Wednesday 25 May 2022: Gaussian processes and physical stellar properties
Belinda Nicholson -
4th Floor Physics + remote 14:00-15:00
Gaussian Process (GP) regression has become an increasing popular data analysis tool in stellar and exoplanet astronomy, yet questions remain as to the extent to which GP hyperparameters relate to physical stellar properties. In this seminar I will present the results of tests of GP regression with the quasi periodic (QP) and QP cosine kernels on a simulated stellar light curves and radial velocity times series, with the aim of determining the correlation, if any, between physical properties of a star, and the recovered GP hyper-parameters. I also explore the differences in the recovered QP GP hyper-parameters between light curve data and 'perfectly' sampled radial velocity data, as well as examining the effects of degrading radial velocity time sampling on recovering the same GP hyper-parameters.