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Based on dynamical cavity method, we propose an approach to the inference of kinetic Ising model, which asks to reconstruct couplings and external fields from given time-dependent output of original system. Our approach gives an exact…

Statistical Mechanics · Physics 2012-07-24 Pan Zhang

The dynamics of an asymmetric kinetic Ising model is studied. Two schemes for improving the existing mean-field description are proposed. In the first scheme, we derive the formulas for instantaneous magnetization, equal-time correlation,…

Disordered Systems and Neural Networks · Physics 2014-05-23 Haiping Huang , Yoshiyuki Kabashima

We study stationary states in a diluted asymmetric (kinetic) Ising model. We apply the recently introduced dynamic cavity method to compute magnetizations of these stationary states. Depending on the update rule, different versions of the…

Disordered Systems and Neural Networks · Physics 2015-05-20 Erik Aurell , Hamed Mahmoudi

Dynamical mean-field theory is a powerful physics tool used to analyze the typical behavior of neural networks, where neurons can be recurrently connected, or multiple layers of neurons can be stacked. However, it is not easy for beginners…

Disordered Systems and Neural Networks · Physics 2024-02-21 Wenxuan Zou , Haiping Huang

Kinetic Ising models are powerful tools for studying the non-equilibrium dynamics of complex systems. As their behavior is not tractable for large networks, many mean-field methods have been proposed for their analysis, each based on unique…

Disordered Systems and Neural Networks · Physics 2021-05-13 Miguel Aguilera , S. Amin Moosavi , Hideaki Shimazaki

We introduce a new variational approach to the stationary state of kinetic Ising-like models. The approach is based on the cluster expansion of the entropy term appearing in a functional which is minimized by the system history. We rederive…

Statistical Mechanics · Physics 2013-07-26 Alessandro Pelizzola

We use the cavity method to study parallel dynamics of disordered Ising models on a graph. In particular, we derive a set of recursive equations in single site probabilities of paths propagating along the edges of the graph. These equations…

Disordered Systems and Neural Networks · Physics 2025-04-23 I. Neri , D. Bollé

We consider large deviations of the dynamical activity -- defined as the total number of configuration changes within a time interval -- for mean-field and one-dimensional Ising models, in the presence of a magnetic field. We identify…

Statistical Mechanics · Physics 2020-08-26 Jules Guioth , Robert Jack

The dynamics of non-equilibrium Ising model with parallel updates is investigated using a generalized mean field approximation that incorporates multiple two-site correlations at any two time steps, which can be obtained recursively. The…

Disordered Systems and Neural Networks · Physics 2015-06-17 Hamed Mahmoudi , David Saad

In this paper we develop the interpolating cavity field technique for the mean field ferromagnetic p-spin. The model we introduce is a natural extension of the diluted Curie-Weiss model to p>2 spin interactions. Several properties of the…

Statistical Mechanics · Physics 2009-12-31 Elena Agliari , Adriano Barra , Federico Camboni

Diluted mean-field models are spin systems whose geometry of interactions is induced by a sparse random graph or hypergraph. Such models play an eminent role in the statistical mechanics of disordered systems as well as in combinatorics and…

Discrete Mathematics · Computer Science 2018-03-14 Amin Coja-Oghlan , Charilaos Efthymiou , Nor Jaafari , Mihyun Kang , Tobias Kapetanopoulos

We study inference and reconstruction of couplings in a partially observed kinetic Ising model. With hidden spins, calculating the likelihood of a sequence of observed spin configurations requires performing a trace over the configurations…

Disordered Systems and Neural Networks · Physics 2021-04-13 Benjamin Dunn , Yasser Roudi

We study a modified mean-field approximation for the Ising Model in arbitrary dimension. Instead of taking a "central" spin, or a small "drop" of fluctuating spins coupled to the effective field of their nearest neighbors as in the…

High Energy Physics - Lattice · Physics 2009-06-09 Cayetano Di Bartolo , Lorenzo Leal

Dynamic processes of interacting units on a network are out of equilibrium in general. In the case of a directed tree, the dynamic cavity method provides an efficient tool that characterises the dynamic trajectory of the process for the…

Disordered Systems and Neural Networks · Physics 2022-05-25 Giuseppe Torrisi , Reimer Kühn , Alessia Annibale

We develop an elementary mean field approach for fully asymmetric kinetic Ising models, which can be applied to a single instance of the problem. In the case of the asymmetric SK model this method gives the exact values of the local…

Disordered Systems and Neural Networks · Physics 2015-05-27 M. Mezard , J. Sakellariou

We simulate the collective dynamics in spin lattices with long range interactions and collective decay in one, two and three dimensions. Starting from a dynamical mean-field approach derived by local factorization of the density operator we…

Quantum Physics · Physics 2016-01-20 S. Krämer , H. Ritsch

A dynamic mean-field theory for spin ensembles (spinDMFT) at infinite temperatures on arbitrary lattices is established. The approach is introduced for an isotropic Heisenberg model with $S = \tfrac12$ and external field. For large…

Statistical Mechanics · Physics 2022-02-03 Timo Gräßer , Philip Bleicker , Dag-Björn Hering , Mohsen Yarmohammadi , Götz S. Uhrig

Using the cavity method and diagrammatic methods, we model the dynamics of batch learning of restricted sets of examples. Simulations of the Green's function and the cavity activation distributions support the theory well. The learning…

Disordered Systems and Neural Networks · Physics 2007-05-23 K. Y. Michael Wong , S. Li , Peixun Luo

The ground state energy and entropy of the dilute mean field Ising model is computed exactly by a single order parameter. An analogous exact solution is obtained in presence of a magnetic field with random locations. Results allow for a…

Disordered Systems and Neural Networks · Physics 2015-05-19 Maurizio Serva

Dynamical mean-field approximations are performed to study the phase transition of a pair contact process with diffusion in different spatial dimensions. The level of approximation is extended up to 18-site clusters for the one-dimensional…

Statistical Mechanics · Physics 2007-05-23 Attila Szolnoki
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