March 2025 arXiv papers — page 51

A. C. Lehum, J. R. Nascimento, A. C. Pina Neto, A. Yu. Petrov

We perform the study of perturbative aspects of a three-dimensional supersymmetric Maxwell-Chern-Simons-Proca theory minimally coupled to scalar superfields. Using the superfield formalism, we derive the propagators for both gauge and matter superfields and compute the leading quantum corrections to the effective action. The presence of the Proca-like term e

Yanhong Li, David Yunis, David McAllester, Jiawei Zhou

There has recently been considerable interest in incorporating information retrieval into large language models (LLMs). Retrieval from a dynamically expanding external corpus of text allows a model to incorporate current events and can be viewed as a form of episodic memory. Here we demonstrate that pre-processing the external corpus into semi-structured ''a

Haozhe Yin, Kai Wang, Wenjie Zhang, Yizhang He

Motif counting plays a crucial role in understanding the structural properties of networks. By computing motif frequencies, researchers can draw key insights into the structural properties of the underlying network. As networks become increasingly complex, different graph models have been proposed, giving rise to diverse motif patterns. These variations intr

Konstantinos Sfairopoulos, Luke Causer, Jamie F. Mair, Stephen Powell

We study classical and quantum spin models derived from one-dimensional cellular automata (CA) with nonlinear update rules, focusing on rules 30, 54 and 201. We argue that the classical models, defined such that their ground states correspond to allowed trajectories of the CA, are frustrated and can be described in terms of local defect variables. Including

Shubham Kala, Hemwati Nandan, Kush Maithani, Saswati Roy

In this paper, we investigate the properties of null geodesics, thermodynamics, gravitational lensing, and black hole shadows in the vicinity of a static regular Frolov black hole. By analyzing the trajectories of null geodesics, we investigate the bending of light in weak field regimes. The black hole shadow is studied in detail, with constraints on its par

Olgica Zaric, Carmen Leser, Vladimir Juras, Alex Farr

Introduction: In sodium (23Na) magnetic resonance imaging (MRI), partial volume effects (PVE) are one of the most common causes of errors in the in vivo quantification of tissue sodium concentration (TSC). Advanced image reconstruction algorithms, such as compressed sensing (CS), have the potential to reduce PVE. Therefore, we investigated the feasibility of

Kaizhe Chen, Jie Ma

We address a problem posed by Erd\H{o}s and Hajnal in 1991, proving that for all $n \geq 600$, every $(2n+1)$-vertex graph with at least $n^2 + n + 1$ edges contains two vertices of equal degree connected by a path of length three. The complete bipartite graph $K_{n,n+1}$ demonstrates that this edge bound is sharp. We further establish an analogous result fo

Christian Gaß, Harold Steinacker

We present an expanding, spatially flat ($k=0$) FLRW quantum spacetime with a Big Bang, considered as a background in Yang-Mills matrix models. The FLRW geometry emerges in the semi-classical limit as a projection from the fuzzy hyperboloid. We analyze the propagation of scalar fields, and demonstrate that their Feynman propagator resembles the Minkowski spa

Peter Boyvalenkov, Sergii Yu. Favorov

Let $\mu$ be a measure on the Euclidean space $\R^d$ of unbounded total variation that is positive or translation bounded and has a pure point Fourier transform in the sense of distributions $\hat\mu$. We prove that the measure $\nu$ with the same support as $\hat\mu$ and masses equal to the squares of the masses of $\hat\mu$ is translation bounded. We also

Yongzhao Zhu, Jie Liu, Renhui Qin, Ligong Bian

We systematically investigate theoretical uncertainties in perturbative analyses of first-order electroweak phase transitions (EWPT). Utilizing the Standard Model Effective Field Theory (SMEFT) framework, we quantify the gauge dependence, renormalization scheme, and scale dependences in predicting phase-transition parameters across both zero and finite chemi

Chi Li, Kaijian Xing, Wenhao Zhai, Luca Sortino

In transition metal dichalcogenides, the valley degree of freedom directly couples valley-polarised excitons - excited by circularly polarised light - to valley-dependent chiral photons, enabling ultrafast light-driven valleytronics. However, achieving fully integrated valley optoelectronics - incorporating on-chip generation, selective routing, and electric

Sree Bhargavi Balija

As artificial intelligence systems increasingly operate in Real-world environments, the integration of multi-modal data sources such as vision, language, and audio presents both unprecedented opportunities and critical challenges for achieving trustworthy intelligence. In this paper, we propose a novel framework that unifies federated learning with explainab

Jakob Reiffenstein

The Nevanlinna matrix of a half-line Jacobi operator coincides, up to multiplication with a constant matrix, with the monodromy matrix of an associated canonical system. This canonical system is discrete in a certain sense, and is determined by two sequences, called "lengths" and "angles". We derive new lower and upper estimates for the norm of the monodromy

Nicolina Istrati, Alexandra Otiman

We review old and new properties of Hopf manifolds from the point of view of their analytic and metric structure.

