March 2025 arXiv papers — page 47

Diana P. L. Aude Craik

This paper proposes a scheme to measure atomic parity violation (APV) in barium ions at <0.1% precision. The scheme is based on using multi-ion entangled states to common-mode reject parity-conserving systematic shifts and selectively detect a parity-violating vector light shift. This measurement protocol eliminates the need to suppress a leading systematic

Tristan L. Smith, Nils Schöneberg

Ever since the Planck satellite measured the the cosmic microwave background (CMB) down to arcminute angular scales, the mismatch between the CMB-inferred value of the Hubble constant and the value inferred from the distance ladder (i.e., the Hubble tension) has been a growing concern and is currently at the $\sim 6 \sigma$ level. There are a handful of prop

Yimeng Min, Carla P. Gomes

We introduce PLUME search, a data-driven framework that enhances search efficiency in combinatorial optimization through unsupervised learning. Unlike supervised or reinforcement learning, PLUME search learns directly from problem instances using a permutation-based loss with a non-autoregressive approach. We evaluate its performance on the quadratic assignm

Jonathan Sauder, Viktor Domazetoski, Guilhem Banc-Prandi, Gabriela Perna

Coral reefs are declining worldwide due to climate change and local stressors. To inform effective conservation or restoration, monitoring at the highest possible spatial and temporal resolution is necessary. Conventional coral reef surveying methods are limited in scalability due to their reliance on expert labor time, motivating the use of computer vision

Karthekeyan Chandrasekaran, Chandra Chekuri, Weihao Zhu

Finding the maximum number of disjoint spanning trees in a given graph is a well-studied problem with several applications and connections. The Tutte-Nash-Williams theorem provides a min-max relation for this problem which also extends to disjoint bases in a matroid and leads to efficient algorithms. Several other packing problems such as element disjoint St

Riccardo Lasagni Manghi, Marco Zannoni, Edoardo Gramigna, Paolo Tortora

This paper outlines the Radio Science Experiment (RSE) proposed for the RAMSES mission to asteroid (99942) Apophis, which will undergo a close Earth encounter in April 2029. This event provides a unique opportunity to study the asteroid's physical and dynamical changes under strong tidal forces. The experiment leverages a combination of Earth-based radiometr

Luyao Zhang, Fabo Feng, Yicheng Rui, Guang-Yao Xiao

Accurate measurements of stellar positions and velocities are crucial for studying galactic and stellar dynamics. We aim to create a Cartesian catalog from Gaia DR3 to serve as a high-precision database for further research using stellar coordinates and velocities. To avoid the negative parallax values, we select 31,129,169 sources in Gaia DR3 with radial ve

Yimeng Min, Carla P. Gomes

We propose an unsupervised approach for learning vertex orderings for the maximum clique problem by framing it within a permutation-based framework. We transform the combinatorial constraints into geometric relationships such that the ordering of vertices aligns with the clique structures. By integrating this clique-oriented ordering into branch-and-bound se

Volodymyr Denysenko, Marek Balcerzak, Artur Dabrowski

This paper describes extension of the Master Stability Function for arrays of non-smooth oscillators. This extension is based on the previously introduced Jacobi matrix estimation method, which can be applied to networks of non-smooth coupled oscillators. Proposed method and its limitations were described. Then the new algorithm was applied to calculate MSF

James Dallas, John Talbot, Makoto Suminaka, Michael Thompson

This manuscript presents a control barrier function based approach to shared control for preventing a vehicle from entering the part of the state space where it is unrecoverable. The maximal phase recoverable ellipse is presented as a safe set in the sideslip angle--yaw rate phase plane where the vehicle's state can be maintained. An exponential control barr

CMS Collaboration

Energy-energy correlators are constructed by averaging the number of charged particle pairs within jets, weighted by the product of their transverse momenta, as a function of the angular separation of the particles within a pair. They are sensitive to a multitude of perturbative and nonperturbative quantum chromodynamics phenomena in high-energy particle col

Kris Wain, Debra P Ritzwoller, Marcelo Coca Perraillon

Health plan deductibles are a form of cost-sharing that require patients to pay out-of-pocket before insurance pays for benefits. Deductible plans have become increasingly common in the United Sates to mitigate escalating healthcare costs. Quantifying the impact of increased cost-sharing from deductibles on utilization is a challenging empirical question bec

Maxime Bouscary, Jiawei Zhang, Saurabh Amin

Contextual Stochastic Bilevel Optimization (CSBO) extends standard stochastic bilevel optimization (SBO) by incorporating context-dependent lower-level problems. CSBO problems are generally intractable since existing methods require solving a distinct lower-level problem for each sampled context, resulting in prohibitive sample and computational complexity,

