English

Chaos in high-dimensional dynamical systems with tunable non-reciprocity

Disordered Systems and Neural Networks 2026-04-16 v2

Abstract

High-dimensional dynamical systems of interacting degrees of freedom are ubiquitous in the study of complex systems. When the directed interactions are totally uncorrelated, sufficiently strong and non-linear, many of these systems exhibit a chaotic attractor characterized by a positive maximal Lyapunov exponent (MLE). On the contrary, when the interactions are completely symmetric, the dynamics takes the form of a gradient descent on a carefully defined cost function, and it exhibits slow dynamics and aging. In this work, we consider the intermediate case in which the interactions are partially symmetric, with a parameter {\alpha} tuning the degree of non-reciprocity. We show that for any value of {\alpha} for which the corresponding system has non-reciprocal interactions, the dynamics lands on a chaotic attractor. Correspondingly, the MLE is a non-monotonous function of the degree of non-reciprocity. This implies that conservative forcing deriving from the gradient field of a rough energy landscape can make the system more chaotic.

Keywords

Cite

@article{arxiv.2601.04702,
  title  = {Chaos in high-dimensional dynamical systems with tunable non-reciprocity},
  author = {Samantha Fournier and Pierfrancesco Urbani},
  journal= {arXiv preprint arXiv:2601.04702},
  year   = {2026}
}
R2 v1 2026-07-01T08:55:43.168Z