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We propose a tensor-network algorithm for discrete-time stochastic dynamics of a homogeneous system in the thermodynamic limit. We map a $d$-dimensional nonequilibrium Markov process to a $(d+1)$-dimensional infinite tensor network by using…

Statistical Mechanics · Physics 2016-06-29 Yoshihito Hotta

Learning the network structure of a large graph is computationally demanding, and dynamically monitoring the network over time for any changes in structure threatens to be more challenging still. This paper presents a two-stage method for…

Applications · Statistics 2010-11-09 Nicholas A. Heard , David J. Weston , Kiriaki Platanioti , David J. Hand

Two-dimensional (2D) turbulence, despite being an idealization of real flows, is of fundamental interest as a model of the spontaneous emergence of order from chaotic flows. The emergence of order often displays critical behavior, whose…

Fluid Dynamics · Physics 2025-03-21 Filip Novotný , Marek Talíř , Šimon Midlik , Emil Varga

We study the nonequilibrium phase transition in a model of aggregation of masses allowing for diffusion, aggregation on contact and fragmentation. The model undergoes a dynamical phase transition in all dimensions. The steady state mass…

Statistical Mechanics · Physics 2015-06-25 Satya N. Majumdar , Supriya Krishnamurthy , Mustansir Barma

We obtain explicit expressions for the long range correlations in the ABC model and in diffusive models conditioned to produce an atypical current of particles.In both cases, the two-point correlation functions allow to detect the…

Statistical Mechanics · Physics 2011-11-29 T. Bodineau , B. Derrida , V. Lecomte , F. van Wijland

We construct the finite-temperature dynamical phase diagram of the fully connected transverse-field Ising model from the vantage point of two disparate concepts of dynamical criticality. An analytical derivation of the classical dynamics…

Statistical Mechanics · Physics 2018-05-07 Johannes Lang , Bernhard Frank , Jad C. Halimeh

Understanding the inductive bias and generalization properties of large overparametrized machine learning models requires to characterize the dynamics of the training algorithm. We study the learning dynamics of large two-layer neural…

Machine Learning · Statistics 2025-10-30 Andrea Montanari , Pierfrancesco Urbani

Scaling ideas and renormalization group approaches proved crucial for a deep understanding and classification of critical phenomena in thermal equilibrium. Over the past decades, these powerful conceptual and mathematical tools were…

Statistical Mechanics · Physics 2017-03-29 Uwe C. Täuber

Biology achieves novel functions like error correction, ultra-sensitivity and accurate concentration measurement at the expense of free energy through Maxwell Demon-like mechanisms. The design principles and free energy trade-offs have been…

Molecular Networks · Quantitative Biology 2016-05-27 Arvind Murugan , Suriyanarayanan Vaikuntanathan

The precise determination of critical point is the basis to extract various critical properties of phase transitions. We identify that for two-dimensional inversion asymmetric insulators, with and without time-reversal symmetry, when…

Mesoscale and Nanoscale Physics · Physics 2018-12-07 Zhongbo Yan

In order to develop systems capable of artificial evolution, we need to identify which systems can produce complex behavior. We present a novel classification method applicable to any class of deterministic discrete space and time dynamical…

Artificial Intelligence · Computer Science 2021-08-04 Barbora Hudcová , Tomáš Mikolov

Gapped fracton phases of matter generalize the concept of topological order and broaden our fundamental understanding of entanglement in quantum many-body systems. However, their analytical or numerical description beyond exactly solvable…

Strongly Correlated Electrons · Physics 2023-05-30 Guo-Yi Zhu , Ji-Yao Chen , Peng Ye , Simon Trebst

Using numerical simulations of a model disk system, we demonstrate that a machine learning generated order parameter can detect depinning transitions and different dynamic flow phases in systems driven far from equilibrium. We specifically…

Statistical Mechanics · Physics 2024-04-23 D. McDermott , C. J. O. Reichhardt , C. Reichhardt

In a Nature article, Scheffer et al. presented a novel data-driven framework to predict critical transitions in complex systems. These transitions, which may stem from failures, degradation, or adversarial actions, have been attributed to…

Optimization and Control · Mathematics 2022-08-09 Mohammad Pirani , Saber Jafarpour

Phase transitions are a fundamental concept in science describing diverse phenomena ranging from, e.g., the freezing of water to Bose-Einstein condensation. While the concept is well-established in equilibrium, similarly fundamental…

We investigate two types of dynamical quantum phase transitions (DQPTs) in the transverse field Ising model on ensembles of Erd\H{o}s-R\'enyi networks of size $N$. These networks consist of vertices connected randomly with probability $p$…

Quantum Physics · Physics 2025-06-24 Tomohiro Hashizume , Felix Herbort , Joseph Tindall , Dieter Jaksch

Topological invariants have proved useful for analyzing emergent function as they characterize a property of the entire system, and are insensitive to local details, disorder, and noise. They support boundary states, which reduce the system…

Statistical Mechanics · Physics 2025-10-10 Jaime Agudo-Canalejo , Evelyn Tang

We review a dynamical approach to non-equilibrium MD (D-NEMD). We show how, using a proper simulation setup, is possible to treat interesting cases in which the initial condition is a stationary non-equilibrium state produced by a suitable…

Computational Physics · Physics 2015-05-27 Sergio Orlandini , Simone Meloni , Giovanni Ciccotti

The dynamics of a one-dimensional stochastic system of classical particles consisting of asymmetric death and branching processes is studied. The dynamical activity, defined as the number of configuration changes in a dynamical trajectory,…

Statistical Mechanics · Physics 2015-06-22 Pegah Torkaman , Farhad H. Jafarpour

The study of many-body quantum systems out of equilibrium remains a significant challenge with complexity barriers arising in both state and operator-based representations. In this work, we review recent approaches based on finding better…

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