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Stochastic processes and disordered systems : around Brownian motion

Abstract : In this thesis, we study stochastic processes appearing in different areas of statistical physics: Firstly, fractional Brownian motion is a generalization of the well-known Brownian motion to include memory. Memory effects appear for example in complex systems and anomalous diffusion, and are difficult to treat analytically, due to the absence of the Markov property. We develop a perturbative expansion around standard Brownian motion to obtain new results for this case. We focus on observables related to extreme-value statistics, with links to mathematical objects: Levy’s arcsine laws and Pickands’ constant. Secondly, the model of elastic interfaces in disordered media is investigated. We consider the case of a Brownian random disorder force. We study avalanches, i.e. the response of the system to a kick, for which several distributions of observables are calculated analytically. To do so, the initial stochastic equation is solved using a deterministic non-linear instanton equation. Avalanche observables are characterized by power-law distributions at small-scale with universal exponents, for which we give new results.
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Submitted on : Tuesday, July 23, 2019 - 4:53:06 PM
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Mathieu Delorme. Stochastic processes and disordered systems : around Brownian motion. Physics [physics]. Université Paris sciences et lettres, 2016. English. ⟨NNT : 2016PSLEE058⟩. ⟨tel-02191877⟩



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