SUNDISH Project - Scientific Analysis of the Solar Images

Scientific Analysis of the Solar Images

Figure 1: Widget of SUNDARA

The radio Sun is dominated by the quiet Sun emission, which covers the entire surface of the solar disk as a mostly uniform background emission with some additional brighter spots. These bright surfaces are called active regions (ARs), characterised by strong or intense local magnetic fields, and provide energy for solar flares and coronal mass ejections (CMEs).

The AR understanding has been pushed forward in the last decade by the ongoing improvement of observation instruments, in particular high-energy facilities on-board several missions, such as Hinode, and Solar Dynamics Observatory (SDO). As opposed to our single-dish radio observations, whose solar maps cannot resolve the detailed AR morphology, these high-energy facilities - characterised by a cadence of the order of 10 minutes and a spatial resolution of the order of arcseconds - allow to show ARs characterised by (1) a complex morphology [1], (2) magnetic structures [2], and (3) the relatively long-term evolution (ranging from hours to months) probably connected with surrounding magnetic fields, and the solar activity cycle (e.g., [3][4][5]). Usually, ARs originate by the emergence of toroidal magnetic flux from the deeper convection zone [3][4], described by several dynamo models (e.g., [6][7][8]). The AR structure is mostly characterised by a simple bipole, and sometimes by a number of magnetic elements of various size scales [9].

We can identify ARs and measure their fluxes and spectra thanks a sophisticated code -fully self-consistent- developed in Python, called SUNDARA (SUNDish Active Region Analyser), adapted for our purposes from Marongiu et al. 2020 [10]. This Python code is very user-friendly thanks its widget (Figure 1), that allows to set up the preferred analysis.

SUNDARA receives in input the maps (in standard FITS format) produced by the observation with the radio telescopes of the INAF Network (Medicina and SRT). After the adjustment of the FITS header of these maps according to the current solar maps features (Figure 2), SUNDARA unearths ARs in the solar disk (or in its edge, Figure 5) through several algorithms, that search images similar to a defined elliptical 2D Gaussian kernel (e.g. [10], [11], [12]), or that extract regions in the solar disk above a specific threshold (3 times the RMS of the solar disk). For a better identification, the program generates a mask which subtract the quiet Sun contribution using the fit described in Landi et al. 2008 [13].

The detected AR are deeply analysed by modelling an elliptical 2D Gaussian with noise [10], where the free parameters are the coordinates of the active region (in heliographic coordinates, LON and LAT), the amplitude (in units of sfu), the semiaxes of the ellipse, the rotation angle of the ellipse and the noise. To guide the modelling, we set up as initial point the AR coordinates estimated by the initial AR detection and the minimum RMS of the quiet Sun of the image. For each modelled AR, SUNDARA sets up a research region with semiaxes fixed at twice the fitted ones (Figure 4).

Moreover, the identified ARs are automatically associate in position with the detected ARs reported in other catalogues at other observing frequencies (Figure 3).

In little more than 5 minutes, SUNDARA produces a complete analysis of a solar map, saving a directory containing images, plots and several tables with physical information (brightness temperatures, fluxes and spectral indices, with respective errors) of the ARs detected in the maps. The uncertainties on the brightness temperature, flux densities and spectral indices originate from the Landi and Chiuderi Drago's fit, the RMS of the map and the calibration procedure. A deep analysis (also a few hours) is possible thanks a Bayesian approach based on Markov Chain MonteCarlo (MCMC) simulation [14].

Figure 2: A solar map showed by SUNDARA

Figure 3: Indication of the AR position from external catalogues in the SUNDARA solar map

Figure 4: Fit procedure for an AR with SUNDARA

Figure 5: SUNDARA is able to analyse ARs in the edge of the solar disk

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