A Semi-Markov Algorithm for Continuous Time Random Walk Limit Distributions

Abstract

The Semi-Markov property of Continuous Time Random Walks (CTRWs) and their limit processes is utilized, and the probability distributions of the bivariate Markov process $(X(t),V(t))$ are calculated: $X(t)$ is a CTRW limit and $V(t)$ a process tracking the age, i.e. the time since the last jump. For a given CTRW limit process $X(t)$, a sequence of discrete CTRWs in discrete time is given which converges to $X(t)$ (weakly in the Skorokhod topology). Master equations for the discrete CTRWs are implemented numerically, thus approximating the distribution of $X(t)$. A consequence of the derived algorithm is that any distribution of initial age can be assumed as an initial condition for the CTRW limit dynamics. Four examples with different temporal scaling are discussed: subdiffusion, tempered subdiffusion, the fractal mobile/immobile model and the tempered fractal mobile/immobile model.

arXiv comment20 pages, 4 figures

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Cited by in corpus (1)

• Variable Order Fractional Fokker-Planck Equations derived from Continuous Time Random Walks