March 2025 arXiv papers — page 108

Sanjeevi Krishnan, Emily Rudman

We claim that the cube category whose morphisms are the interval-preserving monotone functions between finite Boolean lattices is a convenient general-purpose site for cubical sets. This category is the largest possible concrete Eilenberg-Zilber variant excluding the reversals and diagonals. The category admits as monoidal generators all functions between th

Hasibul Jamil, Jacob Goldverg, Elvis Rodrigues, MD S Q Zulkar Nine

The rapid growth of data across fields of science and industry has increased the need to improve the performance of end-to-end data transfers while using the resources more efficiently. In this paper, we present a dynamic, multiparameter deep reinforcement learning (DRL) framework that adjusts application-layer transfer settings during data transfers on shar

Huy Hoang Ha

Large language models (LLMs) have demonstrated remarkable capabilities in various natural language processing tasks. However, achieving strong performance in specialized domains like mathematical reasoning and non-English languages often requires extensive training on massive datasets. This paper investigates a contrasting approach: strategic fine-tuning on

Qian Meng, Jin Peng Zhou, Kilian Q. Weinberger, Hadas Kress-Gazit

This paper presents INPROVF, an automatic framework that combines large language models (LLMs) and formal methods to speed up the repair process of high-level robot controllers. Previous approaches based solely on formal methods are computationally expensive and cannot scale to large state spaces. In contrast, INPROVF uses LLMs to generate repair candidates,

Ertiza Hossain Shopnil, Jahid Emon, Md Nadeem Azad, AKM Monjur Morshed

This study employs molecular dynamics simulations to investigate droplet dynamics when a stationary droplet on a solid surface is struck by another droplet of similar size from above. The focus is on the jumping behavior of the merged droplet and the associated energy conversion. The process is primarily governed by the amount of energy converted into kineti

José Antonio Nájera, Harry Desmond

Redshift-independent distances underpin much of astrophysics, and there exists a plethora of methods to estimate them. However, the extent to which the distances they imply are consistent, while crucial for the integrity of the distance ladder, has been little explored. We construct a statistical framework to assess both internal (between measurements with t

Mert Cemri, Melissa Z. Pan, Shuyi Yang, Lakshya A. Agrawal

Despite enthusiasm for Multi-Agent LLM Systems (MAS), their performance gains on popular benchmarks are often minimal. This gap highlights a critical need for a principled understanding of why MAS fail. Addressing this question requires systematic identification and analysis of failure patterns. We introduce MAST-Data, a comprehensive dataset of 1600+ annota

Tian Zhou, Ryan Rizaldy, Martine Schut, Anupam Mazumdar

In this paper, we will show how finite-temperature corrections and spin-dependent/independent noise will affect the contrast in a matter-wave interferometer, especially with massive objects and large spatial superposition sizes. Typically, spin is embedded in a nanoparticle as a defect, which can be manipulated by the external magnetic field to create a macr

Gary Nash

Unifying the massive spin-1 field with gravity requires the implementation of a regular vector field that satisfies the spin-1 Proca equation and is a fundamental part of the spacetime metric. That vector field is one of the pair of vectors in the line element field (\textbf{X},-\textbf{X}), which is paramount to the existence of all Lorentzian metrics and M

Manisha Mukherjee, Vincent J. Hellendoorn

Large Language Models (LLMs) are widely used for automated code generation. Their reliance on infrequently updated pretraining data leaves them unaware of newly discovered vulnerabilities and evolving security standards, making them prone to producing insecure code. In contrast, developer communities on Stack Overflow (SO) provide an ever-evolving repository

Damiano F. G. Fiorillo, Tetyana Pitik, Edoardo Vitagliano

Feebly interacting particles, such as sterile neutrinos, dark photons, and axions, can be abundantly produced in the proto-neutron star (PNS) formed in core-collapse supernovae (CCSNe). These particles can decay into photons or charged leptons, depositing energy outside the PNS. Strong bounds on new particles can thus be derived from the observed luminosity

Maan Qraitem, Piotr Teterwak, Kate Saenko, Bryan A. Plummer

Vision-language models (VLMs) (e.g. CLIP, LLaVA) are trained on large-scale, lightly curated web datasets, leading them to learn unintended correlations between semantic concepts and unrelated visual signals. These associations degrade model accuracy by causing predictions to rely on incidental patterns rather than genuine visual understanding. Prior work ha

Xingyue Han, An-Hsi Chen, Matthew Brahlek, Liang Wu

MnBi$_2$Te$_4$ (MBT) is an ideal platform for studying the interplay between magnetism and topology. Many exotic topological phenomena, such as the quantum anomalous Hall effect and the axion insulator, have been observed in few-layer MBT. A key feature in MBT is the emergence of the surface exchange gap, which lies in the milli-electron-volt range (1 THz co

