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Abstract
Space plasmas in the inner heliosphere exist in a weakly collisional and turbulent state. Though energy transfer from large scales to smaller scales by turbulent cascade is widely accepted as an important feature of space plasmas, details of its exact dissipation process are lacking. Features arising because of turbulence, such as intermittency and temperature anisotropy, play important roles in the dynamics of space plasmas. Microkinetic linear instabilities induced by temperature anisotropy have been shown to change the statistical characteristics of plasma in a significant way.
Since the two processes, turbulence cascade and microkinetic instabilities, occur in the same physical and phase space, there is an interplay at work. In this study we investigated this interplay and the subsequent competition arising between the two, linear and nonlinear, processes. We found an explicit connection between intermittency and linear instability growth rates. We also showed localization of temperature enhancement regions along the intermittent structures, which in turn can trigger linear instabilities. Investigation of the two processes shed light on why linear theory works as well as it does, and shows the complicated nature of their interplay.
Information related to the exact spatial structure of the interplanetary magnetic field is vital to our understanding of the type of turbulence active in the space plasmas and the mechanism of turbulence cascade. This will help us discern the interplay between the two processes. We thus also report on a proof of concept study of magnetic field topology reconstruction using Gaussian Processes in machine learning.
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