March 2025 arXiv papers — page 3

Yuval Grossman, Bingrong Yu, Siyu Zhou

Axions can naturally be very light due to the protection of an (approximate) shift symmetry. Because of their pseudoscalar nature, the long-range force mediated by the axion at tree level is spin dependent, which cannot lead to observable effects between two unpolarized macroscopic objects. At the one-loop level, however, the exchange of two axions does medi

D. O'Ryan, B. D. Simmons, A. L. Faisst, I. L. Garland

Galaxy interaction and merging have clear effects on the systems involved. We find an increase in the star formation rate (SFR), potential ignition of active galactic nuclei (AGN) and significant morphology changes. However, at what stage during interactions or mergers these changes begin to occur remains an open question. With a combination of machine learn

Brij Mohan, Bijay Kumar Agarwalla, Manabendra Nath Bera

Conventional autonomous quantum refrigerators rely on uncorrelated heat exchange between the working system and baths via two-body interactions enabled by single-photon transitions and positive-temperature work baths, inherently limiting their cooling performance. Here, we introduce distinct qutrit refrigerators that exploit correlated heat transfer via two-

Yacine Mehtar-Tani, Felix Ringer, Balbeer Singh, Varun Vaidya

We derive a factorization formula for inclusive jet production in heavy-ion collisions using the tools of Effective Field Theory (EFT). We show how physics at widely separated scales in this process can be systematically separated by matching to EFTs at successively lower virtualities. Owing to a strong scale separation, we recover a vacuum-like DGLAP evolut

Fernando Arias-Aragón, Giovanni Grilli di Cortona, Enrico Nardi, Léo Veissière

Due to Heisenberg's uncertainty principle, atomic electrons localized around the nucleus exhibit a characteristic momentum distribution that, in elements with high atomic number, remains significant up to relativistic values. Consequently, in fixed-target experiments, atoms can effectively act as electron accelerators, increasing the centre-of-mass energy in

Diptarka Das, Sumit R. Das, Arnab Kundu, Krishnendu Sengupta

This paper investigates the dynamical phases of Floquet Conformal Field Theories (CFTs) in space-time dimensions greater than two. Building upon our previous work [1] which introduced quaternionic representations for studying Floquet dynamics in higher dimensional CFTs, we now explore more general square pulse drive protocols that go beyond a single SU(1,1)

Tal Wasserman, Nir Sapir, Peter Szabo, Eli Waxman

Observations indicate that optically thick circum-stellar medium (CSM) at radii of $10^{14}-10^{15}~$cm around Type II core-collapse supernovae (SN) progenitors is common (and may be present in other types of massive star explosions). The breakout of the SN radiation-mediated shock (RMS) through such CSM leads to the formation of a collisionless shock (CLS).

N. Gupta, J. Kerp, S. A. Balashev, A. P. M. Morelli

We present results of a blind search for Galactic HI 21-cm absorption lines toward 19130 radio sources, using 390 pointings of MALS, each pointing centered on a source brighter than 200 mJy. We detected 3640 HI absorption features. This represents the largest Galactic HI absorption line catalog to date. Based on the strong correlation between the HI 21-cm em

Wissam Chemissany, Elliott Gesteau, Alexander Jahn, Daniel Murphy

We initiate a study of local operator algebras at the boundary of infinite tensor networks, using the mathematical theory of inductive limits. In particular, we consider tensor networks in which each layer acts as a quantum code with complementary recovery, a property that features prominently in the bulk-to-boundary maps intrinsic to holographic quantum err

Junli Li, Jun-Qing Cheng, Trinanjan Datta, Dao-Xin Yao

We investigate the spin dynamics of a 1D spin-1/2 Heisenberg tetramer chain. Employing a combination of Density Matrix Renormalization Group, quantum renormalization group, and perturbation theory techniques, we compute the energy levels and the quantum phase diagram, analyze the phase transitions, and evaluate the $L$ and $K$ -edge resonant inelastic x-ray

H. Mamann, T. Nieddu, F. Hoffet, M. Bozzio

Developments in scalable quantum networks rely critically on optical quantum memories, which are key components enabling the storage of quantum information. These memories play a pivotal role for entanglement distribution and long-distance quantum communication, with remarkable advances achieved in this context. However, optical memories have broader applica

Catherine Zucker, Seth Redfield, Sara Starecheski, Ralf Konietzka

The interstellar medium within $\rm\approx 15 \; pc$ of the Sun consists of a complex of fifteen diffuse, partially ionized clouds. Located within the Local Bubble, these clouds, known as the Cluster of Local Interstellar Clouds (CLIC), constitute the interstellar environment impinging upon our heliosphere. While each individual cloud can be modeled with a d