Shin'ichiro Ando, Kohei Hayashi, Shunichi Horigome, Masahiro Ibe

Self-interacting dark matter (SIDM) has been proposed to address small-scale challenges faced by the cold dark matter (CDM) paradigm, such as the diverse density profiles observed in dwarf galaxies. In this study, we analyze the kinematics of dwarf galaxies by incorporating the effects of gravothermal core collapse into SIDM models using a semi-analytical su

Antonios Valamontes, Ioannis Adamopoulos

This study presents a computational framework for evaluating the detectability of white hole-induced gravitational wave signals and their imprints on the cosmic microwave background (CMB). The approach integrates stochastic gravitational wave background (SGWB) polarization data from LISA with CMB-S4 B-mode anisotropies, utilizing Monte Carlo simulations, Bay

Kanishka Perera, Kaye Silva

We prove the existence, multiplicity, and bifurcation of solutions with prescribed energy for a broad class of scaled problems by introducing a suitable notion of scaling based Nehari manifold. Applications are given to Schr\"{o}dinger--Poisson--Slater type equations.

Giacomo Belli, Marco Mordacci, Michele Amoretti

In this work, a scalable algorithm for the approximate quantum state preparation problem is proposed, facing a challenge of fundamental importance in many topic areas of quantum computing. The algorithm uses a variational quantum circuit based on the Standard Recursive Block Basis (SRBB), a hierarchical construction for the matrix algebra of the $SU(2^n)$ gr

Tomer Milo

We provide a short proof for the Figiel, Lindenstrauss and Milman inequality regarding the number of vertices and faces of certain polytope, with an explicit bound on the universal constant involved. The proof is completely elementary and avoids any form of Dvoretzky's theorem, as well as the spherical isoperimetric inequality.

Chiara Plizzari, Alessio Tonioni, Yongqin Xian, Achin Kulshrestha

Understanding fine-grained temporal dynamics is crucial in egocentric videos, where continuous streams capture frequent, close-up interactions with objects. In this work, we bring to light that current egocentric video question-answering datasets often include questions that can be answered using only few frames or commonsense reasoning, without being necess

Olivier Masset, Roland Bastardis, Francois Vernay

The synthesis of metallic nanoparticle assemblies is nowadays well-controlled, such that these systems offer the possibility of controlling light at a sub-wavelength scale, thanks, for instance, to surface plasmons. Determining the energy dispersion of plasmons likely to couple to light within these nanostructures is, therefore, a necessary preliminary task

David Quiroga, Jason Han, Anastasios Kyrillidis

Computing the excited states of a given Hamiltonian is computationally hard for large systems, but methods that do so using quantum computers scale tractably. This problem is equivalent to the PCA problem where we are interested in decomposing a matrix into a collection of principal components. Classically, PCA is a well-studied problem setting, for which bo

Karina M. Sindermann, Esma S. Gel, Nesim K. Erkip

Industrial Vending Machines (IVMs) automate the dispensing of a variety of supplies like safety equipment and tools at customer sites, providing 24/7 access while tracking inventory in real-time. Industrial distribution companies typically manage the replenishment of IVMs using periodic schedules, which do not take advantage of these advanced real-time monit

Seham Helmi, Junjie Liu, Keith G Andrews, Robert Schreiber

Molecular electronics and other technologies whose components comprise individual molecules have been pursued for half a century because the molecular scale represents the limit of miniaturisation of objects whose structure is tuneable for function. Despite the promise, practical progress has been hindered by the lack of methodologies for directed assembly o

Cain Edie-Michell, Noah Snyder

In this paper we give a diagrammatic description of the categories of modules coming from the conformal embeddings $\mathcal{V}(\mathfrak{sl}_N,N) \subset \mathcal{V}(\mathfrak{so}_{N^2-1},1)$. A small variant on this construction (morally corresponding to a conformal embedding of $\mathfrak{gl}_N$ level $N$ into $\mathfrak{o}_{N^2-1}$ level $1$) has uniform

Gennadi Malaschonok

The matrix LU factorization algorithm is a fundamental algorithm in linear algebra. We propose a generalization of the LU and LEU algorithms to accommodate the case of a commutative domain and its field of quotients. This algorithm decomposes any matrix A into a product of three matrices A=LSU, where each element of the triangular matrices L and U is a minor

