November 2024 arXiv papers — page 56

Carlo Bellavita, Anil Belli, Georgios Nikolaidis, Georgios Stylogiannis

For $g\in BMOA$, we introduce the meromorphic optimal domain $(T_g,H^p)$, i.e. the space containing the meromorphic functions that are mapped under the action of the generalized Volterra operator $T_g$ into the Hardy space $H^p$. We investigate its properties and characterize for which $g_1,g_2 \in BMOA$ the corresponding meromorphic optimal domains coincide

Wanqi Yang, Yanda Li, Meng Fang, Yunchao Wei

Adversarial audio attacks pose a significant threat to the growing use of large audio-language models (LALMs) in voice-based human-machine interactions. While existing research focused on model-specific adversarial methods, real-world applications demand a more generalizable and universal approach to audio adversarial attacks. In this paper, we introduce the

Tristan Benoist, Laurent Bruneau, Vojkan Jakšić, Annalisa Panati

We study entropic fluctuations in the Spin-Fermion model describing an $N$-level quantum system coupled to several independent thermal free Fermi gas reservoirs. We establish the quantum Evans-Searles and Gallavotti-Cohen fluctuation theorems and identify their link with entropic ancilla state tomography and quantum phase space contraction of non-equilibrium

Longhui Xu

We prove the local well-posedness of the 3D free-boundary incompressible elastodynamics with surface tension describing the motion of an elastic medium in a periodic domain with a moving graphical surface. The deformation tensor is assumed to satisfy the neo-Hookean linear elasticity. We adapt the idea in arXiv:2312.11254 to generate an approximate problem w

Giorgio Palma, Andrea Serani, Kevin McTaggart, Shawn Aram

Digital twins are widely considered enablers of groundbreaking changes in the development, operation, and maintenance of novel generations of products. They are meant to provide reliable and timely predictions to inform decisions along the entire product life cycle. One of their most interesting applications in the naval field is the digital twinning of ship

Weijia Wu, Mingyu Liu, Zeyu Zhu, Xi Xia

Recent advancements in video generation models, like Stable Video Diffusion, show promising results, but primarily focus on short, single-scene videos. These models struggle with generating long videos that involve multiple scenes, coherent narratives, and consistent characters. Furthermore, there is no publicly available dataset tailored for the analysis, e

Christian Kurtscheid, Andreas Redmann, Frank Vewinger, Julian Schmitt

The coupling of two-level quantum systems to the thermal environment is a fundamental problem, with applications ranging from qubit state preparation to spin models. However, for the elementary problem of the thermodynamics of an ensemble of bosons populating a two-level system despite its conceptual simplicity experimental realizations are scarce. Using an

Xu Chen, Guangsheng Yu, Zhian Yuan, Hao Wu

Millimeter-wave (MMW) multiple-input multiple-output synthetic aperture radar (MIMO-SAR) system is a technology that can achieve high resolution, high frame rate, and all-weather imaging and has received extensive attention in the non-destructive testing and internal imaging applications of layered dielectric targets. However, the non-ideal scattering effect

Mohammad Hossein Khoeini, Gijs Wensink, Tomislav Vukovic, Ilja Krafft

To investigate the effect of wettability on multiphase flow in porous media, hydrophilic glass surfaces are typically modified through a silanization process. This study examines the nanoscale chemical and structural modifications of glass bead surfaces treated with Surfasil, using inverse gas chromatography and atomic force microscopy. The results show that

Wenhao Zhen, Dein Wong, Songnian Xu

For a connected graph $G$, we denote by $L(G)$, $m_{G}(\lambda)$, $c(G)$ and $p(G)$ the line graph of $G$, the eigenvalue multiplicity of $\lambda$ in $G$, the cyclomatic number and the number of pendant vertices in $G$, respectively. In 2023, Yang et al. \cite{WL LT} proved that $m_{L(T)}(\lambda)\leq p(T)-1$ for any tree $T$ with $p(T)\geq 3$, and characte

Jie Zhang, Christian Schlarmann, Kristina Nikolić, Nicholas Carlini

Ensemble everything everywhere is a defense to adversarial examples that was recently proposed to make image classifiers robust. This defense works by ensembling a model's intermediate representations at multiple noisy image resolutions, producing a single robust classification. This defense was shown to be effective against multiple state-of-the-art attacks

Camilo Chacón Sartori, Christian Blum, Filippo Bistaffa

The fast advancement of Large Vision-Language Models (LVLMs) has shown immense potential. These models are increasingly capable of tackling abstract visual tasks. Geometric structures, particularly graphs with their inherent flexibility and complexity, serve as an excellent benchmark for evaluating these models' predictive capabilities. While human observers

