Permutation Entropy for the Characterization of the Attractive Hamiltonian Mean-Field Model
Melissa Fuentealba, Danilo M. Rivera, Roberto E. Navarro

TL;DR
This paper applies permutation entropy and complexity-entropy analysis to characterize quasi-stationary states of the Hamiltonian Mean-Field model, revealing insights into order, disorder, and chaos in phase-space dynamics.
Contribution
It introduces the use of permutation entropy to analyze magnetization fluctuations in the HMF model, providing a new perspective on its phase transitions and state characterization.
Findings
HMF tends towards order in non-homogeneous states
Homogeneous states tend to disorder with increased initial magnetization
HMF exhibits low entropy but high complexity, indicating chaotic and intermittent behavior
Abstract
The Hamiltonian Mean-Field (HMF) model is a long-range interaction model that exhibits quasi-stationary states associated with a phase transition. Its quasi-stationary states with a lifetime diverging with the number of particles in the system. These states are characterized by homogeneous or non-homogeneous structures in phase-space. There exists a phase-transition between these states that have been traditionally characterized by the their mean magnetization. However, the magnetization also exhibits fluctuations in time around its mean value, that can be an indicator of the kind of quasi-stationary state. Thus, we want to characterize the quasi-stationary states of the HMF model through the time-series of the magnetization and its fluctuations through a measure of information, i.e. the permutation entropy and the complexity-entropy plane. Permutation entropy is a measure for…
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Taxonomy
TopicsOpinion Dynamics and Social Influence · Theoretical and Computational Physics · Advanced Thermodynamics and Statistical Mechanics
