The systematic detection of AGN flares in the era of time domain astronomy

A characteristic feature of AGN is their variable luminosity, which is observed at all wavelengths. Their lightcurves typically vary by a few tenths of a magnitude or more over periods lasting from weeks to years. This variability is caused by the turbulent processes occurring within the accretion disk, meaning that the study of AGN variability is an effective means of studying the accretion process. Recently, a growing number of AGN have been observed to show extreme variability, whereby their lightcurves exhibit luminosity changes that represent a significant departure from their baseline variability. These rare events are known as AGN flares. Since their discovery, AGN flares have quickly become an active area of research with the intention of better understanding accretion physics. Looking ahead to high-cadence surveys such as the Legacy Survey of Space and Time (LSST), which promises millions of transient detections per night in the coming decade, there is a need for the fast and efficient detection and classification of AGN flares. The problem with the systematic detection of AGN flares, however, is the requirement to detect them against a stochastically variable baseline; the ability to define a signal as a significant departure from the ever-present variability is a considerable statistical challenge. In this thesis, I investigate the use of a statistical tool called Gaussian Processes (GPs) to systematically detect AGN flares in optical lightcurves, and I demonstrate that GPs are a viable means of transient detection in the coming era of time domain astronomy.