Mahathi Anand, Raphaël Jungers, Majid Zamani, Frank Allgöwer

This paper is concerned with path-complete barrier functions which offer a graph-based methodology for verifying safety properties in switched systems. The path-complete framework leverages algebraic (barrier functions) as well as combinatorial (graph) components to characterize a set of safety conditions for switched systems, thus offering high flexibility

A. R. Bekirov, A. F. Uspenskiy, V. A. Sitnyansky, B. S. Lukyanchuk

We investigate a method for controlling light scattering based on the excitation of non-radiating states in a half-space through a tailored choice of incident radiation. For a fixed particle geometry, we demonstrate that small variations in the refractive index can lead to a significant redistribution of scattered light between two half spaces while keeping

N. Carlin, J. Y. Cho, J. J. Choi, S. Choi

The annual modulation signal, claimed to be consistent with dark matter as observed by DAMA/LIBRA in a sodium-iodide based detector, has persisted for over two decades. COSINE-100 and ANAIS-112 were designed to test the claim directly using the same target material. COSINE-100, located at Yangyang Underground Laboratory in South Korea, and ANAIS-112, located

Jacco H. Terwel, Kate Maguire, Jesper Sollerman, Phil Wiseman

With large-scale surveys such as the Zwicky Transient Facility (ZTF), it has become possible to obtain a well-sampled light curve spanning the full length of the survey for any discovery within the survey footprint. Similarly, any transient within the footprint that was first detected before the start of the survey will likely have a large number of post-tra

Haim Sawdayee, Chuan Guo, Guy Tevet, Bing Zhou

Text-to-motion generative models span a wide range of 3D human actions but struggle with nuanced stylistic attributes such as a "Chicken" style. Due to the scarcity of style-specific data, existing approaches pull the generative prior towards a reference style, which often results in out-of-distribution low quality generations. In this work, we introduce LoR

Anup Teejo Mathew, Daniel Feliu-Talegon, Yusuf Abdullahi Adamu, Ikhlas Ben Hmida

The inherent challenges of robotic underwater exploration, such as hydrodynamic effects, the complexity of dynamic coupling, and the necessity for sensitive interaction with marine life, call for the adoption of soft robotic approaches in marine exploration. To address this, we present a novel prototype, ZodiAq, a soft underwater drone inspired by prokaryoti

Pablo Rodriguez-Martin, Oscar Adamuz-Hinojosa, Pablo Muñoz, Julia Caleya-Sanchez

Deterministic communications are essential for industrial automation, ensuring strict latency requirements and minimal jitter in packet transmission. Modern production lines, specializing in robotics, require higher flexibility and mobility, which drives the integration of Time-Sensitive Networking (TSN) and 5G networks in Industry 4.0. TSN achieves determin

Jean Durand, Yashas Annadani, Stefan Bauer, Sonali Parbhoo

Causal Bayesian Optimization (CBO) is a methodology designed to optimize an outcome variable by leveraging known causal relationships through targeted interventions. Traditional CBO methods require a fully and accurately specified causal graph, which is a limitation in many real-world scenarios where such graphs are unknown. To address this, we propose a new

Étienne Objois, Adrian Vladu

We provide the first nearly-linear time algorithm for approximating $\ell_{q \rightarrow p}$-norms of non-negative matrices, for $q \geq p \geq 1$. Our algorithm returns a $(1-\varepsilon)$-approximation to the matrix norm in time $\widetilde{O}\left(\frac{1}{q \varepsilon} \cdot \text{nnz}(\boldsymbol{\mathit{A}})\right)$, where $\boldsymbol{\mathit{A}}$ is

Balázs Endre Szigeti, Imre Ferenc Barna, Gergely Gábor Barnaföldi

We studied the Euler--Poisson equation system in the case of cylindrical symmetry with the von Neumann--Sedov--Taylor type of self-similar Ansatz and present scaling solutions. We have analyzed the scenario governed by Chaplygin's equation of state, which has historically been studied as a unifying framework of dark fluid for dark matter and dark energy.

