Probabilistic aspects of critical growth-fragmentation equations

TL;DR

This paper investigates the critical growth-fragmentation equations using probabilistic methods, revealing new phenomena like spontaneous mass generation in non-homogeneous cases.

Contribution

It extends the analysis of growth-fragmentation equations to non-homogeneous rates using Lévy processes and self-similar Markov processes, uncovering unexpected behaviors.

Findings

Existence and uniqueness are straightforward in homogeneous cases.

Non-homogeneous cases exhibit spontaneous mass generation.

Self-similar Markov processes can enter from zero or infinity, causing mass creation.

Abstract

The self-similar growth-fragmentation equation describes the evolution of a medium in which particles grow and divide as time proceeds, with the growth and splitting of each particle depending only upon its size. The critical case of the equation, in which the growth and division rates balance one another, was considered by Doumic and Escobedo in the homogeneous case where the rates do not depend on the particle size. Here, we study the general self-similar case, using a probabilistic approach based on L\'evy processes and positive self-similar Markov processes which also permits us to analyse quite general splitting rates. Whereas existence and uniqueness of the solution are rather easy to establish in the homogeneous case, the equation in the non-homogeneous case has some surprising features. In particular, using the fact that certain self-similar Markov processes can enter $(0,\infty)$ continuously from either $0$ or $\infty$, we exhibit unexpected spontaneous generation of mass in the solutions.