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Much attention has been devoted to understanding the microscopic pathways of phase transition between two equilibrium condensed phases (such as liquids and solids). However, the microscopic pathways between non-equilibrium, non-diffusive…

Chemical Physics · Physics 2024-02-27 Gadha Ramesh , Ved Mahajan , Debasish Koner , Rakesh S. Singh

Non-equilibrium aspects of the BCS model have fascinated physicists for decades, from the seminal works of Eliashberg to modern realizations in cold atom experiments. The latter scenarios have lead to a great deal of interest in the quench…

Superconductivity · Physics 2021-03-12 Colin Rylands , Victor Galitski

We develop an unsupervised machine learning approach to classify disordered phases in a system of oppositely charged colloids. In this system, the interplay between Coulomb and van der Waals interactions leads to transitions in local…

Soft Condensed Matter · Physics 2025-08-26 Yoshitaka Miyahara , Taiki Haga

Understanding the way disordered particle packings transition between jammed (rigid) and unjammed (fluid) states is of both great practical importance and strong fundamental interest. The values of critical packing fraction (and other state…

Soft Condensed Matter · Physics 2026-04-14 Sangwoo Kim , Sascha Hilgenfeldt

We introduce a new approach for decoupling trends (drift) and changepoints (shifts) in time series. Our locally adaptive model-based approach for robustly decoupling combines Bayesian trend filtering and machine learning based…

Methodology · Statistics 2024-01-09 Haoxuan Wu , Toryn L. J. Schafer , Sean Ryan , David S. Matteson

We investigate the two-dimensional melting of deformable polymeric particles with multi-body interactions described by the Voronoi model. We report machine learning evidence for the existence of the intermediate hexatic phase in this…

Soft Condensed Matter · Physics 2022-03-11 Wei-chen Guo , Bao-quan Ai , Liang He

We apply various unsupervised machine learning methods for phase classification to investigate the finite-temperature phase diagram of the spinless Falicov-Kimball model in two dimensions. Using only particle occupation snapshots from Monte…

Strongly Correlated Electrons · Physics 2025-05-27 Lukáš Frk , Pavel Baláž , Elguja Archemashvili , Martin Žonda

The kinetic exchange opinion model shows a well-studied order disorder transition as the noise parameter, representing discord between interacting agents, is increased. A further increase in the noise drives the model, in low dimensions, to…

We study the maximum mean discrepancy (MMD) in the context of critical transitions modelled by fast-slow stochastic dynamical systems. We establish a new link between the dynamical theory of critical transitions with the statistical aspects…

Pattern Formation and Solitons · Physics 2019-01-30 Boumediene Hamzi , Christian Kuehn , Sameh Mohamed

We obtain the steady-state phase diagram of a transverse field XY spin chain coupled at its ends to magnetic reservoirs held at different magnetic potentials. In the long-time limit, the magnetization bias across the system generates a…

Mesoscale and Nanoscale Physics · Physics 2021-01-13 Tharnier O. Puel , Stefano Chesi , Stefan Kirchner , Pedro Ribeiro

We analytically and numerically study the Loschmidt echo and the dynamical order parameters in a spin chain with a deconfined phase transition between a dimerized state and a ferromagnetic phase. For quenches from a dimerized state to a…

Statistical Mechanics · Physics 2020-09-10 Gaoyong Sun , Bo-Bo Wei

Using numerical data coming from Monte Carlo simulations of four-dimensional Causal Dynamical Triangulations, we study how automated machine learning algorithms can be used to recognize transitions between different phases of quantum…

High Energy Physics - Lattice · Physics 2026-05-26 Jan Ambjorn , Zbigniew Drogosz , Jakub Gizbert-Studnicki , Andrzej Görlich , Dániel Németh , Marcus Reitz

In nonlinear dynamical systems, tipping refers to a critical transition from one steady state to another, typically catastrophic, steady state, often resulting from a saddle-node bifurcation. Recently, the machine-learning framework of…

Chaotic Dynamics · Physics 2026-04-09 Smita Deb , Zheng-Meng Zhai , Mulugeta Haile , Ying-Cheng Lai

We have investigated the mean field dynamics of an overdamped viscoelastic medium driven through quenched disorder. The model introduced incorporates coexistence of pinned and sliding degrees of freedom and can exhibit continuous elastic…

Disordered Systems and Neural Networks · Physics 2009-10-31 M. Cristina Marchetti , A. Alan Middleton , Thomas Prellberg

By modeling quantum chaotic dynamics with ensembles of random operators, we explore howmachine learning learning algorithms can be used to detect pseudorandom behavior in qubit systems.We analyze samples consisting of pieces of correlation…

Quantum Physics · Physics 2020-08-27 Daniel W. F. Alves , Michael O. Flynn

An unconventional magnet may be mapped onto a simple ferromagnet by the existence of a high-symmetry point. Knowledge of conventional ferromagnetic systems may then be carried over to provide insight into more complex orders. Here we…

Computational Physics · Physics 2021-07-28 Nihal Rao , Ke Liu , Lode Pollet

We consider the patterns of collective motion emerging when many aligning, self-propelling units move in two dimensions while interacting through a repulsive potential and are also subject to delays and random perturbations. In this…

Soft Condensed Matter · Physics 2023-11-14 Fatemeh Pakpour , Tamás Vicsek

We consider a two-dimensional system of elongated particles driven over a random quenched disorder landscape. For varied pinning site density, external drive magnitude, and particle elongation, we find a wide variety of dynamic phases,…

Soft Condensed Matter · Physics 2024-04-23 A. Libal , S. Stepanov , C. Reichhardt , C. J. O. Reichhardt

The design of reliable indicators to anticipate critical transitions in complex systems is an im portant task in order to detect a coming sudden regime shift and to take action in order to either prevent it or mitigate its consequences. We…

Data Analysis, Statistics and Probability · Physics 2022-12-14 Martin Heßler , Oliver Kamps

We study the order-disorder transition in a collection of polar self-propelled particles, interacting through a distance dependent short range alignment interaction. A distance dependent interaction parameter $a_0$ is introduced such that…

Statistical Mechanics · Physics 2016-12-13 Sudipta Pattanayak , Shradha Mishra