Inferring the Rotation Period Distribution of Stars from their Projected Rotation Velocities and Radii: Application to late-F/early-G Kepler Stars

Abstract

While stellar rotation periods $P_{\mathrm{rot}}$ may be measured from broadband photometry, the photometric modulation becomes harder to detect for slower rotators, which could bias measurements of the long-period tail of the $P_{\mathrm{rot}}$ distribution. Alternatively, the $P_{\mathrm{rot}}$ distribution of stars can be inferred from their projected rotation velocities $v\sin i$ and radii $R$, without being biased against photometrically quiet stars. We solve this inference problem using a hierarchical Bayesian framework, which (i) is applicable to heteroscedastic measurements of $v\sin i$ and $R$ with non-Gaussian uncertainties and (ii) does not require a simple parametric form for the true $P_{\mathrm{rot}}$ distribution. We test the method on simulated data sets and show that the true $P_{\mathrm{rot}}$ distribution can be recovered from $\gtrsim 100$ sets of $v\sin i$ and $R$ measured with precisions of $1km/s$ and $4\%$, respectively, unless the true distribution includes sharp discontinuities. We apply the method to a sample of 144 late-F/early-G dwarfs in the Kepler field with $v\sin i$ measured from Keck/HIRES spectra, and find that the typical rotation periods of these stars are similar to the photometric periods measured from Kepler light curves: we do not find a large population of slow rotators that are missed in the photometric sample, although we find evidence that the photometric sample is biased for young, rapidly-rotating stars. Our results also agree with asteroseismic measurements of $P_{\mathrm{rot}}$ for Kepler stars with similar ages and effective temperatures, and show that $\approx 1.1M_{\odot }$ stars beyond the middle of their main-sequence lifetimes rotate faster than predicted by standard magnetic braking laws.

17 pages, 15 figures, accepted for publication in MNRAS