HiSAXy: A fast methodology for solar wind structure identification in millions of time series
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arXiv
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| Main Authors: | , , , , , , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866917067093966848 |
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| author | Lamdouar, Hala Sundaresan, Sairam Jungbluth, Anna Saikia, Sudeshna Boro Camarata, Amanda Joy Miles, Nathan Scoczynski, Marcella Stone, Mavis Muñoz-Jaramillo, Andrés Narock, Ayris Szabo, Adam |
| author_facet | Lamdouar, Hala Sundaresan, Sairam Jungbluth, Anna Saikia, Sudeshna Boro Camarata, Amanda Joy Miles, Nathan Scoczynski, Marcella Stone, Mavis Muñoz-Jaramillo, Andrés Narock, Ayris Szabo, Adam |
| contents | We present a hybridized unsupervised clustering algorithm Hisaxy as a novel way to identify frequently occurring magnetic structures embedded in the interplanetary magnetic field (IMF) carried by the solar wind. The Hisaxy algorithm utilizes a combination of indexable Symbolic Aggregate approXimation (iSAX) and Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) to efficiently identify clusters of patterns embedded in time series data. We utilized Hisaxy to identify small-scale structures, known as discontinuities, embedded in time series measurements of the IMF. In doing so, we demonstrate the capability of the algorithm to significantly reduce the amount of human analysis hours required to identify these structures, all the while maintaining a high degree of self similarity within a given cluster of time series data. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_04759 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | HiSAXy: A fast methodology for solar wind structure identification in millions of time series Lamdouar, Hala Sundaresan, Sairam Jungbluth, Anna Saikia, Sudeshna Boro Camarata, Amanda Joy Miles, Nathan Scoczynski, Marcella Stone, Mavis Muñoz-Jaramillo, Andrés Narock, Ayris Szabo, Adam Solar and Stellar Astrophysics We present a hybridized unsupervised clustering algorithm Hisaxy as a novel way to identify frequently occurring magnetic structures embedded in the interplanetary magnetic field (IMF) carried by the solar wind. The Hisaxy algorithm utilizes a combination of indexable Symbolic Aggregate approXimation (iSAX) and Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) to efficiently identify clusters of patterns embedded in time series data. We utilized Hisaxy to identify small-scale structures, known as discontinuities, embedded in time series measurements of the IMF. In doing so, we demonstrate the capability of the algorithm to significantly reduce the amount of human analysis hours required to identify these structures, all the while maintaining a high degree of self similarity within a given cluster of time series data. |
| title | HiSAXy: A fast methodology for solar wind structure identification in millions of time series |
| topic | Solar and Stellar Astrophysics |
| url | https://arxiv.org/abs/2511.04759 |