Zeeman Spectral Line Fitting

Abstract The Zeeman effect plays a pivotal role as an observational technique for directly assessing the magnitude of magnetic fields within star-forming regions. Over time, Zeeman effect analysis has primarily relied upon software tools such as the Astronomical Image Processing System and MIRIAD. These tools necessitate manual involvement in the analysis and line fitting processes. This study delves into two potential automated methodologies for Zeeman analysis: one grounded in a least squares framework and the other embracing the maximum-likelihood approach. Our investigation reveals that the utilization of Markov Chain Monte Carlo, anchored in the maximum-likelihood framework, results in improved spectral line fitting outcomes with more favorable residuals. Concluding our efforts, we have encapsulated the automated analysis procedure within a software package, called Zeeman_modelling , installable through pip , accompanied by a straightforward command-line interface.