Cattaneo--type subdiffusion equation

TL;DR

This paper introduces a Cattaneo--type subdiffusion equation (CTSE) incorporating a delay effect in the flux, analyzing its mathematical properties and potential impact on diffusion modeling, especially in epidemic spread scenarios.

Contribution

The paper develops a new CTSE model with an integro-differential operator, derived within the continuous time random walk framework, and analyzes its effects on diffusion dynamics.

Findings

The Cattaneo effect's influence on mean square displacement is generally small.

Long-distance diffusion probability increases with the Cattaneo effect.

The effect can significantly alter diffusion behavior in specific modeling contexts.

Abstract

The ordinary subdiffusion equation, with a fractional time derivative of at most first order, describes a process in which the propagation velocity of diffusing molecules is unlimited. To avoid this non-physical property different forms of the Cattaneo subdiffusion equation have been proposed. We define the Cattaneo effect as a delay of the ordinary subdiffusion flux activation by a random time. By incorporating this effect into the flux equation we get a Cattaneo--type subdiffusion equation (CTSE). We study the CTSE that differs from the ordinary subdiffusion equation by an additional integro--differential operator (AO) controlled by a time delay probability distribution. A method for deriving CTSE within the standard continuous time random walk model is also shown. As examples, we consider the CTSE with AO being the Caputo fractional time derivative of the order independent of the subdiffusion exponent and with the AO with a kernel that is a slowly varying function. In the first case the Cattaneo effect disappears over time much faster than in the second one. Based on the Green's functions, the time evolutions of the first passage time distribution and of the mean square displacement of a diffusing molecule, we discuss whether the influence of the Cattaneo effect is significant. In the considered examples, this influence seems to be small. However, a relative probability of finding a molecule at a long distance from the starting point for the CTSE equation with respect to the ordinary subdiffusion equation increases rapidly with distance. Even small changes caused by the Cattaneo effect can lead to different results in modeling processes where a faster appearance of a diffusing object changes the nature of the process. The effect may be important, for example, in modeling the spread of an epidemic when a diffusing object is a source of infection.