A. D. Fedoseev, A. O. Zlotnikov

Although the appearance of vortex-localized states with zero energy in first-order topological superconductors is well known, their possibility to form in the higher-order topological phase of 2D systems has not been completely uncovered yet. Here we demonstrate the coexistence of zero-energy vortex modes and Majorana corner modes in the model of a 2D second

Junfeng Li, Haixia Yu, Minqun Zhao

In this paper, for general curves $(t,\gamma(t))$ satisfying some suitable curvature conditions, we obtain some $L^p(\mathbb{R})\times L^q(\mathbb{R}) \rightarrow L^r(\mathbb{R})$ estimates for the bilinear fractional integrals $H_{\alpha,\gamma}$ along the curves $(t,\gamma(t))$, where $$H_{\alpha,\gamma}(f,g)(x):=\int_{0}^{\infty}f(x-t)g(x-\gamma(t))\,\fra

Zhuoran Tan, Christos Anagnosstopoulos, Jeremy Singer

Open-source software serves as a foundation for the internet and the cyber supply chain, but its exploitation is becoming increasingly prevalent. While advances in vulnerability detection for OSS have been significant, prior research has largely focused on static code analysis, often neglecting runtime indicators. To address this shortfall, we created a comp

Juan Liu, Nan-Jing Huang, Xian-Jun Long, Xue-song Li

This paper is devoted to the study of acceleration methods for an inequality constrained convex optimization problem by using Lyapunov functions. We first approximate such a problem as an unconstrained optimization problem by employing the logarithmic barrier function. Using the Hamiltonian principle, we propose a continuous-time dynamical system associated

Anaïs Halin, Sébastien Piérard, Renaud Vandeghen, Benoît Gérin

Characterizing domains is essential for models analyzing dynamic environments, as it allows them to adapt to evolving conditions or to hand the task over to backup systems when facing conditions outside their operational domain. Existing solutions typically characterize a domain by solving a regression or classification problem, which limits their applicabil

Carmen Diez Pardos

Cross-section measurements of the associated production of a top quark pair and a photon ($t\bar{t}\gamma$) are performed with an integrated luminosity of 140 fb$^{-1}$ of proton-proton collisions at a centre-of-mass energy of 13 TeV collected by the ATLAS detector at the LHC. The measurement focuses on $t\bar{t}\gamma$ topologies where the photon is radiate

Jiahao Hu, Tianxiong Zhong, Xuebo Wang, Boyuan Jiang

Diffusion-based image editing models have made remarkable progress in recent years. However, achieving high-quality video editing remains a significant challenge. One major hurdle is the absence of open-source, large-scale video editing datasets based on real-world data, as constructing such datasets is both time-consuming and costly. Moreover, video data re

Nasir Ahmad Rather, Sameer Ahmad Mir, Iqbal Mohi Ud Din, Saeed Uddin

In the framework of a constituent quark mass model, the modified baryon masses are incorporated into the hadron resonance gas (HRG) based analysis of the like mass particle ratios in ultra relativistic nucleus-nucleus collisions (URNNC) over a wide range of collision energy. In addition we have incorporated an essential feature of the hadronic interaction at

Sabrina Weber, Benedikt Prifling, Martin Juckel, Yanting Liu

Solid oxide fuel cells (SOFCs) are becoming increasingly important due to their high electrical efficiency, the flexible choice of fuels and relatively low emissions of pollutants. However, the increasingly growing demands for electrochemical devices require further performance improvements. Since it is well known that the 3D morphology of the electrodes, wh

Md. Naimur Rahman, Shafak Shahriar Sozol, Md. Samsuzzaman, Md. Shahin Hossin

In the modern agricultural industry, technology plays a crucial role in the advancement of cultivation. To increase crop productivity, soil require some specific characteristics. For watermelon cultivation, soil needs to be sandy and of high temperature with proper irrigation. This research aims to design and implement an intelligent IoT-based soil character

Lélia Blin, Fedor V. Fomin, Pierre Fraigniaud, Sylvain Gay

The question of 'what can be computed locally?' lies at the heart of distributed computing in networks. As established in Naor and Stockmeyer's seminal paper (STOC 1993), this question is undecidable, even for graph problems whose solutions can be checked locally. In this paper, we adopt a novel perspective on the question, by asking for which classes $\Pi$