Kexian Tang, Junyao Gao, Yanhong Zeng, Haodong Duan

Many real-world applications of spatial intelligence, such as robotic control, autonomous driving, and automated assembly, require spatial reasoning across multiple sequential steps. However, the extent to which current Multimodal Large Language Models (MLLMs) possess this capability remains largely unexplored. Inspired by LEGO construction, a recreational a

Zhangcheng Qiang, Kerry Taylor, Weiqing Wang, Jing Jiang

Hallucinations are often inevitable in downstream tasks using large language models (LLMs). To tackle the substantial challenge of addressing hallucinations for LLM-based ontology matching (OM) systems, we introduce a new benchmark dataset OAEI-LLM-T. The dataset evolves from seven TBox datasets in the Ontology Alignment Evaluation Initiative (OAEI), capturi

Bohan Zhai, Canwen Xu, Yuxiong He, Zhewei Yao

Text-to-SQL demands precise reasoning to convert natural language questions into structured queries. While large language models (LLMs) excel in many reasoning tasks, their ability to leverage Chain-of-Thought (CoT) reasoning for text-to-SQL remains underexplored. We identify critical limitations: zero-shot CoT offers minimal gains, and Direct Preference Opt

Luigi Camerano, Adolfo O. Fumega, Jose L. Lado, Alessandro Stroppa

Altermagnets provide promising platforms for unconventional magnetism, whose controllability would enable a whole new generation of spintronic devices. While a variety of bulk altermagnets have been discovered, altermagnetism in two-dimensional van der Waals materials has remained elusive. Here we demonstrate that the strained honeycomb monolayer VCl$_{3}$ i

Jianping Ye, Michel Wedel, Kunpeng Zhang

Text-to-Image Diffusion models excel at generating images from text prompts but often exhibit suboptimal alignment with content semantics, aesthetics, and human preferences. To address these limitations, this study proposes a novel parameter-efficient framework, Indirect Prompt Gradient Optimization (IPGO), for prompt-level diffusion model fine-tuning. IPGO

Ivanina Ilieva, Carsten Rockstuhl, Ivan Fernandez-Corbaton

In this work, we study the behavior of elementary electromagnetic sources, i.e., point-like electric charges and intrinsic magnetic dipoles, in the presence of homogeneous electromagnetic fields in a classical and covariant setting. We show that the respective evolution equations for both kinds of sources can be formulated using a single Lorentz-like transfo

Zahra K. Valei, Tyler N. Shendruk

Biological systems commonly combine intrinsically out-of-equilibrium active components with passive polymeric inclusions to produce unique material properties. To explore these composite systems, idealized models - such as polymers in active fluids - are essential to develop a predictive theoretical framework. We simulate a single, freely jointed passive cha

Ido Rachbuch, Sinwook Park, Yuval Katz, Touvia Miloh

This study introduces the integration of hybrid magnetic and electric actuation mechanisms to achieve advanced motion capabilities for Janus particle (JP) microrobots. We demonstrate enhanced in-plane motion control through versatile control strategies and present the concepts of interplanar transitions and 2.5-dimensional (2.5D) trajectories, enabled by mag

Uri Zvi, Shivam Mundhra, David Ovetsky, Qing Chen

Nitrogen-vacancy (NV) based quantum sensors hold great potential for real-time single-cell sensing with far-reaching applications in fundamental biology and medical diagnostics. Although highly sensitive, the mapping of quantum measurements onto cellular physiological states has remained an exceptional challenge. Here we introduce a novel quantum sensing mod

H. Abramowicz, E. Adli, F. Alharthi, M. Almanza-Soto

In this paper we review the physics opportunities at linear $e^+e^-$ colliders with a special focus on high centre-of-mass energies and beam polarisation, take a fresh look at the various accelerator technologies available or under development and, for the first time, discuss how a facility first equipped with a technology mature today could be upgraded with

Pei-Kai Huang, Jun-Xiong Chong, Cheng-Hsuan Chiang, Tzu-Hsien Chen

Face anti-spoofing (FAS) plays a pivotal role in ensuring the security and reliability of face recognition systems. With advancements in vision-language pretrained (VLP) models, recent two-class FAS techniques have leveraged the advantages of using VLP guidance, while this potential remains unexplored in one-class FAS methods. The one-class FAS focuses on le

Lipei Zhang, Rui Sun, Zhongying Deng, Yanqi Cheng

Variations in Magnetic resonance imaging (MRI) scanners and acquisition protocols cause distribution shifts that degrade reconstruction performance on unseen data. Test-time adaptation (TTA) offers a promising solution to address this discrepancies. However, previous single-shot TTA approaches are inefficient due to repeated training and suboptimal distribut