Zeyu Qin, Qingxiu Dong, Xingxing Zhang, Li Dong

Large language models (LLMs) achieve strong performance across diverse tasks, largely driven by high-quality web data used in pre-training. However, recent studies indicate this data source is rapidly depleting. Synthetic data emerges as a promising alternative, but it remains unclear whether synthetic datasets exhibit predictable scalability comparable to r

Corentin Fierobe

The conjugation problem for billiard maps conjectures that if two strictly convex billiards have conjugated billiard maps, the billiard tables must be homothetic to each other. We show that if two billiard maps are conjugated, the conjugation diffeomorphism is tangent to a Lazutkin change of coordinates. We also recompute the coefficients in the billiard map

L. A. Head, D. Grodent, B. Bonfond, A. Sulaiman

Jupiters ultraviolet aurora frequently shows a number of arcs between the dusk-side polar region and the main emission, which are denoted as bridges. This work presents a largely automated detection and statistical analysis of bridges over 248 Hubble-Space-Telescope observations, alongside a multi-instrument study of crossings of magnetic field lines connect

Zubair Shaban, Nazreen Shah, Ranjitha Prasad

In 6G wireless networks, Artificial Intelligence (AI)-driven applications demand the adoption of Federated Learning (FL) to enable efficient and privacy-preserving model training across distributed devices. Over-The-Air Federated Learning (OTA-FL) exploits the superposition property of multiple access channels, allowing edge users in 6G networks to efficient

Rishabh Mishra

This paper introduces a novel class of initial data for which the three-dimensional incompressible Navier--Stokes equations yield unique global-in-time solutions. Building on a logarithmically improved regularity criterion, we impose a logarithmically subcritical condition on the initial data. Specifically, if \[ u_0 \in L^2(\mathbb{R}^3) \quad \text{and} \q

Monica Jin, Raphina Liu, Martin Monperrus

In this paper, we present the first large-scale empirical study of smart contract dependencies, analyzing over 41 million contracts and 11 billion interactions on Ethereum up to December 2024. Our results yield four key insights: (1) 59% of contract transactions involve multiple contracts (median of 4 per transaction in 2024) indicating potential smart contr

Ignacio Santamaria, Mohammad Soleymani, Eduard Jorswieck, Jesus Gutierrez

This paper proposes a two-stage approach for passive and active beamforming in multiple-input multiple-output (MIMO) interference channels (ICs) assisted by a beyond-diagonal reconfigurable intelligent surface (BD-RIS). In the first stage, the passive BD-RIS is designed to minimize the aggregate interference power at all receivers, a cost function called int

Jan Kohút, Michal Hradiš

A common use case for OCR applications involves users uploading documents and progressively correcting automatic recognition to obtain the final transcript. This correction phase presents an opportunity for progressive adaptation of the OCR model, making it crucial to adapt early, while ensuring stability and reliability. We demonstrate that state-of-the-art

Elena Buglakova, Anwai Archit, Edoardo D'Imprima, Julia Mahamid

Segmentation of very large images is a common problem in microscopy, medical imaging or remote sensing. The problem is usually addressed by sliding window inference, which can theoretically lead to seamlessly stitched predictions. However, in practice many of the popular pipelines still suffer from tiling artifacts. We investigate the root cause of these iss

Md Abdullah-Al Kaiser, Sugeet Sunder, Clynn Mathew, Michal Rakowski

In this work, we propose a novel differential photonic static random access memory (pSRAM) bitcell design using fabrication-friendly photonic components. The proposed pSRAM overcomes the key limitations of traditional electrical SRAMs, which struggle with speed and power efficiency due to increasing bitline/wordline capacitance and interconnect resistance as

Junwei Zheng, Ruiping Liu, Yufan Chen, Zhenfang Chen

Absolute Pose Regression (APR) predicts 6D camera poses but lacks the adaptability to unknown environments without retraining, while Relative Pose Regression (RPR) generalizes better yet requires a large image retrieval database. Visual Odometry (VO) generalizes well in unseen environments but suffers from accumulated error in open trajectories. To address t

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

By analyzing $e^+e^-$ collision data collected at the center-of-mass energy of 3.773~GeV with the BESIII detector, corresponding to an integrated luminosity of 20.3~fb$^{-1}$, we measure the branching fractions of the doubly Cabibbo-suppressed (DCS) decays $D^0\to K^+\pi^-$, $D^0\to K^+\pi^-\pi^-\pi^+$, $D^0\to K^+\pi^-\pi^0$, $D^0\to K^+\pi^-\pi^0\pi^0$, $D

Miguel Duarte

We establish a relationship between the equations that constitute the so-called good-bad-ugly model, whose nonlinearities are known to mimic those present in the Einstein field equations in generalized harmonic gauge. This relationship between ugly fields and good and bad ones stems from the fact that one can write the equation for the rescaled derivative of

