EQUIVALENCES BETWEEN STOCHASTIC SYSTEMS

TL;DR

This paper explores the relationships between various stochastic models of particle diffusion, coagulation, and annihilation, using similarity transformations to connect stochastic and non-stochastic models, with results validated against experimental data.

Contribution

It introduces a method to relate different stochastic systems through similarity transformations, bridging stochastic and non-stochastic models for particle processes.

Findings

Calculated correlation functions match experimental results

Established equivalences between stochastic models

Validated theoretical models with experimental data

Abstract

Time-dependent correlation functions of (unstable) particles undergoing biased or unbiased diffusion, coagulation and annihilation are calculated. This is achieved by similarity transformations between different stochastic models and between stochastic and soluble {\em non-stochastic} models. The results agree with experiments on one-dimensional annihilation-coagulation processes.