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We study analytically the performance of a recently proposed algorithm for learning the couplings of a random asymmetric kinetic Ising model from finite length trajectories of the spin dynamics. Our analysis shows the importance of the…

Disordered Systems and Neural Networks · Physics 2015-09-30 Ludovica Bachschmid-Romano , Manfred Opper

Dynamic scaling analyses are performed in the spin-glass phase of the $\pm J$ Ising, the {\it XY}, and the Heisenberg models in three dimensions. We found a crossover from the critical dynamics to the ground-state dynamics in the Ising…

Disordered Systems and Neural Networks · Physics 2007-05-23 Tota Nakamura

We study the Glauber dynamics of Ising spin models with random bonds, on finitely connected random graphs. We generalize a recent dynamical replica theory with which to predict the evolution of the joint spin-field distribution, to include…

Disordered Systems and Neural Networks · Physics 2015-05-13 A. Mozeika , A. C. C. Coolen

We consider the equilibrium dynamics of Ising spin models with multi-spin interactions on sparse random graphs (Bethe lattices). Such models undergo a mean field glass transition upon increasing the graph connectivity or lowering the…

Statistical Mechanics · Physics 2009-11-10 Andrea Montanari , Guilhem Semerjian

A parallel implementation of coupled spin-lattice dynamics in the LAMMPS molecular dynamics package is presented. The equations of motion for both spin only and coupled spin-lattice dynamics are first reviewed, including a detailed account…

Statistical Mechanics · Physics 2018-08-01 J. Tranchida , S. J. Plimpton , P. Thibaudeau , A. P. Thompson

The study of nonequilibrium steady-state (NESS) in the Ising model offers rich insights into the properties of complex systems far from equilibrium. This paper explores the nature of NESS phase transitions in two-dimensional (2D)…

Statistical Mechanics · Physics 2024-09-05 Dagne Wordofa Tola , Mulugeta Bekele

We construct a parallel stochastic dynamics with invariant measure converging to the Gibbs measure of the low temperature Ising model. The proof of such convergence requires a polymer expansion based on suitably defined Peierls-type…

Mathematical Physics · Physics 2016-12-21 Aldo Procacci , Benedetto Scoppola , Elisabetta Scoppola

The one-dimensional Ising model with its connections to several physical concepts plays a vital role in comprehension of several principles, phenomena and numerical methods. The Hamiltonian of a coupled one-dimensional dissipative spin…

Using a probabilistic approach we study the parallel dynamics of fully connected Q-Ising neural networks for arbitrary Q. A Lyapunov function is shown to exist at zero temperature. A recursive scheme is set up to determine the time…

Disordered Systems and Neural Networks · Physics 2019-08-15 D. Bollé , G. Jongen , G. M. Shim

We performed two-dimensional simulated tempering (ST) simulations of the two-dimensional Ising model with different lattice sizes in order to investigate the two-dimensional ST's applicability to dealing with phase transitions and to study…

Statistical Mechanics · Physics 2015-06-05 Tetsuro Nagai , Yuko Okamoto

We present local mappings that relate the marginal probabilities of a global probability mass function represented by its primal normal factor graph to the corresponding marginal probabilities in its dual normal factor graph. The mapping is…

Machine Learning · Statistics 2022-08-11 Mehdi Molkaraie

In multi-period stochastic optimization problems, the future optimal decision is a random variable whose distribution depends on the parameters of the optimization problem. We analyze how the expected value of this random variable changes…

Optimization and Control · Mathematics 2020-01-28 Bar Light

We study the Hamiltonian dynamics of the spherical spin model with fully-connected two-body interactions drawn from a Gaussian probability distribution. In the statistical physics framework, the potential energy is of the so-called $p=2$…

Statistical Mechanics · Physics 2018-07-04 Leticia F. Cugliandolo , Gustavo S. Lozano , Nicolas Nessi , Marco Picco , Alessandro Tartaglia

We study the surface phase diagram of the three-dimensional kinetic Ising model below the equilibrium critical point subjected to a periodically oscillating magnetic field. Changing the surface interaction strength as well as the period of…

Statistical Mechanics · Physics 2014-03-19 Keith Tauscher , Michel Pleimling

Using a quantum formulation of the master equation we study a kinetic Ising model with competing stochastic processes: the Glauber dynamics with probability $p$ and the Kawasaki dynamics with probability $1 - p$. Introducing explicitely the…

Statistical Mechanics · Physics 2009-10-31 S. Artz , S. Trimper

The usual setting for learning the structure and parameters of a graphical model assumes the availability of independent samples produced from the corresponding multivariate probability distribution. However, for many models the mixing time…

Machine Learning · Computer Science 2022-10-13 Arkopal Dutt , Andrey Y. Lokhov , Marc Vuffray , Sidhant Misra

Generalized-ensemble Monte Carlo simulations such as the multicanonical method and similar techniques are among the most efficient approaches for simulations of systems undergoing discontinuous phase transitions or with rugged free- energy…

Computational Physics · Physics 2018-02-06 Jonathan Gross , Johannes Zierenberg , Martin Weigel , Wolfhard Janke

We study the two-dimensional Ising model on a network with a novel type of quenched topological (connectivity) disorder. We construct random lattices of constant coordination number and perform large scale Monte Carlo simulations in order…

Statistical Mechanics · Physics 2018-03-07 Manuel Schrauth , Julian A. J. Richter , Jefferson S. E. Portela

We focus on a family of one-dimensional probabilistic cellular automata with memory two: the dynamics is such that the value of a given cell at time $t+1$ is drawn according to a distribution which is a function of the states of its two…

Probability · Mathematics 2017-10-17 Jérôme Casse , Irène Marcovici

Switching dynamical systems are an expressive model class for the analysis of time-series data. As in many fields within the natural and engineering sciences, the systems under study typically evolve continuously in time, it is natural to…

Machine Learning · Computer Science 2022-05-19 Lukas Köhs , Bastian Alt , Heinz Koeppl
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