15–20 Mar 2026
Berlin
Europe/Berlin timezone
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A-5.11 - Statistical Analysis of Energy Distributions of Quiet-Sun EUV Brightenings from High-Resolution Solar Orbiter Observations

Not scheduled
15m
Harnack Haus (Berlin)

Harnack Haus

Berlin

Poster Poster A

Speaker

Caro Hermans (KU Leuven & ROB)

Description

First Name: Caro
Last Name: Hermans
Affiliation: KU Leuven & ROB

All Authors: Authors: Caro Hermans (1,2), Cis Verbeeck (1), Nancy Narang (1), Daye Lim (1,2), Sergei Shestov (1,3), Frédéric Auchère (4), Marilena Mierla (1,5), David Berghmans (1), Antoine Dolliou (6), Wim Schoutens (2), Johan Segers (2), Emil Kraaikamp (1), Konstantina Loumou (1), Ewan Dickson (1), Bogdan Nicula (1), Luciano Rodriguez (1), Andrei Zhukov (1) 1: Royal Observatory of Belgium, Solar-Terrestrial Centre of Excellence 2: KU Leuven, Belgium 3: Centre Spatiale de Liège, Belgium 4: Institut d’Astrophysique Spatiale, France 5: Institute of Geodynamics of the Romanian Academy, Romania 6: Max Plank Institute for Solar System Research, Germany

Abstract: The long-standing coronal heating problem raises the question of whether the solar corona can be heated by the cumulative effect of numerous small energy releases. Motivated by this, we investigated the smallest observable transient events in Quiet Sun. The Solar Orbiter’s High-Resolution Imager observing in the 174 Å (HRIEUV) provided unprecedented observations of the lower solar corona at the finest spatial and temporal resolution to date, enabling the detection of small-scale transient EUV brightenings, the smallest such events observed so far. We used high-cadence, high-resolution HRIEUV observations of the quiet Sun, obtained at close heliocentric distances, to perform a detailed statistical analysis of these brightenings. A wavelet-based automatic detection algorithm was applied to identify and characterize individual events, while SDO/AIA observations were used to estimate their temperatures and emission measures, allowing the derivation of thermal energies. To robustly characterize the energy distribution, the maximum likelihood estimation (MLE) was used to fit both power-law and lognormal models. The rollover region was constrained using methods proposed by Clauset et al. (2009) and Corral et al. (2019), with additional refinements introduced in this study. Goodness-of-fit and likelihood ratio tests were used to evaluate the competing models, and the sensitivity to the choice of the lower energy bound was assessed. The resulting statistical characterization offers new insights into the energetics of small-scale EUV brightenings and their potential contribution to the coronal heating budget.

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