Abstract

We study the extremal properties of a stochastic process x t defined by the Langevin equation , in which ξ t is a Gaussian white noise with zero mean and D t is a stochastic ‘diffusivity’, defined as a functional of independent Brownian motion B t . We focus on three choices for the random diffusivity D t : cut-off Brownian motion, D t ∼ Θ(B t ), where Θ(x) is the Heaviside step function; geometric Brownian motion, D t ∼ exp(−B t ); and a superdiffusive process based on squared Brownian motion, . For these cases we derive exact expressions for the probability density functions of the maximal positive displacement and of the range of the process x t on the time interval t ∈ (0, T). We discuss the asymptotic behaviours of the associated probability density functions, compare these against the behaviour of the corresponding properties of standard Brownian motion with constant diffusivity (D t = D 0) and also analyse the typical behaviour of the probability density functions which is observed for a majority of realisations of the stochastic diffusivity process.

Highlights

  • The statistics of extreme values (EVs) of stochastic processes has been in the focus of extensive research in the mathematical and physical literature over several decades

  • We focus on three choices for the random diffusivity Dt: cut-off Brownian motion, Dt ∼ Θ(Bt), where Θ(x) is the Heaviside step function; geometric Brownian motion, Dt ∼ exp(−Bt); and a superdiffusive process based on squared Brownian motion, Dt ∼ B2t

  • Deviations from standard Brownian motion have been measured in a vast range of systems, starting with Richardson’s cubic law for the relative diffusion of tracers in turbulent media in 1926 [87]

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Summary

February 2021

Denis S Grebenkov1,2 , Vittoria Sposini2,3 , Ralf Metzler2,∗ , Gleb Oshanin and Flavio Seno. Cedex 05, France 5 INFN, Padova Section and Department of Physics and Astronomy ‘Galileo Galilei’, University of Padova, 35131 Padova, Italy ∗ Author to whom any correspondence should be addressed

Introduction
Model I For model I we find that
Probability density function of the maximal displacement
Relation between the moments of the maximum and of the random diffusivity
Probability density function of the range
Model I
Model III
Relation between the moments of the maximum and of the range
Typical behaviour of the probability density function of the maximum
DB aD0 πT
Findings
Conclusion
Full Text
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