Etienne Dreyer, Eilam Gross, Dmitrii Kobylianskii, Vinicius Mikuni

We extend the Particle-flow Neural Assisted Simulations (Parnassus) framework of fast simulation and reconstruction to entire collider events. In particular, we use two generative Artificial Intelligence (genAI) tools, continuous normalizing flows and diffusion models, to create a set of reconstructed particle-flow objects conditioned on truth-level particle

Basabendu Barman, Nicolás Bernal, Javier Rubio

The transition from the end of inflation to a hot, thermal Universe, commonly referred to as (re)heating, is a critical yet often misunderstood phase in early Universe cosmology. This short review aims to provide a comprehensive, conceptually clear, and accessible introduction to the physics of (re)heating, tailored to the particle physics community. We crit

Enora Rice, Ali Marashian, Hannah Haynie, Katharina von der Wense

Cross-lingual transfer learning is an invaluable tool for overcoming data scarcity, yet selecting a suitable transfer language remains a challenge. The precise roles of linguistic typology, training data, and model architecture in transfer language choice are not fully understood. We take a holistic approach, examining how both dataset-specific and fine-grai

Thomas F. M. Spieksma, Enrico Cannizzaro

In axion electrodynamics, magnetic fields enable axion-photon mixing. Recent proposals suggest that rotating, conductive plasmas in neutron star magnetospheres could trigger axion superradiant instabilities -- an intriguing idea, given that such instabilities are typically associated with rotating black holes. In this work, we extend these investigations by

A. J. Levan, B. P. Gompertz, G. P. Smith, M. E. Ravasio

Gravitationally lensed Gamma-ray bursts (GRBs) offer critical advantages over other lensed sources. They can be detected via continuously operating detectors covering most of the sky. They offer extremely high time resolution to determine lensing delays and find short-time delays accurately. They are detectable across most of the visible Universe. However, t

Navami Kairanda, Marc Habermann, Shanthika Naik, Christian Theobalt

3D reconstruction of highly deformable surfaces (e.g. cloths) from monocular RGB videos is a challenging problem, and no solution provides a consistent and accurate recovery of fine-grained surface details. To account for the ill-posed nature of the setting, existing methods use deformation models with statistical, neural, or physical priors. They also predo

Chaebin Kim, Martin Mourigal

We simulate the dynamical spin structure factor (DSSF) $\mathcal{S}({q},\omega)$ of the spin-1/2 Heisenberg antiferromagnetic chain using classical simulations. By employing Landau-Lifshitz Dynamics, we emulate quantum correlations through temperature-dependent corrections, including rescaling of magnetic dipoles and renormalization of exchange interactions.

F. R. Ditrani, M. Longhetti, A. Iovino, M. Fossati

The evolution of quiescent galaxies is driven by numerous physical processes, often considered to be related to their stellar mass and environment over cosmic time. Tracing their stellar populations can provide insight into the processes that transformed these galaxies into their observed quiescent state. In particular, higher-redshift galaxies exhibit more

Graham P. Smith, Tessa Baker, Simon Birrer, Christine E. Collins

We introduce the rapidly emerging field of multi-messenger gravitational lensing - the discovery and science of gravitationally lensed phenomena in the distant universe through the combination of multiple messengers. This is framed by gravitational lensing phenomenology that has grown since the first discoveries in the 20th century, messengers that span 30 o

Roi D. Basha, Ygal Y. Klein, Boaz Katz

The quadrupole Kozai mechanism, which describes the hierarchical three-body problem in the leading order, is shown to be equivalent to a simple pendulum where the change in the eccentricity squared equals the height of the pendulum from its lowest point: $e_{\text{max}}^2-e^2=h=l\left(1-\cos{\theta}\right)$. In particular, this results in useful expressions

Armand Leclerc, Guillaume Laibe

An analytic expression for the frequencies of standing waves in stars, applicable to any radial order n, is derived from ray-tracing equations by the mean of Wigner-Weyl calculus. A correction to previous formulas currently employed in asteroseismology is identified as the Berry phase, which accounts for the vectorial nature of wave propagation in stars. Acc

Aswini Bala, Sachin Jain, Dhruva K. S., Deep Mazumdar

We develop a manifest supertwistor space formalism for three dimensional $\mathcal{N}=1, 2,3,4$ superconformal field theories. This formalism simultaneously makes manifest the supersymmetry, conformal invariance and conservation. We solve two and three point correlators of (half) integer spin conserved supercurrents using the graded supergroup generators. Ap

K-Ryan Hinds, Daniel Perley, Jesper Sollerman, Adam Miller

Although all Type II supernovae (SNe) originate from massive stars possessing a hydrogen-rich envelope, their light curve morphology is diverse, reflecting poorly characterised heterogeneity in the physical properties of their progenitor systems. Here, we present a detailed light curve analysis of a magnitude-limited sample of 639 Type II SNe from the Zwicky