Oscar Wistemar, Felix Ryde, Filip Alamaa

The properties of gamma-ray bursts (GRBs) that are inferred from observations depend on the value of the bulk Lorentz factor, $\Gamma$. Consequently, accurately estimating it is an important aim. In this work, we present a method of measuring $\Gamma$ based on observed photospheric emission, which can also be used for highly dissipative flows that may lead t

Richard J. Tong, Marina Cortês, Jeanine A. DeFalco, Mark Underwood

Generative Artificial Intelligence (AI) is enabling unprecedented automation in content creation and decision support, but it also raises novel risks. This paper presents a first-principles risk assessment framework underlying the IEEE P3396 Recommended Practice for AI Risk, Safety, Trustworthiness, and Responsibility. We distinguish between process risks (r

Zsofi Igo, Andrea Merloni

[abridged] AGN feedback is a crucial ingredient for understanding galaxy evolution. However, a complete quantitative time-dependent framework, including the dependence of such feedback on AGN, host galaxy, and host halo properties, is yet to be developed. Using the complete sample of 682 radio AGN from the LOFAR-eFEDS survey ($z<0.4$), we derive the average

Houjun Zhang, Dajun Liu, Yu-Zhe Liu

In this paper, we give a description of the self-injective dimension of string algebras and obtain a necessary and sufficient condition for a string algebra to be Gorenstein.

J. R. Rocha, H. B. Câmara, F. R. Joaquim

We consider a Dine-Fischler-Srednicki-Zhitnitsky (DFSZ) axion model extended with two right-handed neutrino fields to realize the minimal type-I seesaw. In this $\nu$DFSZ scheme we systematically determine the simplest quark and lepton flavor patterns compatible with masses, mixing and charge-parity violation data, realized by flavored U(1) Peccei-Quinn (PQ)

Shahar Hod

Highly curved spacetimes of compact astrophysical objects are known to possess light rings (null circular geodesics) with {\it discrete} radii on which massless particles can perform closed circular motions. In the present compact paper, we reveal for the first time the existence of isotropic curved spacetimes that possess light disks which are made of a {\i

Yoav Afik, Federica Fabbri, Matthew Low, Luca Marzola

Some of the most astonishing and prominent properties of Quantum Mechanics, such as entanglement and Bell nonlocality, have only been studied extensively in dedicated low-energy laboratory setups. The feasibility of these studies in the high-energy regime explored by particle colliders was only recently shown and has gathered the attention of the scientific

André Melo, Gaspard Beugnot, Fabrizio Minganti

Determining the steady state of an open quantum system is crucial for characterizing quantum devices and studying various physical phenomena. Often, computing a single steady state is insufficient, and it is necessary to explore its dependence on multiple external parameters. In such cases, calculating the steady state independently for each combination of p

Rico K. L. Lo, Leart Sabani, Vitor Cardoso

Theoretical understanding of the characteristic oscillations of a perturbed black hole, also referred to as quasinormal modes (QNMs), is crucial to interpreting the late stage of binary black hole mergers that we now routinely observe in gravitational wave detectors. In this work, we introduce a new approach, based on the generalized Sasaki-Nakamura formalis

S. Wang, M. R. Preciado Rivas, R. B. Mann

The effect of black holes on entanglement harvesting has been of considerable interest over the past decade. Research involving stationary Unruh-DeWitt (UDW) detectors near a (2+1)-dimensional Ba\~nados-Teitelboim-Zanelli (BTZ) black hole has uncovered phenomena such as entanglement shadows, entanglement amplification through black hole rotation, and differe

Greta Ettorre, Emanuele Dalessandro, Cristina Pallanca, Mario Cadelano

The dense cores of globular clusters (GCs) are efficient environments for the production of exotic stellar populations, including millisecond pulsars (MSPs), low-mass X-ray binaries (LMXBs) and cataclysmic variables (CVs). Most of these objects likely form through two- and three-body interactions and are useful tracers of the cluster's dynamical evolution. I

Lukáš Gráf, Chandan Hati, Ana Martín-Galán, Oliver Scholer

The discovery of the lepton number violation would be a smoking gun signal for physics beyond the Standard Model, and its most sensitive probe is the search for neutrinoless double beta decay ($0\nu\beta\beta$). Working in the framework of the Standard Model Effective Field Theory (SMEFT), we show that one-loop effects can remarkably improve the tree-level b

Julián Barragán Amado, Tiago V. Fernandes, David C. Lopes

We consider Proca field perturbations in a five-dimensional Schwarzschild-anti-de Sitter (Schwarzschild-AdS$_{5}$) black hole geometry. Using the vector spherical harmonic (VSH) method, we show that the Proca field decomposes into scalar-type and vector-type components according to their tensorial behavior on the three-sphere. Two degrees of freedom of the f

