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Related papers: More on the Brownian force model: avalanche shapes…

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We study the Brownian force model (BFM), a solvable model of avalanche statistics for an interface, in a general discrete setting. The BFM describes the overdamped motion of elastically coupled particles driven by a parabolic well in…

Disordered Systems and Neural Networks · Physics 2015-12-23 Thimothée Thiery , Pierre Le Doussal , Kay Jörg Wiese

The Brownian force model (BFM) is a mean-field model for the local velocities during avalanches in elastic interfaces of internal space dimension $d$, driven in a random medium. It is exactly solvable via a non-linear differential equation.…

Disordered Systems and Neural Networks · Physics 2016-06-01 Mathieu Delorme , Pierre Le Doussal , Kay Jörg Wiese

Elastic systems, such as magnetic domain walls, density waves, contact lines, and cracks, are all pinned by substrate disorder. When driven, they move via successive jumps called avalanches, with power law distributions of size, duration…

Disordered Systems and Neural Networks · Physics 2015-06-22 Alexander Dobrinevski , Pierre Le Doussal , Kay Jörg Wiese

We point out that the mean-field theory of avalanches in the dynamics of elastic interfaces, the so-called Brownian force model (BFM) developed recently in non-equilibrium statistical physics, is equivalent to the so-called super-Brownian…

Statistical Mechanics · Physics 2022-09-28 Pierre Le Doussal

Slowly driven elastic interfaces, such as domain walls in dirty magnets, contact lines, or cracks proceed via intermittent motion, called avalanches. We develop a field-theoretic treatment to calculate, from first principles, the space-time…

Disordered Systems and Neural Networks · Physics 2013-08-22 Pierre Le Doussal , Kay Joerg Wiese

We study the energy minimization problem for an elastic interface in a random potential plus a quadratic well. As the position of the well is varied, the ground state undergoes jumps, called shocks or static avalanches. We introduce an…

Disordered Systems and Neural Networks · Physics 2015-06-03 Pierre Le Doussal , Kay Joerg Wiese

We study the motion of an elastic object driven in a disordered environment in presence of both dissipation and inertia. We consider random forces with the statistics of random walks and reduce the problem to a single degree of freedom. It…

Disordered Systems and Neural Networks · Physics 2013-08-22 Pierre Le Doussal , Aleksandra Petkovic , Kay Jörg Wiese

We study a generalization of the Alessandro-Beatrice-Bertotti-Montorsi (ABBM) model of a particle in a Brownian force landscape, including retardation effects. We show that under monotonous driving the particle moves forward at all times,…

Disordered Systems and Neural Networks · Physics 2013-09-05 Alexander Dobrinevski , Pierre Le Doussal , Kay Jörg Wiese

We study the correlations between avalanches in the depinning dynamics of elastic interfaces driven on a random substrate. In the mean field theory (the Brownian force model), it is known that the avalanches are uncorrelated. Here we obtain…

Disordered Systems and Neural Networks · Physics 2020-03-18 Pierre Le Doussal , Thimothée Thiery

In disordered elastic systems, driven by displacing a parabolic confining potential adiabatically slowly, all advance of the system is in bursts, termed avalanches. Avalanches have a finite extension in time, which is much smaller than the…

Disordered Systems and Neural Networks · Physics 2017-12-20 Zhaoxuan Zhu , Kay Joerg Wiese

Several years ago, in the context of the physics of hysteresis in magnetic materials, a simple stochastic model has been introduced: the ABBM model. Later, the ABBM model has been advocated as a paradigm for a broad class of diverse…

Statistical Mechanics · Physics 2021-10-05 Andrea Baldassarri

We discuss the dynamics and thermodynamics of the Brownian Mean Field (BMF) model which is a system of N Brownian particles moving on a circle and interacting via a cosine potential. It can be viewed as the canonical version of the…

Statistical Mechanics · Physics 2015-06-16 Pierre-Henri Chavanis

We obtain an exact solution for the motion of a particle driven by a spring in a Brownian random-force landscape, the Alessandro-Beatrice-Bertotti-Montorsi (ABBM) model. Many experiments on quasi-static driving of elastic interfaces…

Disordered Systems and Neural Networks · Physics 2012-05-18 Alexander Dobrinevski , Pierre Le Doussal , Kay Jörg Wiese

We report the measurement of multivariable scaling functions for the temporal average shape of Barkhausen noise avalanches, and show that they are consistent with the predictions of simple mean-field theories. We bypass the confounding…

Disordered Systems and Neural Networks · Physics 2011-08-12 Stefanos Papanikolaou , Felipe Bohn , Rubem L. Sommer , Gianfranco Durin , Stefano Zapperi , James P. Sethna

In this thesis I discuss analytical approaches to disordered systems using field theory. Disordered systems are characterized by a random energy landscape due to heterogeneities, which remains fixed on the time scales of the phenomena…

Disordered Systems and Neural Networks · Physics 2013-12-30 Alexander Dobrinevski

The problem of the spreading of a granular mass released at the top of a rough inclined plane was investigated. We experimentally measure the evolution of the avalanche from the initiation up to the deposit using a Moir\'e image processing…

Soft Condensed Matter · Physics 2019-06-19 Olivier Pouliquen , Yoel Forterre

Disordered systems are characterized by the existence of many sample- dependent local energy minima, that cause a stepwise response when the system is perturbed. In this article we use an approach based on elementary probabilistic methods…

Disordered Systems and Neural Networks · Physics 2017-03-08 Silvio Franz , Stefano Spigler

For a driven elastic object near depinning, we derive from first principles the distribution of instantaneous velocities in an avalanche. We prove that above the upper critical dimension, d >= d_uc, the n-times distribution of the…

Disordered Systems and Neural Networks · Physics 2015-05-27 Pierre Le Doussal , Kay Joerg Wiese

Mean-field theory is an approximation replacing an extended system by a few variables. For depinning of elastic manifolds, these are the position of its center of mass $u$, and the statistics of the forces $F(u)$. There are two proposals to…

Statistical Mechanics · Physics 2022-01-19 Cathelijne ter Burg , Kay Joerg Wiese

We consider scaled Brownian motion (sBm), a random process described by a diffusion equation with explicitly time-dependent diffusion coefficient $D(t) = D_0 t^{\alpha - 1}$ (Batchelor's equation) which, for $\alpha < 1$, is often used for…

Data Analysis, Statistics and Probability · Physics 2015-06-17 Felix Thiel , Igor M. Sokolov
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