Uncovering Solar Wind Phenomena with iSAX, HDBSCAN, Human-in-the-loop and PSP Observations
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arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866909878702833664 |
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| author | Filho, Valmir P Moraes Martin, Daniela Kobayashi, Jasmine R. O'Brien, Connor Hong, Jinsu Samara, Evangelia Gallego, Joseph |
| author_facet | Filho, Valmir P Moraes Martin, Daniela Kobayashi, Jasmine R. O'Brien, Connor Hong, Jinsu Samara, Evangelia Gallego, Joseph |
| contents | The solar wind is a dynamic plasma outflow that shapes heliospheric conditions and drives space weather. Identifying its large-scale phenomena is crucial, yet the increasing volume of high-cadence Parker Solar Probe (PSP) observations poses challenges for scalable, interpretable analysis. We present a pipeline combining symbolic compression, density-based clustering, and human-in-the-loop validation. Applied to 2018-2024 PSP data, it efficiently processes over 150 GB of magnetic and plasma measurements, recovering known structures, detecting uncatalogued CMEs and transient events, and demonstrating robustness across multiple time scales. A key outcome is the systematic use of the magnetic deflection angle ($θ_B$) as a unifying metric across solar wind phenomena. This framework provides a scalable, interpretable, expert-validated approach to solar wind analysis, producing expanded event catalogs and supporting improved space weather forecasting. The code and configuration files used in this study are publicly available to support reproducibility. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_21042 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Uncovering Solar Wind Phenomena with iSAX, HDBSCAN, Human-in-the-loop and PSP Observations Filho, Valmir P Moraes Martin, Daniela Kobayashi, Jasmine R. O'Brien, Connor Hong, Jinsu Samara, Evangelia Gallego, Joseph Solar and Stellar Astrophysics The solar wind is a dynamic plasma outflow that shapes heliospheric conditions and drives space weather. Identifying its large-scale phenomena is crucial, yet the increasing volume of high-cadence Parker Solar Probe (PSP) observations poses challenges for scalable, interpretable analysis. We present a pipeline combining symbolic compression, density-based clustering, and human-in-the-loop validation. Applied to 2018-2024 PSP data, it efficiently processes over 150 GB of magnetic and plasma measurements, recovering known structures, detecting uncatalogued CMEs and transient events, and demonstrating robustness across multiple time scales. A key outcome is the systematic use of the magnetic deflection angle ($θ_B$) as a unifying metric across solar wind phenomena. This framework provides a scalable, interpretable, expert-validated approach to solar wind analysis, producing expanded event catalogs and supporting improved space weather forecasting. The code and configuration files used in this study are publicly available to support reproducibility. |
| title | Uncovering Solar Wind Phenomena with iSAX, HDBSCAN, Human-in-the-loop and PSP Observations |
| topic | Solar and Stellar Astrophysics |
| url | https://arxiv.org/abs/2510.21042 |