Phase Transitions

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Overview

Phase-transition research studies how many interacting parts can shift together from one kind of behavior to another, and why these changes matter for predicting material properties, collective dynamics, and learning systems. Researchers use order parameters, susceptibility, finite-size scaling, and renormalization-group methods to locate critical points and test whether different systems share universal behavior. Neural networks, active learning, persistent homology, and physics-informed simulators extend these tools to settings such as Ising and percolation models, quantum systems, and training dynamics. A central challenge is distinguishing genuine critical transitions from smooth crossovers or finite-size effects, especially in noisy, non-equilibrium systems where standard equilibrium theory may not apply.

Latest papers

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69 papers6 papers in the last four weeks, up 100% on the four weeks before. 0.0% of all new papers.

  1. Ammonia-Hydrogen Phase Equilibria in Planetary Envelopes from First-Principles-Based Machine-Learning Molecular Dynamics

    Oct 19, 2026Akash Gupta, Austin Guo, Jie DengPhase Transitions

    Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544, USA · Department of Geosciences, Princeton University, Princeton, NJ 08544, USA

  2. Sampling the XY model with an attention-based neural network

    Oct 16, 2026Piotr Białas, Christian D. Morales, Tomasz Stebel +1Boltzmann SamplingAutoregressive Transformer

    Institute of Applied Computer Science, Jagiellonian University, ul. Łojasiewicza 11, 30-348 Kraków, Poland · V. N. Karazin Kharkiv National University, 6 Nezalezhnosti Ave, Kharkiv 61022, Ukraine · Institute of Theoretical Physics, Jagiellonian University, ul. Łojasiewicza 11, 30-348 Kraków, Poland +1

  3. The Blume-Capel Model as a φ6φ^6 Field Theory: A Monte Carlo and Flow Model Study

    Oct 14, 2026Ejaaz Merali, Ryan Larson, Ehsan Khatami +1Phase TransitionsNormalizing Flows

    Department of Physics and Astronomy, University of California, Davis, CA 95616, USA · Department of Physics and Astronomy, San José State University, San José, CA 95192 USA

  4. Honeycomb Crystal in a Mass-Asymmetric Electron-Hole Bilayer

    Oct 12, 2026Shengdu Chai, Wangqian Miao, Yuqiang Li +3Quantum Many-Body PhysicsPhase Transitions

    Interdisciplinary Center for Theoretical Physics and Information Sciences (ICTPIS), Fudan University, Shanghai 200433, China · Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China · Department of Physics, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China +3

  5. Learning ab initio phase-field models

    Oct 1, 2026Mengyi Chen, Peichen Zhong, Zihan Zhang +1Phase Transitions

    Department of Mathematics, National University of Singapore, Singapore · Department of Materials Science and Engineering, National University of Singapore, Singapore · Institute for Functional Intelligent Materials, National University of Singapore, Singapore

  6. Absorbing State Phase Transitions in Multi-Agent Search

    Sep 29, 2026Wenwen Zheng, Yuzhe Yang, Helen Qu +2Phase TransitionsMulti-Agent Systems

    Flatiron Institute

  7. Sharp Critical Minimax Laws and No-Learning Thresholds in Continuous-Time Adaptive Control

    Sep 27, 2026Chen JiaAdaptive ControlStochastic Optimal Control

  8. Agentic Limit Order Books: Phase Transitions and Market Impact

    Sep 25, 2026Jan RosenzweigLimit Order Book ModelingPhase Transitions

  9. Phases in a class of associative memories via hidden neurons

    Sep 10, 2026Toshihiro Ota, Masato TakiPhase TransitionsHopfield Networks

    CyberAgent AI Lab, Shibuya, Tokyo 150–0002, Japan · RIKEN iTHEMS, Wako, Saitama 351–0198, Japan · Graduate School of Artificial Intelligence and Science, Rikkyo University, Toshima, Tokyo 171–8501, Japan

  10. Universality and sharp thresholds for ellipsoid fitting

    Aug 27, 2026Frederic Koehler, Youngtak SohnPhase Transitions

    Department of Statistics and Data Science Institute, University of Chicago. · Division of Applied Mathematics, Brown University

  11. Neural Renormalization Group Flow for Percolation

    Aug 27, 2026Anaclara Alvez, Luca Camagna, Sergio Chibbaro +4Phase Transitions

    LISN, AO team, Bˆat 660 Universit´e Paris-Saclay, Orsay Cedex 91405 · Inria Saclay - Tau team, Bˆat 660 Universit´e Paris-Saclay, Orsay Cedex 91405

  12. Dynamical phase selection controls compute scaling in looped transformers

    Aug 27, 2026Gunn KimCritical Slowing DownInference-Time Scaling

    Department of Physics, Sejong University, Seoul 05006, Republic of Korea

  13. Composition-Driven Phase Evolution in Sm-Doped BiFeO3 via Latent-Field Reconstruction of Atomically Resolved STEM Data

    Aug 20, 2026Newsha Javanmardi, Christopher T. Nelson, Anna N. Morozovska +3Materials ScienceMicroscopy Image Analysis

    Department of Materials Science and Engineering, University of Tennessee, Knoxville, Tennessee 37996, USA · Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA · Institute of Physics, National Academy of Sciences of Ukraine, 46 Nauky Avenue, Kyiv 03028, Ukraine +2

