2022
DOI: 10.1029/2022ja030454
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A Database of MMS Bow Shock Crossings Compiled Using Machine Learning

Abstract: Identifying collisionless shock crossings in data sent from spacecraft has so far been done manually or using basic algorithms. It is a tedious job that shock physicists have to go through if they want to conduct case studies or perform statistical studies. We use a machine learning approach to automatically identify shock crossings from the Magnetospheric Multiscale (MMS) spacecraft. We compiled a database of 2,797 shock crossings, spanning a period from October 2015 to December 2020, including various spacec… Show more

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Cited by 26 publications
(29 citation statements)
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“…The shock crossing was observed by MMS 1 on 07 October 2015 at 12:07:10 and documented in the database (Lalti et al. 2022). The model shock normal is used (Farris & Russell 1994).…”
Section: Observational Illustrationmentioning
confidence: 89%
“…The shock crossing was observed by MMS 1 on 07 October 2015 at 12:07:10 and documented in the database (Lalti et al. 2022). The model shock normal is used (Farris & Russell 1994).…”
Section: Observational Illustrationmentioning
confidence: 89%
“…The three selected events are quasi-perpendicular with Alfvén Mach numbers ranging from 9 to 17 which is relatively high compared to most times MMS has encountered the bow shock, cf. (Lalti et al, 2022).…”
Section: Observationsmentioning
confidence: 99%
“…MMS crosses the Earth's bow shock from the downstream magnetosheath to the upstream solar wind. This crossing is selected from over 1000 MMS shock crossings in the database created by Lalti, Khotyaintsev, Dimmock, et al (2022). It displays one of the highest fluxes of energetic electrons, measured in the energy range 10-20 keV.…”
Section: Observationmentioning
confidence: 99%