The maximum likelihood degree of a chemical reaction at the equilibrium

TL;DR

This paper investigates the maximum likelihood degree of chemical reaction networks with a single reaction at equilibrium, providing insights into the complexity of statistical estimation in chemical systems.

Contribution

It introduces a study of the ML degree specifically for single-reaction chemical networks at equilibrium, a novel focus in the intersection of algebraic geometry and chemical kinetics.

Findings

Characterization of ML degree for single-reaction networks

Insights into the algebraic complexity of equilibrium chemical models

Potential applications in chemical data analysis

Abstract

The complexity of a maximum likelihood estimation is measured by its maximum likelihood degree ($ML$ degree). In this paper we study the maximum likelihood problem associated to chemical networks composed by one single chemical reaction under the equilibrium assumption.