| Authors Affiliation: | 1 NASA Postdoctoral Program Fellow, NASA Marshall Space Flight Center, ST13, Huntsville, AL, USA
2 Center for Space Plasma and Aeronomic Research, The University of Alabama in Huntsville, Huntsville, AL, US
3 NASA Marshall Space Flight Center, ST13, Huntsville, AL, USA
4 Department of Physics and Astronomy (MS 108), Rice University, 6100 Main Street, Houston, TX 77005, USA
5 Department of Physics, American University, Washington, DC, USA
6 NASA Goddard Space Flight Center, Heliophysics Science Division, Greenbelt, MD 20771, USA
7 Center for Astrophysics — Harvard & Smithsonian, Cambridge, MA 02138, USA
8 Astronomical Institute,Czech Academy of Sciences, Fricova 298,25165 Ondrejov, CzechRepublic
9 DAMTP, Centre for Mathematical Sciences, University of Cambridge, Wilberforce Road, Cambridge CB3 0WA, UK
10 Space Science Division, Naval Research Laboratory, Washington, DC 20375, USA
11 University of Central Lancashire, Preston, PR1 2HE, UK |
| Abstract : | Nanoflares are thought to be one of the prime candidates that can heat the solar corona to its multimillion kelvin temperature. Individual nanoflares are difficult to detect with the present generation instruments, however their presence can be inferred by comparing simulated nanoflare-heated plasma emissions with the observed emission. Using HYDRAD coronal loop simulations, we model the emission from an X-ray bright point observed by the Marshall Grazing Incidence X-ray Spectrometer (MaGIXS), along with concurrent observations from the Atmospheric Imaging Assembly (AIA) onboard Solar Dynamics Observatory (SDO) and X-Ray Telescope (XRT) onboard Hinode observatory. The length and magnetic field strength of the coronal loops are derived from the potential field extrapolation of the observed photospheric magnetogram by Helioseismic and Magnetic Imager (HMI) onboard SDO. Each loop is assumed to be heated by random nanoflares, whose magnitude and frequency are determined by the loop length and magnetic field strength. The simulation results are then compared and matched against the measured intensity from AIA, XRT, and MaGIXS. Our model results indicate the loop morphology and emissions from the XBP under study could be well matched by a distribution of nanoflares with average delay times 400 s to 800 s, which strongly suggest that the heating is dominated by high-frequency events. Further, we demonstrate the high sensitivity of MaGIXS and XRT to diagnose the heating frequency using this method, while AIA passbands are found to be the least sensitive. |
