April 2026 arXiv papers — page 33

Georgia Channing, Debora Keller, Marta D. Rossell, Philip Torr

The transmission electron microscope facilitates the highest-resolution imaging of any instrument ever created, and its limiting factor is no longer spatial resolution but dose efficiency. Low electron doses avoid sample damage but produce noisy images for which, unlike in classical computer vision, there is no ground truth. Autonomous materials experimentat

Kush Grover, Pratham Gupta, Jan Křetínský

We introduce a new family of temporal logics intended for specifications in motion planning (MP). It builds upon the signal temporal logic (STL), which is a linear-time logic over real-valued signals that possess quantitative semantics and thus became popular in the areas of cyber-physical systems, robotics, and specifically robot MP. However, in contrast to

Eva Krueger, Marcus Rosette, Joseph R. Davidson

Robotic fruit harvesting often fails to reliably detect whether a fruit has been successfully picked, limiting efficiency and increasing crop damage. This problem is difficult due to compliant fruit and grippers, variable stem attachment, and occlusions in orchard environments. Prior work has explored vision-based perception and multi-sensor learning approac

Feliks Bańka, Jarosław A. Chudziak

Decision-making under changing conditions remains a fundamental challenge in many real-world systems. Existing approaches often fail to generalize across shifting regimes and exhibit unstable behavior under uncertainty. This raises the research question: can retrieval-augmented LLM coordination improve the robustness of modular decision pipelines? We propose

Yuehao Bai, Kirill Ponomarev, Andres Santos, Azeem M. Shaikh

This paper considers the problem of testing whether there exists a solution satisfying certain non-negativity constraints to a linear system of equations. Importantly and in contrast to some prior work, we allow all parameters in the system of equations, including the slope coefficients, to be unknown. For this reason, we describe the linear system as having

Nantel Bergeron, Lucas Gagnon, Hunter Spink, Vasu Tewari

We construct a complex of toric varieties we call the quasisymmetric Grassmannian inside the Grassmannian of $r$-planes in $\mathbb{C}^n$. Each irreducible component is a positroid variety and an $S_n$ translate of a toric Richardson variety of ribbon shape. We describe it as the vanishing locus of equations $\Delta_A\Delta_{A'}=0$ in Pl\"ucker coordinates d

Emaan Bilal Khan, Amy Winecoff, Miranda Bogen, Dylan Hadfield-Menell

Foundation models are routinely fine-tuned for use in particular domains, yet safety assessments are typically conducted only on base models, implicitly assuming that safety properties persist through downstream adaptation. We test this assumption by analyzing the safety behavior of 100 models, including widely deployed fine-tunes in the medical and legal do

Lizvette Villafaña, Tommaso Treu, Shu Wang, Misty C. Bentz

The virial coefficient ($f$), which is meant to encapsulate broad-line region (BLR) geometry and kinematics, remains one of the largest sources of systematic uncertainty in black hole mass estimates for Active Galactic Nuclei (AGNs). While the use of a sample average $\langle f \rangle$ enables black hole mass estimates across large samples and cosmological

Adem Limani

These lecture notes are devoted to selected topics related to the uncertainty principle in harmonic analysis. Rather than attempting a systematic treatment, we emphasize only a number of both classical and deep manifestations of this principle, mainly from the perspective of Fourier analysis on the unit circle and on the real line. We consider problems of un

R. Middei, E. Piconcelli, E. Nardini, A. Marinucci

The analysis of X-ray absorption features in active galactic nuclei (AGN) provides a wealth of information about the physical properties of the matter surrounding supermassive black holes (SMBHs). While standard correlations between the ionisation state, column density, and velocity typically distinguish between disc winds and warm absorbers, some sources ex

Magnus Carlson

We show that isomorphisms of fundamental groups of elementary anabelian varieties -- varieties obtained as iterated fibrations of hyperbolic curves -- over sub-$p$-adic fields correspond bijectively to isomorphisms of varieties. Moreover, dominant maps between proper elementary anabelian varieties are in bijection with ``stably cohomologically injective'' ma

Kisung You

Hyperbolic space is increasingly used for hierarchical, tree-like, and network-structured data, but likelihood-based density modeling on hyperbolic space remains relatively limited. This paper develops finite mixture modeling with isotropic Riemannian Gaussian distributions on hyperbolic space under the hyperboloid model. We derive the density, radial normal

Antoine P. Leeman, Shuyu Zhan, Melanie N. Zeilinger, Glen Chou

We propose VISION-SLS, a method for nonlinear output-feedback control from high-resolution RGB images which provides robust constraint satisfaction guarantees under calibrated uncertainty bounds despite partial observability, sensor noise, and nonlinear dynamics. To enable scalability while retaining guarantees, we propose: (i) a learned low-dimensional obse

