ORIGINAL RESEARCH article
Front. Astron. Space Sci.
Sec. Planetary Science
Volume 12 - 2025 | doi: 10.3389/fspas.2025.1608091
This article is part of the Research TopicExploring Solar Wind Interactions with Inner Solar System Bodies: New Frontiers, Insights, and Future DirectionsView all articles
Automated Classification of MESSENGER Plasma Observations via Unsupervised Transfer Learning
Provisionally accepted- 1Applied Physics Laboratory, Johns Hopkins University, Laurel, United States
- 2Southwest Research Institute (SwRI), San Antonio, Texas, United States
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We applied an unsupervised clustering algorithm, initially trained on data from the Magnetospheric Multiscale (MMS) mission at Earth, to MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) observations at Mercury to identify three distinct plasma regions: magnetosphere, magnetosheath, and solar wind. Our methodology demonstrates a proof of concept of the applicability of transfer learning for heliophysics, a machine learning technique where knowledge learned from one task is reused to perform a similar unsupervised learning task with additional fine tuning. While our method requires modifications to the model from post-cleaning rules due to instrument effects, it allows for rapid classification using just a few examples to generate post-cleaning rules. Since there is no ground truth or standardized validation set to compare with, we compare our model's result with published magnetopause and bow shock lists and find that the clustering algorithm is agreement with 67% of bow shock crossings and 74% of magnetopause crossings. These findings highlight the potential use of clustering algorithms across multiple planetary environments.
Keywords: Messenger, machine learning, unsupervised learning, Transfer Learning, Plasma, MMS, bow shock, Magnetopause
Received: 08 Apr 2025; Accepted: 10 Jul 2025.
Copyright: © 2025 Toy-Edens, Mo, Allen, Vines and Raptis. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Vicki Toy-Edens, Applied Physics Laboratory, Johns Hopkins University, Laurel, United States
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