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6 papers in the last four weeks, up 20% on the four weeks before. 0.1% of all new papers.

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Latest papers 48

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Generative Modeling of Stochastic Dynamics for Long-Time Evolution
Sep 30, 2026Yang-yang Tan, Jinyang Li, Lingxiao WangStochastic Dynamics Statistical Physics
Institute for Physics of Intelligence, Graduate School of Science, The University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan · RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS), Wako, Saitama 351-0198, Japan · KEK Theory Center, Institute of Particle and Nuclear Studies +1
Nonequilibrium Phases of Repulsive Self-Attention: Chaos, Attention Condensation, and Emergent Locality
Sep 23, 2026Qucheng Gao, Zuyi Yang, Xiao ChenAttractors Chaos
Department of Physics, Boston College, Chestnut Hill, Massachusetts 02467, USA
Quantum score matching with applications to learning thermal states
Sep 23, 2026Yulong Dong, Jiaqi LengQuantum Learning Hamiltonian
Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan 48109, USA · Institute for Advanced Computing, Virginia Tech, Alexandria, Virginia 22305, USA · Department of Computer Science, Virginia Tech, Alexandria, Virginia 22305, USA
Blind Thermodynamic Ontology Discovery from Anonymous Experiments
Sep 20, 2026Linzhe Zhang, Changming XuThermodynamics Statistical Physics
Graduate School, Northeastern University.
Graph neural networks for exoplanet atmospheres
Sep 15, 2026Antonia Vojtekova, Kai Hou Yip, Ingo P. Waldmann +4Exoplanet Atmospheres Atmospheric Dynamics
Department of Physics and Astronomy, University College London, Gower Street, WC1E 6BT London, United Kingdom · European Space Agency, ESAC, Camino Bajo del Castillo, 28692, Villanueva de la Cañada, Madrid, Spain · Department of Physics, King’s College London, University of London, Strand, London, WC2R 2LS, United Kingdom +1
A Function-Space Approach to the Statistical Mechanics of Learning Dynamics
Sep 9, 2026Yizhou Zhang, Weichen Wu, Lun Du +1Learning Dynamics Anisotropic Loss Landscapes
Variational AI · The Voleon Group · Independent Researcher +1
Symmetries and Causality: Causal Effect Identification Beyond IID Data
Sep 3, 2026Martin Rabel, Jakob RungeCausal Reasoning Causal
Department of Computer Science, University of Potsdam, Potsdam, Germany
The thermodynamic freedom of a thermodynamic computer
Aug 28, 2026Stephen WhitelamThermodynamics Statistical Physics
Molecular Foundry, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
Physics of Agents: Statistical Mechanics Predicts Collective Behavior of AI Agents
Aug 17, 2026Batu El, Jinhee Paeng, Fatih Dinc +7Collective Behaviors Artificial Intelligence Agents
Stanford University · UC Santa Barbara
Equivariant learning of a transferable three-dimensional classical density functional
Aug 13, 2026Bingqing ChengDensity Functional Theory Statistical Physics
Department of Chemistry, UC Berkeley, California 94720, United States · Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, 94720, United States · Bakar Institute of Digital Materials for the Planet, UC Berkeley, California 94720, United States
Virtual Temperature Sensors in Power Transformers Using Neural Ordinary Differential Equations
Aug 13, 2026Berk Hadzhamolla, Alexander Johannes Stasik, Signe Riemer-SørensenEnergy-Based Transformer Neural Ordinary Differential Equations
University of Oslo, Oslo, 0316, Norway · 2,3 SINTEF AS, Department of Mathematics and Cybernetics, Oslo, Norway · Department of Data Science, Norwegian University of Life Sciences, ˚As, Norway
Interaction Creates Dynamical AI Behavior Absent in Isolation
Aug 7, 2026Bella Xinrui Li, Frank Yingjie Huo, Neil F JohnsonAgent Behavior Modeling Artificial Intelligence Systems
1Physics Department, George Washington University, Washington, DC 20052, USA
Leveraging generative models to assist Monte Carlo sampling
Aug 7, 2026Marylou GabriéGenerative Models Statistical Physics
Laboratoire de Physique Statistique, École normale supérieure, PSL Research University, 24 rue Lhomond, 75005 Paris, France
Statistical Mechanics of Learning on Product Wasserstein Manifolds
Aug 2, 2026Srinivasa Rao P Vangmayi P ReddyQuantum Learning Wasserstein Distance
Curlvee Technolabs, India; Former Scientist, C-DAC.
Exploring Structures in Physics Problems: Can AI Agents Discover Statistical Mechanical Mappings?
Jul 29, 2026Wanyu Zhao, Wanbing ZhaoArtificial Intelligence Agents Statistical Physics
Department of Physics and Astronomy Rice University
Stochastic Counterdiabatic Driving via Biorthogonal Liouvillian Eigenmodes
Jul 27, 2026Sandeep Suresh Cranganore, Sebastian Lehner, Johannes Brandstetter +1Fokker--Planck Equation Statistical Physics