Nikesh Subedi, Loris Bazzani, Ziad Al-Halah

In episodic memory with natural language queries (EM-NLQ), a user may ask a question (e.g., "Where did I place the mug?") that requires searching a long egocentric video, captured from the user's perspective, to find the moment that answers it. However, queries can be ambiguous or incomplete, leading to incorrect responses. Current methods ignore this key as

Oscar Veenema, Niranjan Thatte, Dimitra Rigopoulou, Ismael García-Bernete

We present a detailed study of the inner regions of NGC~7582, a nearby Seyfert~2 galaxy, from the Galaxy Activity, Torus and Outflow Survey (GATOS). The galaxy hosts a circumnuclear star-forming disk and an AGN-driven biconical ionised outflow. Using JWST NIRSpec and MIRI/MRS integral-field spectroscopy, we analyse ionic emission lines spanning a wide range

Dario Coscia, Sindy Löwe, Max Welling

Low-Rank Adaptation (LoRA) has become the standard for fine-tuning large pre-trained models at reduced computational cost. However, its low-rank point-estimate updates limit expressiveness, leave a persistent gap relative to full fine-tuning accuracy, and provide no built-in uncertainty quantification, limiting its applicability in settings where reliability

Veronica Bitonti, Noah Kravitz

For a fixed positive integer $d$ and a small real $p>0$, sample a $p$-random subset $A \subseteq \mathbb{Z}_{\geq 0}^d$, and let $S:=\langle A \rangle$ be the generalized numerical semigroup generated by $A$. We show that with high probability (as $p \to 0$), the gap set $\mathbb{Z}_{\geq 0}^d \setminus S$ is well approximated by the shifted hyperboloid regi

Enis Golaszewski, Neal Krawetz, Alan T. Sherman, Edward Zieglar

The rapid rise of generative AI has made it easy to create convincing fake media at scale. In response, an industrial coalition has developed the Coalition for Content Provenance and Authenticity (C2PA), a system intended to provide verifiable provenance for digital content. Our research team conducted the first comprehensive, independent security analysis o

Lei-Yi-Nan Liu, Shi-Rong Peng, Ze-Yuan Huang, Xing-Man Wei

Dual-species Rydberg atom arrays extend single-species platforms by introducing competing interaction scales and enhanced quantum fluctuations, enabling phenomena beyond homogeneous settings. In this work, we study the ground-state phase diagram of a one-dimensional dual-species Rydberg atom ladder using large-scale density-matrix renormalization group calcu

Mario Boneberg, Simon Kochsiek, Igor Lesanovsky

Quantum neural networks generalize classical artificial neural networks into the quantum domain. They are formulated as parameterized quantum circuits which are optimized by measuring and minimizing a suitably chosen loss function. The core challenge in understanding, implementing and ultimately using quantum neural networks is that they represent many-body

Maitreya Patel, Jingtao Li, Weiming Zhuang, Yezhou Yang

We introduce an efficient, resolution-agnostic autoregressive (AR) image synthesis approach that generalizes to arbitrary resolutions and aspect ratios, narrowing the gap to diffusion models at scale. At its core is VibeToken, a novel resolution-agnostic 1D Transformer-based image tokenizer that encodes images into a dynamic, user-controllable sequence of 32

Shannon K. Gallagher, Swati Rallapalli, Tyler Brooks, Chuck Loughin

Evolutionary methods have long been useful for analysis and explanation in genetics, biology, ecology, and related fields. In this work, we extend these methods to neural networks, specifically large language models (LLMs), to better analyze and explain relationships among models. We show how relating weights to genotypes and output text to phenotypes can im

Eric Balkanski, Jason Chatzitheodorou, Flore Sentenac

For the classical maximum coverage problem, the greedy algorithm achieves a worst-case $1-1/e$ approximation, which is optimal unless $\text{P} = \text{NP}$. The notion of coverage appears in a wide range of optimization tasks, where empirical evaluations indicate approximation ratios close to $1$ for the greedy algorithm on real data. Random models have pro

Jesse Ward-Bond, Ali Mashadian, Timothy C. Y. Chan, Edmond W. K. Young

Inertial microfluidic devices (IMDs) offer low-cost, high-throughput alternative techniques for many traditional particle- (or cell-) manipulation tasks, but simulating them requires being able to predict particle migration, and thus particle lift forces, under a variety of possible channel geometries. Recent work has demonstrated that machine learning model

