Issue |
A&A
Volume 699, July 2025
|
|
---|---|---|
Article Number | A73 | |
Number of page(s) | 9 | |
Section | The Sun and the Heliosphere | |
DOI | https://doi.org/10.1051/0004-6361/202554019 | |
Published online | 03 July 2025 |
The uncertainty of magnetic fields in 3D non-local thermodynamic equilibrium inversions
1
Astronomical Institute of the Academy of Sciences, Ondřejov, Czech Republic
2
Instituto de Astrofísica de Canarias, E-38205 La Laguna, Tenerife, Spain
3
Departamento de Astrofísica, Universidad de La Laguna, E-38206 La Laguna, Tenerife, Spain
4
Leibniz Institut für Sonnenphysik (KIS), Georges-Köhler-Allee 401a, 79110 Freiburg, Germany
⋆ Corresponding author: jiri.stepan@asu.cas.cz
Received:
4
February
2025
Accepted:
14
May
2025
We describe our approach to solving the problem of ensuring the solenoidality of the magnetic field vector in 3D inversions, as well as the estimation of the uncertainty in the inferred magnetic field. The solenoidality of the magnetic field vector is often disregarded in the inversion of spectropolarimetric data due to limitations in the traditional 1D inversion techniques. We propose a method for ensuring the solenoidal condition in 3D inversions based on our mesh-free approach. The increase in dimensionality with respect to the 1D inversion techniques is such that some of the traditional methods for determining the uncertainties become unfeasible. We propose a method based on a Monte Carlo approach for determining the uncertainty of the magnetic field inference. Due to the physics of the problem, we can compute the uncertainty while only increasing the total required computational time by a factor of about 2. We also propose a metric for quantifying the uncertainty that thus describes the degree of confidence of the magnetic field inference. Finally, we perform a numerical experiment to demonstrate the feasibility of both the method and the metric proposed to quantify the uncertainty.
Key words: polarization / radiative transfer / methods: numerical / Sun: magnetic fields
© The Authors 2025
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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