The European Physical Journal Special Topics

, Volume 226, Issue 3, pp 341–351

Relating high dimensional stochastic complex systems to low-dimensional intermittency

Regular Article

DOI: 10.1140/epjst/e2016-60264-4

Cite this article as:
Diaz-Ruelas, A., Jensen, H.J., Piovani, D. et al. Eur. Phys. J. Spec. Top. (2017) 226: 341. doi:10.1140/epjst/e2016-60264-4
Part of the following topical collections:
  1. Nonlinearity, Nonequilibrium and Complexity: Questions and Perspectives in Statistical Physics

Abstract

We evaluate the implication and outlook of an unanticipated simplification in the macroscopic behavior of two high-dimensional sto-chastic models: the Replicator Model with Mutations and the Tangled Nature Model (TaNa) of evolutionary ecology. This simplification consists of the apparent display of low-dimensional dynamics in the non-stationary intermittent time evolution of the model on a coarse-grained scale. Evolution on this time scale spans generations of individuals, rather than single reproduction, death or mutation events. While a local one-dimensional map close to a tangent bifurcation can be derived from a mean-field version of the TaNa model, a nonlinear dynamical model consisting of successive tangent bifurcations generates time evolution patterns resembling those of the full TaNa model. To advance the interpretation of this finding, here we consider parallel results on a game-theoretic version of the TaNa model that in discrete time yields a coupled map lattice. This in turn is represented, a la Langevin, by a one-dimensional nonlinear map. Among various kinds of behaviours we obtain intermittent evolution associated with tangent bifurcations. We discuss our results.

Copyright information

© EDP Sciences and Springer 2017

Authors and Affiliations

  1. 1.Instituto de Física, Universidad Nacional Autónoma de México, Ciudad UniversitariaCiudad de MéxicoMexico
  2. 2.Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad UniversitariaCiudad de MéxicoMexico
  3. 3.Centre for Complexity Science and Department of Mathematics, Imperial College London, South Kensington CampusSW7 2AZUK
  4. 4.Centre for Advanced Spatial Analysis. University College LondonLondonUK