Wan Tong Lou, Gino Cassella, Andres Perez Fadon, Halvard Sutterud

We study the zero-temperature phase diagram of the 2D spin-imbalanced Fermi gas with short-ranged attractive interactions using the recently developed neural network variational Monte Carlo method with the AGPs FermiNet Ansatz. The Fulde-Ferrell-Larkin-Ovchinnikov phase is observed in the weakly interacting BCS limit and a polarised superfluid is seen in the

Yoshiyuki Yajima, Sakiko Mishima, Noriyuki Tonami, Tomoyuki Hino

Monitoring sea states across the offshore wind farm areas is essential to keep their structures safe, efficiently operate the systems, and assess the environmental effects of wind turbines. Conventional sea state sensors like buoys limit their observable coverage; therefore, installing many sensors across the wide area is necessary to obtain sufficient sea s

John Seon Keun Yi, Aaron Mueller, Dokyun Lee

Multi-agent debate has been shown to improve reasoning in large language models (LLMs). However, it is compute-intensive, requiring generation of long transcripts before answering questions. To address this inefficiency, we develop a framework that distills multi-agent debate into a single LLM through a two-stage fine-tuning pipeline combining debate structu

Sakiko Mishima, Yoshiyuki Yajima, Noriyuki Tonami, Tomoyuki Hino

This study proposes an anomaly-detection framework for monitoring exposure-length variations in submarine free-span cables using Distributed Acoustic Sensing (DAS), which is one of the distributed fiber-optic sensing technologies. To address environmental variability and limited training data in offshore environments, a regression-based feature extraction me

Jerry Yao-Chieh Hu, Mingcheng Lu, Yi-Chen Lee, Han Liu

We provide a systematic recipe for translating ReLU approximation results to softmax attention mechanism. This recipe covers many common approximation targets. Importantly, it yields target-specific, economic resource bounds beyond universal approximation statements. We showcase the recipe on multiplication, reciprocal computation, and min/max primitives. Th

Nishit Anand, Manan Suri, Christopher Metzler, Dinesh Manocha

Controlling illumination in images is essential for photography and visual content creation. While closed-source models have demonstrated impressive illumination control, open-source alternatives either require heavy control inputs like depth maps or do not release their data and code. We present a fully open-source and reproducible pipeline for learning ill

Yu Xin, Gorkem Can Ates, Jun Ma, Sumin Kim

Text guided 3D medical image segmentation offers a flexible alternative to class based and spatial prompt based models by allowing users to specify regions of interest directly in natural language. This paradigm avoids reliance on predefined label sets, reduces ambiguous outputs, and aligns more naturally with clinical workflows. However, existing text guide

Jayashree Behera, Edward F. Schlafly, Aaron M. Meisner, Lucas Napolitano

We present a new multiband extension to the crowdsource photometric pipeline, enabling simultaneous fitting across multiple imaging bands in crowded fields. The core idea is that multiple images of the same part of the sky should have the same sources at the same locations; only the fluxes in the different images should be allowed to vary in fitting. The fra

Mattia Serrani, Evgeny Skvortsov

Self-dual theories are powerful toy models of their completions. It was shown recently that there are infinitely many SD-theories once massless higher-spin fields are allowed. The maximal SD-theory is chiral higher-spin gravity. Following the recent [arxiv:2602.12176] we show that all SD-theories, including those with massless higher-spin fields, have nontri

Alexandros Gezerlis

This article discusses incorrect statements appearing in textbooks on quantum field theory (QFT); some of these mistakes also appear in the research literature. The focus is not on errors made by an individual author, but on conceptual muddledness that is widespread in introductory textbooks. We start from a bare-bones summary of QFT, meant to establish the

Conrad Strydom, Mark Tame

Quantum random number generation (QRNG) relies on the inherent unpredictability of quantum mechanical phenomena to efficiently generate high-quality random numbers that can be used in a wide range of cryptography and simulation applications. Here we report the experimental demonstration of QRNG from the arrival times of photons emitted by nitrogen vacancy (N

Matthew Chou, Phuong Cao

Post-Quantum Cryptography (PQC) is a rapidly growing deployment challenge as cryptographically relevant quantum computers (CRQC) continue to advance, leaving traditional cryptographic algorithms used in X.509 vulnerable to attack. However, PQC introduces significant deployment challenges in real-world networks, with handshake sizes increasing from 5x to over

Markus Drescher, Laurens Vanderstraeten, Roderich Moessner, Frank Pollmann

The dynamical dimer structure factor is an observable probing spin-singlet excitations of quantum magnets distinct from those commonly studied by the spin structure factor. We report the dimer response for the extended spin-$1/2$ antiferromagnetic Heisenberg model on the triangular lattice using large-scale GPU-accelerated matrix-product-state simulations. W