Dahyun Jung, Seungyoon Lee, Hyeonseok Moon, Chanjun Park

Recent advancements in Large Language Models (LLMs) have significantly enhanced interactions between users and models. These advancements concurrently underscore the need for rigorous safety evaluations due to the manifestation of social biases, which can lead to harmful societal impacts. Despite these concerns, existing benchmarks may overlook the intrinsic

Junjie Chen, Takuro Yamashita

An information broker incentivizes consumers to share their information, while designing an information structure to shape the market segmentation. The information broker is a metaphor for an Internet platform that matches consumers with retailers. We are interested in a market with heterogeneous retailers and heterogeneous consumers. The optimal broking mec

Nicolas Chartier, Md Arif Shaikh, Hyung Mok Lee, JeongCho Kim

In the absence of a unique, gauge-independent definition of eccentricity in General Relativity, there have been efforts to standardize the definition for Gravitational-Wave astronomy. Recently, Shaikh et al. proposed a model-independent measurement of eccentricity $e_{\mathrm{gw}}$ from the phase evolution of the dominant mode. Many works use loss functions

Noam Kahlon, Guy Rom, Anatoly Efros, Filippo Galgani

Phone automation agents aim to autonomously perform a given natural-language user request, such as scheduling appointments or booking a hotel. While much research effort has been devoted to screen understanding and action planning, complex tasks often necessitate user interaction for successful completion. Aligning the agent with the user's expectations is c

Emma Fernández-Alvar, Tomás Ruiz-Lara, Carme Gallart, Santi Cassisi

Understanding the formation and evolution of the Milky Way's thin and thick discs is crucial to galaxy formation studies. We derive age and metallicity distributions of the kinematic thick and thin discs using the CMDft.Gaia pipeline and Gaia DR3 data within 250 pc of the Sun, covering 1 kpc in height. Our results show that the kinematic thick disc is mostly

Maurizio Boccia, Veronica Dal Sasso, Leonardo Lamorgese, Carlo Mannino

Union Pacific (UP) is one of the largest transportation companies in the world, with over 50.000 kms of rail network covering 23 states in the United States. In 2017 Union Pacific embarked on a project that within 5 years would lead it to become the only rail operator in the world equipped with a technology capable of fully automating the real-time managemen

Céline Cunen, Thea Roksvåg, Claudio Heinrich-Mertsching, Alex Lenkoski

Combining forecasts from multiple numerical weather prediction (NWP) models have shown substantial benefit over the use of individual forecast products. Although combination, in a broad sense, is widely used in meteorological forecasting, systematic studies of combination methodology in meteorology are scarce. In this article, we study several combination me

Michel Matignon, Guillaume Pagot, Daniele Turchetti

Let $p$ be a prime number. Motivated by the local lifting problem for $(\mathbb{Z}/p\mathbb{Z})^n$ with $n>1$, we prove several new results on certain $\mathbb{F}_p$-vector spaces of logarithmic differential forms on the projective line in characteristic $p$, called "spaces $L_{m+1,n}$". Expanding the previous work by the first two authors, we prove positive

Quentin Faes, Maksymilian Manko

Building on the work of Nenciu we provide examples of non-factorizable ribbon Hopf algebras, and introduce a stronger notion of non-factorizability. These algebras are designed to provide invariants of $4$-dimensional $2$-handlebodies up to 2-deformations. We prove that some of the invariants derived from these examples are invariants dependent only on the b

Micha Moffie, Omer Boehm, Anatoly Koyfman, Eyal Bin

The advent of quantum computing poses a significant challenge as it has the potential to break certain cryptographic algorithms, necessitating a proactive approach to identify and modernize cryptographic code. Identifying these cryptographic elements in existing code is only the first step. It is crucial not only to identify quantum vulnerable algorithms but

Suhas G Hegde, Shilpy Kaur, Aruna Tiwari

Popular PEFT methods reduce trainable parameter count for fine-tuning by parameterizing new low-rank or sparse trainable weights in parallel to the frozen pre-trained weights $W$. However, these weights are trained from scratch, and there exists a performance gap between these methods and full fine-tuning, especially in low-budget settings. We introduce Vect

Omid Esrafilian, Rakesh Mundlamuri, Florian Kaltenberger, Raymond Knopp

This paper considers the challenge of localizing ground users with the help of a radio-equipped unmanned aerial vehicle (UAV) that collects measurements from users. We utilize time-of-arrival (ToA) measurements estimated from the radio signals received from users collected by a UAV at different locations. Since the UAV's location might not be perfectly known

