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Non-Gaussianity and random diffusivity models

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FD2W01 - Deterministic and stochastic fractional differential equations and jump processes

Over the last years a considerable number of systems have been reported in which Brownian yet non-Gaussian dynamics is observed. These are processes characterised by a linear growth in time of the mean squared displacement, yet the probability density function of the particle displacement is distinctly non-Gaussian, and often of exponential (Laplace) shape. This behaviour has been interpreted as resulting from diffusion in heterogeneous environments and mathematically described through the introduction of a variable, stochastic diffusion coefficient. In this talk I will present a general overview on random diffusivity processes, with the main goal of showing how the linear scaling of the mean squared displacement can be reconciled with a non-Gaussian probability density function. This talk is based on a series of joint publications with Ralf Metzler, Gianni Pagnini, Aleksei Chechkin and Falvio Seno. 

This talk is part of the Isaac Newton Institute Seminar Series series.

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