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Automated Classification of Plasma Regions Using 3D Particle Energy Distributions

Journal of geophysical research. Space physics, 2021-10, Vol.126 (10) [Peer Reviewed Journal]

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Title:
Automated Classification of Plasma Regions Using 3D Particle Energy Distributions
Author: Olshevsky, Viacheslav ; Khotyaintsev, Yuri, V ; Lalti, Ahmad ; Divin, Andrey ; Delzanno, Gian Luca ; Anderzén Rodenkirchen, Sven ; Herman, Pawel ; Chien, Steven W. D. ; Avanov, Levon ; Dimmock, Andrew P. ; Markidis, Stefano
Subjects: bow shock ; machine learning ; MMS
Is Part Of: Journal of geophysical research. Space physics, 2021-10, Vol.126 (10)
Description: We investigate the properties of the ion sky maps produced by the Dual Ion Spectrometers (DIS) from the Fast Plasma Investigation (FPI). We have trained a convolutional neural network classifier to predict four regions crossed by the Magnetospheric Multiscale Mission (MMS) on the dayside magnetosphere: solar wind, ion foreshock, magnetosheath, and magnetopause using solely DIS spectrograms. The accuracy of the classifier is >98%. We use the classifier to detect mixed plasma regions, in particular to find the bow shock regions. A similar approach can be used to identify the magnetopause crossings and reveal regions prone to magnetic reconnection. Data processing through the trained classifier is fast and efficient and thus can be used for classification for the whole MMS database.
Language: English
Identifier: ISSN: 2169-9402
ISSN: 2169-9380
EISSN: 2169-9402
DOI: 10.1029/2021JA029620
Source: SWEPUB Freely available online

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