| dc.description.abstract | Current rotational evolution models (REMs) are broadly able to explain the rotational distributions of low mass (0.1 - 1.3 solar masses) cluster stars for a variety of ages, but no model can precisely replicate all features. The shortcomings of current models result from the current understanding of stellar wind torques, and interior angular momentum transport. There exists however a wealth of high precision rotation periods from space-based missions, with many more expected in the near future. As a result, data-sets abundant in rotation periods are available for several clusters across many ages. This flood of cluster rotation data, combined with a two-dimensional fitting statistic, is key to calibrating rotational evolution models. Whilst visually these models overlap strongly with the data, in order to improve on them there is a need for a quantitative fit.
In this thesis, I adapt the two-dimensional fitting statistic τ squared (originally designed for fitting isochrones in the colour-magnitude diagram) to the period-mass plane. The τ squared statistic simultaneously considers all cluster rotation data to return a goodness of fit, allowing for data-driven improvement of REMs. I use τ squared to asses the goodness of fit of REMs to observed distributions of low mass stars on the period-mass plane. I construct data sets for Upper Sco, the Pleiades, and Praesepe, to which the REMs are tuned. As a first demonstration of the τ squared statistic, I find the best-fitting gyrochronology age for Praesepe, which is in good agreement with the literature.
I then talk about varying the stellar wind torques in a parameter study. I demonstrate that by systematically changing three parameters in the torque law, best-fit values are successfully found by minimizing τ squared. The values found vary slightly between clusters, mass determinations, and initial conditions, highlighting the precision of τ squared and its potential for constraining REMs, gyrochronology, and our understanding of stellar physics. The resulting REMs, which implement the best-possible fitting form of a broken-power-law torque, are statistically improved on previous REMs using similar formulations, but still do not simultaneously describe the observed rotation distributions of the lowest masses, which have both slow and fast rotators by the Praesepe age, and the shape of the converged sequence for higher masses. Further complexity in the REMs is thus required to accurately describe the data, which increases the dimensionality of the parameter searches. I finally present a more efficient method of searching parameters in the context of this problem. | en_GB |