Han Yan, Jan Harms

Lunar gravitational-wave (GW) detectors relying on the measurement of the response of the Moon to GWs are susceptible to a seismic background, which might pose a fundamental sensitivity limitation. The Lunar Gravitational-wave Antenna (LGWA) was conceived as an array of accelerometers with the idea that data can be processed to distinguish between a GW signa

Marco Benini, Victor Carmona, Alexander Schenkel

This paper revisits the theory of superselection sectors in algebraic quantum field theory from the modern perspective of prefactorization algebras. Under the standard assumptions of Haag duality and a locally faithful vacuum representation, it is shown that every AQFT defined over a filtered orthogonal category of spacetime regions, satisfying some mild add

Marco Benini, Ryan A. Cullinan, Alexander Schenkel, Benoit Vicedo

We propose a general framework for integrable field theories in arbitrary spacetime dimension $d+1$ which is based on $d$-term $L_\infty$-algebras. Specifically, we introduce cyclic $L_\infty$-algebras describing topological-holomorphic higher Chern-Simons theories on $M \times \mathbb{C}P^1$ with suitable singularity structures and boundary conditions, cont

Leon H. Butterworth, Ashley Spindler

We measure the influence of image augmentations and training dataset size when training a deep neural network to classify galaxy morphology. Data augmentation is an integral step when training machine learning models and often astronomers add augmentations assuming they will always improve the performance of their models. We train multiple versions of the sa

Francesco Del Porro, Stefano Liberati, Marc Schneider

We investigate Hawking-like particle production in analogue gravity systems with superluminal modified dispersion relations. For a broad class of even, convex, and polynomially bounded dispersion relations, we show that the relevant outgoing modes are governed by an effective horizon induced by dispersive propagation. Extending the near-horizon S-matrix meth

Yermek Aldabergenov, Wei Lin, Rongjian Li, Ding Ding

We construct a Born-Infeld-type $f(R,{\cal G})$ modification of gravity, where ${\cal G}$ is the Gauss-Bonnet term, by embedding Born-Infeld electrodynamics in a five-dimensional pure modified gravity. This method leads to the correspondence between curvature scalars and electromagnetic field strength scalars -- $R\leftrightarrow F_{μν}F^{μν}$ and ${\cal G}\

Kishore Iyer, Andreas Feuerpfeil, Valentin Crépel, Nicolas Regnault

Fractional Chern insulators (FCIs) are zero magnetic field analogs of fractional quantum Hall states. While the electrons forming an FCI are not subject to an external magnetic field, their anyonic excitations experience a magnetic field with finite-flux due to a many-body Berry phase, whose lattice periodicity generically induces some dispersion. From Laugh

Carlos Payá, César Robles, Pablo San-Jose, Elsa Prada

Tunneling spectroscopy cannot be used as an unambiguous detection tool for Majorana zero modes (MZMs) in conventional partial-shell nanowires. The presence of smooth confinement at the end of the hybrid wire (among other sources of disorder) can create exponentially pinned zero-energy states, called quasi-MZMs, that mimic all local signatures of MZMs but lac

Nerea Gurrutxaga, Vignesh Vaikundaraman, Joanna Drazkowska

Dust growth is a crucial step in planet formation, and the efficiency of this process is controlled by the physical and chemical properties of the dust grains. Monte Carlo-based methods are commonly used to follow the collisional evolution of dust while tracking their properties. However, current Monte Carlo methods in planet formation do not strictly conser

A. Bartolomei, L. Origlia, C. Fanelli, L. Chiappino

In this paper we present the chemical screening of the stellar population belonging to the globular cluster NGC 6553 in the Galactic bulge. This study has been conducted in the contest of the Bulge Cluster Origin (BulCO) survey, an ESO-VLT Large Program currently ongoing with CRIRES in the NIR domain. This survey is performing an unprecedented chemical scree

Apollonas S. Matsoukas-Roubeas, Oscar Scholin, Lucas Sá, Arinjoy De

The development and spread of entanglement in complex quantum systems is central to exploring many-body phenomena out of equilibrium. Measuring entanglement dynamics can shed light on information scrambling and thermalisation, namely on transitions from many-body quantum chaos to localisation in disordered, interacting systems. In quantum computing systems,

Daniel A. Boyea, Julio F. Navarro, Jaclyn Jensen, Raphaël Errani

Most dwarf spheroidal (dSph) satellites of the Milky Way follow exponential surface density profiles that decline sharply in the outer regions. The Sculptor (Scl) and Ursa Minor (UMi) dSphs deviate from this trend and show a clear excess of stars in the outskirts. Individual members have recently been identified as far as ${\sim}10$ effective radii from the

