Limit Theorems for the Dynamical Foundation of the Fractional Brownian Motion and Related Models of Anomalous Diffusion with Random Diffusion Coefficient and Time-Dependent Random Hurst parameter
Christian Bender, Yana A. Butko, Mirko D'Ovidio, Gianni Pagnini

TL;DR
This paper establishes a dynamical foundation for models of anomalous diffusion, including fractional Brownian motion with random parameters, by analyzing a particle system governed by Langevin equations and deriving the limiting Gaussian processes.
Contribution
It provides a rigorous derivation of generalized Gaussian processes, including fractional Brownian motion with random parameters, from a particle system with Langevin dynamics, extending the theoretical understanding of anomalous diffusion.
Findings
Limit N→∞ leads to non-Markovian Gaussian processes.
Proper mass distributions yield fractional Brownian motion models.
Derived generalized Kolmogorov–Fokker–Planck equations.
Abstract
Anomalous diffusion is an established phenomenon but still a theoretical challenge in non-equilibrium statistical mechanics. Physical models are built incrementally, and the most recent and most general family is based on the fractional Brownian motion (fBm) with a random diffusion coefficient (superstatistical fBm) together with a time-dependent random Hurst parameter. We provide here a dynamical foundation for such general family of models. We consider a dynamical system describing the motion of a test-particle surrounded by Brownian particles with different masses. This dynamic is governed by underdamped Langevin equations. Physical principles of conservation of momentum and energy are met. We prove that, in the limit , the test-particle diffuses in time according to a quite general (non-Markovian) Gaussian process whose covariance function is determined by the…
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Taxonomy
TopicsFractional Differential Equations Solutions · Stochastic processes and financial applications · Complex Systems and Time Series Analysis