Apostolos Giannopoulos, Natalia Tziotziou

Let $\mu$ be a centered log-concave probability measure on ${\mathbb R}^n$ and let $\Lambda_{\mu}^{\ast}$ denote the Cram\'{e}r transform of $\mu$, i.e. $\Lambda_{\mu}^{\ast}(x)=\sup\{\langle x,\xi\rangle-\Lambda_{\mu}(\xi):\xi\in\mathbb{R}^n\}$ where $\Lambda_{\mu}$ is the logarithmic Laplace transform of $\mu$. We show that $\mathbb{E}_{\mu}\left[\exp\left

J. Butterworth, S. Viti, Y. Wang

(Abridged) The identification of AGN and SB regions in galaxies is crucial for understanding the role of various physical processes in galaxy evolution. Molecular line ratios, such as the HCN/HCO+ ratio, have been proposed as potential tracers of these distinct environments. This paper aims to assess the reliability of the HCN/HCO+ ratio, from J = 1-0 to J =

Katherine I. Dale, Alessandro Morbidelli, David C. Rubie, David Nesvorny

We address Earth formation from an elemental perspective, using a method similar to Rubie et al. (2015) but with updates from Dale et al. (2023) to simulate the chemical evolution of Earth's mantle during metal-silicate equilibration events from accretional collisions. Our model introduces two key differences: (1) Earth forms from a dense ring of planetesima

Yike Qiao, Xiaodong He, An Zhuo, Zhiyong Sun

Vector fields are advantageous in handling nonholonomic motion planning as they provide reference orientation for robots. However, additionally incorporating curvature constraints becomes challenging, due to the interconnection between the design of the curvature-bounded vector field and the tracking controller under underactuation. In this paper, we present

Edoardo Bianchi

Recommender systems must balance personalization, diversity, and robustness to cold-start scenarios to remain effective in dynamic content environments. This paper introduces an adaptive, exploration-based recommendation framework that adjusts to evolving user preferences and content distributions to promote diversity and novelty without compromising relevan

Subhashree Patra, Subarna Bhattacharjee

In this work, we have taken up some distributions, mostly Weibull family, whose quantile functions could not be obtained using the traditional inversion method. We have solved the same quantile functions by using the inversion method only, with the additional help of transcendental functions like the Lambert W function. The usage of the Lambert W function ha

Beyza Cinar, Jennifer Daniel Onwuchekwa, Maria Maleshkova

Type 1 diabetes (T1D) management can be significantly enhanced through the use of predictive machine learning (ML) algorithms, which can mitigate the risk of adverse events like hypoglycemia. Hypoglycemia, characterized by blood glucose levels below 70 mg/dL, is a life-threatening condition typically caused by excessive insulin administration, missed meals,

Xin Cai

In this article, we primarily examine a variety of RL-based and RL-free methods designed to address Reinforcement Learning from Human Feedback (RLHF) and Large Reasoning Models (LRMs). We begin with a concise overview of the typical steps involved in RLHF and LRMs. Next, we reinterpret several RL-based and RL-free algorithms through the perspective of neural

Giuseppe Orlando

Exact solution of stigmatic two-reflector optical system in presence of Herschel's condition is demonstrated. Details of how the solution is calculated are reported. Ray tracing verification on different optical systems validates the obtained results.

Mario Jelitte, Boris S. Mordukhovich

Metric regularity is among the central concepts of nonlinear and variational analysis, constrained optimization, and their numerous applications. However, metric regularity can be elusive for some important ill-posed classes of problems including polynomial equations, parametric variational systems, smooth reformulations of complementarity systems with degen

Aarati Chacko, Erwin Hack, Sebastian Lohde, Robin Bucher

Titanium dioxide (TiO2) is a key material in optoelectronic and energy conversion technologies, including solar cells and photocatalysis. However, integrating TiO2 into flexible or temperature-sensitive devices requires deposition techniques that avoid high-temperature processing while maintaining control over both phase composition and crystallinity. In thi

Wenwei Gu, Renyi Zhong, Jianping Zhang, Michael R. Lyu

Adversarial attacks in time series classification (TSC) models have recently gained attention due to their potential to compromise model robustness. Imperceptibility is crucial, as adversarial examples detected by the human vision system (HVS) can render attacks ineffective. Many existing methods fail to produce high-quality imperceptible examples, often gen

Sakshi Dhankhar, Stefan Wittek, Hamidreza Eivazi, Andreas Rausch

Study Region: Goslar and G\"ottingen, Lower Saxony, Germany. Study Focus: In July 2017, the cities of Goslar and G\"ottingen experienced severe flood events characterized by short warning time of only 20 minutes, resulting in extensive regional flooding and significant damage. This highlights the critical need for a more reliable and timely flood forecasting

