Kinematic Analysis of Protoplanetary Disks Using Machine Learning

Exoplanets in protoplanetary disks cause localized deviations from Keplerian velocity in channel maps of molecular line emission. Current methods of characterizing these deviations are time consuming, and there is no unified standard approach. We demonstrate that machine learning can quickly and accurately detect the presence of planets and constraint their locations. We train our model on synthetic images generated from simulations and apply it to real observations to identify forming planets in real systems. Previous discoveries are replicated, and a new planet is identified in HD 142666.