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We study the mean field equation of motion for driven domain walls in random media. We discuss the two cases of an external constant as well as an oscillating driving force. Our main focus lies on the critical dynamics close to the…

Statistical Mechanics · Physics 2015-05-20 Friedmar Schütze , Thomas Nattermann

In this communication we report the existence of a dynamic ``spin-reversal'' transition in an Ising system perturbed by a pulsed external magnetic field. The transition is achieved by tuning the strength ($h_p$) and/or the duration ($\Delta…

Condensed Matter · Physics 2015-06-25 A. Misra , B. K. Chakrabarti

New advances in experiments on the random-field Ising model, as realized in dilute antiferromagnets, have brought us much closer to a full characterization of the static and dynamic critical behavior of the unusual phase transition in three…

Disordered Systems and Neural Networks · Physics 2008-02-03 D. P. Belanger

We establish a new theoretical framework, based on a time-dependent mean field approach, to address the dynamics of the driven Dicke model. The joint evolution of both mean fields and quantum fluctuations gives rise to a rich and generally…

Quantum Physics · Physics 2016-08-18 G. Francica , S. Montangero , M. Paternostro , F. Plastina

A family of nonequilibrium kinetic Ising models, introduced earlier, evolving under the competing effect of spin flips at {\it zero temperature} and nearest neighbour random spin exchanges is further investigated here. By increasing the…

Condensed Matter · Physics 2009-10-28 N. Menyhard , G. Odor

Nonequilibrium behavior and dynamic phase transition properties of a kinetic Ising model under the influence of periodically oscillating random-fields have been analyzed within the framework of effective field theory (EFT) based on a…

Statistical Mechanics · Physics 2012-07-10 Yusuf Yüksel , Erol Vatansever , Ümit Akıncı , Hamza Polat

The dynamic phase transitions have been studied, within a mean-field approach, in the kinetic spin-1 Ising model Hamiltonian with arbitrary bilinear and biquadratic pair interactions in the presence of a time varying (sinusoidal) magnetic…

Statistical Mechanics · Physics 2009-11-11 Mustafa Keskin , Osman Canko , Ersin Kantar

Using dynamical mean-field theory (DMFT) we study a simplified model for heterostructures involving superconductors. The system is driven out-of-equilibrium by a voltage bias, imposed as an imbalance of chemical potential at the interface.…

Strongly Correlated Electrons · Physics 2016-03-21 A. Amaricci , M. Capone

Cluster Dynamical Mean Field Theories are analyzed in terms of their semiclassical limit and their causality properties, and a translation invariant formulation of the cellular dynamical mean field theory, PCDMFT, is presented. The…

Strongly Correlated Electrons · Physics 2009-11-10 G. Biroli , O. Parcollet , G. Kotliar

We investigate how a quenched random field influences the damage spreading transition in kinetic Ising models. To this end we generalize a recent master equation approach and derive an effective field theory for damage spreading in random…

Statistical Mechanics · Physics 2009-10-30 Thomas Vojta

We perform large-scale Monte Carlo simulations using the Machta-Newman-Chayes algorithms to study the critical behavior of both the diluted antiferromagnet in a field with 30% dilution and the random-field Ising model with Gaussian random…

Disordered Systems and Neural Networks · Physics 2013-11-14 Bjoern Ahrens , Jianping Xiao , Alexander K. Hartmann , Helmut G. Katzgraber

We study the stochastic relaxation dynamics of the Ising p-spin model on a random graph, a well-known model with glassy dynamics at low temperatures. We introduce and discuss a new closure scheme for the master equation governing the…

Statistical Mechanics · Physics 2024-05-27 David Machado , Roberto Mulet , Federico Ricci-Tersenghi

We consider the problem of predicting the spin states in a kinetic Ising model when spin trajectories are observed for only a finite fraction of sites. In a Bayesian setting, where the probabilistic model of the spin dynamics is assumed to…

Disordered Systems and Neural Networks · Physics 2015-06-19 Ludovica Bachschmid Romano , Manfred Opper

A comparison is made between mean-field models and direct numerical simulations of rotating magnetoconvection and the geodynamo. The mean-field coefficients are calculated with the fluid velocity taken from the direct numerical simulations.…

Astrophysics · Physics 2009-11-11 M. Schrinner , K. -H. Raedler , D. Schmitt , M. Rheinhardt , U. R. Christensen

We develop a generic method to compute the dynamics induced by quenches in completely connected quantum systems. These models are expected to provide a mean-field description at least of the short time dynamics of finite dimensional system.…

Quantum Gases · Physics 2014-05-13 Bruno Sciolla , Giulio Biroli

We use the annealed formulation of complex networks to study the dynamical behavior of disease spreading on both static and adaptive networked systems. This unifying approach relies on the annealed adjacency matrix, representing one network…

Physics and Society · Physics 2010-11-09 Beniamino Guerra , Jesus Gomez-Gardenes

The phase transition of a random mixed-bond Ising ferromagnet on a cubic lattice model is studied both numerically and analytically. In this work, we use the Cluster algorithms of Wolff and Glauber to simulate the dynamics of the system. We…

Disordered Systems and Neural Networks · Physics 2010-02-02 J. B. Santos-Filho , N. O. Moreno , Douglas F. de Albuquerque

It is known that on directed graphs, the correlations between neighbours of a given site vanish and thus simple mean-field-like arguments can be used to describe exactly the behaviour of Ising-like systems. We analyse heterogeneous…

Statistical Mechanics · Physics 2025-03-03 Adam Lipowski , Antonio Luis Ferreira , Dorota Lipowska , Aleksandra Napierala-Batygolska

This article studies the dynamics of the mean-field approximation of continuous random networks. These networks are stochastic integrodifferential equations driven by Gaussian noise. The kernels in the integral operators are realizations of…

Disordered Systems and Neural Networks · Physics 2025-02-04 W. A. Zúñiga-Galindo

The interactions between the components of many real-world systems are best modelled by networks with multiple layers. Different theories have been proposed to explain how multilayered connections affect the linear stability of…

Physics and Society · Physics 2022-03-25 Charo I. del Genio , Sergio Faci-Lázaro , Jesús Gómez-Gardeñes , Stefano Boccaletti