Horia D. Cornean, Radu Purice

We continue the study of the perturbation problem discussed in \cite{CP3} and get rid of the 'slow variation' assumption by considering symbols of the form $a\big(x+\delta\,F(x),\xi\big)$ with $a$ a real H\"{o}rmander symbol of class $S^0_{0,0}(\mathbb{R}^d\times\mathbb{R}^d)$ and $F$ a smooth function with all its derivatives globally bounded, with $|\delta

Chenfan Qu, Yiwu Zhong, Fengjun Guo, Lianwen Jin

Existing Image Manipulation Localization (IML) methods mostly rely heavily on task-specific designs, making them perform well only on the target IML task, while joint training on multiple IML tasks causes significant performance degradation, hindering real applications. To this end, we propose Omni-IML, the first generalist model designed to unify IML across

Di-Lun Yang

We analyze the spin alignment of vector mesons stemming from spin correlation of the quark and antiquark induced by background color fields in relativistic heavy ion collisions. The quark-coalescence equation relating the collision kernel of the vector-meson kinetic equation to spin alignment is expanded to the relativistic case. Focusing on the color-octet

Haris Aziz, Gergely Csáji, Péter Biró

A probabilistic approach to the stable matching problem has been identified as an important research area with several important open problems. When considering random matchings, ex-post stability is a fundamental stability concept. A prominent open problem is characterizing ex-post stability and establishing its computational complexity. We investigate the

Jean-Pierre Labesse

We give the stabilisation of local orbital integrals and the trace formula over a global field for $SL(2)$ with proofs valid in any characteristic. New features appear in characteristic 2. We obtain, via the stabilisation, an asymptotic expansion near the identity of local orbital integrals which is equivalent, up to a Fourier transform, to the standard germ

Sergio Gómez, Chiara Perinati, Paul Stocker

We propose and analyze a space-time Local Discontinuous Galerkin method for the approximation of the solution to parabolic problems. The method allows for very general discrete spaces and prismatic space-time meshes. Existence and uniqueness of a discrete solution are shown by means of an inf-sup condition, whose proof does not rely on polynomial inverse est

Stefano Olla, Makiko Sasada, Hayate Suda

We study the space-time scaling limits of solitons in the box-ball system with random initial distribution. In particular, we show that any recentered tagged soliton converges to a Brownian motion in the diffusive space-time scale, and also prove the large deviation principle for the tagged soliton under certain shift-ergodic invariant distributions, includi

Hongyi Zhou

Quantum random number generators (QRNGs) harness quantum mechanical unpredictability to produce true randomness, which is crucial for cryptography and secure communications. Among various QRNGs, source-independent QRNGs (SI-QRNGs) relax the trust on the quantum source, allowing for flexible use of advanced detectors to achieve high randomness generation rate

Haoyuan Li, Chang Xu, Wen Yang, Li Mi

Unmanned Aerial Vehicle (UAV) Cross-View Geo-Localization (CVGL) presents significant challenges due to the view discrepancy between oblique UAV images and overhead satellite images. Existing methods heavily rely on the supervision of labeled datasets to extract viewpoint-invariant features for cross-view retrieval. However, these methods have expensive trai

Jani Penttala, Christophe Royon

We study exclusive $J/\psi$ and $\Upsilon$ photoproduction for proton and Pb targets in the high-energy limit, with the energy dependence computed using the linear Balitsky-Fadin-Kuraev-Lipatov and the nonlinear Balitsky-Kovchegov evolution equations. The difference between these two evolution equations can be directly attributed to gluon saturation physics.

Pieter Belmans, Andreas Demleitner, Pedro Núñez

We explicitly describe the Albanese morphism of a hyperelliptic variety, i.e., the quotient $X$ of an abelian variety $A$ by a finite group $G$ acting freely and not only by translations, by giving a description of the Albanese variety and the Albanese fibers in terms of $A$ and $G$. In particular, the fibers are themselves abelian or hyperelliptic varieties

Ion I. Cotaescu

Models of evaporating black holes are constructed using the new solutions of Einstein's equations with perfect fluid in space-times with FLRW asymptotic behaviour derived recently [I. I. Cotaescu, Eur. Phys. J. C (2022) 82:86]. The dynamics of these models is exclusively due to the interplay between black holes and their environments, without resorting to ad

Yuya Tanizaki, Akio Tomiya, Hiromasa Watanabe

We investigate the stability of topological charge under gradient flow taking the admissibility condition into account. For the $SU(2)$ Wilson gauge theory with $\beta=2.45$ and $L^4=12^4$, we numerically show that the gradient flows with the Iwasaki and DBW2 gauge actions stabilize the topological sectors significantly, and they have qualitatively different

