Disposition Scores for LEO-Vetter: Fully Automated Flux- and Pixel-Level Vetting of TESS Planet Candidates to Support Occurrence Rates

For years, the Kepler Space Telescope collected groundbreaking data on what lies beyond our solar system. It collected data on thousands of exoplanets and hundreds of thousands of stars, creating a vast databank that continues to store valuable information about our universe. Over the years, many researchers have used the Kepler data to continue finding planet candidates (PCs) and provide evidence for answers to various research questions.

All of these PCs have been put into a database, where hundreds of pieces of information per datapoint are stored. This creates an expansive wealth of information, filled with almost all the data one needs to find far-away planets. However, due to the immense quantity of PCs, it is nearly impossible to weed out the false positives (FPs) manually.

This is where the Kepler Robovetter comes in. This takes any individual PC and declares it an FP or not. Along with this is a value called the Disposition Score, a number between 0 and 1, that assesses the confidence of the Robovetter's computation. However, after Kepler came the Transiting Exoplanet Survey Satellite (TESS), which has even more data points than Kepler but is formatted differently, meaning the Robovetter doesn't work for this new dataset. Currently, the Leovetter is in development, which is effectively the Robovetter but for TESS. However, this does not currently include a disposition score. My project is to write the code to include a disposition core in the Leovetter package.