A. Arcusa, S. Ahyoune, K. Altenmuller, I. Antolin

The International Axion Observatory (IAXO) is a next-generation axion helioscope designed to search for solar axions with unprecedented sensitivity. IAXO holds a unique position in the global landscape of axion searches, as it will probe a region of the axion parameter space inaccessible to any other experiment. In particular, it will explore QCD axion model

Sebastian Harris, Yasuaki Hikida, Volker Schomerus, Takashi Tsuda

The study of non-local operators in gauge theory and holography, such as line-operators or interfaces, has attracted significant attention. Two-dimensional symmetric product orbifolds are close cousins of higher-dimensional gauge theory. In this work, we construct a novel family of interfaces in symmetric product orbifolds. These may be regarded as two-dimen

Ahmed Alenezi, Cari Cesarotti, Stefania Gori, Jessie Shelton

We explore the detection prospects for a minimal secluded dark matter model, where a fermionic dark matter particle interacts with the Standard Model (SM) via a kinetically mixed dark photon. We focus on scenarios where the dark photon decays visibly, making it a prime target for beam-dump experiments. In this model, the dark matter relic abundance can be ac

Xingyu Chen, Yue Chen, Yuliang Xiu, Andreas Geiger

Recent advances in DUSt3R have enabled robust estimation of dense point clouds and camera parameters of static scenes, leveraging Transformer network architectures and direct supervision on large-scale 3D datasets. In contrast, the limited scale and diversity of available 4D datasets present a major bottleneck for training a highly generalizable 4D model. Th

Andras Szabo, Aline Ramires

UTe$_2$ has been the focus of numerous experimental and theoretical studies in recent years, as it is recognized as an odd-parity bulk superconductor. Its surface has also been probed, revealing charge density wave (CDW), pair density wave (PDW), and time-reversal symmetry breaking (TRSB). In this work, we propose that the interplay between the order paramet

Chenyang Li, Wenxuan Liu, Guoqiang Gong, Xiaobo Ding

Underwater object detection is critical for oceanic research and industrial safety inspections. However, the complex optical environment and the limited resources of underwater equipment pose significant challenges to achieving high accuracy and low power consumption. To address these issues, we propose Spiking Underwater YOLO (SU-YOLO), a Spiking Neural Net

Zhonghan Zhao, Wenwei Zhang, Haian Huang, Kuikun Liu

Reasoning before action and imagining potential outcomes (i.e., world models) are essential for embodied agents operating in complex open-world environments. Yet, prior work either incorporates only one of these abilities in an end-to-end agent or integrates multiple specialized models into an agent system, limiting the learning efficiency and generalization

Lee Hsin-Ying, Kelvin C. K. Chan, Ming-Hsuan Yang

While text-to-image generative models can synthesize diverse and faithful content, subject variation across multiple generations limits their application to long-form content generation. Existing approaches require time-consuming fine-tuning, reference images for all subjects, or access to previously generated content. We introduce Contrastive Concept Instan

Konstantinos Konstantinou, Yansheng Zhang, Paul H. C. Wong, Feiyang Wang

The tendency of identical bosons to bunch, seen in the Hanbury Brown-Twiss effect and Bose-Einstein condensation, is a hallmark of quantum statistics. This bunching can enhance the rates of fundamental processes such as atom-atom and atom-light scattering when atoms scatter into already occupied states. For non-interacting bosons, the enhancement of light sc

Noah Sailer, Joseph DeRose, Simone Ferraro, Shi-Fan Chen

We use a Hybrid Effective Field Theory (HEFT) model to constrain the evolution of low-redshift $(z\lesssim0.4)$ matter fluctuations by cross-correlating DESI Bright Galaxy Survey (BGS) legacy imaging with the latest CMB lensing maps from Planck and ACT. Our tomographic BGS analysis finds that the evolution and amplitude of matter fluctuations align with CMB-

Andrew G. Sullivan, Roger W. Romani

The intrabinary shocks (IBS) of spider pulsars emit non-thermal synchrotron X-rays from accelerated electrons and positrons in the shocked pulsar wind, likely energized by magnetic reconnection. In redback spider pulsars, the IBS typically wraps around the pulsar, leading to a near-normal IBS shock with relatively bright X-ray emission. The characteristic en

Xiao Li, Yufei Wang, Ligeng Yu, Bo Song

We report laser cooling and trapping of ytterbium atoms in a two-color magneto-optical trap (MOT). Benefited from both the broad singlet transition ($^1\text{S}_0\rightarrow {}^1\text{P}_1$) and the narrow intercombination transition ($^1\text{S}_0\rightarrow {}^3\text{P}_1$) of ytterbium atoms, the two-color MOT enables rapid loading and efficient cooling.