Institute for Machine Learning (Ellis Unit), Johannes Kepler University, Linz · Mistral AI, Paris, France · AMLab, Informatics Institute, University of Amsterdam, The Netherlands +1
Explaining Machine Learning and Memorization with Statistical Mechanics
Jun 30, 2026Robin TheriaultDense Associative Memory Neural Network
Faculty of Science
Learning the structure of open quantum systems
Jun 29, 2026Laura Lewis, Ewin Tang, John WrightQuantum Learning Qubit
UC Berkeley
PhysRAG: Enhancing Physics-Awareness in Video Generation via Retrieval-Augmented Generation
Jun 25, 2026Kexu Cheng, Zicheng Liu, Mingju Gao +2Video Generation Text-To-Video Generation Model
School of Computer Science, Peking University, Beijing, China · Institute of AI for Industries, Chinese Academy of Sciences, Nanjing, China
Statistical Properties of Training & Generalization
Jun 18, 2026Itay Lavie, Noam Levi, Yonatan KahnPhysics-Informed Learning Inductive Bias
John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA · Tel Aviv University, Tel Aviv, Israel · Department of Physics, University of Toronto and Vector Institute, Toronto, ON, Canada
Stochastic Thermodynamics and SDE-based Generative Models
Jun 13, 2026Yaowen ZhangSchrödinger Bridges Statistical Physics
Department of Physics, The Hong Kong University of Science and Technology
Physics of anticipatory active matter, with application to crowd dynamics
Jun 12, 2026Alexis Raulin-Foissac, Alexandre NicolasAgent-Based Model Pedestrian
ILM, UCBL · Université Claude Bernard Lyon 1, Institut Lumière Matière, CNRS, UMR 5306, 69100, Villeurbanne, France · ILM, CNRS
GENERIC-FNO: Embedding Energy Conservation and Entropy Production into Fourier Neural Operators
Jun 6, 2026Jason Sulskis, Sathya RaviFourier Neural Operators Neural Operators
Department of Computer Science University of Illinois at Chicago · Electronic Systems Laboratory, Applied Embedded Systems Division Georgia Tech Research Institute
Capturing non-Markovian dynamics in non-equilibrium stochastic systems using flow matching
Jun 4, 2026Bhargav Sriram Siddani, John B. Bell, Alejandro L. Garcia +1Stochastic Dynamics Stochastic Differential Equations
Lawrence Berkeley National Laboratory · San Jose State University
Reconciling Causality and Non-Equilibrium Thermodynamics with Hamiltonian Causal Models
Jun 3, 2026Dario Rancati, Max Welling, Francesco LocatelloCausal Modeling Causal Reasoning
Institute of Science and Technology Austria · University of Amsterdam
A Kinetic Theory of Encounter-Based Information Propagation in Multi-Robot Systems
Jun 1, 2026Alkesh K. Srivastava, Philip DamesMulti-Robot Systems Statistical Physics
Temple University, Philadelphia, PA, 19122 USA
Ridge Regression from Poisson Resetting: A Renewal Perspective on Spectral Regularization
May 28, 2026Petar JolakoskiKernel Ridge Regression Regularization
Research Center for Computer Science and Information Technologies, Macedonian Academy of Sciences and Arts, Bul. Krste Misirkov 2, 1000 Skopje, Macedonia
Thermodynamic Irreversibility of Training Algorithms
May 21, 2026Liu Ziyin, Yuanjie Ren, Adam Levine +1Irreversibility Statistical Physics
1Massachusetts Institute of Technology · 2NTT Research
Thermodynamic Networks: Harnessing Non-Equilibrium Steady States for Computation
May 15, 2026Patryk Lipka-Bartosik, Gianmichele Blasi, Javier Lalueza Puértolas +3Thermodynamics Statistical Physics
Center for Theoretical Physics, Polish Academy of Sciences, Warsaw, Poland · Instituto de Física Interdisciplinar y Sistemas Complejos IFISC (CSIC-UIB), E-07122 Palma de Mallorca, Spain · Física Teòrica: Informació i Fenòmens Quàntics, Department de Física, Universitat Autònoma de Barcelona, 08193 Bellaterra (Barcelona), Spain +1
The critical slowing down in diffusion models
May 12, 2026Luca Maria Del Bono, Giulio Biroli, Patrick Charbonneau +1Diffusion Models Statistical Physics
Dipartimento di Fisica, Sapienza Università di Roma, Piazzale Aldo Moro 5, Rome 00185, Italy · CNR-Nanotec, Rome unit, Piazzale Aldo Moro 5, Rome 00185, Italy · Laboratoire de Physique Statistique, École normale supérieure, PSL Research University, 24 rue Lhomond, 75005 Paris, France +3
Probing Non-Equilibrium Grain Boundary Dynamics with XPCS and Domain-Adaptive Machine Learning
May 12, 2026Mouyang Cheng, Bowen Yu, Chu-Liang Fu +14X-Ray Photon Correlation Spectroscopy Particle Dynamics
Quantum Measurement Group, MIT, Cambridge, MA 02139, USA · Center for Computational Science and Engineering, MIT, Cambridge, MA 02139, USA · Department of Materials Science and Engineering, MIT, Cambridge, MA 02139, USA +9
Collective Alignment in LLM Multi-Agent Systems: Disentangling Bias from Cooperation via Statistical Physics
May 11, 2026Cristiano De NobiliMulti-Agent Large Language Model Systems Collective Behaviors
Critiqality, Milan, Italy
