Spectroscopic characterization of LOFAR radio-emitting M dwarfs

Recent observations with the LOw Frequency ARray (LOFAR) have revealed 19 nearby M dwarfs showing bright circularly polarized radio emission. One of the possible sources of such emission is through magnetic star-planet interactions (MSPIs) with unseen close-in planets. We present the initial results from a spectroscopic survey with the Habitable-zone Planet Finder (HPF) and NEID spectrographs designed to characterize this sample and further investigate the origin of the radio emission. We provide four new insights into the sample. I) We uniformly characterized the stellar properties, constraining their effective temperatures ( T eff ), surface gravities (log g ), metallicities ([Fe/H]), projected rotational velocities ( v sin i ⋆ ), rotation periods ( P rot ), stellar radii ( R ⋆ ), and stellar inclinations ( i ⋆ ) where possible. Further, from a homogeneous analysis of the HPF spectra, we inferred their chromospheric activity and spectroscopic multiplicity states. From this, we identified GJ 625, GJ 1151, and LHS 2395 as single, quiescent stars amenable to precise radial velocity follow-up, making them strong MSPI candidates. II) We show that the distribution of stellar inclinations are compatible with an isotropic distribution, providing no evidence for a preference to pole-on configurations. III) We refined the radial velocity solution for GJ 625 b, the only currently known close-in planet in the sample, reducing the uncertainty in its orbital period by a factor of three, to facilitate future phase-dependent radio analysis. IV) Finally, we identified GJ 3861 as a spectroscopic binary with an orbital period of P = 14.841181 −0.00010 +0.00011 d and with a mass ratio of q = 0.7663 −0.0018 +0.0020 , making it the only confirmed binary with a relatively short orbit in the sample, where we surmise the radio emission is likely related to magnetospheric interactions between the two stars. These results advance our understanding of radio-emitting M dwarfs and establish an observational foundation for identifying MSPIs.