Chong Bao, Xiyu Zhang, Zehao Yu, Jiale Shi

Neural rendering has demonstrated remarkable success in high-quality 3D neural reconstruction and novel view synthesis with dense input views and accurate poses. However, applying it to extremely sparse, unposed views in unbounded 360{\deg} scenes remains a challenging problem. In this paper, we propose a novel neural rendering framework to accomplish the un

Yuping Wang, Xiangyu Huang, Xiaokang Sun, Mingxuan Yan

We introduce UniOcc, a comprehensive, unified benchmark and toolkit for occupancy forecasting (i.e., predicting future occupancies based on historical information) and occupancy prediction (i.e., predicting current-frame occupancy from camera images. UniOcc unifies the data from multiple real-world datasets (i.e., nuScenes, Waymo) and high-fidelity driving s

Xin-Chi Zhou, Bing-Chen Yao, Yongjian Wang, Yucheng Wang

The disordered quantum systems host three classes of quantum states, the extended, localized, and critical, which bring up seven distinct fundamental phases in nature: three pure phases and four coexisting ones with mobility edges, yet a unified theory built on universal mechanism and full realization of all these phases has not been developed. Here we propo

Shengqiong Wu, Weicai Ye, Jiahao Wang, Quande Liu

To address the bottleneck of accurate user intent interpretation within the current video generation community, we present Any2Caption, a novel framework for controllable video generation under any condition. The key idea is to decouple various condition interpretation steps from the video synthesis step. By leveraging modern multimodal large language models

Anne E Blackwell, David L Moutard, Jake A Miller

The field of astronomy evolves rapidly, and it is essential to keep up with these changes in order to effectively communicate with the broader community. However, communication itself also changes as new words, phrases, and slang terms enter the common vernacular. This is especially true for the current youngest generations, who are capable of efficiently co

Harsha Kokel, Michael Katz, Kavitha Srinivas, Shirin Sohrabi

The ACPBench dataset provides atomic reasoning tasks required for efficient planning. The dataset is aimed at distilling the complex plan generation task into separate atomic reasoning tasks in their easiest possible form, boolean or multiple-choice questions, where the model has to choose the right answer from the provided options. While the aim of ACPBench

Rui Wang, Hongru Wang, Boyang Xue, Jianhui Pang

Recent advancements in Large Language Models (LLMs) have significantly enhanced their ability to perform complex reasoning tasks, transitioning from fast and intuitive thinking (System 1) to slow and deep reasoning (System 2). While System 2 reasoning improves task accuracy, it often incurs substantial computational costs due to its slow thinking nature and

Yi Chen, Yuying Ge, Rui Wang, Yixiao Ge

Recent advancements in Chain of Thought (COT) generation have significantly improved the reasoning capabilities of Large Language Models (LLMs), with reinforcement learning (RL) emerging as an effective post-training approach. Multimodal Large Language Models (MLLMs) inherit this reasoning potential but remain underexplored in tasks requiring both perception

N. Tripathi, S. W. Hancock, H. M. Milchberg

The nature of the transverse orbital angular momentum (tOAM) associated with spatiotemporal optical vortex (STOV) pulses has been the subject of recent debate. We demonstrate that the approaches to tOAM presented in several recent papers are incorrect and lead to unphysical results, including erroneous claims of zero total tOAM. We emphasize the importance o

Maxim V. Shugaev, Vincent Chen, Maxim Karrenbach, Kyle Ashley

This work addresses the problem of novel view synthesis in diverse scenes from small collections of RGB images. We propose ERUPT (Efficient Rendering with Unposed Patch Transformer) a state-of-the-art scene reconstruction model capable of efficient scene rendering using unposed imagery. We introduce patch-based querying, in contrast to existing pixel-based q

Li Chen, Andrei Graur, Aaron Sidford

We provide $m^{1+o(1)}k\epsilon^{-1}$-time algorithms for computing multiplicative $(1 - \epsilon)$-approximate solutions to multi-commodity flow problems with $k$-commodities on $m$-edge directed graphs, including concurrent multi-commodity flow and maximum multi-commodity flow. To obtain our results, we provide new optimization tools of potential independe

R. Bauerschmidt, T. Bodineau, B. Dagallier

For a class of mean-field particle systems, we formulate a criterion in terms of the free energy that implies uniform bounds on the log-Sobolev constant of the associated Langevin dynamics. For certain double-well potentials with quadratic interaction, the criterion holds up to the critical temperature of the model, and we also obtain precise asymptotics on

Tesshu Fujinami, Bruce D. Lee, Nikolai Matni, George J. Pappas

Domain randomization (DR) enables sim-to-real transfer by training controllers on a distribution of simulated environments, with the goal of achieving robust performance in the real world. Although DR is widely used in practice and is often solved using simple policy gradient (PG) methods, understanding of its theoretical guarantees remains limited. Toward a

