reach a state of agreement. In such applications, it is additionally desirable that the actions at various nodes may not be anticipated by malicious eavesdroppers. Motivated by this, we investigate the problem of secure multi-terminal strong coo

Sojwal Manoorkar, Gülce Kalyoncu, Hamdi Omar, Soetkin Barbaix

Underground hydrogen storage in saline aquifers is a potential solution for seasonal renewable energy storage. Among potential storage sites, facilities used for underground natural gas storage have advantages, including well-characterized cyclical injection-withdrawal behavior and partially reusable infrastructure. However, the differences between hydrogen-

Tingyuan Zhu, Shudong Liu, Yidong Wang, Derek F. Wong

Constructing high-quality Supervised Fine-Tuning (SFT) datasets is critical for the training of large language models (LLMs). Recent studies have shown that using data from a specific source, Ruozhiba, a Chinese website where users ask "silly" questions to better understand certain topics, can lead to better fine-tuning performance. This paper aims to explor

Fadhlul Mubarak, Vinny Yuliani Sundara, Nurniswah

This research aims to predict the price of rice in Banda Aceh after the occurrence of Covid-19. The last observation carried forward (LOCF) imputation technique has been used to solve the problem of missing values from this research data. Furthermore, the technique used to forecast rice prices in Banda Aceh is auto-ARIMA which is the best ARIMA model based o

Wenqiang Xu, Wenrui Dai, Duoduo Xue, Ziyang Zheng

Generative diffusion models have shown empirical successes in point cloud resampling, generating a denser and more uniform distribution of points from sparse or noisy 3D point clouds by progressively refining noise into structure. However, existing diffusion models employ manually predefined schemes, which often fail to recover the underlying point cloud str

Fan Yang, Sahoko Ishida, Mengyan Zhang, Daniel Jenson

Remote sensing imagery offers rich spectral data across extensive areas for Earth observation. Many attempts have been made to leverage these data with transfer learning to develop scalable alternatives for estimating socio-economic conditions, reducing reliance on expensive survey-collected data. However, much of this research has primarily focused on dayti

Juliya M. Gudenko, Oleksandr S. Pylypchuk, Victor V. Vainberg, Igor A. Gvozdovskyy

We reveal the visible influence of the ultra-small concentrations (1 wt.% or less) of the BaTiO3 nanoparticles (average size 24 nm) on the current-voltage characteristics and capacitance of the dielectric liquid crystal (LC) 5CB. The pure LC cell demonstrates higher current (and thus smaller resistance) than the LC cells filled with a very small concentratio

Egor E. Nuzhin, Nikolai V. Brilliantov

We report a novel, computationally efficient approach for solving hard nonlinear problems of reinforcement learning (RL). Here we combine umbrella sampling, from computational physics/chemistry, with optimal control methods. The approach is realized on the basis of neural networks, with the use of policy gradient. It outperforms, by computational efficiency

Zhi-yong Li, Ya-kang Xiao, Yan-cheng Li, Li Yu

In this research, a two-dimensional numerical simulation is conducted to determine the equivalent wall slip length for flow around a circular cylinder featuring a super-hydrophobic surface. The super-hydrophobic surface is modeled as an alternating distribution of slip and no-slip conditions along the cylinder's surface. The smallest unit of this alternating

Calum J. Gibb, Jordan Hobbs, Richard J. Mandle

Ferroelectric nematic (NF) liquid crystals combine liquid-like fluidity and orientational order of conventional nematics with macroscopic electric polarization comparable in magnitude to solid state ferroelectric materials. Here, we present a systematic study of twenty-seven homologous materials with various fluorination patterns, giving new insight into the

Hui-Ke Jin, Hong-Hao Tu, Ya-Hui Zhang

We revisit the challenging problem of identifying the quantum spin liquid candidate in the spin-1/2 $J_1$-$J_2$ Heisenberg antiferromagnet on the square lattice. By integrating the Gutzwiller-guided density matrix renormalization group method with analytical analyses, we present clear evidence that the ground state is a Z$_2$ Dirac spin liquid. This state ca

Wei-Yu Liao, Wen-Xiao Wang, Shihao Zhang, Yang Zhang

Multilayer rhombohedral graphene (RG) has recently emerged as a new, structurally simple flat-band system, which facilitates the exploration of interaction-driven correlation states with highly ordered electron arrangements. Despite a variety of many-body order behaviors observed in RG by transport measurements, the direct microscopic visualization of such c

Jianquan Ge, Ya Tao, Yi Zhou

For compact submanifolds in Euclidean and Spherical space forms with Ricci curvature bounded below by a function $\alpha(n,k,H,c)$ of mean curvature, we prove that the submanifold is either isometric to the Einstein Clifford torus, or a topological sphere for the maximal bound $\alpha(n,[\frac{n}{2}],H,c)$, or has up to $k$-th homology groups vanishing. This

Rounak Ray

In real life, networks are dynamic in nature; they grow over time and often exhibit power-law degree sequences. To model the evolving structure of the internet, Barab\'{a}si and Albert introduced a simple dynamic model with a power-law degree distribution. This model has since been generalised, leading to a broad class of affine preferential attachment model

Changyue Jiang, Xudong Pan, Geng Hong, Chenfu Bao

Retrieval-Augmented Generation (RAG) expands the knowledge boundary of large language models (LLMs) by integrating external knowledge bases, whose construction is often time-consuming and laborious. If an adversary extracts the knowledge base verbatim, it not only severely infringes the owner's intellectual property but also enables the adversary to replicat

Ziyi Wang, Feng Gao, Junyu Dong, Qian Du

Recently Transformer-based hyperspectral image (HSI) change detection methods have shown remarkable performance. Nevertheless, existing attention mechanisms in Transformers have limitations in local feature representation. To address this issue, we propose Global and Local Attention-based Transformer (GLAFormer), which incorporates a global and local attenti

Manfred Requardt

We argue in this paper that the entropy of the BH is located in the BH singularity and that the localization around the event horizon is perhaps a secondary effect. We show in particular that the dependence of the entropy located in the singularity is also proportional to $M^2$. We furthermore show that our analysis leads in a natural way to information loss