  14. Absence of critical scaling in the Schelling segregation model

    Aug 17, 2026Mouhssine RifakiPhase TransitionsAgent-Based Modeling

    Stanford University, Stanford, CA 94305, USA

  15. Demons on a Budget: Adaptive Measurement Placement at the Entanglement Phase Transition

    Aug 16, 2026Rohan PandeyPhase Transitions

    Independent researcher

  16. Universal Thermodynamic Interatomic Potentials for Crystalline Materials

    Aug 14, 2026Juno Nam, Bowen Deng, Xiaochen Du +3Computational Materials ScienceFree Energy Calculation

    Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA · Fundamental AI Research, Meta, San Francisco, CA 94105, USA

  17. Non-Shattering at and Above the Dynamical Temperature in the Spherical Pure p-Spin Model

    Aug 14, 2026Taegyun KimPhase TransitionsMean-Field Theory

  18. Data Driven Equation Discovery for Phase-Ordering Dynamics : From Allen Cahn to the Ising Model

    Aug 4, 2026Partha Sarathi Mondal, Manav Kumar Jalan, Anish Kumar +1Sparse Identification of Nonlinear DynamicsPDE Discovery

    Department of Physics, Indian Institute of Technology (BHU) Varanasi, India 221005

  19. The Kinetics of Training: A Driven-Nucleation Rate Law for Emergence, Plasticity Loss, and Circuit Control in Language Models

    Jul 29, 2026Lei DongLoss of PlasticityPhase Transitions

    Independent Researcher

  20. Teacher Knows It Best: Spontaneous Symmetry Breaking and Tipping Points in Networked Langevin Dynamics AI Sycophancy

    Jul 27, 2026Sayantari Ghosh, Saumik Bhattacharya, Partha Pratim ChakrabartiLLM SycophancyLangevin Dynamics

    National Institute of Technology Durgapur, Durgapur, India · Indian Institute of Technology Kharagpur, Kharagpur, India

  21. Weight-Space Physics: Interpretable Hypernetworks for Lattice Quantum Field Theories

    Jul 8, 2026Tobias Göbel, Julian R. Ebelt, Zier Mensch +2Phase TransitionsNeural Network Interpretability

    Institute of Physics, University of Amsterdam, Amsterdam, Netherlands · Department of Physics, National Taiwan University, Taipei, Taiwan · Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA +2

  22. Grokking Is Conditional and Fragile: A Fully-Tractable, Multi-Seed Study at 12K Parameters

    Jul 6, 2026Yoshiyuki OotaniPhase TransitionsML Reproducibility

    Independent Researcher

  23. Broken Ergodicity and the Violation of the Fluctuation-Dissipation Theorem Lead to Generalization Beyond Overfitting in Machine Learning

    Jul 5, 2026Chan Li, Nigel GoldenfeldDynamical Mean-Field TheoryStatistical Physics of Learning

    Department of Physics, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA. · Halıcıoğlu Data Science Institute, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA

  24. MatPhaseBench: A Semantics-Guided Benchmark for Materials Phase Diagrams Understanding

    Jul 3, 2026Hanwen Wang, Sihan Liang, Zhiwei Liu +4VLM EvaluationAI for Science

    Computer Network Information Center, Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing, China · University of Manchester Manchester, UK · Institute of Metal Research, Chinese Academy of Sciences Shenyang, China +1

  25. World-Model Collapse as a Phase Transition

    Jun 30, 2026Xinyuan Song, Zekun CaiPhase TransitionsModel Collapse

    Emory University, Atlanta, GA, USA · The University of Tokyo, Tokyo, Japan · LocationMind, Tokyo, Japan

  26. Data-Driven Energy-Based Learning via Gibbs Measures on Hierarchical Structures

    Jun 29, 2026L. U. Abdullaev, F. Herrera, U. A. Rozikov +1Statistical Physics of LearningPhase Transitions

    National University of Singapore, Singapore · Department of Computer Science and Artificial Intelligence, University of Granada, E-18071 Granada, Spain · V.I. Romanovskiy Institute of Mathematics, Uzbekistan Academy of Sciences, 9, Universitet str., 100174, Tashkent, Uzbekistan +3

  27. MeGAS: Thermomechanical Dynamic Gaussian Splatting for Thermophysical Scene Editing

    Jun 22, 2026Zesong Yang, Yuanhang Lei, Liyuan Cui +63D Gaussian Splatting3D Scene Editing

    State Key Laboratory of CAD&CG, Zhejiang University · University of British Columbia

  28. Noise-Driven Escape from Metastable Phases explains Grokking in Deep Neural Networks

    Jun 15, 2026Ibrahim Talha Ersoy, Karoline WiesnerStatistical Physics of LearningNeural Network Generalization

    Complexity Science Group, Institute of Physics and Astronomy, University of Potsdam, Potsdam, Germany

  29. Phase Transition in Convex Relaxations for Graph Alignment

    Jun 14, 2026Laurent Massoulié, Sushil Mahavir Varma, Louis Vassaux +1Convex RelaxationPhase Transitions

    INRIA, DI/ENS, PSL Research University, Paris, France · Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan, USA. · CNRS, INRIA, Universit´e Paris Dauphine, Paris, France

  30. The Geometry of Phase Transitions in Generative Dynamics via Projection Caustics

    Jun 11, 2026Ryosuke Sakamoto, Kotaro SakamotoDiffusion SamplingPhase Transitions

    Institute for the Advanced Study of Human Biology, Institute for Advanced Study, Kyoto University · Graduate School of Engineering, The University of Tokyo