# Gyro-Kinematic Ages for around 30,000 Kepler Stars

**Authors:**  Yuxi,  Lu, Ruth Angus, Jason L. Curtis, Trevor J. David, Rocio Kiman  
**arXiv:** [2102.01772](https://arxiv.org/abs/2102.01772)  
**Date:** 2021-02-02  
**Summary page:** https://www.summarizepaper.com/en/arxiv-id/2102.01772v1/

## Key points

- Stellar ages are important for understanding the evolution of stars, exoplanets, and the Milky Way galaxy
- Determining the age of low-mass stars such as K and M dwarfs is challenging due to their slow evolution on the main sequence and faintness
- A recent study by Kiman et al. calculated gyro-kinematic ages for around 30,000 Kepler stars using their rotation and kinematic properties
- The study applied an age-velocity-dispersion relation (AVR) to estimate average stellar ages for groupings of coeval stars
- The method was able to estimate ages for clusters and asteroseismic stars with an RMS of 1.22 Gyr and 0.26 Gyr respectively
- Using their Astraea machine learning algorithm which predicts rotation periods they suggested a new selection criterion (a weight of 0.15) to increase the size of the McQuillian et al. (2014) catalog of Kepler rotation periods by up to 25%
- Using predicted rotation periods allowed them to estimate gyro-kinematic ages for stars without measured rotation periods
- The study provides a valuable approach to estimating stellar ages for low-mass stars using their kinematics properties
- This method has potential applications in furthering our understanding of stellar evolution and galactic history

## Summary

Stellar ages are crucial for understanding the evolution of stars and exoplanets, as well as investigating the history of our Milky Way galaxy. However, determining the age of low-mass stars such as K and M dwarfs remains challenging due to their slow evolution on the main sequence and faintness. In a recent study by Kiman et al., gyro-kinematic ages were calculated for around 30,000 Kepler stars using their rotation and kinematic properties. The study applied an age-velocity-dispersion relation (AVR) to estimate average stellar ages for groupings of coeval stars. The assumption was made that velocity dispersion increases over time, allowing for conversion of velocity dispersion to kinematic age via an AVR. Vertical velocity dispersion was calculated in bins of absolute magnitude, temperature, rotation period and Rossby number to estimate gyro-kinematic ages for 29,949 Kepler stars with measured rotation periods. The results showed that the method was able to estimate ages for clusters and asteroseismic stars with an RMS of 1.22 Gyr and 0.26 Gyr respectively. Additionally, using their Astraea machine learning algorithm which predicts rotation periods they suggested a new selection criterion (a weight of 0.15) to increase the size of the McQuillian et al. (2014) catalog of Kepler rotation periods by up to 25%. Using predicted rotation periods allowed them to estimate gyro-kinematic ages for stars without measured rotation periods. Furthermore Kiman et al., in prep., studied all the stars in a cluster using this method and found promising results when comparing detailed age-element abundance trends with literature values. Overall this study provides a valuable approach to estimating stellar ages for low-mass stars using their kinematics properties and highlights its potential applications in furthering our understanding of stellar evolution and galactic history.