Modelling the molecular Zeeman effect in M-dwarfs: methods and first results

TL;DR

This paper introduces a new spectral synthesis method for measuring magnetic fields in M-dwarfs using atomic and molecular lines, revealing systematically lower magnetic field strengths than previous estimates.

Contribution

The study develops a detailed spectral synthesis approach incorporating Hund's case-dependent Landé g-factors for FeH lines, enabling more accurate magnetic field measurements in M-dwarfs.

Findings

Confirmed strong magnetic fields in three M-dwarfs, but with lower mean intensities than previously reported.

Demonstrated that earlier magnetic field estimates were likely overestimated by 15-30%.

Established a method for measuring magnetic fields in very low-mass stars using polarized radiative transfer.

Abstract

We present first quantitative results of the surface magnetic field measurements in selected M-dwarfs based on detailed spectra synthesis conducted simultaneously in atomic and molecular lines of the FeH Wing-Ford $F^4\,\Delta-X^4\,\Delta$ transitions. A modified version of the Molecular Zeeman Library (MZL) was used to compute Land\'e g-factors for FeH lines in different Hund's cases. Magnetic spectra synthesis was performed with the Synmast code. We show that the implementation of different Hund's case for FeH states depending on their quantum numbers allows us to achieve a good fit to the majority of lines in a sunspot spectrum in an automatic regime. Strong magnetic fields are confirmed via the modelling of atomic and FeH lines for three M-dwarfs YZ~CMi, EV~Lac, and AD~Leo, but their mean intensities are found to be systematically lower than previously reported. A much weaker field ($1.7-2$~kG against $2.7$~kG) is required to fit FeH lines in the spectra of GJ~1224. Our method allows us to measure average magnetic fields in very low-mass stars from polarized radiative transfer. The obtained results indicate that the fields reported in earlier works were probably overestimated by about $15-30$\%. Higher quality observations are needed for more definite results.