Tong Wu, Chong Xiang, Jiachen T. Wang, G. Edward Suh

Reasoning-enhanced large language models (LLMs) explicitly generate intermediate reasoning steps prior to generating final answers, helping the model excel in complex problem-solving. In this paper, we demonstrate that this emerging generation framework offers a unique opportunity for more fine-grained control over model behavior. We propose Thinking Interve

T. W. Cruz, V. A. De Lorenci, E. Guzmán-Herrera, C. C. H. Ribeiro

Nonlinear electrodynamics has been an important area of research for a long time. Investigations based on nonlinear Lagrangians, such as Euler-Heisenberg and Born-Infeld, are instrumental in exploring the limits of classical and quantum field theories, providing valuable insights into strong-field phenomena. In this context, this work considers how light pro

Xiaoran Zhang, Eric Z. Chen, Lin Zhao, Xiao Chen

We propose a novel approach that adapts hierarchical vision foundation models for real-time ultrasound image segmentation. Existing ultrasound segmentation methods often struggle with adaptability to new tasks, relying on costly manual annotations, while real-time approaches generally fail to match state-of-the-art performance. To overcome these limitations,

Thomas C. Nicholas, Daniel F. Thomas du Toit, Louise A. M. Rosset, Davide M. Proserpio

Amorphous metal-organic frameworks are an important emerging materials class that combine the attractive physical properties of the amorphous state with the versatility of metal-organic framework (MOF) chemistry. The structures of amorphous MOFs have largely been inferred by drawing analogies to crystalline polymorphs and inorganic glasses, but ultimately th

Shakiba Kheradmand, Delio Vicini, George Kopanas, Dmitry Lagun

3D Gaussian splatting (3DGS) is a popular radiance field method, with many application-specific extensions. Most variants rely on the same core algorithm: depth-sorting of Gaussian splats then rasterizing in primitive order. This ensures correct alpha compositing, but can cause rendering artifacts due to built-in approximations. Moreover, for a fixed represe

Patrick Knab, Sascha Marton, Udo Schlegel, Christian Bartelt

As neural networks become dominant in essential systems, Explainable Artificial Intelligence (XAI) plays a crucial role in fostering trust and detecting potential misbehavior of opaque models. LIME (Local Interpretable Model-agnostic Explanations) is among the most prominent model-agnostic approaches, generating explanations by approximating the behavior of

Łukasz Borchmann, Marek Wydmuch

We propose a novel approach for generating complex outputs that significantly improves accuracy in text-to-SQL tasks. Our method leverages execution results to select the most semantically consistent query from multiple candidates, enabling smaller, cost-effective models to surpass computationally intensive reasoning methods such as o1, o3-mini, and DeepSeek

Yuxuan Sun, Weiru Fan, Xingqi Xu, Da-Wei Wang

XY models with continuous spin orientation play a pivotal role in understanding topological phase transitions and emergent frustration phenomena, such as superconducting and superfluid phase transitions. However, the complex energy landscapes arising from frustrated lattice geometries and competing spin interactions make these models computationally intracta

Lucas Ventura, Antoine Yang, Cordelia Schmid, Gül Varol

We address the task of video chaptering, i.e., partitioning a long video timeline into semantic units and generating corresponding chapter titles. While relatively underexplored, automatic chaptering has the potential to enable efficient navigation and content retrieval in long-form videos. In this paper, we achieve strong chaptering performance on hour-long

Ujun Jeong, Lynnette Hui Xian Ng, Kathleen M. Carley, Huan Liu

Decentralized online social networks have evolved from experimental stages to operating at unprecedented scale, with broader adoption and more active use than ever before. Platforms like Mastodon, Bluesky, Hive, and Nostr have seen notable growth, particularly following the wave of user migration after Twitter's acquisition in October 2022. As new platforms

Abhiram Maddukuri, Zhenyu Jiang, Lawrence Yunliang Chen, Soroush Nasiriany

Large real-world robot datasets hold great potential to train generalist robot models, but scaling real-world human data collection is time-consuming and resource-intensive. Simulation has great potential in supplementing large-scale data, especially with recent advances in generative AI and automated data generation tools that enable scalable creation of ro

Cosimo Marconcini, Alessandro Marconi, Giovanni Cresci, Filippo Mannucci

Supermassive black holes at the centre of galaxies gain mass through accretion disks. Models predict that quasi-spherical winds, expelled by the black hole during active accretion phases, have a key role in shaping galaxy evolution by regulating star formation, the distribution of metals over kiloparsec scales, and by sweeping ambient gas to the outskirts an

Hao Wang, Ligong Han, Kai Xu, Akash Srivastava

The key-value (KV) cache accelerates LLMs decoding by storing KV tensors from previously generated tokens. It reduces redundant computation at the cost of increased memory usage. To mitigate this overhead, existing approaches compress KV tensors into lower-bit representations; however, quantization errors can accumulate as more tokens are generated, potentia