Yuhang Song, Mario Gianni, Chenguang Yang, Kunyang Lin

This paper addresses the challenge of fine-grained alignment in Vision-and-Language Navigation (VLN) tasks, where robots navigate realistic 3D environments based on natural language instructions. Current approaches use contrastive learning to align language with visual trajectory sequences. Nevertheless, they encounter difficulties with fine-grained vision n

Marcel Robeer, Michiel Bron, Elize Herrewijnen, Riwish Hoeseni

We present the Explabox: an open-source toolkit for transparent and responsible machine learning (ML) model development and usage. Explabox aids in achieving explainable, fair and robust models by employing a four-step strategy: explore, examine, explain and expose. These steps offer model-agnostic analyses that transform complex 'ingestibles' (models and da

Sunjin Choi, Vladimir Stojanović

This paper introduces the concept of autonomous microring arbitration, or wavelength arbitration, to address the challenge of multi-microring initialization in microring-based Dense-Wavelength-Division-Multiplexed (DWDM) transceivers. This arbitration is inherently policy-driven, defining critical system characteristics such as the spectral ordering of micro

Pavel Sakov

It was recently found with the aid of machine learning that for a variety of toy data assimilation systems with chaotic Lorenz-96 model it is possible to achieve a nearly-optimal data assimilation without carrying the state error covariance between cycles. This result does not look surprising on its own because not carrying covariance is the approach taken b

Dengsheng Chen, Jie Hu, Tiezhu Yue, Xiaoming Wei

Recently, autoregressive models have demonstrated remarkable performance in class-conditional image generation. However, the application of next-token prediction to high-resolution text-to-image generation remains largely unexplored. In this paper, we introduce \textbf{D-JEPA$\cdot$T2I}, an autoregressive model based on continuous tokens that incorporates in

Luca Parolari, Elena Izzo, Lamberto Ballan

Referring Expression Comprehension (REC) aims to identify a particular object in a scene by a natural language expression, and is an important topic in visual language understanding. State-of-the-art methods for this task are based on deep learning, which generally requires expensive and manually labeled annotations. Some works tackle the problem with limite

Mashniah A. Gazwani, James A. McCoy

We study families of smooth, embedded, regular planar curves $ \alpha : \left [-1,1 \right ]\times \left [0,T \right )\to \mathbb{R}^{2}$ with generalised Neumann boundary conditions inside cones, satisfying three variants of the fourth-order nonlinear $L^2$- gradient flow for the elastic energy: (1) elastic flow with a length penalisation, (2) elastic flow

Mikhail Sidorenko, Sergei Tretyakov, Constantin Simovski

In this work, we consider instantaneous transitions of an infinitely extended uniaxial dielectric into a wire medium (WM) of continuous infinitely long conducting wires. Due to the strong spatial dispersion in the WM the known (Morgenthaler's) theory of temporal discontinuities is not applicable. We solve this problem analytically in time domain. We show tha

Dominik Walter, Björn Eichmann

Turbulent magnetic fields are to some extent a universal feature in astrophysical phenomena. Charged particles that encounter these turbulence get on average accelerated according to the so-called second-order Fermi process. However, in most astrophysical environments there are additional competing processes, such as different kinds of first-order energy cha

Konstantinos Sourounis, Aurélien Manchon

Altermagnets, a recently identified class of magnetic materials, possess a spin-split Fermi surface that results in the so-called spin splitter effect, enabling the generation of a spin current transverse to the injection direction and whose polarization lies along the N\'eel vector. In this study, we investigate how magnons interact with electrons in an alt

Vebjørn H. Bakkestuen, Vegard Falmår, Maryam Lotfigolian, Markus Penz

The key features of density-functional theory (DFT) within a minimalistic implementation of quantum electrodynamics are demonstrated, thus allowing to study elementary properties of quantum-electrodynamical density-functional theory (QEDFT). We primarily employ the quantum Rabi model, that describes a two-level system coupled to a single photon mode, and als

Jun Wang, Zhaoyang Yin

In this paper, we study the almost sure well-posedness theory and orbital stability for the nonlinear Schr\"odinger equation with potential \begin{equation*} \left\{\begin{array}{l} i \partial_t u+\Delta u-V(x)u+|u|^{2}u=0,\ (x, t) \in \mathbb{R}^4 \times \mathbb{R}, \\ \left.u\right|_{t=0}=f \in H ^s(\mathbb{R}^4), \end{array}\right. \end{equation*} where $

