24.–27. Jan. 2022
Europe/Berlin Zeitzone
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This event is part of the Laser-Plasma Accelerator Seminars. Click here for more information, including data protection.

Towards deep learning-accelerated particle-in-cell simulations: application to Compton scattering events

26.01.2022, 18:45
5m

Sprecher

Pablo Jaime Bilbao Santiago (Golp/IPFN, Instituto Superior Tecnico, Universidade de Lisboa, Lisboa Portugal)

Beschreibung

We present a novel method to efficiently implement Machine Learning methods within Particle-in-Cell (PIC) simulation codes. Such codes are vital to fully understand the kinetic processes involved in Laser Wakefield acceleration and constitute a key tool to comprehend experimental setups and their diagnostics data. However, their computational cost prevents large parameter scans in 3D simulations. We showcase our preliminary implementation within the OSIRIS PIC code, with a Compton scattering AI-based module that employs models directly trained from analytical data. We compare and show how the code can leverage the advantage of Machine Learning methods. These results offer a very promising avenue for future applications of Machine Learning methods with PIC codes.

Hauptautoren

Pablo Jaime Bilbao Santiago (Golp/IPFN, Instituto Superior Tecnico, Universidade de Lisboa, Lisboa Portugal) Chiara Badiali (Golp/IPFN, Instituto Superior Tecnico, Universidade de Lisboa, Lisboa Portugal) Dr. Fabio Cruz (Golp/IPFN, Instituto Superior Tecnico, Universidade de Lisboa, Lisboa Portugal)

Präsentationsmaterialien