On the Impulsive Heating of Quiet Solar Corona

TL;DR

This study investigates impulsive heating in the quiet solar corona using observational data and machine learning, revealing frequent impulsive events and supporting impulsive heating as a key mechanism.

Contribution

It combines empirical impulsive heating models with machine learning to quantify uncertainties and analyze impulsive events in quiet Sun regions.

Findings

2-3 impulsive events per minute occur in QS regions

Power law slope of impulsive event distribution peaks above 2

Conduction losses dominate over radiative cooling losses

Abstract

The solar corona consists of a million-degree Kelvin plasma. A complete understanding of this phenomenon demands the study of Quiet Sun (QS) regions. In this work, we study QS regions in the 171 {\AA}, 193 {\AA} and 211 {\AA} passbands of the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO), by combining the empirical impulsive heating forward model of Pauluhn & Solanki (2007) with a machine-learning inversion model that allows uncertainty quantification. We find that there are {\approx} 2--3 impulsive events per min, with a lifetime of about 10--20 min. Moreover, for all the three passbands, the distribution of power law slope {\alpha} peaks above 2. Our exploration of correlations among the frequency of impulsive events and their timescales and peak energy suggests that conduction losses dominate over radiative cooling losses. All these finding suggest that impulsive heating is a viable heating mechanism in QS corona.