Working Principle of the Calibration Algorithm for High Dynamic Range Solar Imaging with Square Kilometre Array Precursor
Devojyoti Kansabanik

TL;DR
This paper explains the working principle of a calibration algorithm that enables high-dynamic-range, high-fidelity solar imaging at low radio frequencies, demonstrating its effectiveness through analysis and simulation, and highlighting its suitability for future large radio arrays.
Contribution
It introduces and analyzes a calibration algorithm, AIRCARS, that leverages partial phase stability for high-quality solar imaging with the MWA, and discusses its potential for SKA and future interferometers.
Findings
AIRCARS produces the best spectroscopic snapshot solar images to date.
The algorithm effectively utilizes the MWA's partial phase stability.
It is suitable for high-dynamic-range solar imaging with future arrays.
Abstract
Imaging the low-frequency radio Sun is an intrinsically challenging problem. Meter-wavelength solar emission spans angular scales from a few arcminutes to a few degrees. These emissions show temporal and spectral variability on a sub-second and sub-MHz scales. The brightness temperature of these emissions also varies by many orders of magnitude, which requires high-dynamic-range spectroscopic snapshot imaging. With the unique array configuration of the Murchison Widefield Array (MWA), and the robust calibration and imaging pipeline, Automated Imaging Routine for the Compact Arrays for the Radio Sun (AIRCARS) produces the best spectroscopic snapshot solar images available to date. The working principle and the strength of this algorithm are demonstrated using statistical analysis and simulation. AIRCARS uses the partial phase stability of the MWA, which has a compact core with a large…
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Taxonomy
TopicsSolar Radiation and Photovoltaics · Calibration and Measurement Techniques · Infrared Target Detection Methodologies
