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We develop a machine learning algorithm to infer the emergent stochastic equation governing the evolution of an order parameter of a many-body system. We train our neural network to independently learn the directed force acting on the order…

Disordered Systems and Neural Networks · Physics 2024-12-10 Francesco Carnazza , Federico Carollo , Sabine Andergassen , Georg Martius , Miriam Klopotek , Igor Lesanovsky

The analysis of noise-induced escape in populations of bistable elements is challenging, because nonlinearity, coupling, and noise all play essential roles. We show that the interplay of these three factors yields three qualitatively…

Adaptation and Self-Organizing Systems · Physics 2026-03-06 Hidemasa Ishii , Hiroshi Kori

We integrate machine learning approaches with nonlinear time series analysis, specifically utilizing recurrence measures to classify various dynamical states emerging from time series. We implement three machine learning algorithms Logistic…

Data Analysis, Statistics and Probability · Physics 2024-03-21 Dheeraja Thakur , Athul Mohan , G. Ambika , Chandrakala Meena

We review the depinning and nonequilibrium phases of collectively interacting particle systems driven over random or periodic substrates. This type of system is relevant to vortices in type-II superconductors, sliding charge density waves,…

Superconductivity · Physics 2017-12-06 C. Reichhardt , C. J. Olson Reichhardt

We employ unsupervised learning tools to identify different phases and their transition in quantum systems subject to the combined action of unitary evolution and stochastic measurements. Specifically, we consider principal component…

Statistical Mechanics · Physics 2022-11-03 Xhek Turkeshi

Quantum criticality emerges from the collective behavior of many interacting quantum particles, often at the transition between different phases of matter. It is one of the cornerstones of condensed matter physics, which we access on noisy…

Quantum Physics · Physics 2022-07-14 Maxime Dupont , Joel E. Moore

The competition between scrambling and projective measurements can lead to measurement-induced entanglement phase transitions (MIPT). In this work, we show that the universality class of the MIPT is drastically altered when the system is…

Quantum Physics · Physics 2024-10-04 Hyunsoo Ha , Akshat Pandey , Sarang Gopalakrishnan , David A. Huse

We investigate the lifetime of dynamical regimes under the impact of noise motivated by low-dimensional models of the atmosphere. One may expect that the inclusion of noise tends to make the system leave prescribed regions of the state…

Numerical Analysis · Mathematics 2026-05-01 Henry Schoeller , Robin Chemnitz , Péter Koltai , Maximilian Engel , Stephan Pfahl

Dynamic state and parameter estimation methods for dynamic security assessment in power systems are becoming increasingly important for system operators. Usually, the data used for this type of applications stems from phasor measurement…

Systems and Control · Electrical Eng. & Systems 2022-09-01 Nicolai Lorenz-Meyer , René Suchantke , Johannes Schiffer

Measurement-induced phase transitions (MIPT), characterizing abrupt changes in entanglement properties in quantum many-body systems subjected to unitary evolution with interspersed projective measurements, have garnered increasing interest.…

Quantum Physics · Physics 2024-11-12 Wantao Wang , Shuo Liu , Jiaqiang Li , Shi-Xin Zhang , Shuai Yin

We numerically examine the dynamics of a probe particle driven at a constant force through an assembly of particles with competing long-range repulsion and short-range attraction that forms a bubble or stripe state. In the bubble regime, we…

Soft Condensed Matter · Physics 2025-05-27 C. Reichhardt , C. J. O. Reichhardt

Can activity be transmitted from smaller to larger scales? We report on such a transfer from a homogeneous active medium to a Newtonian spherical probe. The active medium consists of faster and dilute self-propelled particles, modeled as…

Statistical Mechanics · Physics 2025-12-30 Ji-Hui Pei , Christian Maes

We present a numerical study of the phase behavior of repulsively interacting active polar particles that align their active velocities nematically. The amplitude of the active velocity, and the noise in its orientational alignment control…

Soft Condensed Matter · Physics 2019-11-01 Biplab Bhattacherjee , Debasish Chaudhuri

We use numerical simulations and linear stability analysis to study the dynamics of an active liquid crystal film on a substrate in the regime where the passive system would be isotropic. Extensile activity builds up local orientational…

Soft Condensed Matter · Physics 2023-09-26 Fernando Caballero , Zhihong You , M. Cristina Marchetti

The cloud of cold atoms obtained from a magneto-optical trap is known to exhibit two types of instabilities in the regime of high atomic densities: stochastic instabilities and deterministic instabilities. In the present paper, the…

Atomic Physics · Physics 2009-11-10 Daniel Hennequin

Active systems -- including sperm cells, living organisms like bacteria, fish, birds, or active soft matter systems like synthetic ''microswimmers'' -- are characterized by motility, i.e., the ability to propel using their own ''engine''.…

Soft Condensed Matter · Physics 2024-04-09 V. R. Misko , L. Baraban , D. Makarov , T. Huang , P. Gelin , I. Mateizel , K. Wouters , N. De Munck , F. Nori , W. De Malsche

Distinguishing active from passive dynamics is a fundamental challenge in understanding the motion of living cells and other active matter systems. Here, we introduce a framework that combines physical modeling, analytical theory, and…

Analytical formulas for effective drift, diffusivity, run times, and run lengths are derived for an intracellular transport system consisting of a cargo attached to two cooperative but not identical molecular motors (for example, kinesin-1…

Subcellular Processes · Quantitative Biology 2021-01-22 Joseph J. Klobusicky , John Fricks , Peter R. Kramer

Rare transitions between long-lived metastable states underlie a great variety of physical, chemical and biological processes. Our quantitative understanding of reactive mechanisms has been driven forward by the insights of transition state…

Max-min-plus-scaling (MMPS) systems generalize max-plus, min-plus and max-min-plus models with more flexibility in modelling discrete-event dynamics. Especially, implicit MMPS models capture a wide range of real world discrete-event…

Systems and Control · Electrical Eng. & Systems 2026-02-04 Sreeshma Markkassery , Ton van den Boom , Bart De Schutter
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