The Central Limit Theorem for the Smoluchovski Coagulation Model

TL;DR

This paper establishes a central limit theorem for fluctuations in the coagulation model with unbounded kernels, providing precise convergence rates around the law of large numbers.

Contribution

It introduces the CLT for the coagulation model with unbounded kernels and quantifies convergence rates, advancing understanding of stochastic coagulation processes.

Findings

CLT proven for unbounded coagulation kernels

Explicit convergence rates for LLN and CLT

Enhanced understanding of fluctuations in coagulation models

Abstract

The general model of coagulation is considered. For basic classes of unbounded coagulation kernels the central limit theorem (CLT) is obtained for the fluctuations around the dynamic law of large numbers (LLN). A rather precise rate of convergence is given both for LLN and CLT.