Abstract

K2 is the repurposed Kepler satellite, and has been active for nearly 2 years. In this time, it has surveyed many more bright stars than were available in the additional mission, and discovered some 200 planet candidates. ~100 of these have been confirmed or validated, including a range of unusual and exciting systems, many of which are amenable to further study. These include planetary systems with strong TTVs, new bright Neptune mass planets and even the first detection of planetesimals orbiting a white dwarf. I will introduce the mission and its discoveries, then describe some of the work being performed at Warwick to find both new planets and variable stars in the data. This involved the development of novel machine learning techniques, in particular Self-Organising Maps and Random Forests. Their use has applications not only to the classification of variable stars but also to the selection and prioritisation of transiting planetary candidates.