Automatic Detection and Correction Algorithms for Magnetic Saturation in the SMFT/HSOS longitudinal Magnetograms

TL;DR

This paper presents an automated method to detect and correct magnetic saturation in solar magnetograms, improving measurement accuracy in strong magnetic field regions using polynomial fitting and validation against HMI data.

Contribution

The study introduces a novel automated algorithm for saturation detection and correction in SMFT/HSOS magnetograms, enhancing measurement reliability in strong magnetic fields.

Findings

Detection accuracy of ~99.4%

Correction accuracy of ~88%

Effective validation against HMI magnetograms

Abstract

longitudinal magnetic field often suffers the saturation effect in strong magnetic field region when the measurement performs in a single-wavelength point and linear calibration is adopted. In this study, we develop a method that can judge the threshold of saturation in Stokes $V/I$ observed by the Solar Magnetic Field Telescope (SMFT) and correct for it automatically. The procedure is that first perform the second-order polynomial fit to the Stokes $V/I$ \textit{vs} $I/I_{m}$ ($I_{m}$ is the maximum value of Stokes $I$) curve to estimate the threshold of saturation, then reconstruct Stokes $V/I$ in strong field region to correct for saturation. The algorithm is proved to be effective by comparing with the magnetograms obtained by the Helioseismic and Magnetic Imager (HMI). The accurate rate of detection and correction for saturation is $\sim$99.4\% and $\sim$88\% respectively among 175 active regions. The advantages and disadvantages of the algorithm are discussed.