Michael Herrmann, Guillaume James, Karsten Matthies

In a dissipative Fermi-Pasta-Ulam-Tsingou chain particles interact with their nearest neighbors through anharmonic potentials and linear dissipative forces. We prove the existence of front solutions connecting two different uniformly compressed (or stretched) states at $\pm \infty$ using an implicit function argument starting at a suitable continuum limit in

Stefano Bo, Lars Hubatsch, Frank Jülicher

Biomolecular condensates provide distinct chemical environments, which control various cellular processes. The diffusive dynamics and chemical kinetics inside phase-separated condensates can be studied experimentally by fluorescently labeling molecules, providing key insights into cell biology. We discuss how condensates govern the kinetics of chemical react

Liming Zheng, Feng Yan, Fanfan Liu, Chengjian Feng

The growing adoption of Vision-Language-Action (VLA) models in embodied AI intensifies the demand for diverse manipulation demonstrations. However, high costs associated with data collection often result in insufficient data coverage across all scenarios, which limits the performance of the models. It is observed that the spatial reasoning phase (SRP) in lar

Monica Billio, Roberto Casarin, Fausto Corradin, Antonio Peruzzi

Anomalies in economic and financial data -- often linked to rare yet impactful events -- are of theoretical interest, but can also severely distort inference. Although outlier-robust methodologies can be used, many researchers prefer pre-processing strategies that remove outliers. In this work, an efficient sequential Bayesian framework is proposed for outli

Ho Ka Chan, Taro Toyoizumi

People frequently deviate from classical utility theories when making risky and intertemporal decisions. While the effects of risk and temporal delay have been extensively studied in isolation, their interplay and underlying theoretical basis remain debated. In this work, we extend our previously proposed anticipated surprise framework to risky intertemporal

Franz Waltenberger, Angelina Voggenreiter, Martin Paul Wessel, Juergen Pfeffer

This paper investigates the behavior of Reddit users who relied on alternative mobile apps, such as Apollo and RiF, before and after their forced shutdown by Reddit on July 1, 2023. The announcement of the shutdown led many observers to predict significant negative consequences, such as mass migration away from the platform. Using data from January to Novemb

Jie Song, Mengqiao He, Shumin Ren, Bairong Shen

Many rare genetic diseases exhibit recognizable facial phenotypes, which are often used as diagnostic clues. However, current facial phenotype diagnostic models, which are trained on image datasets, have high accuracy but often suffer from an inability to explain their predictions, which reduces physicians' confidence in the model output.In this paper, we co

Mengfei Sun, Jie Wu, Jin Li, Brendan Mccane

Gravitational waves from binary neutron star mergers provide critical insights into dense matter physics and strong-field gravity, yet accurate waveform modeling remains computationally intensive. We present a deep generative model for gravitational waveforms from binary neutron star mergers that captures the late inspiral, merger, and ringdown phases while

Ivan Penkov, Valdemar Tsanov

By a grassmannian we understand a usual complex grassmannian or possibly an orthogonal or symplectic grassmannian. We classify, with few exceptions, linear embeddings of grassmannians into larger grassmannians, where the linearity requirement is the condition that the embedding induces an isomorphism on Picard groups. This classification implies that most li

Sheng Wang

As robotic technologies advancing towards more complex multimodal interactions and manipulation tasks, the integration of advanced Vision-Language Models (VLMs) has become a key driver in the field. Despite progress with current methods, challenges persist in fusing depth and RGB information within 3D environments and executing tasks guided by linguistic ins

Reznichenko Evgenii

It is proved that if some boundary $B$ of a convex compact subset $X$ of a locally convex linear space has a countable network, then the convex compact space $X$ is metrizable. If the boundary $B$ is a Lindelof $\Sigma$-space, then the network weight $nw(B)$ of $B$ coincides with the weight $w(K)$ of $K$.

Kartik Jangra, Aman Kumar Singh, Yashwani Mann, Geetanjali Rathee

Recent advancements in vision-language models have achieved remarkable results in making language models understand vision inputs. However, a unified approach to align these models across diverse tasks such as image captioning and visual question answering remains a challenge. Existing methods either require very big language models or very big datasets whic

A. Krämer-Flecken, X. Han, G. Weir, T. Windisch

The estimation of the poloidal velocity of the turbulence and the poloidal mean flow velocity are important quantities for the study of sheared flows on turbulence and transport. The estimation depends on the underlying model of the turbulence. Beside the propagation time of the turbulence, its decay with the fading time must be considered. For the descripti

