Understanding angular momentum evolution of solar-age stars with K2 data

Gyrochronology, which describes the empirical relationship among stellar mass, rotation period, and age, is a potentially powerful tool for determining the ages of stars, upon which the understanding of stellar evolutionary models hangs. Well-calibrated with open clusters up to the age of ~2.5 Gyr, predictions from gyrochronology are in conflict with asteroseismic observations of older stars, and the underlying physics are poorly understood. The solar-age, open cluster M67, recently observed by the NASA K2 mission, offers the opportunity to test both gyrochronology and more physically-motivated angular momentum evolution models. Here, we seek to gain insight into the angular momentum evolution of solar-age stars through the analysis of K2 data. Using our own pipeline, we extract and process K2 light curves that encompass the inner and outer portions of M67. We describe various rotation period detection methods, focusing on the Lomb-Scargle periodogram, autocorrelation function (ACF), and Gaussian processes (GPs), before presenting our own preliminary results. Observed scatter between colour and period, combined with disagreement from the first published sets of K2 M67 periods, prompted a comprehensive round of sinusoidal injection tests to probe our absolute detection limits with K2 data using two different light curve preparation pipelines. Finding low sensitivity for 25 d, 0.1% amplitude signals and lingering systematics on the order of 25 d and greater, we use a combination of the Lomb-Scargle, ACF, and GP methods to determine our ‘final’ M67 rotation periods from K2 data. We find agreement between tidal synchronization theory and observed rotation periods for our M67 binaries. While angular momentum evolution models may perform slightly better than gyrochronology, we cannot make any conclusive statements regarding the validity of either due to the inherent scatter and small sample size. Future work at refining detection methods is needed, along with complementary data from upcoming missions such as LSST and PLATO.