English

Counting equilibria of large complex systems by instability index

Mathematical Physics 2022-05-17 v2 Disordered Systems and Neural Networks math.MP Adaptation and Self-Organizing Systems

Abstract

We consider a nonlinear autonomous system of N1N\gg 1 degrees of freedom randomly coupled by both relaxational ('gradient') and non-relaxational ('solenoidal') random interactions. We show that with increased interaction strength such systems generically undergo an abrupt transition from a trivial phase portrait with a single stable equilibrium into a topologically non-trivial regime of 'absolute instability' where equilibria are on average exponentially abundant, but typically all of them are unstable, unless the dynamics is purely gradient. When interactions increase even further the stable equilibria eventually become on average exponentially abundant unless the interaction is purely solenoidal. We further calculate the mean proportion of equilibria which have a fixed fraction of unstable directions.

Keywords

Cite

@article{arxiv.2008.00690,
  title  = {Counting equilibria of large complex systems by instability index},
  author = {Gérard Ben Arous and Yan V Fyodorov and Boris A Khoruzhenko},
  journal= {arXiv preprint arXiv:2008.00690},
  year   = {2022}
}

Comments

Main paper - 7 pages, Supplementary Information - 20 pages. Revised version - minor changes, including adding short discussion of model assumptions

R2 v1 2026-06-23T17:35:37.254Z