May-Wigner transition in large random dynamical systems
Mathematical Physics
2017-10-25 v2 Disordered Systems and Neural Networks
Statistical Mechanics
math.MP
Probability
Abstract
We consider stability in a class of random non-linear dynamical systems characterised by a relaxation rate together with a Gaussian random vector field which is white-in-time and spatial homogeneous and isotropic. We will show that in the limit of large dimension there is a stability-complexity phase transition analogue to the so-called May-Wigner transition known from linear models. Our approach uses an explicit derivation of a stochastic description of the finite-time Lyapunov exponents. These exponents are given as a system of coupled Brownian motions with hyperbolic repulsion called geometric Dyson Brownian motions. We compare our results with known models from the literature.
Cite
@article{arxiv.1705.05047,
title = {May-Wigner transition in large random dynamical systems},
author = {J. R. Ipsen},
journal= {arXiv preprint arXiv:1705.05047},
year = {2017}
}
Comments
14 pages, 1 figure. to appear in J. Stat. Mech