Flare and back again: the analysis of high energy emission from small solar flares

Cooper, Kristopher (2022) Flare and back again: the analysis of high energy emission from small solar flares. PhD thesis, University of Glasgow.

Abstract

The solar atmosphere has a peculiar property where its outer layer, the corona, is hotter than its base, the photosphere; this issue is termed the coronal heating problem. One possible solution is that small solar flares—microflares and nanoflares—occur in such a frequency that they produce more net energy than their larger counterparts, that are insufficient in themselves, to heat the corona. To investigate this premise, microflare extreme ultraviolet (EUV) and X-ray emission must be studied to determine their production mechanisms and energetics.

In this thesis, we focus on the observations of, and analytical tools for, the study of high energy microflare emission with particular emphasis on X-ray spectroscopy. In Chapter 1, we introduce the necessary context for microflares with respect to the solar atmosphere as well as a description of their high energy EUV and X-ray emission and how this can be modelled mathematically. Chapter 2 provides an overview of the hard X-ray, soft X-ray, and EUV instruments used throughout this thesis with specific attention given to the Nuclear Spectroscopic Telescope ARray (NuSTAR).

NuSTAR is an astrophysical X-ray telescope capable of observing the Sun with direct imaging spectroscopy providing a unique sensitivity >2.5 keV. In Chapter 3, we investigate ten NuSTAR microflares that originated from active region AR12721 and occurred between 2018 September 9–10. The ten microflares are all weak sub-A GOES class and still reach temperatures up to ∼10MK. One microflare shows direct evidence for non-thermal emission and eight of the ten show indications of photospheric magnetic flux cancellation in proximity to their footpoints. Chapter 4 then investigates the weakest microflare from Chapter 3 further, finding it to be the weakest active region X-ray microflare.

Chapter 5 provides an overview of X-ray spectral fitting approaches where the nuances of X-ray spectral data analysis, utilising different fitting and statistical methods, are discussed. We then describe two widely used X-ray spectral fitting programs, OSPEX and XSPEC, detailing their advantages and limitations before introducing a new Python X-ray spectral fitting tool called Sunxspex. Sunxspex is optimised for solar data products and aims to combine the capabilities of OSPEX and XSPEC into one program.

Using examples fromNuSTAR, the Reuven Ramaty High-Energy Solar Spectroscopic Imager (RHESSI), and Solar Orbiter’s Spectrometer/Telescope for Imaging X-rays (STIX), we showcase the abilities of Sunxspex in Chapter 6. We re-analyse data from existing NuSTAR and RHESSI studies, finding good agreement between fitted model parameter values, while executing new analysis with the same data and STIX data that was not possible with software like OSPEX and XSPEC. Chapter 7 describes the nested sampling algorithm which is made available in Sunxspex and allows for quantitative comparisons between different models being fitted to the same data.

Finally, Chapter 8 presents the analysis of five microflares and a jet observed by NuSTAR. The first two microflares are observed during the 2020 January solar observation campaign while the last three microflares and the jet are from the 2021 November campaign. The microflares show evidence of temperatures>10MKbeing present with several of the microflares showing potential direct evidence of non-thermal emission. The jet reaches quiescent, non-flaring active region temperatures of ∼4MK while being located far from the closest active region.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Subjects: Q Science > QB Astronomy
• Colleges/Schools: College of Science and Engineering > School of Physics and Astronomy
• Supervisor's Name: Hannah, Dr. Iain
• Date of Award: 2022
• Depositing User: Theses Team
• Unique ID: glathesis:2022-83305
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 12 Dec 2022 16:14
• Last Modified: 13 Feb 2023 09:24
• Thesis DOI: 10.5525/gla.thesis.83305
• URI: https://theses.gla.ac.uk/id/eprint/83305