Empirical, Accurate Masses and Radii of Single Stars with TESS and Gaia
Keivan G. Stassun (1), Enrico Corsaro (2), Joshua Pepper (3), Scott, Gaudi (4) ((1) Vanderbilt University, (2) INAF Osservatorio Astrofisico di, Catania, (3) Lehigh University, (4) Ohio State University)

TL;DR
This paper introduces a new empirical method combining Gaia and TESS data to measure stellar masses and radii of single stars with high precision, without needing binary systems or spatial resolution.
Contribution
The paper presents a novel approach to determine stellar masses and radii using surface gravity, flux, and distance measurements, applicable to a large number of stars.
Findings
Masses can be measured with ~25% precision using current data.
Expected improvements could yield radii accurate to a few percent.
Method applicable to hundreds of thousands of stars across the sky.
Abstract
We present a methodology for the determination of empirical masses of single stars through the combination of three direct observables with Gaia and TESS: (i) the surface gravity via granulation-driven variations in the TESS light curve, (ii) the bolometric flux at Earth via the broadband spectral energy distribution, and (iii) the distance via the Gaia parallax. We demonstrate the method using 525 Kepler stars for which these measures are available in the literature, and show that the stellar masses can be measured with this method to a precision of 25\%, limited by the surface-gravity precision of the granulation "flicker" method (0.1~dex) and by the parallax uncertainties (10\% for the Kepler sample). We explore the impact of expected improvements in the surface gravity determinations---through the application of granulation background fitting and the use of…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