Yongxin Ma, Jie Xu, Shenghai Yuan, Tian Zhi

SLAM plays a crucial role in automation tasks, such as warehouse logistics, healthcare robotics, and restaurant delivery. These scenes come with various challenges, including navigating around crowds of people, dealing with flying plastic bags that can temporarily blind sensors, and addressing reduced LiDAR density caused by cooking smoke. Such scenarios can

Xiaohui Sun, Jiangwei Mo, Hanlin Wu, Jie Ma

Recent advancements in diffusion models (DMs) have greatly advanced remote sensing image super-resolution (RSISR). However, their iterative sampling processes often result in slow inference speeds, limiting their application in real-time tasks. To address this challenge, we propose the latent consistency model for super-resolution (LCMSR), a novel single-ste

Eméric Gbaguidi

Stochastic coordinate descent algorithms are efficient methods in which each iterate is obtained by fixing most coordinates at their values from the current iteration, and approximately minimizing the objective with respect to the remaining coordinates. However, this approach is usually restricted to canonical basis vectors of $\mathbb{R}^d$. In this paper,

Osmar M. Guerra-Alvarado, Nienke van der Marel, Jonathan P. Williams, Paola Pinilla

Most of the exoplanets discovered in our galaxy to date orbit low-mass stars, which tend to host small disks in their early stages. To better elucidate the link between planet formation and disk substructures, observational biases should be reduced through observations of these small, faint disks at the highest resolution using the Atacama Large Millimeter A

Jiahao Qin, Feng Liu, Lu Zong

Multimodal sentiment analysis has emerged as a critical tool for understanding human emotions across diverse communication channels. While existing methods have made significant strides, they often struggle to effectively differentiate and integrate modality-shared and modality-specific information, limiting the performance of multimodal learning. To address

Juncen Guo, Xiaoguang Zhu, Liangyu Teng, Hao Yang

Class-incremental Learning (CIL) enables the model to incrementally absorb knowledge from new classes and build a generic classifier across all previously encountered classes. When the model optimizes with new classes, the knowledge of previous classes is inevitably erased, leading to catastrophic forgetting. Addressing this challenge requires making a trade

Qi Chen, Yinghao Cui, Guobin Hong, Karumuri Ashok

El Ni\~no-Southern Oscillation (ENSO) is a prominent mode of interannual climate variability with far-reaching global impacts. Its evolution is governed by intricate air-sea interactions, posing significant challenges for long-term prediction. In this study, we introduce CTEFNet, a multivariate deep learning model that synergizes convolutional neural network

Lizao Ye

We extend to nilpotent orbits the notion of chiral Hecke algebra introduced by Beilinson-Drinfeld. Upon analysing their isotypic components, we produce many new modules over simple affine vertex algebras at non-admissible integer levels, as well as their ways of fusion.

Yaofei Wang, Gang Pei, Kejiang Chen, Jinyang Ding

Steganography embeds confidential data within seemingly innocuous communications. Provable security in steganography, a long-sought goal, has become feasible with deep generative models. However, existing methods face a critical trade-off between security and efficiency. This paper introduces SparSamp, an efficient provably secure steganography method based

Steven Louis, Hannah Bradley, Vasyl Tyberkevych

Dynamics of a ferromagnetic macrospin (e.g., a free layer of a magnetic tunnel junction (MTJ)) can be described in terms of equivalent capacitor charge $Q$ and inductor flux $\Phi$, in a manner similar to a standard electric LC circuit, but with strongly nonlinear and coupled capacitance and inductance. This description allows for the inclusion of Gilbert da

Yujing Lu, Ling Zhong, Jing Yang, Weiming Li

Chart Question Answering (CQA) evaluates Multimodal Large Language Models (MLLMs) on visual understanding and reasoning over chart data. However, existing benchmarks mostly test surface-level parsing, such as reading labels and legends, while overlooking deeper scientific reasoning. We propose DomainCQA, a framework for constructing domain-specific CQA bench

Le Mau Hai, Pham Hoang Hiep, Trinh Tung

In this paper, we introduce the notion of strong locally irreducible complex spaces $\widetilde{X}$. Based on this notion we prove the equality $\bar{\nu}_{\varphi}(x)=$ mult$(\widetilde{X},x). \nu_{\varphi}(x)$ for all $x\in \widetilde{X}$, where $\bar{\nu}_{\varphi}(x)$ is the projective mass of a plurisubharmonic function $\varphi$ at $x$ and mult$(\widet

Mohammad Daffa Robani, Paul Saves, Pramudita Satria Palar, Lavi Rizki Zuhal

Surrogate models are of high interest for many engineering applications, serving as cheap-to-evaluate time-efficient approximations of black-box functions to help engineers and practitioners make decisions and understand complex systems. As such, the need for explainability methods is rising and many studies have been performed to facilitate knowledge discov

