Sufficient conditions for linear stability of complex-balanced equilibria in generalized mass-action systems

TL;DR

This paper establishes sufficient conditions based on sign-vector criteria for the linear stability of complex-balanced equilibria in generalized mass-action systems, applicable across various scientific fields without explicit steady state computation.

Contribution

It introduces new sign-vector and graph Laplacian decomposition methods to guarantee stability for all rate constants in generalized mass-action systems.

Findings

Guarantees Jacobian as a P-matrix under certain conditions

Provides stability criteria applicable to biological and chemical models

Validates results with examples from ecology, biochemistry, and systems biology

Abstract

Generalized mass-action systems are power-law dynamical systems arising from chemical reaction networks. Essentially, every nonnegative ODE model used in chemistry and biology (for example, in ecology and epidemiology) and even in economics and engineering can be written in this form. Previous results have focused on existence and uniqueness of special steady states (complex-balanced equilibria) for all rate constants, thereby ruling out multiple (special) steady states. Recently, necessary conditions for linear stability have been obtained. In this work, we provide sufficient conditions for the linear stability of complex-balanced equilibria for all rate constants (and also for the non-existence of other steady states). In particular, via sign-vector conditions (on the stoichiometric coefficients and kinetic orders), we guarantee that the Jacobian matrix is a $P$-matrix. Technically, we use a new decomposition of the graph Laplacian which allows to consider orders of (generalized) monomials. Alternatively, we use cycle decomposition which allows a linear parametrization of all Jacobian matrices. In any case, we guarantee stability without explicit computation of steady states. We illustrate our results in examples from chemistry and biology: generalized Lotka-Volterra systems and SIR models, a two-component signaling system, and an enzymatic futile cycle.