Kinetic theory for Transformers and the lost-in-the-middle phenomenon
May 9, 2026Mitia Duerinckx, Borjan Geshkovski, Stefano RossiMean-Field Limit Causal Attention
Spherical Boltzmann machines: a solvable theory of learning and generation in energy-based models
May 9, 2026Thomas Tulinski, Simona Cocco, Rémi Monasson +1Statistical Physics Mean-Field Limit
Laboratoire de Physique de l’École Normale Supérieure, PSL, CNRS UMR8023, Sorbonne Université, 24 rue Lhomond, 75005 Paris, France · Institut de Physique Théorique, Université Paris-Saclay,2026 CNRS UMR3681, CEA, Gif-sur-Yvette, France
Higher-Order Equilibrium Tracking for EM-Compressible Online Estimation
May 9, 2026ZhiMing Li, Yue SongState Estimation Latent Variable
School of Computer Science and Technology TianJin University Tianjin 300350, China · College of AI Tsinghua University Beijing 100084, China
Susceptibilities and Patterning: A Primer on Linear Response in Bayesian Learning
May 8, 2026Chris Elliott, Daniel MurfetBayesian Neural Networks Bayesian
Timaeus
Lecture Notes on Statistical Physics and Neural Networks
May 7, 2026Olaf HohmStatistical Physics Spatial Photonic Ising Machines
Institute for Physics, Humboldt University Berlin, Zum Großen Windkanal 2, D-12489 Berlin, Germany
Leveraging Pretrained Language Models as Energy Functions for Glauber Dynamics Text Diffusion
May 5, 2026Tarun Kathuria, Sachin KumarDiffusion Language Models Large Language Model Pretraining
UC Berkeley · Ohio State University
Phase Transitions in Driven Informational Systems: A Two-Field Perspective on Learning Theory and Non-Equilibrium Chemistry
May 5, 2026Truong Xuan KhanhPhase Transitions Statistical Physics
H&K Research Studio, Clevix LLC Hanoi, Vietnam
Active-learning mapping of the Vicsek model phase diagram
Apr 30, 2026Grace T. Bai, Brandon B. LePhase Transitions Statistical Physics
Department of Computer Science, University of Virginia, Charlottesville, Virginia 22904, USA · Department of Physics, University of Virginia, Charlottesville, Virginia 22904, USA
DataCenterGym: A Physics-Grounded Simulator for Multi-Objective Data Center Scheduling
Apr 17, 2026Nilavra Pathak, Samadrita Biswas, Nirmalya RoyData Centers Schedulers
Marketing Data Science, Expedia Group · Analytical Development, Curia Global · Department of Information Systems, University of Maryland, Baltimore County
Emergence of Nonequilibrium Latent Cycles in Unsupervised Generative Modeling
Dec 12, 2025Marco Baiesi, Alberto RossoStatistical Physics Generative Models
Department of Physics and Astronomy, University of Padova, Via Marzolo 8, I-35131 Padova, Italy · INFN, Sezione di Padova, Via Marzolo 8, I-35131 Padova, Italy · LPTMS, CNRS, Universit´e Paris-Saclay, 91405, Orsay, France
Quantum Flow Matching
Aug 17, 2025Zidong Cui, Pan Zhang, Ying TangQubit Quantum Circuits
Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China · Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190, China · School of Fundamental Physics and Mathematical Sciences, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China +3
Emergent interactions lead to collective frustration in robotic matter
Jul 29, 2025Onurcan Bektas, Adolfo Alsina, Steffen RulandsCollective Behaviors Statistical Physics
Arnold-Sommerfeld-Center for Theoretical Physics and Center for NanoSciences, Ludwig-Maximilians-Universität München, Theresienstr. 37, München, 80333, Germany. · Max-Planck-Institute for the Physics of Complex Systems, Noethnitzer Str. 38, Dresden, 01187, Germany. · GISC, Universidad Rey Juan Carlos, c/ Tulip´an s/n, 28933, M´ostoles, Spain.
A statistical physics framework for optimal learning
Jul 10, 2025Francesca Mignacco, Francesco MoriOptimal Learner Stochastic Gradient Descent
1Joseph Henry Laboratories of Physics, Princeton University, Princeton, NJ 08544, USA · 2Graduate Center, City University of New York, New York, NY 10016, USA · Center of Mathematical Sciences and Applications, Harvard University, Cambridge, MA 02138, USA
Local Learning Rules for Out-of-Equilibrium Physical Generative Models
Jun 23, 2025Cyrill Bösch, Geoffrey Roeder, Marc Serra-Garcia +1Statistical Physics Generative Models
Department of Computer Science, Princeton University, Princeton, NJ 08540, USA · AMOLF, Science Park 104, 1098 XG Amsterdam, The Netherlands
Learning thermodynamic master equations for open quantum systems
Jun 2, 2025Peter Sentz, Stanley Nicholson, Yujin Cho +3Quantum Learning Hamiltonian
Department of Data and Decision Sciences, Emory University, Atlanta, GA 30322 · 2Division of Applied Mathematics, Brown University, Providence, RI 02912 · 3Lawrence Livermore National Laboratory, Livermore, CA 94550
Statistical Mechanics of Semantic Compression
Date pendingTankut CanData Compression Methods Statistical Physics
Department of Physics, Emory University, Atlanta, GA

