Abstract

One of the fundamental open questions in plasma physics is the role of non-thermal particles distributions in poorly collisional plasma environments, a system that is commonly found throughout the Universe, e.g., the solar wind and the Earth’s magnetosphere correspond to natural plasma physics laboratories in which turbulent phenomena can be studied. Our study perspective is born from the method of Horizontal Visibility Graph (HVG) that has been developed in the last years to analyze time series avoiding the tedium and the high computational cost that other methods offer. Here, we build a complex network based on directed HVG technique applied to magnetic field fluctuations time series obtained from Particle In Cell (PIC) simulations of a magnetized collisionless plasma to distinguish the degree distributions and calculate the Kullback–Leibler Divergence (KLD) as a measure of relative entropy of data sets produced by processes that are not in equilibrium. First, we analyze the connectivity probability distribution for the undirected version of HVG finding how the Kappa distribution for low values of tends to be an uncorrelated time series, while the Maxwell–Boltzmann distribution shows a correlated stochastic processes behavior. Subsequently, we investigate the degree of temporary irreversibility of magnetic fluctuations that are self-generated by the plasma, comparing the case of a thermal plasma (described by a Maxwell–Botzmann velocity distribution function) with non-thermal Kappa distributions. We have shown that the KLD associated to the HVG is able to distinguish the level of reversibility that is associated to the thermal equilibrium in the plasma, because the dissipative degree of the system increases as the value of parameter decreases and the distribution function departs from the Maxwell–Boltzmann equilibrium.

Highlights

  • In a turbulent collisionless plasma, movement on a kinetic scale occurs in a chaotic manner, and it is determined by large-scale collective behavior and localized small-scale processes

  • The Kullback–Leibler Divergence (KLD) or relative entropy value, is a measure of temporary irreversibility of data sets produced by processes that are not in equilibrium, and it gives information on the production of entropy generated by the physical system, when considering a high degree of irreversibility as a chaotic and dissipative system [40]

  • We apply the Horizontal Visibility Graph (HVG) method to study the time series of magnetic fluctuations that were obtained from the Particle In Cell (PIC) simulations

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Summary

Introduction

In a turbulent collisionless plasma (in which Coulomb collisions are neglected), movement on a kinetic scale (spatial scales of the order of the particles Larmor radius or skindepth) occurs in a chaotic manner, and it is determined by large-scale collective behavior and localized small-scale processes. The KLD or relative entropy value, is a measure of temporary irreversibility of data sets produced by processes that are not in equilibrium, and it gives information on the production of entropy generated by the physical system, when considering a high degree of irreversibility as a chaotic and dissipative system [40] Under this context, the recent results by Acosta et al [48] have suggested that the use of the HVG method can provide valuable information to characterize turbulence in collisionless plasmas, and that the KLD may be used as a proxy to establish how thermal or non-thermal are the velocity distributions of a plasma, only by looking at the magnetic fluctuations and their properties.

Horizontal Visibility Graph
Particle in Cell Simulations
Results
Discussion and Conclusions
Full Text
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