A multidisciplinary view of space plasma dynamics inspired by the stochastic process theory


Turbulent plasmas are ubiquitous in space and astrophysical settings and display a variety of collective phenomena that, in turn, have a great impact in the dynamics of stellar atmospheres, stellar winds, solar coronal heating, etc. Most of these phenomena are related to the microphysics of nearly-collisionless plasmas, such as the ion-kinetic scale processes transferring energy from electromagnetic fields to particles and leading to energy dissipation and plasma energization. The solar wind, a strongly turbulent plasma flowing in the heliosphere from the expansion of the solar Corona, constitutes an excellent natural laboratory to get precious clues about ion-kinetic scale plasma dynamics. During the last decades, space missions provided in situ data of diverse space plasma environments with an increasingly higher resolution. This enabled the possibility to investigate peculiar properties of fluctuations in the magnetic field and plasma parameters, transitioning from the magnetohydrodynamic (MHD) to the ion-kinetic regime. The kinetic regime is characterized by a global self-similar statistics of the fluctuations, in other words their statistical properties at different scales can be simply superimposed by rescaling. This is a contrasting feature with respect to the local scale-invariance universally observed in the MHD range, where strongly non-Gaussian fluctuations tend to develop towards small scales thus producing the “fat tailed” distributions observed everywhere. In a series of works, we developed a data-driven approach based on the Langevin equation in order to model statistical features of space plasma kinetic fluctuations. In practical terms, the stochastic variable is represented by the fluctuation of the magnetic field and the process is its evolution through the scales. This rather simple framework allows us to make predictions about statistical properties observed in different space plasma environments which have been tested on several spacecraft data samples and numerical simulations. As far as such fluctuations are of the Langevin type, their statistics evolve according to a Fokker-Planck equation. A derivation of the ion-kinetic scale statistics based on this equation makes it possible to derive the invariant distribution function, which turns out to be a generalized kappa distribution. The aim of this contribution is to introduce the framework of stochastic modeling in the context of space plasma physics and to illustrate how this methodology is truly general, and thus suitable for applications in many different physical contexts.

06/03/2024

Speaker: Simone Benella (INAF-IAPS)
Date: Wednesday 6 March 2024, at 11:00
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