Jade Pasté, Céline Gouin, Nabila Aghanim, Jenny G. Sorce

Galaxy clusters grow through the matter accretion from the cosmic web, mainly along filaments. We aim to characterize the gas accretion onto clusters, focusing on the role of filaments in driving anisotropic inflows and thermodynamic properties, as it remains a key challenge for cosmology. In this study, we analyzed 415 galaxy clusters from the IllustrisTNG-

Anshuman Tripathi, Mircea Trif, Thore Posske

Topological frequency converters exploit a quantized transfer of power between two driving fields in a quantum system, a phenomenon topologically protected by the Chern number of the associated fiber bundle. While realizations with few-spin systems have theoretically demonstrated this effect, the conversion factors have typically been restricted to small int

Hajime Fukuda, Keisuke Harigaya

We present a solution to the strong CP problem in which a simple chiral U(1) gauge symmetry gives rise to an accidental Peccei-Quinn symmetry that is both explicitly and spontaneously broken by mirror QCD dynamics, yielding a framework without massless fermions or a light QCD axion. The model contains no stable domain walls or colored relics, and it accommod

Azin Kazemi-Moridani, Samuele Giuli, Tsung-Han Lee, A. -M. S. Tremblay

We investigate the magnetic phase diagram of the half-filled Hubbard model on the anisotropic triangular lattice using the Gutzwiller approximation (GA) and its ghost generalization (ghost-GA). By combining a rotating spin-frame formulation with high-resolution momentum grids, we determine magnetic ground states through direct total-energy minimization over

Bowen Yang, Matthew Yu

We classify mobile Pauli stabilizer codes up to gapped interfaces and coarse-graining using the framework of algebraic $\mathrm{L}$-theory. We compare this classification with that of framed TQFTs, theories that arise naturally in the continuum, highlighting a close structural relationship between the two. Our approach is formulated in the category of perfec

Suk-Jin Yoon, Inhyuk Park, Woong-Bae G. Zee, Chul Chung

We present a forward-modeling framework for synthesizing Type Ia supernova (SN Ia) populations by coupling cosmological hydrodynamic simulations to binary population synthesis (BPS). Using IllustrisTNG star particles as simple stellar populations, we generate binaries and evolve them with COMPAS to produce synthetic SNe Ia tagged with explosion times and pro

Roberto Tejada Arevalo, Adam Burrows, Ankan Sur, Yubo Su

We present \texttt{ORCHARD}, a publicly available planetary evolution code based on the gas giant evolution code, \texttt{APPLE}, capable of modeling the evolution and structures of terrestrial, super-Earth, sub-Neptune, Neptune, and gas giant planets and exoplanets from 0.5 M$_\oplus$ to 10 M$_J$. It supports not only the inhomogeneous and non-adiabatic evo

Tomasz R. Taylor, Bin Zhu

We study three-gluon scattering amplitudes in global de Sitter spacetime, in the angular momentum basis of SO(1,4) symmetry representations. At the tree level, they are determined by the intertwiner integrals of harmonic one-forms on the three-sphere. We derive a general formula valid for all helicity configurations of incoming and outgoing gluons and expres

Saskia Demulder, Dieter Lust, Carmine Montella, Thomas Raml

Motivated by the Swampland Distance Conjecture, we study distances in field space using the framework of Optimal Transport. The associated optimisation problem naturally leads to a notion of distance in terms of a (generalised) Wasserstein distance between probability distributions over field space. In the absence of dynamical gravity, we relate the transpor

Yale Song, Yiwen Song, Nick Losier, Nathan Hodson

While diffusion models generate high-fidelity video clips, transforming them into coherent storytelling engines remains challenging. Current agentic pipelines automate this via chained modules but suffer from semantic drift and cascading failures due to independent, handcrafted prompting. We present Co-Director, a hierarchical multi-agent framework formalizi

Francesco Moretti, Ulrich Nierste, Pascal Reeck, Matthias Steinhauser

The total decay widths of heavy mesons can be systematically calculated in terms of an expansion in the two parameters $1/m_Q$ and $\alpha_s(m_Q)$, where $Q=c,b$ denotes the heavy quark. The dominant contributions to meson lifetime splittings stem from terms which are suppressed by $1/m_Q^3$ with respect to the leading universal contribution to the total dec

Andreas Stergiou

The three-dimensional cubic conformal field theory governs the critical behaviour of Heisenberg magnets with cubic anisotropy. Studying this theory non-perturbatively is challenging, because its most easily accessible observables are numerically very close to those of the more symmetric $O(3)$ model. In this work, we overcome this difficulty using the fuzzy