Matthew H. Hamil

We state and prove a stratification result that allows us to classify the tensor ideal localizing subcategories for the stable module category $\text{Stab}(\mathcal{C}_{(\mathfrak{g}, \mathfrak{g}_{\bar 0})})$ of Lie superalgbera representations which are semisimple as representations of $\mathfrak{g}_{\bar 0}$ under the hypotheses that $\mathfrak{g}$ is a c

Shuheng Li, Jiayun Zhang, Xiaohan Fu, Xiyuan Zhang

In human activity recognition (HAR), activity labels have typically been encoded in one-hot format, which has a recent shift towards using textual representations to provide contextual knowledge. Here, we argue that HAR should be anchored to physical motion data, as motion forms the basis of activity and applies effectively across sensing systems, whereas te

Gudrun Hiller, Lara Nollen, Daniel Wendler

The Standard Model Effective Field Theory (SMEFT) is a widely utilized framework for exploring new physics effects in a model-independent manner. In previous studies, Drell-Yan collider data has emerged as a promising signature due to its energy enhancement relative to Standard Model predictions. We present recent works, extending this approach by also consi

André Augusto, André Vasconcelos, Miguel Correia, Luyao Zhang

The number of blockchain interoperability protocols for transferring data and assets between blockchains has grown significantly. However, no open dataset of cross-chain transactions exists to study interoperability protocols in operation. There is also no tool to generate such datasets and make them available to the community. This paper proposes XChainData

Jihye Jeon, Erik P. Gilson, Michael Hepler, Alexander Glaser

Neutron sources can play a variety of roles in warhead verification. For transmission radiography, a source of directed high energy neutrons is required, while for applications to detect fissile isotopes, sub-MeV neutrons are preferred. The Excalibur (Experiment for Calibration with Uranium) neutron source has been built and used in a variety of verification

Nenad Teofanov, Filip Tomic, Milica Zigic

We consider spaces of smooth functions obtained by relaxing Gevrey-type regularity and decay conditions. It is shown that these classes fit well within the general framework of the weighted matrices approach to ultradifferentiable functions. We examine equivalent ways of introducing Gelfand-Shilov spaces related to the extended Gevrey regularity and derive t

Pavel Putrov, Rajath Radhakrishnan

The anomaly of non-invertible higher-form symmetries is determined by the braiding of topological operators implementing them. In this paper, we study a method to classify braidings on topological line and surface operators by leveraging the fact that topological operators which admit a braiding are symmetries of their associated SymTFT. This perspective all

DES Collaboration, T. M. C. Abbott, M. Aguena, A. Alarcon

Galaxy clusters provide a unique probe of the late-time cosmic structure and serve as a powerful independent test of the $\Lambda$CDM model. This work presents the first set of cosmological constraints derived with ~16,000 optically selected redMaPPer clusters across nearly 5,000 $\rm{deg}^2$ using DES Year 3 data sets. Our analysis leverages a consistent mo

Chun-Hao To, Elisabeth Krause, Chihway Chang, Hao-Yi Wu

We introduce an updated To&Krause2021 model for joint analyses of cluster abundances and large-scale two-point correlations of weak lensing and galaxy and cluster clustering (termed CL+3x2pt analysis) and validate that this model meets the systematic accuracy requirements of analyses with the statistical precision of the final Dark Energy Survey (DES) Year 6

Eren Volkan Küçük

This paper explores the historical development of the theory of quantum mechanics between 1900 and 1927 by chronological examination of the foundational papers and ideas. Beginning with Planck's introduction of energy quantisation in blackbody radiation, we follow the emergence of Einstein's light quanta hypothesis, Bohr's atomic model, and the statistical i

V. Pugatch, F. Alessio, V. Balagura, F. Blanc

After an upgrade in 2019--2021, the LHCb experiment is taking data in Run 3 (2022--2026) with an instantaneous luminosity of proton-proton collisions of $2\!\times\!10^{33}$ cm$^{-2}$s$^{-1}$. This article presents the Radiation Monitoring System (RMS-R3) for controlling the beam and background conditions at LHCb. It runs continuously during the detector's o

Michael A. Bender, William Kuszmaul, Renfei Zhou

A hash table is said to be open-addressed (or non-obliviously open-addressed) if it stores elements (and free slots) in an array with no additional metadata. Intuitively, open-addressed hash tables must incur a space-time tradeoff: The higher the load factor at which the hash table operates, the longer insertions/deletions/queries should take. In this paper,

Jenna C. Fromer, Alexandra D. Volkova, Connor W. Coley

Early stage drug discovery and molecular design projects often follow iterative design-make-test cycles. The selection of which compounds to synthesize from all possible candidate compounds is a complex decision inherent to these design cycles that must weigh multiple factors. We build upon the algorithmic downselection framework SPARROW that considers synth

