Entropy–complexity analysis in some globally-coupled systems

Antoine M. Chrisment and Marie-Christine Firpo

Physica A: Statistical Mechanics and its Applications, 2016, vol. 460, issue C, 162-173

Abstract: Globally-coupled N-body systems are well known to possess an intricate dynamics. When N is large, collective effects may drastically lower the effective dimension of the dynamics breaking the conditions on ergodicity necessary for the applicability of statistical mechanics. These problems are here illustrated and discussed through an entropy–complexity analysis of the repulsive Hamiltonian mean-field model. Using a Poincaré section of the mean-field time series provides a natural sampling time in the entropy–complexity treatment. This approach is shown to single-out the out-of-equilibrium dynamical features and to uncover a transition of the system dynamics from low-energy non-Boltzmann quasi-stationary states to high-energy stochastic-like behavior.

Keywords: Deterministic chaos; Stochasticity; Long-range interacting systems; Mean-field models; Quasi-stationary states (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437116301947
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:460:y:2016:i:c:p:162-173

DOI: 10.1016/j.physa.2016.05.009

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().