Analyzing Diffusion and Flow-driven Instability using Semidefinite Programming

TL;DR

This paper introduces semidefinite programming-based algorithms to efficiently analyze the stability of reaction-diffusion-advection systems, enabling prediction of pattern formation without extensive simulations.

Contribution

It develops SOS optimization methods to determine transport-driven instability, simplifying stability analysis of complex chemical systems.

Findings

SOS optimization effectively predicts instability regions.

Method enables design of concentration gradients.

Analysis reduces computational complexity.

Abstract

Diffusion and flow-driven instability, or transport-driven instability, is one of the central mechanisms to generate inhomogeneous gradient of concentrations in spatially distributed chemical systems. However, verifying the transport-driven instability of reaction-diffusion-advection systems requires checking the Jacobian eigenvalues of infinitely many Fourier modes, which is computationally intractable. To overcome this limitation, this paper proposes mathematical optimization algorithms that determine the stability/instability of reaction-diffusion-advection systems by finite steps of algebraic calculations. Specifically, the stability/instability analysis of Fourier modes is formulated as a sum-of-squares (SOS) optimization program, which is a class of convex optimization whose solvers are widely available as software packages. The optimization program is further extended for facile computation of the destabilizing spatial modes. This extension allows for predicting and designing the shape of concentration gradient without simulating the governing equations. The streamlined analysis process of self-organized pattern formation is demonstrated with a simple illustrative reaction model with diffusion and advection.