Robustness of steady state and stochastic cyclicity in generalized coalescence-fragmentation models

TL;DR

This paper investigates the robustness of steady states and cyclic behaviors in generalized coalescence-fragmentation models, revealing conditions under which power-law distributions and cycles persist or break down.

Contribution

It introduces a generalized model with various parameters and analyzes how steady states and cycles are affected by these variations, providing insights into their stability.

Findings

Power-law steady states persist with accretion and erosion.

Broader fragment size distributions disrupt steady states and cycles.

Model clarifies dynamics observed in coalescence-fragmentation systems.

Abstract

Processes of coalescence and fragmentation are used to understand the time-evolution of the mass distribution of various systems and may result in a steady state or in stable deterministic or stochastic cycles. Motivated by applications in insurgency warfare we investigate coalescence-fragmentation systems. We begin with a simple model of size-biased coalescence accompanied by shattering into monomers. Depending on the parameters this model has an approximately power-law-distributed steady state or stochastic cycles of alternating gelation and shattering. We conduct stochastic simulations of this model and its generalizations to include different kernel types, accretion and erosion, and various distributions of non-shattering fragmentation. Our central aim is to explore the robustness of the steady state and gel-shatter cycles to these variations. We show that an approximate power-law steady state persists with the addition of accretion and erosion, and with partial rather than total shattering. However, broader distributions of fragment sizes typically vitiate both the power law steady state and gel-shatter cyclicity. This work clarifies features shown in coalescence/fragmentation model simulations and elucidates the relationship between the microscopic dynamics and observed phenomena in this widely applicable interdisciplinary model type.