A Database of MMS Bow Shock Crossings Compiled Using Machine Learning

Identifying collisionless shock crossings in data sent from spacecraft has so far been done manually. It is a tedious job that physicists have to go through if they want conduct case studies or perform statistical studies. We use machine learning approach automatically identify the Magnetospheric Multiscale (MMS) spacecraft. compile database of those including various related and parameters for each event. Furthermore, we show shocks properties are spread out both real space parameter space. also present possible science application by looking correlations between ion acceleration efficiency at different such as $\theta_{Bn}$ $M_A$. investigate statistically efficiency. find no clear correlation $M_A$ quasi-parallel more efficient accelerating ions.