Rajeev S. Erramilli

The method of extremal flows has presented an alluring alternative approach to numerically solving bootstrap constraints. Here I present the development and adaptation of that approach to a more general class of flows with apparent discontinuities. I focus on upgrading solutions of gap maximization for the spinning modular bootstrap from low to high numerica

Ethan Baker, Hongwan Liu, Siddharth Mishra-Sharma

We present spectroxide, a code package for computing cosmic microwave background spectral distortions in which all ${\sim}14{,}500$ lines of Rust code, Python interface, and ${\sim}400$ automated tests were written by an AI assistant (Claude Code) under human physicist supervision. The solver evolves the photon Boltzmann equation under Compton scattering, do

Sergio Contreras, Raul E. Angulo, Giovanni Aricò, Lurdes Ondaro-Mallea

Empirical models often rely on key relations from the galaxy--halo connection to construct mock galaxy catalogues. These relations typically describe central galaxies more accurately than satellite galaxies, which are generally less massive and orbit within larger haloes. Satellite galaxies are affected by a variety of physical processes that pose significan

Daniel DeFelippis, Shy Genel, Greg L. Bryan

The circumgalactic medium (CGM) is known to contain multiphase gas in various stages of evolution and interaction with the galaxy. In order to characterize its detailed behavior on short timescales, we use a subregion of the TNG100 cosmological simulation to study the evolution of the $z=1$ CGM around six galaxies in $10^{11.5}-10^{12}$ $M_{\odot}$ halos at

Malcolm Fairbairn, María Olalla Olea-Romacho, Juan Urrutia, Ville Vaskonen

Primordial magnetic fields (PMFs) enhance small-scale structure formation through the Lorentz force acting on baryons, boosting the abundance of low-mass halos and their hosted galaxies. We show that the reionisation history calibrated with the UV luminosity function (UVLF) provides stringent bounds: strong PMFs induce a characteristic double reionisation at

Seyed Hamidreza Mirpoorian, Meng-Xiang Lin, Levon Pogosian

Type Ia supernovae (SNIa) play a central role in constraining the late-time expansion history of the Universe and are directly implicated in current cosmological tensions. Motivated by the possibility of unaccounted redshift-dependent calibration systematics or new physics, we investigate the impact of a phenomenological correction to SNIa magnitudes that sc

Joseph Tindall, Grace M. Sommers, Hilbert Kappen

Recent years have seen a growing interest in the use of belief propagation - an algorithm originally introduced for performing statistical inference on graphical models - for approximate, but highly efficient, tensor network contraction. Here, we detail how to apply generalized belief propagation (GBP) - where messages are passed within a hierarchy of overla

Tingwu Wang, Olivier Dionne, Michael De Ruyter, David Minor

Despite transformative advances in generative motion synthesis, real-time interactive motion control remains dominated by traditional techniques. In this work, we identify two key challenges in bridging research and production: 1) Real-time scalability: Industry applications demand real-time generation of a vast repertoire of motion skills, while generative

Z. Bazzi, M. I. N. Kobayashi, D. Colombo, F. Bigiel

Multiple mechanisms are proposed for the formation of giant molecular clouds (GMCs), from gravitational free-fall caused by self-gravity to stellar feedback-driven gas compression. Both the galactic environment and galaxy conditions could play an additional role in enhancing the formation via their gas surface density and star formation activity. In this pap

Griffin Pitts, Muntasir Hoq, Peter Brusilovsky, Narges Norouzi

Adaptive programming practice often relies on fixed libraries of worked examples and practice problems, which require substantial authoring effort and may not correspond well to the logical errors and partial solutions students produce while writing code. As a result, students may receive learning content that does not directly address the concepts they are

Pietro Dall'Ara

Coordination is an important aspect of innovative contexts, where: the more innovative a course of action, the more uncertain its outcome. To study the interplay of coordination and informational ``complexity'', I embed a beauty-contest game into a complex environment. I identify a new conformity phenomenon. This effect may push towards the exploration of un

Jugal Garg, Shayan Taherijam, Vijay V Vazirani

Our main contribution is a strongly polynomial algorithm for computing an equilibrium for the Arctic Auction, which is the quasi-linear extension of the linear Fisher market model. We build directly on Orlin's strongly polynomial algorithm for the linear Fisher market (Orlin, 2010). The first combinatorial polynomial algorithm for the linear Fisher market wa

Yifei Wang, Yu Zhao, Yingcheng Li, Hao Song

We present a framework for non-Abelian p-loop, fracton, and planon condensation in 3+1 dimensions by constructing extended cage-net fracton models using decoupled layers of the Hu-Geer-Wu (HGW) string-net model. These cage-net models extend the conventional cage-net models based on the Levin-Wen (LW) string-net model in the sense that they inherit the tail d

Jean-François Burnol

We prove that the (suitably rescaled) moments of certain discrete measures on the unit interval, which are related to the numerical evaluation of zeta series with missing digits in radix $b$, are asymptotically $1$-periodic in the base $b$ logarithm of the index, i.e. asymptotically invariant under multiplication by $b$ of the index.