Jan-Erik Christian, Ishfaq Ahmad Rather, Hosein Gholami, Marco Hofmann

In this work, we investigate the properties of hadronic and quark matter that would allow for a first order phase transition between them within neutron stars. To this end, we use a parameterizable Relativistic Mean-Field (RMF) description for the hadronic phase and a Renormalization Group-consistent Nambu-Jona-Lasino (RG-NJL) model for the quark phase. This

Zi Haur Pang, Yahui Fu, Divesh Lala, Mikey Elmers

We investigate the impact of robot appearance on users' spoken behavior during real-world interactions by comparing a human-like android, ERICA, with a less anthropomorphic humanoid, TELECO. Analyzing data from 42 participants at SIGDIAL 2024, we extracted linguistic features such as disfluencies and syntactic complexity from conversation transcripts. The re

Amir Ali-Pour, Julien Gascon-Samson

Federated Learning is widely discussed as a distributed machine learning concept with stress on preserving data privacy. Various structures of Federated Learning were proposed. Centralized Federated learning for instance has been the primary structure that suits cloud computing. Decentralized Federated learning also has been proposed for ecosystems where com

Sai Vijay Kumar Surineela, Prathyusha Kanakamalla, Harigovind Harikumar, Tomojit Ghosh

We present a supervised dimensionality reduction technique called Convex Linear Discriminant Analysis (ConvexLDA). The proposed model optimizes a multi-objective cost function by balancing two complementary terms. The first term pulls the samples of a class towards its centroid by minimizing a sample's distance from its class-centroid in low dimensional spac

H. Movahedi-Lankarani, R. Wells

The purpose of this paper is to study more general real-valued functions of two variables than just metrics on a set X. We concentrate mainly on the classes of distances and almost distances. We also introduce the notion of a bridge on the disjoint union of two sets and show that it induces a symmetric distance on the disjoint union.

Florian Mai, David Kaczér, Nicholas Kluge Corrêa, Lucie Flek

Two core challenges of alignment are 1) scalable oversight and 2) accounting for the dynamic nature of human values. While solutions like recursive reward modeling address 1), they do not simultaneously account for 2). We sketch a roadmap for a novel algorithmic framework that trains a superhuman reasoning model to decompose complex tasks into subtasks that

Micheline Bénédicte Moumoula, Serge Lionel Nikiema, Abdoul Kader Kabore, Jacques Klein

Large Language Models (LLMs) have achieved state-of-the-art performance across software engineering tasks, from code generation to translation. However, we identify and systematically evaluate a critical failure mode: Programming Language Confusion (PLC) -- the generation of code in unintended languages despite explicit instructions. Through evaluation of 10

Spyros Reveliotis, Eva Robillard

Motivated by the increasing interest in the explicit representation and handling of various "preference" structures arising in modern digital economy, this work introduces a new class of "one-to-many stable-matching" problems where a set of atomic tasks must be stably allocated to a set of agents. An important characteristic of these stable-matching problems

Adam Olczak, Ryszard Sobierajski, Przemyslaw Dziegielewski, Salman Ali Kahn

The primary distinction between solid and liquid phases is mechanical rigidity, with liquids having a disordered atomic structure that allows flow. While melting is a common phase transition, its microscopic mechanisms still remain unclear. This study uses molecular dynamics simulations to investigate ultrafast melting in polycrystalline palladium, focusing

Hao Li, Yubin Xiao, Ke Liang, Mengzhu Wang

Single Domain Generalization (SDG) aims to train models that maintain consistent performance across diverse scenarios using data from a single source. While latent diffusion models (LDMs) show promise for augmenting limited source data, our analysis reveals that directly employing synthetic data may not only fail to provide benefits but can actually compromi

Nicolas Thomé, Matthias Wolfrum, Katharina Krischer

Clustered solutions in oscillator networks provide an important insight into how a system might diversify from a synchronous solution into spatiotemporal complex solutions. They can therefore form a link between fully synchronized and incoherent states. Despite their fundamental role in coupled oscillator dynamics, our understanding of how these clusters for

Luis Pedro García-Pintos, Yi-Kai Liu, Alexey V. Gorshkov

While the microscopic laws of physics are often symmetric under time reversal, most natural processes that we observe are not. The emergent asymmetry between typical and time-reversed processes is referred to as the arrow of time. In quantum physics, an arrow of time emerges when a sequence of measurements is performed on a system. We introduce quantum contr

Yusuf Aydogdu, Navaratnam Sri Namachchivaya

Reduced order modeling (ROM) aims to mitigate computational complexity by reducing the size of a high-dimensional state space. In this study, we demonstrate the efficiency, accuracy, and stability of proper orthogonal decomposition (POD)-Galerkin ROM when applied to the El Nino Southern Oscillation model, which integrates coupled atmosphere, ocean, and sea s

