Machine Learning Methods Applied to the Global Modeling of Event-Driven Pitch Angle Diffusion Coefficients During High Speed Streams

Machine Learning Methods Applied to the Global Modeling of Event-Driven Pitch Angle Diffusion Coefficients During High Speed Streams

Whistler-mode waves in the inner magnetosphere cause electron precipitation in the atmosphere through the physical process of pitch-angle diffusion. The computation of pitch-angle diffusion relies on quasi-linear theory and becomes time-consuming as soon as it is performed at high temporal resolutio...

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Bibliographic Details
Main Authors: G. Kluth , J.-F. Ripoll , S. Has , A. Fischer , M. Mougeot , E. Camporeale 
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-05-01
Series:Frontiers in Physics
Subjects:
machine learning
pitch angle diffusion
event-driven
data exploration
high speed streams
Online Access:https://www.frontiersin.org/articles/10.3389/fphy.2022.786639/full

Internet

https://www.frontiersin.org/articles/10.3389/fphy.2022.786639/full

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