Refinements to the Solar Polar Magnetic Flux: Implications from Inversion Methodologies

TL;DR

This study refines estimates of solar polar magnetic flux using spectropolarimetric inversions, highlighting the impact of model assumptions and inversion settings on flux measurements, and emphasizing the need for improved observational and analytical techniques.

Contribution

It introduces a detailed analysis of inversion methodologies for solar polar magnetic fields, comparing 1- and 2-component models and assessing their effects on flux estimates.

Findings

Magnetic flux estimates vary significantly with model assumptions.

Model degeneracy limits the precision of flux inference to several tens of percent.

Including unresolved magnetic structures improves the reliability of measurements.

Abstract

The magnetic fields in the solar polar region are important to our understanding of the internal dynamo process, the global coronal structure, and the origin of the solar wind. The inference of polar fields based on spectropolarimetric observation is highly model-dependent and can suffer from various systematic effects. Here we analyze a raster map of the southern polar region taken by the Hinode Spectro-Polarimeter, utilizing the Stokes Inversion based on Response functions code. The inversions provide height-dependent vector magnetic field maps between optical depths $\log_{10}\tau = -2$ and $0$. We examine the impact on the total magnetic flux estimate from adopting (1) 1- vs 2-component atmospheric models via a "filling factor" parameter and (2) different analysis schemes. At $\log_{10}\tau = -1.5$, the polar magnetic flux is estimated to be $(1.84 \pm 0.03) \times 10^{21}$ Mx and $(1.38 \pm 0.02) \times 10^{21}$ Mx under the 1- and 2-component atmosphere assumption, respectively. The magnetic flux is approximately constant or increases slightly with height, respectively. We find that the 2-component (1-component) configuration is preferred for 58.3% (32.3%) of the pixels. Different initial guesses, including the input atmosphere model and the filling factor, as well as different inversion settings, can significantly affect the results, especially for locations with weaker polarization signals. Our work highlights the importance of including unresolved magnetic structures or stray light into consideration. Model degeneracy and the convergence to local minima limit the precision of the polar magnetic flux inference (no better than several tens of percent in this case). Higher-resolution observations and advanced inversion and disambiguation algorithms may alleviate these limitations.