Nontapat Wanwieng, Apimook Watcharangkool

A matter wave propagating through curved spacetime accumulates phase that encodes both geometry and gauge structure. We develop a semiclassical framework for charged spin-$1/2$ matter-wave interferometers based on a WKB expansion of the covariant Dirac equation, in which the phase decomposes into dynamical, spin, and electromagnetic Aharonov-Bohm (AB) contri

Chirag Pabbaraju

While the optimal sample complexity of binary classification in terms of the VC dimension is well-established, determining the optimal sample complexity of multiclass classification has remained open. The appropriate complexity parameter for multiclass classification is the DS dimension, and despite significant efforts, a gap of $\sqrt{\text{DS}}$ has persis

Zhangyong Liang

In this paper, we propose a harmonized rotational gradient method, termed HRGrad, for simultaneously tackling multiscale time-dependent kinetic problems with varying small parameters. These parameters exhibit asymptotic transitions from microscopic to macroscopic physics, making it a challenging multi-task problem to solve over all ranges simultaneously. Sol

Simon Karch, Melissa Will, Irene Prieto Rodriguez, Nikolas Liebster

Locally constrained gauge theories underpin our understanding of fundamental interactions in particle physics and the emergent behaviour of quantum materials. In strongly correlated systems, they can give rise to quantum spin liquids that lack conventional order and are defined by coherent superpositions of an extensive number of many-body configurations. Re

Paul Dario, Diederik van Engelenburg, Christophe Garban

We study the behaviour of four spins systems (the XY model, the Villain model, the XY height function and the integer-valued Gaussian free field) in the presence of a non-elliptic quenched disorder. In the article [DG25], it was shown that the phase transitions of the XY model (the Berezinskii-Kosterlitz-Thouless phase transition in $d = 2$ and the order/dis

Karina Zakharova, Artem Chernikov, Sergey Sysoev

This paper presents an analysis of the applicability of a quantum amplitude redistribution algorithm to the data filtering problem and the results of modeling the algorithm's operation in comparison with a median filter.

Soumyabrata Saha, Jitendra Kethepalli, Benjamin Guiselin, Jacopo De Nardis

We uncover an emergent universality in the large-scale, long-time statistics of a one-dimensional hard-rod gas evolving under two fundamentally different classes of microscopic dynamics: stochastic (diffusive) and unitary (ballistic). Remarkably, despite the difference of the two systems, the one-time joint distribution of the positions of multiple tracers e

Yuxiang Wang, Yu Xiang, Baojian Zhou, Qifang Zhao

Masked diffusion language models (MDMs) have recently emerged as a promising alternative to standard autoregressive large language models (AR-LLMs), yet their optimization can be substantially less stable. We study blockwise MDMs and compare them with AR-LLMs on three controlled tasks that stress different aspects of structured generation: in-context linear

Yousef Mafi, Ali G. Moghaddam, Teemu Ojanen

Combining recent advances in superconducting quantum hardware, we explore quantum correlations in a previously inaccessible regime by observing \emph{simultaneously} high-dimensional and many-body Bell non-locality. We report a high-confidence Bell violation in the correlations between two $d=64$-dimensional systems encoded in twelve qubits. For system sizes

Jason D. Chadwick, Frederic T. Chong

Semiconductor spin qubits are a promising platform for large-scale quantum computing, but have yet to take full advantage of the broad class of quantum low-density parity check (QLDPC) codes, which promise high encoding rates and efficient logic but require nonlocal connectivity between physical qubits. In this work, we investigate the implementation of QLDP

Raz Slutsky

Let $\alpha\colon G\curvearrowright A$ be an action of a countable discrete group on a separable unital $C^*$-algebra. We study the simplex $\mathrm{T}(A)^G$ of $G$-invariant traces and ask when it is Bauer. Our main result is a noncommutative version of the Glasner-Weiss theorem: if $(G,H)$ has relative property (T) and the $H$-action on the von Neumann alg

Nirmit Joshi, Roey Magen, Nathan Srebro, Nikolaos Tsilivis

We study learning with Chain-of-Thought (CoT) supervision from multiple thinkers, all of whom provide correct but possibly systematically different solutions, e.g., step-by-step solutions to math problems written by different thinkers, or step-by-step execution traces of different programs solving the same problem. We consider classes that are computationall