Paryag Sharma, Raghunathan Srianand, Hum Chand, Labanya Kumar Guha

Using a sample of 166 projected quasar pairs we investigate the influence of active galactic nuclei on the circumgalactic medium (CGM) of the quasar host galaxies probed using strong Mg II absorption (i.e., $W_{2796}\ge 1\dot{A}$) at impact parameters ($D$) $<$100 kpc. The foreground quasars are restricted to the redshift range $0.4 \leq z \leq 0.8$ and have

Siyang Ling, Sabeela Shah, Sam S. C. Wong

Nonlinear tails in black hole perturbations, arising from second-order effects, present a distinct departure from the well-known Price tail of linear theory. We present an analytical derivation of the power law indices and amplitudes for nonlinear tails stemming from outgoing sources, and validate these predictions to percent-level accuracy with numerical si

Li Wang, Dengkai Jiang, Chengyuan Li, Licai Deng

Identifying bifurcated blue straggler (BS) sequences in color-magnitude diagrams (CMDs) of star clusters has long been regarded as a powerful diagnostic for distinguishing different BS formation mechanisms. While such bifurcations are typically associated with core-collapsed clusters, their detection in dynamically young clusters raises new questions about t

Z. Eker, V. Bakis

The development line of bolometric corrections within the brief history of photometry was described from the perspective of the Kuhnian philosophy of science. The luminous efficiency and heat index were two previous concepts to imply visual and bolometric brightness difference of a star, which was mainly suggested and used as auxiliary tools for calibrating

Dan Ryczanowski, Jeff Cooke, James Freeburn, Benjamin Gompertz

Making an unambiguous detection of lensed gravitational waves is challenging with current generation detectors due to large uncertainties in sky localisations and other inferred parameter distributions. However, in the case of binary neutron star (BNS) mergers this challenge can be overcome by detecting multiple images of its lensed kilonova counterpart, sim

Motoo Suzuki, Ling-Xiao Xu

We demonstrate that non-invertible fusion algebras give rise to a class of selection rules with genuine organizing power in particle physics models, which we call non-invertible selection rules (NISRs). We identify the algebraic structures that distinguish NISRs from ordinary group-based selection rules and from their generic explicit breaking. As a minimal

Bilal Hawashin, Michael M. Scherer, Lukas Janssen

Two-dimensional van-der-Waals materials offer a highly tunable platform for engineering electronic band structures and interactions. By employing techniques such as twisting, gating, or applying pressure, these systems enable precise control over the electronic excitation spectrum. In moir\'e bilayer graphene, the tunability facilitates the transition from a

Tyler Corbett, Jay Desai, O. J. P. Eboli, M. C. Gonzalez-Garcia

We study Drell-Yan production in universal theories consistently including effects beyond dimension six in the SMEFT. Within universal SMEFT and with $C$ and $P$ conservation we find that eleven dimension-eight operators contribute in addition to the six contributing at dimension-six. We first work in an operator basis in which operators with higher derivati

Michalis Kourniotis, Michaela Kraus, Maria Laura Arias, Lydia S. Cidale

In this Letter, we shed light on the evolutionary phase of HD 144812, a Galactic yellow supergiant showing infrared excess that is typically expected for evolved stars undergoing enhanced mass-loss activity. We present high-resolution spectroscopy of the star in the $H-$ and $K-$band acquired with the GRating INfrared Spectrometer (IGRINS) and further explor

Kiara Carloni, Yago Porto, Carlos A. Argüelles, P. S. Bhupal Dev

Although the sources of astrophysical neutrinos are still unknown, they are believed to be produced by a population of sources in the distant universe. Measurements of the diffuse, all-sky astrophysical flux can thus be sensitive to flavor and energy-dependent propagation effects, such as very long baseline oscillations. These oscillations are present in cer

Keith R. Dienes, Lucien Heurtier, Daniel Hoover, Fei Huang

As discussed in a number of recent papers, cosmological stasis is a phenomenon wherein the abundances of multiple cosmological energy components with different equations of state remain constant for an extended period despite the expansion of the universe. One of the most intriguing aspects of the stasis phenomenon is that it can give rise to cosmological ep

Alvaro Herráez, Dieter Lüst, Carmine Montella

In this work, we investigate the connection between black hole instabilities and Swampland constraints, presenting new insights into the AdS Distance Conjecture. By examining the scale at which horizon instabilities of Schwarzschild-AdS$_d$ black holes take place$-\Lambda_{\mathrm{BH}}-$we uncover a universal scaling relation, $\Lambda_{\mathrm{BH}}\sim |\La