Shuaizheng Liu, Jianqi Ma, Lingchen Sun, Xiangtao Kong

Despite the significant progress in diffusion prior-based image restoration, most existing methods apply uniform processing to the entire image, lacking the capability to perform region-customized image restoration according to user instructions. In this work, we propose a new framework, namely InstructRestore, to perform region-adjustable image restoration

Chao Luan, Ronald Davis, Zaijun Chen, Dirk Englund

The ever-increasing data demand craves advancements in high-speed and energy-efficient computing hardware. Analog optical neural network (ONN) processors have emerged as a promising solution, offering benefits in bandwidth and energy consumption. However, existing ONN processors exhibit limited computational parallelism, and while certain architectures achie

Sudong Wang, Yunjian Zhang, Yao Zhu, Jianing Li

Large Vision-Language Models (LVLMs) are gradually becoming the foundation for many artificial intelligence applications. However, understanding their internal working mechanisms has continued to puzzle researchers, which in turn limits the further enhancement of their capabilities. In this paper, we seek to investigate how multimodal knowledge evolves and e

Spyros Basilakos, Andreas Lymperis, Maria Petronikolou, Emmanuel N. Saridakis

In this work we apply the gravity-thermodynamics approach for the case of generalized mass-to-horizon entropy, which is a two-parameter extension of Bekenstein-Hawking entropy that arises from the extended mass-to-horizon relation, that is in turn required in order to have consistency with the Clausius relation. We extract the modified Friedmann equations an

Rana Muhammad Shahroz Khan, Dongwen Tang, Pingzhi Li, Kai Wang

Parameter generation has emerged as a novel paradigm for neural network development, offering an alternative to traditional neural network training by synthesizing high-quality model weights directly. In the context of Low-Rank Adaptation (LoRA) for evolving ($\textit{i.e.}$, constantly updated) large language models (LLMs), this approach promises efficient

Yuya Kusuki, Hirosi Ooguri, Sridip Pal

We use the thermal effective theory to prove that, for the vacuum state in any conformal field theory in $d$ dimensions, the $n$-th R\'enyi entropy $S_A^{(n)}$ behaves as $S_A^{(n)} = \frac{f}{(2\pi n)^{d-1}} \frac{ {\rm Area}(\partial A)}{(d-2)\epsilon^{d-2}}\left(1+O(n)\right)$ in the $n \rightarrow 0$ limit when the boundary of the entanglement domain $A$

Brian Bockelman, Rahul Chauhan, Diego Ciangottini, Dave Dykstra

Within the LHC community, a momentous transition has been occurring in authorization. For nearly 20 years, services within the Worldwide LHC Computing Grid (WLCG) have authorized based on mapping an identity, derived from an X.509 credential, or a group/role, derived from a VOMS extension issued by the experiment. A fundamental shift is occurring to capabili

Siddharth Iyer

We prove a sensitivity-to-communication lifting theorem for arbitrary gadgets. Given functions $f: \{0,1\}^n\to \{0,1\}$ and $g : \mathcal X\times \mathcal Y\to \{0,1\}$, denote $f\circ g(x,y) := f(g(x_1,y_1),\ldots,g(x_n,y_n))$. We show that for any $f$ with sensitivity $s$ and any $g$, \[D(f\circ g) \geq s\cdot \bigg(\frac{\Omega(D(g))}{\log\mathsf{rk}(g)}

Sanjay Chakraborty, Fredrik Heintz

This paper introduces FANTF (Fuzzy Attention Network-Based Transformers), a novel approach that integrates fuzzy logic with existing transformer architectures to advance time series forecasting, classification, and anomaly detection tasks. FANTF leverages a proposed fuzzy attention mechanism incorporating fuzzy membership functions to handle uncertainty and

Xiao-Gang He, Chia-Wei Liu, Jusak Tandean

The LHCb Collaboration has recently found a large CP-violating rate asymmetry in the $b$-baryon decay $\Lambda^0_b \to pK^-\pi^+\pi^-$. This is the first observation of CP violation in baryon processes, opening a new window to test its standard model origin. Many more baryon decays are expected to exhibit observable signals of CP violation. We show that ther

Md Shafiullah Shafin, Md Fazle Rabbi, S. M. Mahedy Hasan, Minhaz F. Zibran

In modern software ecosystems, dependency management plays a critical role in ensuring secure and maintainable applications. However, understanding the relationship between release practices and their impact on vulnerabilities and update cycles remains a challenge. In this study, we analyze the release histories of 10,000 Maven artifacts, covering over 203,0

Zhong-Bo Kang, Robert Kao, Meijian Li, Jani Penttala

We study the transverse energy--energy correlator (TEEC) observable in photon--hadron and photon--jet production in p+p and p+A collisions at small $x$. We derive the relevant expressions in the high-energy limit of the scattering where the dipole picture is applicable and show how the dependence on the fragmentation function of the hadron cancels due to the

Daria Rudneva, Eddy Ardonne

We study the unitarity and modularity of ribbon tensor categories derived from simple affine Lie algebras, via their associated quantum groups. Based on numerical calculations, and assuming two conjectures, we provide the complete picture for which values of $q$ these ribbon tensor categories are (pseudo-)unitary and for which values of $q$ they are modular.