Alvise Bastianello, Alexey Tikan, Francois Copie, Stephane Randoux

In generic classical and quantum many-body systems, where typically energy and particle number are the only conserved quantities, stationary states are described by thermal equilibrium. In contrast, integrable systems showcase an infinite hierarchy of conserved quantities that inhibits conventional thermalization, forcing relaxation to a Generalized Gibbs En

Zachary N. Mauri, Christopher J. Ciccarino, Jonah B. Haber, Diana Y. Qiu

Exciton-polaritons -- hybrid states of photons and excitons -- offer unique avenues for controlling electronic, optical, and chemical properties of materials. However, their modeling is mostly limited to formalisms that wash out atomistic details and many-body physics critical to describing real systems. Here, we present an ab initio Green's function formali

Tommaso Bartalesi, Stefano Ettori, Carlo Nipoti

We search for evidence of rotational support by analyzing the thermodynamic profiles of the intracluster medium (ICM) in a sample of nearby, massive galaxy clusters. For each object of the XMM-Newton Cluster Outskirts Project (X-COP) sample, we present axisymmetric models of rotating ICM with composite polytropic distributions, in equilibrium in spherically

Li-Ren Liu, Miguel Aguirre, Stephen R. Kane, Brian K. Kendrick

We report the measurement of the electric dipole moment of aluminum monochloride (AlCl) using a cryogenic buffer-gas beam source. Using Stark shift spectroscopy, we derive values for the dipole moments in the body-fixed frame of the two lowest vibrational states for the $X^1\Sigma^+$ electronic state, $\mu_X(v''=0) = -1.679$ D and $\mu_X(v'' = 1) = -1.761$ D

Becca VanDrunen, Juanjuan Ren, Sebastian Franke, Stephen Hughes

We present a general theory of gain-modified emission dynamics between two quantum emitters (two level systems) in a linear gain medium, demonstrating how gain modifies the usual radiative decay rates and inter-emitter coupling and decay rates, that are well known from purely lossy systems. We derive a Born-Markov master equation that shows explicitly how ga

Qing Huang, Hao Zhang, Yiqing Hao, Weiliang Yao

Pair condensates appear in multiple branches of physics, always introducing exotic phenomena. The pair condensate in quantum magnetism is the spin nematic, whose static (quadrupolar) order is difficult to access, favoring dynamical probes. Here, we perform high-resolution neutron spectroscopy to obtain direct evidence for the presence of two spin-nematic pha

William O. Balmer, Jens Kammerer, Laurent Pueyo, Marshall D. Perrin

High-contrast observations with JWST can reveal key composition and vertical mixing dependent absorption features in the spectra of directly imaged planets across the 3-5 $\mu$m wavelength range. We present novel coronagraphic images of the HR 8799 and 51 Eri planetary systems using the NIRCam Long Wavelength Bar in an offset "narrow" position. These observa

Garv Chauhan, R. Andrew Gustafson, Ian M. Shoemaker

Heavy sterile neutrinos can be produced in core-collapse supernovae (CCSNe), which are superb particle generators because of their high densities and temperatures. If the sterile neutrinos are long-lived, these may be produced inside the supernova core and escape the stellar envelope, later decaying into SM particles like photons and neutrinos. In this work,

L. -A. Hühn, C. P. Dullemond, U. Lebreuilly, R. S. Klessen

Protoplanetary disks naturally emerge during protostellar core-collapse. In their early evolutionary stages, infalling material dominates their dynamical evolution. In the context of planet formation, this means that the conditions in young disks are different from the typically considered disks where infall has subsided. High inward velocities are caused by

A. Lawrence Gould, Erina Paul, Piyali Basak, Arinjita Bhattacharyya

In many biomedical applications with high-dimensional features, such as single-cell RNA-sequencing, it is not uncommon to observe numerous structural zeros. Identifying important features from a pool of high-dimensional data for subsequent detailed analysis is often of interest. Here, we describe an exact, rapid Bayesian screening approach with attractive di

Jan Behrends, Roni Ilan, Moshe Goldstein

The Berry curvature characterizes one aspect of the geometry of quantum states. It materializes, among other consequences, as an anomalous velocity of wave packets. In non-Hermitian systems, wave packet dynamics is enriched by additional terms that can be expressed as generalizations of the Berry connection to non-orthogonal eigenstates. Here, we contextuali