Jie Chang, Zhuoran Li, Zhongyi Wang, Louis Tao

Spiking neuronal networks (SNNs) are widely used in computational neuroscience, from biologically realistic modeling of local cortical networks to phenomenological modeling of the whole brain. Despite their prevalence, a systematic mathematical theory for finite-sized SNNs remains elusive, even for idealized homogeneous networks. The primary challenges are t

Gehui Li, Bin Chen, Chen Zhao, Lei Zhang

Exposure correction is a fundamental problem in computer vision and image processing. Recently, frequency domain-based methods have achieved impressive improvement, yet they still struggle with complex real-world scenarios under extreme exposure conditions. This is due to the local convolutional receptive fields failing to model long-range dependencies in th

Roderich Tumulka, Jonte Weixler

Completely positive trace-preserving maps $S$, also known as quantum channels, arise in quantum physics as a description of how the density operator $\rho$ of a system changes in a given time interval, allowing not only for unitary evolution but arbitrary operations including measurements or other interaction with an environment. It is known that if the Hilb

A. A. Vasil'eva

In this paper, we obtain order estimates for the Gelfand widths of intersections of finite-dimensional balls under some conditions on parameters.

Shulin Lan, Kanlin Liu, Yazhou Zhao, Chen Yang

Current passive deepfake face-swapping detection methods encounter significance bottlenecks in model generalization capabilities. Meanwhile, proactive detection methods often use fixed watermarks which lack a close relationship with the content they protect and are vulnerable to security risks. Dynamic watermarks based on facial features offer a promising so

Ke Zhu, Yu Wang, Yanpeng Sun, Qiang Chen

Multimodal RLHF usually happens after supervised finetuning (SFT) stage to continually improve vision-language models' (VLMs) comprehension. Conventional wisdom holds its superiority over continual SFT during this preference alignment stage. In this paper, we observe that the inherent value of multimodal RLHF lies in its negative supervision, the logit of th

Dafang Zhao, Xihao Piao, Zheng Chen, Zhengmao Li

Accurate forecasting of the electrical load, such as the magnitude and the timing of peak power, is crucial to successful power system management and implementation of smart grid strategies like demand response and peak shaving. In multi-time-scale optimization scheduling, rolling optimization is a common solution. However, rolling optimization needs to cons

Vijaya Kalavakonda, Vimaladevi Madhivanan, Abhay Lal, Senthil Rithika

Osteoporosis, a prevalent condition among the aging population worldwide, is characterized by diminished bone mass and altered bone structure, increasing susceptibility to fractures. It poses a significant and growing global public health challenge over the next decade. Diagnosis typically involves Dual-energy X-ray absorptiometry to measure bone mineral den

Fan Deng, Yaguang Wu, Xinyang Yu, Xiangjun Huang

Recently, text-to-image models based on diffusion have achieved remarkable success in generating high-quality images. However, the challenge of personalized, controllable generation of instances within these images remains an area in need of further development. In this paper, we present LocRef-Diffusion, a novel, tuning-free model capable of personalized cu

Youwei Zhou, Tianyang Xu, Cong Wu, Xiaojun Wu

The shared topology of human skeletons motivated the recent investigation of graph convolutional network (GCN) solutions for action recognition. However, most of the existing GCNs rely on the binary connection of two neighboring vertices (joints) formed by an edge (bone), overlooking the potential of constructing multi-vertex convolution structures. Although

Dongning Song, Weijian Huang, Jiarun Liu, Md Jahidul Islam

Accurate segmentation of blood vessels is essential for various clinical assessments and postoperative analyses. However, the inherent challenges of vascular imaging, such as sparsity, fine granularity, low contrast, data distribution variability, and the critical need for preserving topological structure, making generalized vessel segmentation particularly

Haitao Li, Ziyu Li, Yiheng Mao, Ziyi Liu

Multimodal large language models (MLLMs) are increasingly being applied in the medical field, particularly in medical imaging. However, developing MLLMs for ECG signals, which are crucial in clinical settings, has been a significant challenge beyond medical imaging. Previous studies have attempted to address this by converting ECGs into several text tags usi

Songhao Han, Wei Huang, Hairong Shi, Le Zhuo

The advancement of Large Vision Language Models (LVLMs) has significantly improved multimodal understanding, yet challenges remain in video reasoning tasks due to the scarcity of high-quality, large-scale datasets. Existing video question-answering (VideoQA) datasets often rely on costly manual annotations with insufficient granularity or automatic construct

