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Exploring Mutual Information between IRIS Spectral Lines. II. Calculating the Most Probable Response in all Spectral Windows

Type of publication Peer-reviewed
Publikationsform Original article (peer-reviewed)
Author Panos Brandon, Kleint Lucia,
Project Machine Learning based Analytics for Big Data in Astronomy
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Original article (peer-reviewed)

Journal The Astrophysical Journal
Volume (Issue) 915(2)
Page(s) 77 - 77
Title of proceedings The Astrophysical Journal
DOI 10.3847/1538-4357/ac00c0


A three-dimensional picture of the solar atmosphere's thermodynamics can be obtained by jointly analyzing multiple spectral lines that span many formation heights. In Paper I, we found strong correlations between spectral shapes from a variety of different ions during solar flares in comparison to the quiet Sun. We extend these techniques to address the following questions: which regions of the solar atmosphere are most connected during a solar flare, and what are the most likely responses across several spectral windows based on the observation of a single Mg ii spectrum? Our models are derived from several million IRIS spectra collected from 21 M- and X-class flares. We applied this framework to archetypal Mg ii flare spectra and analyzed the results from a multiline perspective. We find that (1) the line correlations from the photosphere to the transition region are highest in flare ribbons. (2) Blueshifted reversals appear simultaneously in Mg ii, C ii, and Si iv during the impulsive phase, with Si iv displaying possible optical depth effects. Fe ii shows signs of strong emission, indicating deep early heating. (3) The Mg ii line appears to typically evolve a blueshifted reversal that later returns to line center and becomes single peaked within 1–3 minutes. The widths of these single-peaked profiles slowly erode with time. During the later flare stages, strong red-wing enhancements indicating coronal rain are evident in Mg ii, C ii, and Si iv. Our framework is easily adaptable to any multiline data set and enables comprehensive statistical analyses of the atmospheric behavior in different spectral windows.