Reaction-subdiffusion equations with species-dependent movement

TL;DR

This paper derives and analyzes fractional reaction-subdiffusion equations for multiple molecular species with species-dependent movement, providing a stochastic framework and validating with simulations.

Contribution

It introduces a novel derivation of reaction-subdiffusion equations allowing different species to have distinct movement dynamics, extending previous models.

Findings

Derived equations for multiple species with different diffusivities and drifts

Established stochastic process representations for individual molecules

Validated equations through agreement with stochastic simulations

Abstract

Reaction-diffusion equations are one of the most common mathematical models in the natural sciences and are used to model systems that combine reactions with diffusive motion. However, rather than normal diffusion, anomalous subdiffusion is observed in many systems and is especially prevalent in cell biology. What are the reaction-subdiffusion equations describing a system that involves first-order reactions and subdiffusive motion? In this paper, we answer this question. We derive fractional reaction-subdiffusion equations describing an arbitrary number of molecular species which react at first-order rates and move subdiffusively with general space-dependent diffusivities and drifts. Importantly, different species may have different diffusivities and drifts, which contrasts previous approaches to this question which assume that each species has the same movement dynamics. We derive the equations by combining results on time-dependent fractional Fokker-Planck equations with methods of analyzing stochastically switching evolution equations. Furthermore, we construct the stochastic description of individual molecules whose deterministic concentrations follow these reaction-subdiffusion equations. This stochastic description involves subordinating a diffusion process whose dynamics are controlled by a subordinated Markov jump process. We illustrate our results in several examples and show that solutions of the reaction-subdiffusion equations agree with stochastic simulations of individual molecules.