João Barata, Ian Moult, Andrey V. Sadofyev, João M. Silva

Energy correlators have recently attracted significant attention in the study of heavy ion collisions due to their potential to robustly connect experimental measurements with an underlying quantum field theoretic description. While theoretical studies have so far primarily focused on the simplest two-point correlator, mapping out the dynamics of the quark-g

Facundo Rodriguez, Manuel Merchán, Daniela Galárraga-Espinosa, Agustina del Valle Marsengo-Colazo

Observations indicate that central galaxies show a significant alignment of their main shape axes with other galaxies in their group, as well as with the large-scale structure of the universe. Simulations have corroborated this finding, providing further insights into how the shape of the stellar component aligns with the surrounding dark matter halo. In thi

Yugo Takada, Hayata Yamasaki

Reducing space and time overheads of fault-tolerant quantum computation (FTQC) has been receiving increasing attention as it is crucial for the development of quantum computers and also plays a fundamental role in understanding the feasibility and limitations of realizing quantum advantages. Shorter time overheads are particularly essential for demonstrating

Masahiro Hoshino, Masaki Oshikawa, Yuto Ashida

Understanding universal aspects of many-body systems is one of the central themes in modern physics. Recently, the stabilizer Rényi entropy (SRE) has emerged as a computationally tractable measure of nonstabilizerness, a crucial resource for fault-tolerant universal quantum computation. While numerical results suggested that the SRE in critical states can ex

Haider Alhazmi, Doojin Kim, Kyoungchul Kong, Gopolang Mohlabeng

We examine the signals produced by dark matter interactions with electrons, which play a crucial role in direct detection experiments employing heavy target materials, particularly in many well-motivated sub-GeV dark matter scenarios. When the momentum transfer to target electrons is comparable to or exceeds their binding energy, atomic effects related to el

Maciej Kierkla, Philipp Schicho, Bogumila Swiezewska, Tuomas V. I. Tenkanen

Focusing on supercooled phase transitions in models with classical scale symmetry, we formulate a state-of-the art framework for computing the bubble-nucleation rate, accounting for the presence of various energy scales. In particular, we examine the limitations of derivative expansions in constructing a thermal effective field theory for bubble nucleation.

Ross Glew

Given a graph its set of connected subgraphs (tubes) can be defined in two ways: either by considering subsets of edges, or by considering subsets of vertices. We refer to these as binary tubes and unary tubes respectively. Both notions come with a natural compatibility condition between tubes which differ by a simple adjacency constraint. Compatible sets of

M. D'Addona, A. Mercurio, C. Grillo, P. Rosati

We investigate the fundamental plane (FP) of selected early-type (ETG) member galaxies of the galaxy cluster PLCK G287.0+32.9 ($ z_c = 0.3833 $), exploring also four-dimensional hyperplane extensions. We measure ETGs structural parameters and photometry from Hubble Space Telescope (HST) observations. We use high-quality spectroscopic data from the Multi Unit

Ohana Benevides Rodrigues, Matheus Hostert, Kevin J. Kelly, Bryce Littlejohn

The sterile neutrino interpretation of the LSND and MiniBooNE neutrino anomalies is currently being tested at three Liquid Argon detectors: MicroBooNE, SBND, and ICARUS. It has been argued that a degeneracy between $\nu_\mu \to \nu_e$ and $\nu_e \to \nu_e$ oscillations significantly degrades their sensitivity to sterile neutrinos. Through an independent stud

Simon Caron-Huot, Miguel Correia, Giulia Isabella, Mikhail Solon

We introduce a novel method to compute gravitational wave amplitudes within the framework of effective field theory. By reinterpreting the Feynman diagram expansion as a Born series, our method offers several key advantages. It directly yields partial wave amplitudes, streamlining the matching with black hole perturbation theory. Long-distance gravitational

Yen-Ting Lin, Kai-Feng Chen, Tsung-Chi Chen, Chen-Yu Chuang

A critical issue in studying the evolution of galaxy clusters is to find ways that enable meaningful comparisons of clusters observed at different redshifts, as well as in various stages of their growth. Studies in the past have typically suffered from uncertainties in cluster mass estimates due to the scatter between cluster observables and mass. Here we pr

Kedron Silsbee, Brandon S. Hensley, Jamey R. Szalay, Petr Pokorný

A systematic torque from anisotropic radiation can rapidly spin up irregular grains to the point of breakup. We apply the standard theory of rotational disruption from radiative torques to solar system grains, finding that grains with radii $\sim$0.03 --3 $\mu$m at 1 a.u. from the Sun are spun to the point of breakup on timescales $\lesssim1$ yr even when as