Stefano Della Fiore, Alessandro Gnutti, Marco Dalai, Pierangelo Migliorati

Traditional image compression methods aim to reconstruct images for human perception, prioritizing visual fidelity over task relevance. In contrast, Coding for Machines focuses on preserving information essential for automated understanding. Building on this principle, we present an end-to-end compression framework that retains text-specific features for Opt

R. Xu, W. Sheng, F. Zhou, B. N. J. Persson

This paper presents a comprehensive review of wear mechanisms, with a primary focus on rubber wear under sliding conditions. Beginning with classical wear theories, including the Archard and Rabinowicz models, we analyze their applicability to both metals and elastomers and discuss extensions relevant to elastic contact and multiscale surface roughness. Vari

Yiyin Cao, Chuangyin Dang

Sequential equilibrium requires a consistent assessment and sequential rationality, where the consistent assessment emerges from a convergent sequence of totally mixed behavioral strategies and associated beliefs. However, the original definition lacks explicit guidance on constructing such convergent sequences. To overcome this difficulty, this paper presen

Shigeki Sugimoto, Taichi Tsukamoto

We study the energy-momentum tensor of a baryon in a top-down holographic QCD. In holographic QCD, the baryons are represented as solitons in a 5-dimensional gauge theory. We obtain the soliton solution by solving the equations of motion numerically. Using this result, the energy-momentum tensor and related quantities such as the mass, mean square radii, and

Seunguk Song, Dhiren K. Pradhan, Zekun Hu, Yinuo Zhang

The discovery of wurtzite ferroelectrics opens new frontiers in polar materials, yet their behavior at cryogenic temperatures remains unexplored. Here, we reveal unprecedented ferroelectric properties in ultrathin (10 nm) Al$_{0.68}$Sc$_{0.32}$N (AlScN) at cryogenic temperatures where the properties are fundamentally distinct from those of conventional oxide

Selene Sachero, Richard Waltrich, Emilio Corte, Sviatoslav Ditalia Tchernij

Solid state quantum emitters, in particular group-IV vacancy centers in diamond, are at the forefront of research in quantum technologies due to their unique optical and spin properties. Reduction of the diamond host size to the nanoscale enables new opportunities in terms of integration and scalability. However, creating optically coherent quantum emitters

Jing Gao, Xueliang Li

A theta graph $\theta_{r,p,q}$ is the graph obtained by connecting two distinct vertices with three internally disjoint paths of length $r,p,q$, where $q\geq p\geq r\geq1$ and $p\geq2$. A graph is $\theta_{r,p,q}$-free if it does not contain $\theta_{r,p,q}$ as a subgraph. The maximum spectral radius of $\theta_{1,p,q}$-free graphs with given size has been d

Jiguang Li, Jacek Bieroń, Michel Godefroid, Per Jönsson

The multiconfiguration Dirac-Hartree-Fock method implemented in the Grasp2018 package was employed to calculate the magnetic dipole hyperfine interaction constants and electric field gradients of levels in the ground configuration of the neutral bismuth atom. Combining the calculated electric field gradient of the ground state with the measured electric quad

Huan Ding, Liu Liu, Xinghui Zhong

In this paper, we develop an asymptotic-preserving and positivity-preserving discontinuous Galerkin (DG) method for solving the semiconductor Boltzmann equation in the diffusive scaling. We first formulate the diffusive relaxation system based on the even-odd decomposition method, which allows us to split into one relaxation step and one transport step. We a

Zhengwentai Sun, Chenghong Li, Hongjie Liao, Xihe Yang

Achieving fine-grained controllability in human image synthesis is a long-standing challenge in computer vision. Existing methods primarily focus on either facial synthesis or near-frontal body generation, with limited ability to simultaneously control key factors such as viewpoint, pose, clothing, and identity in a disentangled manner. In this paper, we int

Alexandre Didier, Melanie N. Zeilinger

We present an optimisation-based approach to ensure robust asymptotic stability stability of a desired set in the state space of nonlinear dynamical systems, while optimising a general control objective. The approach relies on the decrease of a robust predictive control barrier function (PCBF), which is defined as the optimal value function of a slack minimi

Zhe Sun, Pengfei Tian, Xiaozhu Hu, Xiaoyu Zhao

In the pursuit of realizing artificial general intelligence (AGI), the importance of embodied artificial intelligence (AI) becomes increasingly apparent. Following this trend, research integrating robots with AGI has become prominent. As various kinds of embodiments have been designed, adaptability to diverse embodiments will become important to AGI. We intr