Estimating the division rate and kernel in the fragmentation equation

TL;DR

This paper develops a method to estimate fragmentation parameters, specifically the division rate and kernel, from size distribution data over time, under certain assumptions, using asymptotic analysis and Mellin transforms.

Contribution

It provides a novel approach to uniquely identify the division rate and fragmentation kernel from experimental data using asymptotic behavior and Mellin transform techniques.

Findings

Proved uniqueness of the fragmentation parameters under specified assumptions.

Derived a representation formula for the fragmentation kernel.

Ensured the Mellin transform of the asymptotic profile does not vanish.

Abstract

We consider the fragmentation equation $\dfrac{\partial}{\partial t}f (t, x) = --B(x)f (t, x) + \int\_{ y=x}^{ y=\infty} k(y, x)B(y)f (t, y)dy,$ and address the question of estimating the fragmentation parameters-i.e. the division rate $B(x)$ and the fragmentation kernel $k(y, x)$-from measurements of the size distribution $f (t, $\times$)$ at various times. This is a natural question for any application where the sizes of the particles are measured experimentally whereas the fragmentation rates are unknown, see for instance (Xue, Radford, Biophys. Journal, 2013) for amyloid fibril breakage. Under the assumption of a polynomial division rate $B(x) = \alpha x^{\gamma}$ and a self-similar fragmentation kernel $k(y, x) = \frac{1}{y} k\_0 (x/ y)$, we use the asymptotic behaviour proved in (Escobedo, Mischler, Rodriguez-Ricard, Ann. IHP, 2004) to obtain uniqueness of the triplet $(\alpha, \gamma, k \_0)$ and a representation formula for $k\_0$. To invert this formula, one of the delicate points is to prove that the Mellin transform of the asymptotic profile never vanishes, what we do through the use of the Cauchy integral.