Jonah Kudler-Flam, Kartik Prabhu, Gautam Satishchandran

We analyze the asymptotic behavior of quantum fields and perturbative quantum gravity in de Sitter space. We show that the necessary and sufficient condition for the existence of a de Sitter invariant vacuum state in the free theory is if the local field observables commute with the ``memory observable'' on any cosmological horizon. This criterion yields sim

Benjamin A. Seidel, Rhea-Silvia Remus, Lucas M. Valenzuela, Lucas C. Kimmig

From the scale-free nature of gravity, the structure in the universe is expected to be self-similar on large scales. However, this self-similarity will eventually break down due to small-scale gas physics such as star formation, AGN and stellar feedback as well as non-linear effects gaining importance relative to linear structure formation. In this work we i

Elly Moghtaderi, Brayden R. Hull, Jerome Quintin, Ghazal Geshnizjani

Quantum fields can notoriously violate the null energy condition (NEC). In a cosmological context, NEC violation can lead to, e.g., dark energy at late times with an equation-of-state parameter smaller than $-1$ and nonsingular bounces at early times. However, it is expected that there should still be a limit in semiclasssical gravity to how much `negative e

Sam Bennett, Amihay Hanany, Guhesh Kumaran

The technique of $\textit{orthosymplectic quotient quiver subtraction}$ is introduced for framed orthosymplectic quivers. This involves subtracting an $\textit{orthosymplectic quotient quiver}$ from a framed orthosymplectic $3d\;\mathcal N=4$ quiver gauge theory which has the effect of gauging an $\mathrm{SO}(n)$ or $\mathrm{Sp}(n)$ subgroup of the IR Coulom

Lingdong Kong, Dongyue Lu, Xiang Xu, Lai Xing Ng

Cross-platform adaptation in event-based dense perception is crucial for deploying event cameras across diverse settings, such as vehicles, drones, and quadrupeds, each with unique motion dynamics, viewpoints, and class distributions. In this work, we introduce EventFly, a framework for robust cross-platform adaptation in event camera perception. Our approac

Luigi Barchiesi, F. J. Carrera, C. Vignali, F. Pozzi

Understanding the AGN-galaxy co-evolution, feedback processes, and the evolution of Black Hole Accretion rate Density (BHAD) requires accurately estimating the contribution of obscured Active Galactic Nuclei (AGN). However, detecting these sources is challenging due to significant extinction at the wavelengths typically used to trace their emission. We evalu

Sangwon Baik, Hyeonwoo Kim, Hanbyul Joo

We present a method for learning 3D spatial relationships between object pairs, referred to as object-object spatial relationships (OOR), by leveraging synthetically generated 3D samples from pre-trained 2D diffusion models. We hypothesize that images synthesized by 2D diffusion models inherently capture realistic OOR cues, enabling efficient collection of a

Mingju Gao, Yike Pan, Huan-ang Gao, Zongzheng Zhang

As interest grows in world models that predict future states from current observations and actions, accurately modeling part-level dynamics has become increasingly relevant for various applications. Existing approaches, such as Puppet-Master, rely on fine-tuning large-scale pre-trained video diffusion models, which are impractical for real-world use due to t

Xiang Xu, Lingdong Kong, Hui Shuai, Wenwei Zhang

LiDAR representation learning has emerged as a promising approach to reducing reliance on costly and labor-intensive human annotations. While existing methods primarily focus on spatial alignment between LiDAR and camera sensors, they often overlook the temporal dynamics critical for capturing motion and scene continuity in driving scenarios. To address this

Ruben Van Assche, Sarah Masaad, Emmanuel Gooskens, Stijn Sackesyn

Communication through optical fibres experiences limitations due to chromatic dispersion and nonlinear Kerr effects that degrade the signal. Mitigating these impairments is typically done using complex digital signal processing algorithms. However, these equalisation methods require significant power consumption and introduce high latencies. Photonic reservo

Chuong Huynh, Jinyu Yang, Ashish Tawari, Mubarak Shah

Composed Image Retrieval (CIR) is a complex task that aims to retrieve images based on a multimodal query. Typical training data consists of triplets containing a reference image, a textual description of desired modifications, and the target image, which are expensive and time-consuming to acquire. The scarcity of CIR datasets has led to zero-shot approache

Timothée Riom, Sabine Houy, Bruno Kreyssig, Alexandre Bartel

Fuzzing is a well-established technique for detecting bugs and vulnerabilities. With the surge of fuzzers and fuzzer platforms being developed such as AFL and OSSFuzz rises the necessity to benchmark these tools' performance. A common problem is that vulnerability benchmarks are based on bugs in old software releases. For this very reason, Magma introduced t