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Generative Modeling of Stochastic Dynamics for Long-Time Evolution

Yang-yang Tan, Jinyang Li, Lingxiao Wang

Institute for Physics of Intelligence, Graduate School of Science, The University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan · RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS), Wako, Saitama 351-0198, Japan · KEK Theory Center, Institute of Particle and Nuclear Studies+1

Stochastic Dynamics Statistical Physics Stochastic Differential Equations Diffusion Dynamics Generative Models Diffusion Models+1

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Exact stochastic equations for non-equilibrium dynamics are rarely accessible. We show that the long-time evolution of stochastic dynamics can be predicted from configuration pairs at a fixed short time lag, without knowledge of the equation of motion. Generative diffusion models learn the finite-time transition kernel from these pairs, and iterating it propagates the dynamics far beyond the training lag. For two-dimensional Model B, the diffusive dynamics of a conserved order parameter, the learned kernels reproduce dynamic critical scaling and self-similar

t^{1/3}

coarsening. Agreement with direct simulations persists on lattices twice the largest training size and for initial ensembles absent from training. For driven colloids in a periodic optical potential, ten minutes of measured trajectories suffice to predict the particle current and mean passage time over the next twenty minutes within experimental uncertainty. Short-time observations thus contain the information needed to predict emergent non-equilibrium dynamics at much longer times.

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