Leonardo Oleynik, Junaid ur Rehman, Seid Koudia, Symeon Chatzinotas

Entanglement distribution is essential for unlocking the potential of distributed quantum information processing. We consider an $N$-partite network where entanglement is distributed via a central source over lossy channels, and network participants cooperate to establish entanglement between any two chosen parties under local operations and classical commun

The ATLAS Collaboration, Belle II Collaboration, CMS Collaboration, LHCb Collaboration

Precision studies of flavour-changing processes involving quarks and leptons provide a number of ways to improve knowledge of the Standard Model and search for physics beyond it. There are excellent short- and mid-term prospects for significantly improved measurements in heavy flavour physics (involving b and c hadrons and $\tau$ leptons), with upgrades in p

Fang Yan, Jianfeng Wu, Jiawen Li, Wei Wang

The complexity and variability inherent in high-resolution pathological images present significant challenges in computational pathology. While pathology foundation models leveraging AI have catalyzed transformative advancements, their development demands large-scale datasets, considerable storage capacity, and substantial computational resources. Furthermor

Nishchhal Verma, Raquel Queiroz

The discovery of correlated states in moire materials has challenged the established methods of projecting interactions into a local Wannier basis due to topological obstructions that manifest in extended interactions. This difficulty can sometimes be evaded by decomposing the band into a basis of extended itinerant states and a lattice of local states, usin

E. Chaussidon, M. White, A. de Mattia, R. Gsponer

Recently the Dark Energy Spectroscopic Instrument (DESI) provided constraints on the expansion history from their Data Release 2 (DR2). The DESI baryon acoustic oscillation (BAO) measurements are well described by a flat $\Lambda$CDM model, but the preferred parameters are in mild ($2.3\sigma$) tension with those determined from the cosmic microwave backgrou

Eli Brock, Jingqi Li, Javad Lavaei, Somayeh Sojoudi

We propose a real-time nodal pricing mechanism for cost minimization and voltage control in a distribution network with autonomous distributed energy resources and analyze the resulting market using stochastic game theory. Unlike existing methods, the proposed pricing scheme does not require device-aware centralized coordination or communication between pros

Sarah K. Mann, Angus Cowley-Semple, Emma Bryan, Ziqiu Huang

Optical detection of magnetic resonance enables spin-based quantum sensing with high spatial resolution and sensitivity-even at room temperature-as exemplified by solid-state defects. Molecular systems provide a complementary, chemically tunable, platform for room-temperature optically detected magnetic resonance (ODMR)-based quantum sensing. A critical para

Ashkan Soleymani, Georgios Piliouras, Gabriele Farina

We establish the first uncoupled learning algorithm that attains $O(n \log^2 d \log T)$ per-player regret in multi-player general-sum games, where $n$ is the number of players, $d$ is the number of actions available to each player, and $T$ is the number of repetitions of the game. Our results exponentially improve the dependence on $d$ compared to the $O(n\,

Amir Sivan, Milan Šindelka, Meir Orenstein, Nimrod Moiseyev

We demonstrate that calculating the spontaneous emission decay rate from metastable resonance states (states with finite lifetimes embedded in the continuum) requires considering transitions to all continuum states, not just to lower states. This holds even when the lifetimes of the metastable states are very long and might be effectively considered as bound

Sanjay Chakraborty, Fredrik Heintz

QCAAPatchTF is a quantum attention network integrated with an advanced patch-based transformer, designed for multivariate time series forecasting, classification, and anomaly detection. Leveraging quantum superpositions, entanglement, and variational quantum eigensolver principles, the model introduces a quantum-classical hybrid self-attention mechanism to c

Maria Andrade, Valter Borges, Hiuri Reis

In this paper, we study $n$-dimensional gradient $\rho$-Einstein solitons whose Bach tensor is radially nonnegative. Under this assumption, we show that such $\rho$-Einstein solitons are locally warped products of an interval and an Einstein manifold, provided either $\rho\neq0$ or $\rho=0$ and the soliton is rectifiable. We obtain as a consequence that thes

Arturo Arroyo-Castro, Ignazio Scimemi, Alexey Vladimirov

The transverse momentum dependent (TMD) factorization theorem accommodates various types of power corrections. Among them, the least studied are qT/Q corrections, which become significant at large values of transverse momentum. These corrections partially originate from higher-twist TMD distributions, which exhibit singularity at small transverse distances.

