Скачать или смотреть Automated bow shock and magnetopause detection with Cassini with threshold and deep learning methods

Presented by Matthew Cheng (University College London)
ML4PSP Seminar November 2021

The Cassini mission spent 13 years in orbit around Saturn collecting a wealth of data about its magnetic field and plasma populations. A catalogue of bow shock and magnetopause boundary crossings is needed to study the structure of Saturn’s magnetosphere and fundamental plasma processes like instabilities. However, a very challenging aspect is the manual identification of thousands of crossings. It is both time-consuming and prone to human error. This calls for ways to standardize the detection of these boundaries through automation. A range of techniques is explored from traditional time-series analysis on the magnetic field and plasma moments data to modern machine learning techniques like evidential deep learning which quantify classification uncertainty applied to electron energy spectrograms.