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Related papers: Gaps between avalanches in 1D Random Field Ising M…

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We present a detailed numerical study of the elementary condensation events (avalanches) associated to the adsorption of $^4$He in silica aerogels. We use a coarse-grained lattice-gas description and determine the nonequilibrium behavior of…

Disordered Systems and Neural Networks · Physics 2009-11-11 F. Detcheverry , E. Kierlik , M. L. Rosinberg , G. Tarjus

We study the qualitative and quantitative properties of the Barkhausen noise emerging at finite temperatures in random Ising models. The random-bond Ising Model is studied with a Wolff cluster Monte-Carlo algorithm to monitor the avalanches…

Statistical Mechanics · Physics 2025-05-23 Federico Ettori , Filippo Perani , Stefano Turzi , Paolo Biscari

A review is given on some recent developments in the theory of the Ising model in a random field. This model is a good representation of a large number of impure materials. After a short repetition of earlier arguments, which prove the…

Statistical Mechanics · Physics 2008-02-03 T. Nattermann

A bundle of fibers has been considered here as a model for composite materials, where breaking of the fibers occur due to a combined influence of applied load (stress) and external noise. Through numerical simulation and a mean-field…

Statistical Mechanics · Physics 2013-07-26 Srutarshi Pradhan , Anjan Kumar Chandra , Bikas K. Chakrabarti

We study persistence in one-dimensional ferromagnetic and anti-ferromagnetic nearest-neighbor Ising models with parallel dynamics. The probability P(t) that a given spin has not flipped up to time t, when the system evolves from an initial…

Statistical Mechanics · Physics 2009-11-07 G. I. Menon , P. Ray , P. Shukla

The ground state critical properties of the Random Field Ising Model (RFIM) on the diamond hierarchical lattice are investigated via a combining method encompassing real space renormalization group and an exact recurrence procedure. The…

Disordered Systems and Neural Networks · Physics 2007-05-23 Alexandre Rosas , Sérgio Coutinho

We investigate the connection between a formal property of the critical behavior of several systems in the presence of quenched disorder, known as "dimensional reduction", and the presence in the same systems at zero temperature of…

Disordered Systems and Neural Networks · Physics 2015-06-11 Gilles Tarjus , Maxime Baczyk , Matthieu Tissier

The Random Field Ising Model (RFIM) is the simplest physical model reflecting effect of quenched disorder on the different types of phase transitions in solids. The presence of multiple energy minima in the RFIM is an important feature…

Disordered Systems and Neural Networks · Physics 2007-05-23 A. A. Likhachev

Instabilities and avalanches in granular flows represent hallmarks of failure: they can both disrupt industrial process flows and signal dangerous conditions, like those in grain silos and snowy mountaintops. We investigate intermittency…

Soft Condensed Matter · Physics 2025-01-06 Saeed Alborzi , Sara M. Hashmi

We investigated the yielding phenomenon in the quasistatic limit using numerical simulations of soft particles. Two different deformation scenarios, simple shear (passive) and self-random force (active), and two interaction potentials were…

Soft Condensed Matter · Physics 2023-10-10 Carlos Villarroel , Gustavo Düring

We analyse by numerical simulations and scaling arguments the avalanche statistics of 1-dimensional elastic interfaces in random media driven at a single point. Both global and local avalanche sizes are power-law distributed, with universal…

Disordered Systems and Neural Networks · Physics 2016-01-28 L. E. Aragón , A. B. Kolton , P. Le Doussal , K. J. Wiese , E. A. Jagla

We revisit the phenomenon of spinodals in the presence of quenched disorder and develop a complete theory for it. We focus on the spinodal of an Ising model in a quenched random field (RFIM), which has applications in many areas from…

Soft Condensed Matter · Physics 2016-05-23 Saroj Kumar Nandi , Giulio Biroli , Gilles Tarjus

We calculate numerically the sizes S of jumps (avalanches) between successively pinned configurations of an elastic line (d=1) or interface (d=2), pulled by a spring of (small) strength m^2 in a random-field landscape. We obtain strong…

Disordered Systems and Neural Networks · Physics 2013-05-29 Alberto Rosso , Pierre Le Doussal , Kay Joerg Wiese

We investigate the influence of the driving mechanism on the hysteretic response of systems with athermal dynamics. In the framework of local-mean field theory at finite temperature (but neglecting thermallly activated processes), we…

Disordered Systems and Neural Networks · Physics 2009-11-11 Xavier Illa , Martin-Luc Rosinberg , Eduard Vives

We investigate thermal avalanche dynamics in amorphous solids using elastoplastic models with local activation rules and no external driving. Dynamical heterogeneities, quantified through persistence measurements and the associated…

Disordered Systems and Neural Networks · Physics 2026-02-26 Gieberth Rodriguez-Lopez , Ezequiel E. Ferrero

The effects of locally random magnetic fields are considered in a nonequilibrium Ising model defined on a square lattice with nearest-neighbors interactions. In order to generate the random magnetic fields, we have considered random…

Statistical Mechanics · Physics 2009-11-13 N. Crokidakis

Record-breaking avalanches generated by the dynamics of several driven nonlinear threshold models are studied. Such systems are characterized by intermittent behavior, where slow buildup of energy is punctuated by an abrupt release of…

Statistical Mechanics · Physics 2013-06-14 Robert Shcherbakov , Jörn Davidsen , Kristy F. Tiampo

Interfaces pinned by quenched disorder are often used to model jerky self-organized critical motion. We study static avalanches, or shocks, defined here as jumps between distinct global minima upon changing an external field. We show how…

Disordered Systems and Neural Networks · Physics 2015-05-13 Pierre Le Doussal , Kay Jörg Wiese

In studying the avalanches and noise in a model of hysteresis loops we have developed two relatively straightforward algorithms which have allowed us to study large systems efficiently. Our model is the random-field Ising model at zero…

Disordered Systems and Neural Networks · Physics 2017-06-06 Matthew C. Kuntz , Olga Perkovic , Karin A. Dahmen , Bruce W. Roberts , James P. Sethna

The energy landscape for the random-field Ising model (RFIM) is complex, yet algorithms such as the push-relabel algorithm exist for computing the exact ground state of an RFIM sample in time polynomial in the sample volume. Simulations…

Disordered Systems and Neural Networks · Physics 2007-05-23 Jan H. Meinke , A. Alan Middleton