Lalitha Sairam, Nikku Madhusudhan

Planetary systems orbiting M dwarf host stars are promising targets for atmospheric characterisation of low-mass exoplanets. Accurate characterisation of M dwarf hosts is important for detailed understanding of the planetary properties and physical processes, including potential habitability. Recent studies have identified several candidate Hycean planets or

Xuan Ju, Weicai Ye, Quande Liu, Qiulin Wang

Current video generative foundation models primarily focus on text-to-video tasks, providing limited control for fine-grained video content creation. Although adapter-based approaches (e.g., ControlNet) enable additional controls with minimal fine-tuning, they encounter challenges when integrating multiple conditions, including: branch conflicts between inde

Hongyu Liu, Xuan Wang, Ziyu Wan, Yue Ma

This work focuses on open-domain 4D avatarization, with the purpose of creating a 4D avatar from a portrait image in an arbitrary style. We select parametric triplanes as the intermediate 4D representation and propose a practical training paradigm that takes advantage of both generative adversarial networks (GANs) and diffusion models. Our design stems from

M. Cécere, P. F. Wyper, G. Krause, A. Sahade

Context: Solar eruptions are crucial for space weather studies. Understanding the mechanisms influencing their evolution is key to improving predictions of their geoeffectiveness. Helmet streamers (HSs) are persistent structures in the solar corona, present in both minimum and maximum solar activity periods. These structures contain a current sheet of low ma

Stefan Stojanov, David Wendt, Seungwoo Kim, Rahul Venkatesh

Estimating motion in videos is an essential computer vision problem with many downstream applications, including controllable video generation and robotics. Current solutions are primarily trained using synthetic data or require tuning of situation-specific heuristics, which inherently limits these models' capabilities in real-world contexts. Despite recent

Zihang Lai, Andrea Vedaldi

Temporal consistency is critical in video prediction to ensure that outputs are coherent and free of artifacts. Traditional methods, such as temporal attention and 3D convolution, may struggle with significant object motion and may not capture long-range temporal dependencies in dynamic scenes. To address this gap, we propose the Tracktention Layer, a novel

Baifeng Shi, Boyi Li, Han Cai, Yao Lu

High-resolution perception of visual details is crucial for daily tasks. Current vision pre-training, however, is still limited to low resolutions (e.g., 378 x 378 pixels) due to the quadratic cost of processing larger images. We introduce PS3 that scales CLIP-style vision pre-training to 4K resolution with a near-constant cost. Instead of contrastive learni

Fernando Julio Cendra, Kai Han

The inherent ambiguity in defining visual concepts poses significant challenges for modern generative models, such as the diffusion-based Text-to-Image (T2I) models, in accurately learning concepts from a single image. Existing methods lack a systematic way to reliably extract the interpretable underlying intrinsic concepts. To address this challenge, we pre

Liang Pan, Zeshi Yang, Zhiyang Dou, Wenjia Wang

Synthesizing diverse and physically plausible Human-Scene Interactions (HSI) is pivotal for both computer animation and embodied AI. Despite encouraging progress, current methods mainly focus on developing separate controllers, each specialized for a specific interaction task. This significantly hinders the ability to tackle a wide variety of challenging HSI

Hao Yu, Zhuokai Zhao, Shen Yan, Lukasz Korycki

The rapid advancement of large vision-language models (LVLMs) has driven significant progress in multimodal tasks, enabling models to interpret, reason, and generate outputs across both visual and textual domains. While excelling in generative tasks, existing LVLMs often face limitations in tasks requiring high-fidelity representation learning, such as gener

Thiago Matheus Cavalheiro, Alexandre José Santana, Victor Ayala

In control theory, researchers need to understand a system's local and global behaviors in relation to its initial conditions. When discussing observability, the main focus is on the ability to analyze the system using an output space defined by an output map. In this study, our objective was to establish conditions for characterizing the observability prope

Jiaming Pan, Gen Ye

It has been observed that the hint about dynamical dark energy in the DESI BAO observation might point to non-minimally coupled gravity. We report the first $3\sigma$ evidence for non-minimal coupling in a model-agnostic effective field theory (EFT) approach. In a non-parametric reconstruction approach, we detect a clear departure from the General Relativity

Lifu Wang, Daqing Liu, Xinchen Liu, Xiaodong He

Text encoders in diffusion models have rapidly evolved, transitioning from CLIP to T5-XXL. Although this evolution has significantly enhanced the models' ability to understand complex prompts and generate text, it also leads to a substantial increase in the number of parameters. Despite T5 series encoders being trained on the C4 natural language corpus, whic

