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We study the stochastic parallel dynamics of Ising spin systems defined on finitely connected directed random graphs with arbitrary degree distributions, using generating functional analysis. For fully asymmetric graphs the dynamics of the…

Disordered Systems and Neural Networks · Physics 2009-09-24 Kazushi Mimura , A. C. C. Coolen

We study the dynamics of bond-disordered Ising spin systems on random graphs with finite connectivity, using generating functional analysis. Rather than disorder-averaged correlation and response functions (as for fully connected systems),…

Disordered Systems and Neural Networks · Physics 2009-11-10 J. P. L. Hatchett , B. Wemmenhove , I. Perez Castillo , T. Nikoletopoulos , N. S. Skantzos , A. C. C. Coolen

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

A method to approximately close the dynamic cavity equations for synchronous reversible dynamics on a locally tree-like topology is presented. The method builds on $(a)$ a graph expansion to eliminate loops from the normalizations of each…

Disordered Systems and Neural Networks · Physics 2015-07-03 Gino Del Ferraro , Erik Aurell

Using a formalism based on the spectral decomposition of the replicated transfer matrix for disordered Ising models, we obtain several results that apply both to isolated one-dimensional systems and to locally tree-like graph and factor…

Disordered Systems and Neural Networks · Physics 2014-08-04 Carlo Lucibello , Flaviano Morone , Tommaso Rizzo

A method is introduced for studying large deviations in the context of statistical physics of disordered systems. The approach, based on an extension of the cavity method to atypical realizations of the quenched disorder, allows us to…

Disordered Systems and Neural Networks · Physics 2009-11-11 Olivier Rivoire

We start from the Theory of Random Point Processes to derive n-point coupled master equations describing the continuous dynamics of discrete variables in random graphs. These equations constitute a hierarchical set of approximations that…

Disordered Systems and Neural Networks · Physics 2021-11-24 David Machado , Roberto Mulet

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

Understanding and quantifying the dynamics of disordered out-of-equilibrium models is an important problem in many branches of science. Using the dynamic cavity method on time trajectories, we construct a general procedure for deriving the…

Disordered Systems and Neural Networks · Physics 2015-06-22 Andrey Y. Lokhov , Marc Mézard , Lenka Zdeborová

We present a new method to close the Master Equation representing the continuous time dynamics of Ising interacting spins. The method makes use of the the theory of Random Point Processes to derive a master equation for local conditional…

Disordered Systems and Neural Networks · Physics 2017-05-17 Erik Aurell , Gino Del Ferraro , Eduardo Dominguez , Roberto Mulet

Stochastic dynamics on sparse graphs and disordered systems often lead to complex behaviors characterized by heterogeneity in time and spatial scales, slow relaxation, localization, and aging phenomena. The mathematical tools and…

Disordered Systems and Neural Networks · Physics 2025-06-05 Mattia Tarabolo , Luca Dall'Asta

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

We study Ising spin models on finitely connected random interaction graphs which are drawn from an ensemble in which not only the degree distribution $p(k)$ can be chosen arbitrarily, but which allows for further fine-tuning of the topology…

Disordered Systems and Neural Networks · Physics 2009-11-13 C. J. Perez-Vicente , A. C. C. Coolen

We study the dynamics of macroscopic observables such as the magnetization and the energy per degree of freedom in Ising spin models on random graphs of finite connectivity, with random bonds and/or heterogeneous degree distributions. To do…

Disordered Systems and Neural Networks · Physics 2009-11-11 J. P. L. Hatchett , I. Pérez Castillo , A. C. C. Coolen , N. S. Skantzos

In this paper we introduce an approximate method to solve the quantum cavity equations for transverse field Ising models. The method relies on a projective approximation of the exact cavity distributions of imaginary time trajectories…

Disordered Systems and Neural Networks · Physics 2023-03-29 E. Domínguez , H. J. Kappen

We introduce and apply a novel efficient method for the precise simulation of stochastic dynamical processes on locally tree-like graphs. Networks with cycles are treated in the framework of the cavity method. Such models correspond, for…

Statistical Mechanics · Physics 2019-04-09 Thomas Barthel , Caterina De Bacco , Silvio Franz

We consider ferromagnetic Ising models on graphs that converge locally to trees. Examples include random regular graphs with bounded degree and uniformly random graphs with bounded average degree. We prove that the "cavity" prediction for…

Probability · Mathematics 2016-09-08 Amir Dembo , Andrea Montanari

In this paper we study the inference of the kinetic Ising model on sparse graphs by the decimation method. The decimation method, which was first proposed in [Phys. Rev. Lett. 112, 070603] for the static inverse Ising problem, tries to…

Disordered Systems and Neural Networks · Physics 2016-06-30 Aurélien Decelle , Pan Zhang

Randomly coupled Ising spins constitute the classical model of collective phenomena in disordered systems, with applications covering ferromagnetism, combinatorial optimization, protein folding, stock market dynamics, and social dynamics.…

Disordered Systems and Neural Networks · Physics 2016-08-24 David Dahmen , Hannah Bos , Moritz Helias

We present a new solution of the asymmetric two-matrix model in the large $N$ limit which only involves a saddle point analysis. The model can be interpreted as Ising in the presence of a magnetic field, on random dynamical lattices with…

Statistical Mechanics · Physics 2007-05-23 P. Zinn-Justin
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