Abstract
Abstract Estimating stellar ages is important for advancing our understanding of stellar and exoplanet evolution and investigating the history of the Milky Way. However, ages for low-mass stars are hard to infer as they evolve slowly on the main sequence. In addition, empirical dating methods are difficult to calibrate for low-mass stars as they are faint. In this work, we calculate ages for Kepler F, G, and crucially K and M dwarfs, using their rotation and kinematic properties. We apply the simple assumption that the velocity dispersion of stars increases over time and adopt an age–velocity-dispersion relation (AVR) to estimate average stellar ages for groupings of coeval stars. We calculate the vertical velocity dispersion of stars in bins of absolute magnitude, temperature, rotation period, and Rossby number and then convert velocity dispersion to kinematic age via an AVR. Using this method, we estimate gyro-kinematic ages for 29,949 Kepler stars with measured rotation periods. We are able to estimate ages for clusters and asteroseismic stars with an rms of 1.22 Gyr and 0.26 Gyr respectively. With our Astraea machine-learning algorithm, which predicts rotation periods, we suggest a new selection criterion (a weight of 0.15) to increase the size of the McQuillan et al. catalog of Kepler rotation periods by up to 25%. Using predicted rotation periods, we estimated gyro-kinematic ages for stars without measured rotation periods and found promising results by comparing 12 detailed age–element abundance trends with literature values.
Highlights
The age of a star is one of its most important, yet difficult to determine, quantities
If the number of stars exceeded the minimum or maximum limit, the bin was reduced/increased by 10% until the number of stars in each bin was within the limits or the bin size had changed by more than 100% from its original bin size
After optimizing the bin size for gyro-kinematic procedure, we calculated gyro-kinematic ages for members of stars clusters and for two white dwarf–M dwarf binaries. For the former, we used the Curtis et al (2020) catalog which is an assembly of rotation periods from a variety of benchmark clusters, including the Pleiades (120 Myr; Rebull et al 2016), Praesepe (670 Myr; Douglas et al 2017, 2019), Hyades (730 Myr; Douglas et al 2016, 2019), NGC 6811 (1 Gyr; Meibom et al 2011; Curtis et al 2019), NGC 752 (1.4 Gyr; Agueros et al 2018), NGC 6819 (2.5 Gyr; Meibom et al 2015), and Ruprecht 147 (2.7 Gyr; Curtis et al 2020)
Summary
The age of a star is one of its most important, yet difficult to determine, quantities. The age of exoplanets can be inferred from their host stars, and can be used to study how the properties of exoplanets change over time (e.g., David et al 2020). The ages of stars can be used to understand how the Milky Way formed and is evolving (Spina et al 2018; Bedell et al 2018; Ness et al 2019). Age is not a directly measurable physical quantity, but rather an estimation of a star’s evolutionary dated. This only applies to a small number of stars, and getting precise and accurate ages for old field M dwarfs remains challenging. This only applies to a small number of stars, and getting precise and accurate ages for old field M dwarfs remains challenging. 1
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