Alexey Ermakov, Alessandro Principi

We study charge and spin transport in systems composed of itinerant electrons and localized magnetic moments of a Kitaev quantum spin liquid (QSL) phase. For example, $\alpha-{\rm RuCl}_3$ either intrinsically doped or in proximity to graphene. Our analysis reveals distinct temperature-dependent transport behaviors due to the QSL gap and the Majorana excitat

Soumangsu Chakraborty, Pierre Heidmann

We provide a new roadmap for constructing microstates of non-extremal black holes in supergravity. First, we review the non-linear sigma model of five-dimensional supergravity governing stationary solutions with a U(1) isometry and present the first generalized Ernst formulation of this model. We then revisit solution-generating techniques associated to the

Shiran Yuan, Hao Zhao

Methods based on diffusion backbones have recently revolutionized novel view synthesis (NVS). However, those models require pretrained 2D diffusion checkpoints (e.g., Stable Diffusion) as the basis for geometrical priors. Since such checkpoints require exorbitant amounts of data and compute to train, this greatly limits the scalability of diffusion-based NVS

Qin Liu, Wenxuan Zhou, Nan Xu, James Y. Huang

One critical challenge for large language models (LLMs) for making complex reasoning is their reliance on matching reasoning patterns from training data, instead of proactively selecting the most appropriate cognitive strategy to solve a given task. Existing approaches impose fixed cognitive structures that enhance performance in specific tasks but lack adap

Zhenyu Wu, Yuheng Zhou, Xiuwei Xu, Ziwei Wang

Mobile manipulation is the fundamental challenge for robotics to assist humans with diverse tasks and environments in everyday life. However, conventional mobile manipulation approaches often struggle to generalize across different tasks and environments because of the lack of large-scale training. In contrast, recent advances in vision-language-action (VLA)

Dingkang Liang, Dingyuan Zhang, Xin Zhou, Sifan Tu

We present UniFuture, a unified 4D Driving World Model designed to simulate the dynamic evolution of the 3D physical world. Unlike existing driving world models that focus solely on 2D pixel-level video generation (lacking geometry) or static perception (lacking temporal dynamics), our approach bridges appearance and geometry to construct a holistic 4D repre

Ye Liu, Kevin Qinghong Lin, Chang Wen Chen, Mike Zheng Shou

Videos, with their unique temporal dimension, demand precise grounded understanding, where answers are directly linked to visual, interpretable evidence. Despite significant breakthroughs in text-based reasoning with large language models, multi-modal reasoning - especially for videos - remains limited. In this work, we fill this gap by introducing VideoMind

Haoyang Li, Liang Wang, Chao Wang, Jing Jiang

The Base-New Trade-off (BNT) problem universally exists during the optimization of CLIP-based prompt tuning, where continuous fine-tuning on base (target) classes leads to a simultaneous decrease of generalization ability on new (unseen) classes. Existing approaches attempt to regulate the prompt tuning process to balance BNT by appending constraints. Howeve

Boryana Hadzhiyska, Roger de Belsunce, Andrei Cuceu, Julien Guy

The currently observing Dark Energy Spectroscopic Instrument (DESI) places sub-percent constraints on the Baryon Acoustic Oscillations (BAO) scaling parameters from the Lyman-$\alpha$ (Ly-$\alpha$) forest. However, no systematic error budget stemming from non-linearities in the 3D clustering of the Ly-$\alpha$ forest is included in the DESI-Ly-$\alpha$ analy

Ri-Zhao Qiu, Shiqi Yang, Xuxin Cheng, Chaitanya Chawla

Training manipulation policies for humanoid robots with diverse data enhances their robustness and generalization across tasks and platforms. However, learning solely from robot demonstrations is labor-intensive, requiring expensive tele-operated data collection which is difficult to scale. This paper investigates a more scalable data source, egocentric huma

Yingyue Li, Bencheng Liao, Wenyu Liu, Xinggang Wang

With the advancement of RNN models with linear complexity, the quadratic complexity challenge of transformers has the potential to be overcome. Notably, the emerging Mamba-2 has demonstrated competitive performance, bridging the gap between RNN models and transformers. However, due to sequential processing and vanishing gradients, RNN models struggle to capt

Tianhao Wu, Chuanxia Zheng, Frank Guan, Andrea Vedaldi

Most image-based 3D object reconstructors assume that objects are fully visible, ignoring occlusions that commonly occur in real-world scenarios. In this paper, we introduce Amodal3R, a conditional 3D generative model designed to reconstruct 3D objects from partial observations. We start from a "foundation" 3D generative model and extend it to recover plausi

Tania Ghosh, Soumitro Banerjee

Generalized synchronization (GS) describes a state in which two coupled dynamical systems exhibit a functional relationship between their variables. GS can be achieved by appropriately designing the coupling to constrain the dynamics onto an invariant submanifold, a concept well established in theory. However, experimental validation remains crucial. In this

