Understand thy star, understand thy planet

Abstract

Instrumental precision is no longer the biggest impediment to the discovery of Earth-like planets. Indeed, future space missions and next generation spectrographs are technically capable at finding and characterising Earth-analogue planets. However, it is now stellar activity that poses a critical challenge on the pathway to detect habitable Earth-like worlds. This thesis is therefore dedicated to understanding the effect stellar activity has on spectroscopically observed radial-velocity (RV) variations used to detect the Doppler wobble reflex motion induced by orbiting planets on their host star.

In this thesis, I first outline one of the most common processes by which exoplanets are detected by presenting the discovery of two hot Jupiters by NGTS. Following this discovery, I investigate how to detect smaller exoplanets using our best example: the Sun. Using the HARPS-N solar telescope, I study the possibility of detecting Venus using the RV method. However, finding Venus is proven to be impossible unless solar activity can be corrected for to some certain level. Therefore, in order to better understand stellar activity, I compare the Sun with a large number of relatively inactive stars, from F-type to M-type stars, over long timescales, with the aim of improving our detection of long-period exoplanets. I analyse the long-term changes seen for multiple activity indicators and study their correlation with the RVs. The sign of the correlations appears to vary as a function of stellar spectral type, and the transition in sign signals a noteworthy change in the stellar activity properties where earlier type stars appear more plage dominated. These transitions become more clearly defined when considered as a function of the convective zone depth. Therefore, it is the convective zone depth (which can be altered by stellar metallicity) that appears to be the underlying fundamental parameter driving the observed activity correlations. In addition, for most of the stars, I find that the RVs become increasingly red-shifted as activity levels increase, which can be explained by the increase in the suppression of convective blue-shift. However, I also find that for a minority of stars, those with deeper convective envelopes, the RVs become increasingly blue-shifted as activity levels increase. Then, using the correlations found between activity indicators and RVs, I perform a simple cleaning of the long-term RV signals induced by stellar activity. This RV noise cleaning allows me to improve the planetary detection at longer orbital periods. Using these cleaned curves, some new planetary candidates are identified.

Finally, I present a new approach to search for activity indicators. By comparing active spectra from inactive ones, I aim to classify individual lines as either sensitive or insensitive to stellar activity. Such classification would then improve our data-reduction techniques, by reducing the RV variations due to stellar activity, by analysing the activity insensitive lines, or conversely providing more precise information on the stellar surface variability.

Date of Award	Dec 2021
Original language	English
Awarding Institution	Queen's University Belfast
Supervisor	Christopher Watson (Supervisor) & Ernst de Mooij (Supervisor)