Using Modern Day Machine Learning Techniques for Detection of Sunlight Contamination in FEEPS Data

The Fly's Eye Electron Proton Spectrometer (FEEPS) is part of the Energetic Particle Detector Investigation on the Magnetospheric Multiscale (MMS) mission. Following launch and commissioning some of the electron eyes were seen to have sunlight contamination in the data. This contamination is seen as a periodic saturation in the data. Detecting the contamination has been a manual process scanning through data regularly to identify which spin-sectors were affected. We will present results from an investigation using modern-day machine learning algorithms to automatically detect sunlight contamination in FEEPS data. Finally we will describe how this will be implemented in a production environment to update data quality indicators.