Jooyoung Choi, Chaehun Shin, Yeongtak Oh, Heeseung Kim

Recent text-to-image diffusion models generate high-quality images but struggle to learn new, personalized styles, which limits the creation of unique style templates. In style-driven generation, users typically supply reference images exemplifying the desired style, together with text prompts that specify desired stylistic attributes. Previous approaches po

Kouki Mikuni, Toshiki Hiraoka, Takumi Kuramoto, Yasuhiro Fujii

Ferrimagnetic materials with a compensation temperature have recently attracted interest because of their unique combination of ferromagnetic and antiferromagnetic properties. However, their magnetization dynamics near the compensation temperature are complex and cannot be fully explained by conventional ferromagnetic resonance (FMR) or exchange resonance mo

Carlos Navarrete-Benlloch

I argue that a single driven quantum Van der Pol oscillator should not be considered a dissipative time crystal, contrary to previous claims. In particular, I show that its phase is prone to randomly drift when considering dephasing or additional nonlinearities, and hence its oscillations are not robust in that sense. The arguments I provide are applicable t

Jiawei Lu, Chengrong Wu

Log-system is an important mechanism for recording the runtime status and events of Web service systems, and anomaly detection in logs is an effective method of detecting problems. However, manual anomaly detection in logs is inefficient, error-prone, and unrealistic. Existing log anomaly detection methods either use the indexes of event templates, or form v

Hitesh Khungla, Kulbir Singh, Mohit Kumar

Marine accidents highlight the crucial need for human safety. They result in loss of life, environmental harm, and significant economic costs, emphasizing the importance of being proactive and taking precautionary steps. This study aims to identify the root causes of accidents, to develop effective strategies for preventing them. Due to the lack of accurate

Mikhail Hlushchanka, Han Peters

We study the zero sets of the independence polynomial on recursive sequences of graphs. We prove that for a maximally independent starting graph and a stable and expanding recursion algorithm, the zeros of the independence polynomial are uniformly bounded. Each of the recursion algorithms leads to a rational dynamical system whose formula, degree and the dim

Zheni Zeng, Yuxuan Chen, Shi Yu, Ruobing Wang

Although retrieval-augmented generation (RAG) remains essential for knowledge-based question answering (KBQA), current paradigms face critical challenges under specific domains. Existing methods struggle with targeted adaptation on small-scale KBs: vanilla unsupervised training exhibits poor effectiveness, while fine-tuning incurs prohibitive costs of extern

Hongbo Liu

Contrastive Language-Image Pre-training (CLIP) has attracted a surge of attention for its superior zero-shot performance and excellent transferability to downstream tasks. However, training such large-scale models usually requires substantial computation and storage, which poses barriers for general users with consumer-level computers. Motivated by this obse

Yoojin Choi, Juhee Han, Kyoseung Koo, Bongki Moon

Query optimizers are essential components of relational database management systems that directly impact query performance as they transform input queries into efficient execution plans. While users can obtain the final execution plan using the EXPLAIN command and leverage existing visualization tools for intuitive understanding, the internal decision-making

Jing-Lun Li, Paul S. Julienne, Johannes Hecker Denschlag, José P. D'Incao

We theoretically investigate the spin structure of weakly bound diatomic van der Waals molecules formed by two identical bosonic alkali atoms. Our studies were performed using known Born-Oppenheimer potentials while developing a reduced interaction potential model. Such reduced potential models are currently a key for solving certain classes of few-body prob

Xiaofei Wu, Tao Liu, Caoji Li, Yuexin Ma

Effectively modeling the interaction between human hands and objects is challenging due to the complex physical constraints and the requirement for high generation efficiency in applications. Prior approaches often employ computationally intensive two-stage approaches, which first generate an intermediate representation, such as contact maps, followed by an

Xiwei Liu, Mohamad Kassab, Min Xu, Qirong Ho

Cryo-Electron Tomography (Cryo-ET) enables detailed 3D visualization of cellular structures in near-native states but suffers from low signal-to-noise ratio due to imaging constraints. Traditional denoising methods and supervised learning approaches often struggle with complex noise patterns and the lack of paired datasets. Self-supervised methods, which uti

Zhiwei Jia, Yuesong Nan, Huixi Zhao, Gengdai Liu

Recent research has shown that fine-tuning diffusion models (DMs) with arbitrary rewards, including non-differentiable ones, is feasible with reinforcement learning (RL) techniques, enabling flexible model alignment. However, applying existing RL methods to step-distilled DMs is challenging for ultra-fast ($\le2$-step) image generation. Our analysis suggests