Viachaslau I. Murashka, Alexander F. Vasil'ev

For a finite group $G$ and its maximal subgroup $M$ we proved that the generalized Fitting height of $M$ can't be less by 2 than the generalized Fitting height of $G$ and the non-$p$-soluble length of $M$ can't be less by 1 than the non-$p$-soluble length of $G$. We constructed a hereditary saturated formation $\mathfrak{F}$ such that $\{n_\sigma(G, \mathfra

Alexa Siu, Raymond Fok

As Generative AI (GenAI) capabilities expand, understanding how to preserve and develop human expertise while leveraging AI's benefits becomes increasingly critical. Through empirical studies in two contexts -- survey article authoring in scholarly research and business document sensemaking -- we examine how domain expertise shapes patterns of AI delegation

Arturo Berrones Santos, Gerardo Palafox Castillo, Sareé González Huesca, Carlos Alberto Aldana Sandoval

Theoretical arguments and empirical evidence for the emergence of macroscopic epidemic type behavior, in the form of Susceptible-Infected-Susceptible (SIS) or Susceptible-Infected-Recovered (SIR) processes in urban traffic congestion from microscopic network flows is given. Moreover, it's shown that the emergence of SIS/SIR implies a relationship between tra

Shouvanik Chakrabarti, Dylan Herman, Jacob Watkins, Enrico Fontana

We explore the potential for quantum speedups in convex optimization using discrete simulations of the Quantum Hamiltonian Descent (QHD) framework, as proposed by Leng et al., and establish the first rigorous query complexity bounds. We develop enhanced analyses for quantum simulation of Schr\"odinger operators with black-box potential via the pseudo-spectra

Keshav Das Agarwal, Tanoy Kanti Konar, Leela Ganesh Chandra Lakkaraju, Aditi Sen De

The non-Hermitian transverse $XY$ model with Kaplan-Shekhtman-Entin-Wohlman-Aharony (KSEA) interaction having $\mathcal{RT}$-symmetry, referred to as $iKSEA$ model, possesses both an exceptional point at which eigenvectors coalesce and a quantum critical point where gap-closing occurs. To precisely estimate the magnetic field of the system, we prove that the

Daniel Molpeceres, Sirui Lu, J. Ignacio Cirac, Barbara Kraus

Preparation of low-energy quantum many-body states has a wide range of applications in quantum information processing and condensed matter physics. Quantum cooling algorithms offer a promising alternative to other methods based, for instance, on variational and adiabatic principles, or on dissipative state preparation. In this work, we investigate a set of c

Rongxuan Li

The graph matching problem is a significant special case of the Quadratic Assignment Problem, with extensive applications in pattern recognition, computer vision, protein alignments and related fields. As the problem is NP-hard, relaxation and regularization techniques are frequently employed to improve tractability. However, most existing regularization ter

Hang Yu, Wei Wei, Zheng Tan, Jing-lei Liu

To reduce the human intervention in the preference measure process,this article proposes a preference collaborative measure framework based on an updated belief system,which is also capable of improving the accuracy and efficiency of preferen-ce measure algorithms.Firstly,the distance of rules and the average internal distance of rulesets are proposed for sp

Paramita Dutta

This article reviews recent advances in low-temperature electronic thermal transport properties of thermally biased superconductor heterostructures focusing on the two-terminal transport. Since the last decade, ferromagnetism has been widely used to enhance the thermoelectricity in heterostructures based on ordinary superconductors. The possibility of gettin

Rupert Polley, Sai Vignesh Abishek Deenadayalan, J. Marius Zöllner

Deep neural networks for aerial image segmentation require large amounts of labeled data, but high-quality aerial datasets with precise annotations are scarce and costly to produce. To address this limitation, we propose a self-supervised pretraining method that improves segmentation performance while reducing reliance on labeled data. Our approach uses inpa

Daniel Garces, Stephanie Gil

We consider a multi-robot setting, where we have a fleet of multi-capacity autonomous robots that must service spatially distributed pickup-and-delivery requests with fixed maximum wait times. Requests can be either scheduled ahead of time or they can enter the system in real-time. In this setting, stability for a routing policy is defined as the cost of the

Sourish Das, Sudeep Shukla, Abbinav Sankar Kailasam, Anish Rai

Agricultural price volatility, driven by market dynamics and meteorological factors such as temperature and precipitation, poses challenges for sustainable finance, planning, and policy. This study analyzes the impact of climate on crop price volatility for soybean in Madhya Pradesh (India) and Illinois (US), rice in Assam (India), wheat in North Dakota (US)