Giacomo Arcieri, Konstantinos G. Papakonstantinou, Daniel Straub, Eleni Chatzi

This work introduces a novel deep learning-based architecture, termed the Deep Belief Markov Model (DBMM), which provides efficient, model-formulation agnostic inference in Partially Observable Markov Decision Process (POMDP) problems. The POMDP framework allows for modeling and solving sequential decision-making problems under observation uncertainty. In co

Dmitry Khudoteplov, Alexei Morozov, Alexey Sleptsov

Quantum knot invariants (like colored HOMFLY-PT or Kauffman polynomials) are a distinguished class of non-perturbative topological invariants. Any known way to construct them (via Chern-Simons theory or quantum R-matrix) starts with a finite simple Lie algebra. Another set of knot invariants - of finite type - is related to quantum invariants via a perturbat

Lijie Fan, Luming Tang, Siyang Qin, Tianhong Li

We present UniFluid, a unified autoregressive framework for joint visual generation and understanding leveraging continuous visual tokens. Our unified autoregressive architecture processes multimodal image and text inputs, generating discrete tokens for text and continuous tokens for image. We find though there is an inherent trade-off between the image gene

Ling Yang, Kaixin Zhu, Juanxi Tian, Bohan Zeng

With the rapid development of 3D reconstruction technology, research in 4D reconstruction is also advancing, existing 4D reconstruction methods can generate high-quality 4D scenes. However, due to the challenges in acquiring multi-view video data, the current 4D reconstruction benchmarks mainly display actions performed in place, such as dancing, within limi

Yaowei Li, Lingen Li, Zhaoyang Zhang, Xiaoyu Li

As user expectations for image editing continue to rise, the demand for flexible, fine-grained manipulation of specific visual elements presents a challenge for current diffusion-based methods. In this work, we present BlobCtrl, a framework for element-level image editing based on a probabilistic blob-based representation. Treating blobs as visual primitives

Valcho Milchev

This article examines the tilings of a strip with equilateral triangles. The number of ways in which the lattices can be covered with a combination of tiles of the two types of triangles is related to Pell's numbers. Additionally, the question of the number of tiles required for all possible tilings - both the number of tiles in total and by type - is develo

Johan Edstedt

The gold-standard for robustly estimating relative pose through image matching is RANSAC. While RANSAC is powerful, it requires setting the inlier threshold that determines whether the error of a correspondence under an estimated model is sufficiently small to be included in its consensus set. Setting this threshold is typically done by hand, and is difficul

Marta Grzeskiewicz

Determining consumer preferences and utility is a foundational challenge in economics. They are central in determining consumer behaviour through the utility-maximising consumer decision-making process. However, preferences and utilities are not observable and may not even be known to the individual making the choice; only the outcome is observed in the form

Dillon Bowen, Ann-Kathrin Dombrowski, Adam Gleave, Chris Cundy

The rapid advancement of AI systems has raised widespread concerns about potential harms of frontier AI systems and the need for responsible evaluation and oversight. In this position paper, we argue that frontier AI companies should report both pre- and post-mitigation safety evaluations to enable informed policy decisions. Evaluating models at both stages

Vincent Herrmann, Róbert Csordás, Jürgen Schmidhuber

Detecting when a neural sequence model does "interesting" computation is an open problem. The next token prediction loss is a poor indicator: Low loss can stem from trivially predictable sequences that are uninteresting, while high loss may reflect unpredictable but also irrelevant information that can be ignored by the model. We propose a better metric: mea

Thomas Monninger, Md Zafar Anwar, Stanislaw Antol, Steffen Staab

Autonomous driving requires understanding infrastructure elements, such as lanes and crosswalks. To navigate safely, this understanding must be derived from sensor data in real-time and needs to be represented in vectorized form. Learned Bird's-Eye View (BEV) encoders are commonly used to combine a set of camera images from multiple views into one joint late

Nhi Pham, Artur Jesslen, Bernt Schiele, Adam Kortylewski

With the rise of deep neural networks, especially in safety-critical applications, robustness and interpretability are crucial to ensure their trustworthiness. Recent advances in 3D-aware classifiers that map image features to volumetric representation of objects, rather than relying solely on 2D appearance, have greatly improved robustness on out-of-distrib

Aaron Held, Hyun Lim

We report on the first numerical-relativity simulations of black-hole binaries that deviate from General Relativity due to quadratic-curvature corrections. Said theory of Quadratic Gravity propagates additional massive modes and admits both Kerr and non-Kerr black-hole solutions. We chose the respective masses "at threshold", i.e., such that (at least) one o