Mikhail Ermakov

A parametric theory of statistical inference is developed for the moderate deviation probability zone. The new approach to the proofs is based on the Taylor series expansion of the logarithm of the likelihood ratio based on the Hellinger distance. The Large Deviation Principle in the moderate deviation probability zone is proven for Bayesian estimators and m

Arthur C. R. Dutra, Roberto D. Baldijão, Marcelo Terra Cunha

The emergence of classicality is fundamentally driven by the interaction between a quantum system and its environment. Foundational open-system approaches, notably the Caldeira-Leggett model, successfully captured how these interactions lead to macroscopic effects like quantum dissipation and decoherence. However, these approaches often leave the precise def

Grayson R. Frazier, Colton Lelievre, Yi Li

In a Josephson junction network, anisotropic coupling between spin triplet pairing correlations can lead to frustrated $d$ vector textures that support spontaneous Josephson currents and nonintegral flux trapping. Such networks can appear in superconducting polycrystals, as well as single-crystal superconductors. In analogy to classical spin systems, in whic

Andrew Putman

Minahan and the author recently proved results that allow the calculation of the second rational cohomology group of the Torelli group. This builds on two key ingredients: Hain's calculation of the image of the cup product pairing on the first cohomology group, and Kupers--Randal-Williams's calculation of the maximal algebraic subrepresentation of the second

Shiliang Zuo

Linear contracts are ubiquitous in practice, yet optimal contract theory often prescribes complex, nonlinear structures. We provide a distributional robustness justification for linear contracts. We study a principal-agent problem where the agent exerts costly effort across multiple tasks, generating a stochastic signal upon which the principal conditions pa

Andrea Bonito, Vivette Girault, Diane Guignard

We study a model describing the slow flow of a fluid through a deformable, porous, elastic solid undergoing small deformations. The stress-strain relationship of the solid incorporates nonlinear effects, formulated as a perturbation of the classical linear elasticity. To approximate the coupled system, we introduce a discrete scheme based on a first order se

Lionel Mulato, Jaroslav Merc, Stéphane Charbonnel, Olivier Garde

The Gaia DR3, released in June 2022, included low-resolution BP/RP (XP) spectra that have been exploited for the classification of various types of emission-line objects using machine-learning techniques. The Gaia Extended Stellar Parametrizer for Emission-Line Stars (ESP-ELS) algorithm identified 273 sources as potential planetary nebulae (PNe). We aim to a

Zijian Guo, İlker Işık, H. M. Sabbir Ahmad, Wenchao Li

Specification-guided reinforcement learning (RL) provides a principled framework for encoding complex, temporally extended tasks using formal specifications such as linear temporal logic (LTL). While recent methods have shown promising results, their ability to generalize across unseen specifications and diverse environments remains insufficiently understood

Muhamad Abdillah Ahen, Ivan Hadinata, Raudhatul Mufizah

In this paper, we introduce the concept of partial extended b-metric spaces (PEBMS) as a unification and generalization of extended b-metric spaces and partial b-metric spaces. This new structure incorporates a point-dependent control function together with the possibility of non-zero self-distance, providing a more flexible framework for the study of genera

Th. K. Mavrogordatos

We propose a contextual cavity/circuit QED analogue and extension of the Stern-Gerlach experiment, where the pseudo-spin of a two-state `atomic' transition plays the role of the ``spin'', while the resonant field driving the transition stands for the ``magnetic field''. A phase-sensitive continuous detection of the cavity field coupled to the induced `atomic

Subramanyam Natarajan

In practical early-stage battery-electric vehicle studies, analysis workflows may become fragmented across spreadsheets, notebooks, and project-specific scripts, making reuse, audit, and extension harder. VEHRON is an open-source Python framework for a deterministic, traceable workflow built around prescribed-speed longitudinal simulation of battery-electric

Ansgar Jüngel, Flora Philipp

The existence of global weak solutions to the compressible Navier-Stokes equations for the density of endothelial cells and their velocity, coupled to a reaction-diffusion equation for the concentration of the chemoattractant, is established in a three-dimensional torus for energy-finite initial data. The coupling of the equations arises through the chemotax

Yiping Liu, Xiaozhe Wang, Geza Joos

Vehicle-to-Grid (V2G) technology allows bidirectional power flow for real-time grid support, making electric vehicles (EVs) well-suited for ancillary services such as frequency regulation. However, existing methods for flexibility estimation and coordinating aggregated EVs often rely on individual EV traveling information (e.g., arrival/departure time) and/o