Temperature evolution plots during an M1.0 flare on July 21, 2016. Each plot shows a different assumption of the abundance of elements in the Sun: coronal (left) and photospheric (right)
Probing Solar Flares: Unveiling Insights with XRT Data, XRTpy Analysis, and CHIANTI Database
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Elemental abundances play a pivotal role in thermal analysis when investigating solar flares. By observing elemental abundances during the peak of a flare, we can gain valuable insights into chromospheric evaporation. Leveraging elemental abundance assumptions alongside XRT data and spectroscopy enhances our understanding of flare formation, development, and decay processes. To facilitate this analysis, we utilized XRTpy, an innovative Python package tailored for such investigations. XRTpy offers three preset elemental abundance settings from the CHIANTI 10.0 database: Coronal, Hybrid, and Photospheric. The CHIANTI database provides essential plasma emission model data, dependent on wavelength and temperature. The GIF showcases temperature evolution during an M1.0 flare peaking on July 21, 2016, with two abundance assumptions: coronal and photospheric. On the right, the photospheric assumption displays a distinctive greenish-blue palette compared to the coronal assumption of the left. Utilizing the filter-ratio method, this signifies that the photospheric assumption yields a lower temperature reading for the same temperature response ratio captured by XRT. The pursuit of unraveling the intricacies of solar flares remains an exhilarating journey! Keywords: Flare, AR Tracking Filters: Thin-Be, Med-Be |
(Prepared by Anna Chen and Joy Velasquez)
The XRT instrument team is comprised of SAO, NASA, JAXA, and NAOJ.
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