Ilana Kats, Tomer Eini, Itai Epstein

Hyperbolic materials are natural or engineered artificial structures that provide means to manipulate and control electromagnetic radiation, leading to a variety of strong light-matter interactions at the nanoscale. In this work, we explore the physical properties of the optical response of 2D semiconductor-based superlattices, which are engineered with atom

Apurba Bera, Clancy W. James, Mark M. McKinnon, Ronald D. Ekers

Fast radio bursts (FRBs) are highly energetic events of short-duration intense radio emission, the origin of which remains elusive till date. Polarization of the FRB signals carry information about the emission source as well as the magneto-ionic media the signal passes through before reaching terrestrial radio telescopes. Currently known FRBs show a diverse

Mahammad Humayoo

In numerous episodic reinforcement learning (RL) environments, SARSA-based methodologies are employed to enhance policies aimed at maximizing returns over long horizons. Traditional SARSA algorithms face challenges in achieving an optimal balance between bias and variation, primarily due to their dependence on a single, constant discount factor ($\eta$). Thi

Tae-Ho Park, Han-Yong Choi

We investigate the emergence of the collective mode in the phonon spectra of the superconducting state within the Holstein model by varying the electron-phonon coupling. Using dynamical mean field theory (DMFT) combined with the numerical renormalization group (NRG) technique, we calculate the phonon spectra. In the superconducting state with a pairing gap (

Junde Liu, Danpei Zhao, Bo Yuan, Wentao Li

Significant advancements have been made in semantic image synthesis in remote sensing. However, existing methods still face formidable challenges in balancing semantic controllability and diversity. In this paper, we present a Hybrid Semantic Embedding Guided Generative Adversarial Network (HySEGGAN) for controllable and efficient remote sensing image synthe

Jinming Sun, Manna Chen, Stefan Schumacher, Wei Hu

Dark solitons carrying quantized phase information arouse great interest in different nonlinear systems. A dark soliton in 1D can be stabilized in microcavity polariton condensates as a confinement is imposed on it to prevent its decay. Such a confinement can be realized by optical manners, i.e., by using optically induced potential traps. Under nonresonant

Lingfei Jin, Liming Ma, Chaoping Xing, Haiyan Zhou

MDS codes have garnered significant attention due to their wide applications in practice. To date, most known MDS codes are equivalent to Reed-Solomon codes. The construction of non-Reed-Solomon (non-RS) type MDS codes has emerged as an intriguing and important problem in both coding theory and finite geometry. Although some constructions of non-RS type MDS

Adam H. T. P. Höfler, Iurii Chubak, Christos N. Likos, Jan Smrek

Polymers with active segments constitute prospective future materials and are used as a model for some biological systems such as chromatin. The directions of the active forces are typically introduced with temporal or spatial correlations to establish directional motion of the chain and corresponding active dynamics. Instead, here we consider an active-pass

Shuzhe Cai, Xuanrui Feng, Yun Gong, Zhenfu Wang

We derive the quantitative propagation of chaos in the sense of relative entropy for the first time for the 2D Log gas or the weakly interacting particle systems with 2D Coulomb interactions on the whole space. We resolve this problem by adapting the modulated free energy method in [BJW23] to the whole space setting and establishing the crucial logarithmic g

Eddy Ardonne, Viktor Kurasov

We study the non-hermitian Kitaev chain model, for arbitrary complex parameters. In particular, we give a concise characterisation of the curves of eigenvalues in the complex plane in the infinite size limit, using a novel method which can be applied to other non-hermitian systems. Using this solution, we characterise under which conditions the skin effect i

Harin Park, Inha Lee, Minje Kim, Hyungyu Park

As service environments have become diverse, they have started to demand complicated tasks that are difficult for a single robot to complete. This change has led to an interest in multiple robots instead of a single robot. C-SLAM, as a fundamental technique for multiple service robots, needs to handle diverse challenges such as homogeneous scenes and dynamic

Declan Curran, Hira Saleem, Sanaa Hobeichi, Flora Salim

Understanding future weather changes at regional and local scales is crucial for planning and decision-making, particularly in the context of extreme weather events, as well as for broader applications in agriculture, insurance, and infrastructure development. However, the computational cost of downscaling Global Climate Models (GCMs) to the fine resolutions

M. E. Egwe, J. I. Opadara

A collection of infinite dimensional complete vector fields $\left\{V_i\right\}_{i=1}^{\infty}$ acting on a locally convex manifolds $M$ on which a smooth positive measure $\mu$ is defined was considered. It was assumed that the vector fields generates an infinite dimensional Lie algebra $\mathfrak{g}$ and satisfies H$\ddot{o}$rmander's condition. The sum of

