A Genetic Algorithm to model Solar Radio Active Regions from 3D Magnetic Field Extrapolations
Alexandre Jos\'e de Oliveira e Silva, Caius L. Selhorst, Joaquim E. R., Costa, Paulo J. A. Sim\~oes, C. Guillermo Gim\'enez de Castro, Sven, Wedemeyer, Stephen M. White, Roman Braj\v{s}a, Adriana Valio

TL;DR
This paper introduces a genetic algorithm-based model to simulate solar active region atmospheres using multi-frequency radio observations, providing insights into the height of the transition region and matching observed brightness temperatures.
Contribution
It presents a novel data-constrained model employing a genetic algorithm to determine plasma profiles and magnetic fields in solar active regions from radio data.
Findings
Transition region height varies with region type: 1080 km for umbrae, 1800 km for penumbrae, 2000 km outside sunspots.
Model achieves good agreement with observed brightness temperature maps.
Model can predict emission at unobserved frequencies.
Abstract
In recent decades our understanding of solar active regions (ARs) has improved substantially due to observations made with better angular resolution and wider spectral coverage. While prior AR observations have shown that these structures were always brighter than the quiet Sun at centimeter wavelengths, recent observations at millimeter and submillimeter wavelengths have shown ARs with well defined dark umbrae. Given this new information, it is now necessary to update our understanding and models of the solar atmosphere in active regions. In this work, we present a data-constrained model of the AR solar atmosphere, in which we use brightness temperature measurements of NOAA 12470 at three radio frequencies: 17 (NoRH), 100 and 230 GHz (ALMA). Based on our model, which assumes that the radio emission originates from thermal free-free and gyroresonance processes, we calculate radio…
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