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Related papers: Exact mean field inference in asymmetric kinetic I…

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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

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

The inverse Ising problem consists in inferring the coupling constants of an Ising model given the correlation matrix. The fastest methods for solving this problem are based on mean-field approximations, but which one performs better in the…

Disordered Systems and Neural Networks · Physics 2012-08-28 Federico Ricci-Tersenghi

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

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

We present an exact analytical solution for the one-dimensional Ising model in the presence of an external magnetic field applied periodically to every $k$-th site. The problem is handled using the symmetrized transfer matrix approach, we…

Statistical Mechanics · Physics 2025-11-20 Malek Telfah , Abdalla Obeidat

Recently proposed analog solvers based on dynamical systems, such as Ising machines, are promising platforms for large-scale combinatorial optimization. Yet, given the heuristic nature of the field, there is very limited insight on…

Disordered Systems and Neural Networks · Physics 2026-03-27 Shu Zhou , K. Y. Michael Wong , Juntao Wang , David Shui Wing Hui , Daniel Ebler , Jie Sun

We discuss a generalized self-consistent mean field (MF) treatment, based on the selection of an arbitrary subset of operators for representing the system density matrix, and its application to the problem of entanglement evaluation in…

Quantum Physics · Physics 2015-06-23 A. Boette , R. Rossignoli , N. Canosa , J. M. Matera

We analyze in some detail a recently proposed transfer matrix mean field approximation which yields the exact critical point for several two dimensional nearest neighbor Ising models. For the square lattice model we show explicitly that…

Condensed Matter · Physics 2009-10-22 A. Pelizzola , A. Stella

The large amounts of data from molecular biology and neuroscience have lead to a renewed interest in the inverse Ising problem: how to reconstruct parameters of the Ising model (couplings between spins and external fields) from a number of…

Disordered Systems and Neural Networks · Physics 2012-08-13 H. Chau Nguyen , Johannes Berg

In this set of notes, a complete, pedagogical tutorial for applying mean field theory to the two-dimensional Ising model is presented. Beginning with the motivation and basis for mean field theory, we formally derive the Bogoliubov…

Statistical Mechanics · Physics 2025-04-24 Dalton A R Sakthivadivel

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

We present a systematic small-correlation expansion to solve the inverse Ising problem: find a set of couplings and fields corresponding to a given set of correlations and magnetizations. Couplings are calculated up to the third order in…

Disordered Systems and Neural Networks · Physics 2009-01-07 Vitor Sessak , Rémi Monasson

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

A mean field feedback artificial neural network algorithm is developed and explored for the set covering problem. A convenient encoding of the inequality constraints is achieved by means of a multilinear penalty function. An approximate…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Mattias Ohlsson , Carsten Peterson , Bo Söderberg

A disordered spin glass model where both static and dynamical properties depend on macroscopic magnetizations is presented. These magnetizations interact via random couplings and, therefore, the typical quenched realization of the system…

Disordered Systems and Neural Networks · Physics 2009-10-31 M. Pasquini , M. Serva

The phase behavior of Ising spin fluids is studied in the presence of an external magnetic field with the integral equation method. The calculations are performed on the basis of a soft mean spherical approximation using an efficient…

Statistical Mechanics · Physics 2016-08-31 I. P. Omelyan , I. M. Mryglod , R. Folk , W. Fenz

Non-equilibrium systems lack an explicit characterisation of their steady state like the Boltzmann distribution for equilibrium systems. This has drastic consequences for the inference of parameters of a model when its dynamics lacks…

Statistical Mechanics · Physics 2016-11-15 Simon L. Dettmer , H. Chau Nguyen , Johannes Berg

We derive and study dynamical TAP equations for Ising spin glasses obeying both synchronous and asynchronous dynamics using a generating functional approach. The system can have an asymmetric coupling matrix, and the external fields can be…

Disordered Systems and Neural Networks · Physics 2011-05-17 Yasser Roudi , John Hertz

The mean field approximation to the Ising model is a canonical variational tool that is used for analysis and inference in Ising models. We provide a simple and optimal bound for the KL error of the mean field approximation for Ising models…

Machine Learning · Computer Science 2018-02-22 Vishesh Jain , Frederic Koehler , Elchanan Mossel
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