Qian Liang, Yi Zeng, Menghaoran Tang

Musical mode is one of the most critical element that establishes the framework of pitch organization and determines the harmonic relationships. Previous works often use the simplistic and rigid alignment method, and overlook the diversity of modes. However, in contrast to AI models, humans possess cognitive mechanisms for perceiving the various modes and ke

Yilan Wang, Feng Tian, Wendi Huang, Taojie Zhou

Nanolasers, characterized by enhanced optical localization at subwavelength scale, have emerged as promising coherent light sources for ultra-compact, high-speed and energy-efficient photonic integrated circuits. Twisted photonic crystal nanocavity, constructed by stacking two layers of photonic crystal structure with a specified rotation angle, enables stro

Busra Tegin, Tolga M Duman

Channels with synchronization errors, exhibiting deletion and insertion errors, find practical applications in DNA storage, data reconstruction, and various other domains. Presence of insertions and deletions render the channel with memory, complicating capacity analysis. For instance, despite the formulation of an independent and identically distributed (i.

Xiangyun Meng, Xuning Yang, Sanghun Jung, Fabio Ramos

Existing navigation systems mostly consider "success" when the robot reaches within 1m radius to a goal. This precision is insufficient for emerging applications where the robot needs to be positioned precisely relative to an object for downstream tasks, such as docking, inspection, and manipulation. To this end, we design and implement Aim-My-Robot (AMR), a

Mickaël D. Chekroun, Niccolò Zagli, Valerio Lucarini

We present a generalized linear response theory for mixed jump-diffusion models -- combining Gaussian and L\'evy noise interacting with nonlinear dynamics -- by deriving comprehensive response formulas accounting for perturbations to both the drift term and the jumps law. This class of models is particularly relevant for parameterizing the effects of unresol

Silin Zhou, Shuo Shang, Lisi Chen, Peng Han

Trajectory representation learning (TRL) maps trajectories to vectors that can be used for many downstream tasks. Existing TRL methods use either grid trajectories, capturing movement in free space, or road trajectories, capturing movement in a road network, as input. We observe that the two types of trajectories are complementary, providing either region an

Manasa N. Vempati

In this article we obtain the characterization for the commutators of maximal functions on the weighted Morrey spaces in the setting of spaces of homogeneous type. More precisely, we characterize BMO spaces using the commutators of Hardy-Littlewood maximal function, sharp and fractional maximal functions.

Pierre Andreoletti

Axis-driven random walks were introduced by P. Andreoletti and P. Debs [AD23] to provide a rough description of the behaviour of a particle trapped in a localized force field. In contrast to their work, we examine the scenario where a repulsive force (controlled by a parameter $\alpha$) is applied along the axes, with the hypothesis that the walk remains dif

Stefan K. Nielsen, Tan M. Nguyen

Contrastive learning has proven instrumental in learning unbiased representations of data, especially in complex environments characterized by high-cardinality and high-dimensional sensitive information. However, existing approaches within this setting require predefined modelling assumptions of bias-causing interactions that limit the model's ability to lea

Jie Du, Haixia Gu, Zhenhua Li, Jinkui Wan

In [DGLW], we use certain special elements and their commutation relations in the Hecke-Clifford algebras $H^c_{r,R}$ to derive some fundamental multiplication formulas associated with the natural bases in queer $q$-Schur superalgebras $Q_q(n,r;R)$ introduced in [DW2]. Here a natural basis element is defined by a special element $T_{A^{\star}}$ in $H^c_{r,R}

Amira Guesmi, Bassem Ouni, Muhammad Shafique

Quantized neural networks (QNNs) are increasingly used for efficient deployment of deep learning models on resource-constrained platforms, such as mobile devices and edge computing systems. While quantization reduces model size and computational demands, its impact on adversarial robustness-especially against patch-based attacks-remains inadequately addresse

Sebastian Kranz

Analysing the Stata regression commands from 4,420 reproduction packages of leading economic journals, we find that, among the 40,571 regressions specifying heteroskedasticity-robust standard errors, 98.1% adhere to Stata's default HC1 specification. We then compare several heteroskedasticity-robust inference methods with a large-scale Monte Carlo study base

Huiwon Jang, Sihyun Yu, Jinwoo Shin, Pieter Abbeel

Efficient tokenization of videos remains a challenge in training vision models that can process long videos. One promising direction is to develop a tokenizer that can encode long video clips, as it would enable the tokenizer to leverage the temporal coherence of videos better for tokenization. However, training existing tokenizers on long videos often incur