Statistical Analysis of STIX Observed Compact Flares
Abstract
Since the start of operation in January 2021, the Spectrometer/telescope for Imaging X-rays (STIX) onboard the Solar Orbiter registered thousands of very weak (B-class) to very strong (X-(GOES) class) flares. A rapidly growing database of continuous high-quality observations of flares enables us to investigate large groups of events and perform statistical analysis of their properties with the help of existing (e.g. OSPEX) and recently-developed spectral and image reconstruction algorithms based on SolarSoftWare (SSW). In this regard, we have selected a large number (150+) of flares that present compact morphology i.e. one source without any additional structure seen in images reconstructed with grids 3-10. It is to note that while single grid No. 3 has a nominal FWHM resolution close to 15 arcsec, both the very weak as well as strong M-class flares are found to be originated from such a small area. The thermal (Temperature and emission measure) and nonthermal (particle beam properties (electron power, power-law index, cutoff energy) characteristics of the flare plasma have been deduced by fitting the observed STIX spectra using the OSPEX package. With special care, we treated the image reconstruction problem as post-launch STIX grids' geometry is yet to be fully understood. We compared images reconstructed with several algorithms (EM, MEM-GE, MARLIN, Forward Fit) and carefully estimated the sizes of observed sources. The quantities namely volume and thermal energy contained in plasma as well as their time evolution have been derived. For this purpose, the area of the reconstructed X-ray images has been derived in a repetitive manner based on a different cutoff of signal-to-noise ratio. Non-thermal part of the energy budget has also been estimated. We will discuss the differences between the results obtained with this statistical analysis and that obtained with previous HXR observatories.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFMSH22B..07S