研究目的
Investigating the thermal distribution of a solar active region to confirm the presence of a very hot plasma component using EUV spectroscopic data.
研究成果
The study confirms the presence of a very hot plasma component in the solar active region core, with a peak at log T = 6.6, supporting impulsive heating models. The methodology provides tighter constraints on emission measure distributions, but future work requires more spectral lines sensitive to high temperatures for improved diagnostics.
研究不足
Uncertainties in the analysis may be underestimated as only photon statistical errors are considered; systematic errors from instrument calibration, atomic data, and chemical abundances are not fully accounted for. The DEM structures are reliable only on scales larger than Δ log T = 0.2, and the presence of very hot components is based on limited spectral lines.
1:Experimental Design and Method Selection:
The study uses spectroscopic data from Hinode/EIS, imaging data from SDO/AIA and Hinode/XRT. The Markov-chain Monte Carlo (MCMC) method is applied for emission measure distribution reconstruction, with cross-checks using a different inversion method (Del Zanna method) and additional data from imagers.
2:Sample Selection and Data Sources:
Data from active region AR 11289 observed on 2011 September
3:Two sub-regions are selected:
one hot and one cool, based on AIA channel intensities.
4:List of Experimental Equipment and Materials:
Hinode/EIS spectrometer, SDO/AIA imager, Hinode/XRT telescope. Specific filters and channels used include AIA 171 ?, 335 ?, 94 ?, and XRT Ti_poly filter.
5:Experimental Procedures and Operational Workflow:
EIS data processed with eis_prep routine for dark current removal, cosmic ray correction, and radiometric calibration. Images co-aligned using SolarSoft routines. Spectra averaged over selected strips, lines fitted with Gaussian profiles, and fluxes measured. DEM reconstruction performed with MCMC and Del Zanna methods.
6:Data Analysis Methods:
Emission measure loci method and MCMC technique for DEM reconstruction. Flux ratios and uncertainties calculated, with cross-validation using AIA and XRT data.
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