Please use this identifier to cite or link to this item: http://hdl.handle.net/2248/8303
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dc.contributor.authorSreedevi, Anu-
dc.contributor.authorJha, Bibhuti K-
dc.contributor.authorKarak, Bidya Binay-
dc.contributor.authorBanerjee, D-
dc.date.accessioned2024-01-04T05:18:52Z-
dc.date.available2024-01-04T05:18:52Z-
dc.date.issued2023-10-
dc.identifier.citationThe Astrophysical Journal Supplement Series, Vol. 268, No. 2, 58en_US
dc.identifier.issn0067-0049-
dc.identifier.urihttp://hdl.handle.net/2248/8303-
dc.descriptionOpen Accessen_US
dc.descriptionOriginal content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.-
dc.description.abstractBipolar magnetic regions (BMRs) provide crucial information about solar magnetism. They exhibit varying morphology and magnetic properties throughout their lifetime, and studying these properties can provide valuable insights into the workings of the solar dynamo. The majority of previous studies have counted every detected BMR as a new one and have not been able to study the full life history of each BMR. To address this issue, we have developed Automatic Tracking Algorithm for BMRs (AutoTAB) that tracks the BMRs for their entire lifetime or throughout their disk passage. AutoTAB uses the binary maps of detected BMRs and their overlapping criterion to automatically track the regions. In this first article of this project, we provide a detailed description of the working of the algorithm and evaluate its strengths and weaknesses by comparing it with existing algorithms. AutoTAB excels in tracking even for the small BMRs (with a flux of ∼1020 Mx), and it has successfully tracked 9152 BMRs over the last two solar cycles (1996–2020), providing a comprehensive data set that depicts the evolution of various properties for each BMR. The tracked BMRs exhibit the well-known butterfly diagram and 11 yr solar cycle variation, except for small BMRs, which appear at all phases of the solar cycle and show a weak latitudinal dependence. Finally, we discuss the possibility of adapting our algorithm to other data sets and expanding the technique to track other solar features in the future.en_US
dc.language.isoenen_US
dc.publisherAmerican Astronomical Societyen_US
dc.relation.urihttps://doi.org/10.3847/1538-4365/acec47-
dc.rights© 2023. The Author(s)-
dc.subjectSolar magnetic fieldsen_US
dc.subjectSolar active regionsen_US
dc.subjectSunspotsen_US
dc.subjectBipolar sunspot groupsen_US
dc.subjectSolar cycleen_US
dc.subjectSolar magnetic flux emergenceen_US
dc.subjectSunspot groupsen_US
dc.subjectSunspot cycleen_US
dc.titleAutoTAB: Automatic Tracking Algorithm for Bipolar Magnetic Regionsen_US
dc.typeArticleen_US
Appears in Collections:IIAP Publications

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