Jayne Thompson, Paul M. Riechers, Andrew J. P. Garner, Thomas J. Elliott

Agents often execute complex strategies -- adapting their response to each input stimulus depending on past observations and actions. Here, we derive the minimal energetic cost for classical agents to execute a given strategy, highlighting that they must dissipate a certain amount of heat with each decision beyond Landauer's limit. We then prove that quantum

František Štampach, Jakub Waclawek

It was recently proved by Fischer, Keller, and Pogorzelski in [Integr. Equ. Oper. Theory, 95(24), 2023] that the classical discrete $p$-Hardy inequality admits an improvement, and the optimal $p$-Hardy weight $\omega_{p}$ was determined therein. We prove that $\omega_{p}$ directly corresponds to a Herglotz-Nevanlinna function, establish an integral represent

Yuncheng Lu, Shuang Liang, Hongxiang Fan, Ce Guo

While existing quantum hardware resources have limited availability and reliability, there is a growing demand for exploring and verifying quantum algorithms. Efficient classical simulators for high-performance quantum simulation are critical to meeting this demand. However, due to the vastly varied characteristics of classical hardware, implementing hardwar

Lukas Mack, Felix Grüninger, Benjamin A. Richardson, Regine Lendway

Accurate 3D pose estimation of grasped objects is an important prerequisite for robots to perform assembly or in-hand manipulation tasks, but object occlusion by the robot's own hand greatly increases the difficulty of this perceptual task. Here, we propose that combining visual information and proprioception with binary, low-resolution tactile contact measu

Rodrigo Ribeiro

We investigate the asymptotic behavior of the number of parts $K_n$ in the Ewens--Pitman partition model under the regime where the diversity parameter is scaled linearly with the sample size, that is, $\theta = \lambda n$ for some~$\lambda > 0$. While recent work has established a law of large numbers (LLN) and a central limit theorem (CLT) for $K_n$ in thi

Tasnum Reza, Sergey M. Frolov

Hybrid superconductor-semiconductor nanowire Josephson junctions exhibit skewed and phi-shifted current phase relations when an in-plane magnetic field is applied along the weak link's spin-orbit effective field direction. These junctions can have an asymmetric Josephson potential with odd-order nonlinearities. A dominant third-order nonlinearity can be achi

Thiago Matheus Cavalheiro, Alexandre José Santana, Victor Ayala

In control theory, understanding the observability property of a system is crucial for effectively managing and controlling dynamical systems. This property empowers us to deduce the internal state of a system from its outputs over time, even when direct measurements are impossible. By harnessing observability, we can accurately estimate the complete state o

Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou

Metamaterials, renowned for their exceptional mechanical, electromagnetic, and thermal properties, hold transformative potential across diverse applications, yet their design remains constrained by labor-intensive trial-and-error methods and limited data interoperability. Here, we introduce CrossMatAgent -- a novel multi-agent framework that synergistically

B. Bale, G. Tautvaisiene, R. Minkeviciute, A. Drazdauskas

Context. Various element transport processes modify the photospheric chemical composition of low-mass stars during their evolution. The most prominent one is the first dredge-up that occurs at the beginning of the red giant branch. Then, various extra-mixing processes, such as those caused by thermohaline- and/or rotation-induced mixing, come into action. Th

Andrew D. King, Alberto Nocera, Marek M. Rams, Jacek Dziarmaga

In a recent preprint [1] (arXiv:2503.05693), Tindall et al. presented impressive classical simulations of quantum dynamics using tensor networks. Their methods represent a significant improvement in the classical state of the art, and in some cases show lower errors than recent simulations of quantum dynamics using a quantum annealer [2] (King et al., Scienc

Alejandro Ortega

Recent progress in AI capabilities has heightened concerns that AI systems could pose a threat to national security, for example, by making it easier for malicious actors to perform cyberattacks on critical national infrastructure, or through loss of control of autonomous AI systems. In parallel, federal legislators in the US have proposed nascent 'AI incide

Abdulmoneam Ali, Ahmed Arafa

We address the problem of cluster identity estimation in a personalized federated learning (PFL) setting in which users aim to learn different personal models. The backbone of effective learning in such a setting is to cluster users into groups whose objectives are similar. A typical approach in the literature is to achieve this by training users' data on di

Renata Kallosh, Andrei Linde, Diederik Roest

We show that the simplest generalization of the chaotic inflation model $\tfrac12 {m^{2}\phi^{2}}$ with nonminimal coupling to gravity $(1+\phi) R$ provides a good match to the results of the latest data release of the Atacama Cosmology Telescope, with $r \approx10^{-2}$.

