This thesis develops new and powerful methods for identifying
planetary signals in the presence of "noise" generated by stellar
activity, and explores the physical origin of stellar intrinsic
variability, using unique observations of the Sun seen as a star.
In particular, it establishes that the intrinsic stellar
radial-velocity variations mainly arise from suppression of
photospheric convection by magnetic fields. With the advent of
powerful telescopes and instruments we are now on the verge of
discovering real Earth twins in orbit around other stars. The
intrinsic variability of the host stars themselves, however,
currently remains the main obstacle to determining the masses of
such small planets. The methods developed here combine
Gaussian-process regression for modeling the correlated signals
arising from evolving active regions on a rotating star, and
Bayesian model selection methods for distinguishing genuine
planetary signals from false positives produced by stellar magnetic
activity. The findings of this thesis represent a significant step
towards determining the masses of potentially habitable planets
orbiting Sun-like stars.
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