RV exoplanets and stellar activity

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While the radial velocity (RV) method dominated the field of exoplanet discovery for over a decade, in recent years it has been somewhat overshadowed by the wealth of results from space-based transit surveys such as the Kepler mission. However, RVs remain a powerful tool to search for low-mass planets in temperate orbits around nearby stars, a crucial component of the characterisation of any transiting planet, and a direct (and much cheaper) complement to direct imaging methods which probe the outer parts of planetary systems. Nowadays, RV spectrographs routinely reach sub-m/s precision, and it is astrophysical noise sources, particularly stellar activity, that limit their sensitivity to low-mass planets on temperate orbits. To overcome this, we are developing innovative methods to extract and model RVs and distinguish between stellar and planetary signals, using state-of-the art Bayesian machine learning techniques. Specifically, the stellar spectra are modelled directly as multiple observations of a Gaussian process (GP) sampled at slightly different rest wavelengths, and the wavelength shifts between epoch are optimized together with the parameters of the GP. The resulting relative RVs are then analysed simultaneously with various stellar activity indicators to disentangle activity and planetary signals.These tools still need further development, but are already giving very promising results. This PhD project will consist in developing and testing these methods further, and applying them to new data from RV surveys, as well as RV follow-up of new transiting planets discovered by the K2 and TESS satellites. It may provide support to the CHEOPS mission and will ultimately help optimized the follow-up of the PLATO mission, as well as the analysis of data from future RV spectrographs such as INT/HARPS3, VLT/ESPRESSO and E-ELT/HIRES.This project falls within the STFC key science question: B: How do stars and planetary systems develop and is life unique to our planet? It will involve collaborations with a number of groups leading RV searches for exoplanets, including Prof D. Queloz's group at the University of Cambridge, as well as with experts in the application of GPs to exoplanet datasets, including Dr D. Foreman-Mackey (Center for Computational Astrophysics, Flatiron Institute).