Rama Murthy Garimella, Marcos Eduardo Valle, Guilherme Vieira, Anil Rayala

In this paper, we explore the dynamics of structured complex-valued Hopfield neural networks (CvHNNs), which arise when the synaptic weight matrix possesses specific structural properties. We begin by analyzing CvHNNs with a Hermitian synaptic weight matrix and establish the existence of four-cycle dynamics in CvHNNs with skew-Hermitian weight matrices opera

Dimitrios Skiathas, Constantinos Kalapotharakos, Zorawar Wadiasingh, Demosthenes Kazanas

We detail new force-free simulations to investigate magnetosphere evolution and precursor electromagnetic (EM) signals from binary neutron stars. Our simulations fully follow a representative inspiral motion, capturing the intricate magnetospheric dynamics and their impact on EM outflows. We explore a range of stellar magnetic moment orientations and relativ

Shun Feng, Aidan J. Campbell, Bibi Mary Francis, Hyeonjun Baek

We report the experimental observation of quadrupolar exciton states in the reflectance contrast spectrum of 2$H$-stacked bilayer MoSe$_2$. The application of a vertical electric field results in a quadratic energy redshift of these quadrupolar excitons, in contrast to the linear energy splitting observed in the coexisting dipolar excitons within the bilayer

Dylan Butson, Sujay Nair

We give a geometric proof of inverse Hamiltonian reduction for all finite W-algebras in type $A$, a certain embedding of the finite W-algebra corresponding to an arbitrary nilpotent in $\mathfrak{gl}_N$ into that corresponding to a larger nilpotent with respect to the closure order on orbits, tensored with an auxiliary algebra of differential operators. We f

Tianhao Qi, Jianlong Yuan, Wanquan Feng, Shancheng Fang

Sora has unveiled the immense potential of the Diffusion Transformer (DiT) architecture in single-scene video generation. However, the more challenging task of multi-scene video generation, which offers broader applications, remains relatively underexplored. To bridge this gap, we propose Mask$^2$DiT, a novel approach that establishes fine-grained, one-to-on

Erik Adli, Joshua Appleby, Timothy L. Barklow, Marica Biagini

HALHF is a hybrid linear collider that uses electron-driven plasma-wakefield acceleration to accelerate electrons to high energy while using radio-frequency cavity technology to accelerate positrons. The most cost-effective solution collides low-energy positrons with high-energy electrons, producing a boost to the final state in the electron direction with $

Farhad Mehdifar, Mani H. Dhullipalla, Charalampos P. Bechlioulis, Dimos V. Dimarogonas

This paper addresses the problem of collaboratively satisfying long-term spatial constraints in multi-agent systems. Each agent is subject to spatial constraints, expressed as inequalities, which may depend on the positions of other agents with whom they may or may not have direct communication. These constraints need to be satisfied asymptotically or after

Nengbo Wang, Xiaotian Han, Jagdip Singh, Jing Ma

Large language models (LLMs) have revolutionized natural language processing (NLP), particularly through Retrieval-Augmented Generation (RAG), which enhances LLM capabilities by integrating external knowledge. However, traditional RAG systems face critical limitations, including disrupted contextual integrity due to text chunking, and over-reliance on semant

John A. Snoap

This dissertation presents several novel deep-learning (DL)-based approaches for classifying digitally modulated signals, one method of which involves the use of capsule networks (CAPs) together with cyclic cumulant (CC) features of the signals. These were blindly estimated using cyclostationary signal processing (CSP) and were then input into the CAP for tr

Kishanthan Thangarajah, Arthur Leung, Boyuan Chen, Ahmed E. Hassan

The integration of AI-assisted coding tools within development environments drastically reduces development time, and allows developers to focus more on creative and critical aspects of software engineering through the use of Code Large Language Models (CodeLLMs). These coding assistants automate repetitive and time-consuming coding tasks such as code genera

Andrea Kubin, Giorgio Saracco, Giorgio Stefani

Given $p\in[1,\infty)$ and a bounded open set $\Omega\subset\mathbb R^d$ with Lipschitz boundary, we study the $\Gamma$-convergence of the weighted fractional seminorm \[ [u]_{s,p,f}^p = \int_{\mathbb R^d} \int_{\mathbb R^d} \frac{|\tilde{u}(x)- \tilde{u}(y)|^p}{\|x-y\|^{d+sp}}\,f(x)\,f(y)\,\mathrm{d} x\,\mathrm{d} y \] as $s\to1^-$ for $u\in L^p(\Omega)$, w

Youguang Chen, George Biros

We consider the problem of selecting a subset of points from a dataset of $n$ unlabeled examples for labeling, with the goal of training a multiclass classifier. To address this, we build upon the regret minimization framework introduced by Allen-Zhu et al. in "Near-optimal design of experiments via regret minimization" (ICML, 2017). We propose an alternativ