Classification of Magnetosheath Jets Using Neural Networks and High Resolution OMNI (HRO) Data - Raptis, Savvas; Aminalragia-Giamini, Sigiava; Karlsson, Tomas; Lindberg, Martin (Frontiers in Astronomy and Space Sciences, 2020)
Magnetosheath jets are transient, localized dynamic pressure enhancements found downstream of the Earth's bow shock in the magnetosheath region. Using a pre-existing database of magnetosheath jets we train a neural network to distinguish between jets found downstream of a quasi-parallel bow shock θBn <45) and jets downstream of a quasi-perpendicular bow shock (θBn >45). The initial database was compiled using MMS measurements in the magnetosheath (downstream) to identify and classify them as "quasi-parallel" or "quasi-perpendicular", while the neural network uses only solar wind (upstream) measurements from the OMNIweb database. To evaluate the results, a comparison with three physics-based modeling approaches is done. It is shown that neural networks are systematically outperforming the other methods by achieving a ~93 agreement with the initial dataset, while the rest of the methods achieve around 80%. The better performance of the neural networks likely is due to the fact that they use information from more solar wind quantities than the physics-based models, even in the absence of certain upstream properties, such as IMF direction.