Articles | Volume 41, issue 1
Regular paper
24 Jan 2023
Regular paper |  | 24 Jan 2023

Machine learning detection of dust impact signals observed by the Solar Orbiter

Andreas Kvammen, Kristoffer Wickstrøm, Samuel Kociscak, Jakub Vaverka, Libor Nouzak, Arnaud Zaslavsky, Kristina Rackovic Babic, Amalie Gjelsvik, David Pisa, Jan Soucek, and Ingrid Mann

Data sets

AndreasKvammen/ML_dust_detection: v1.0.0 Andreas Kvammen

Model code and software

AndreasKvammen/ML_dust_detection: v1.0.0 Andreas Kvammen

Short summary
Collisional fragmentation of asteroids, comets and meteoroids is the main source of dust in the solar system. The dust distribution is however uncharted and the role of dust in the solar system is largely unknown. At present, the interplanetary medium is explored by the Solar Orbiter spacecraft. We present a novel method, based on artificial intelligence, that can be used for detecting dust impacts in Solar Orbiter observations with high accuracy, advancing the study of dust in the solar system.