GammaLearn

GammaLearn is a project to develop deep learning solutions for Imaging Atmospheric Cherenkov Telescopes data analysis and in particular for the Cherenkov Telescope Array (CTA) currently under construction. Its first application is the event reconstruction (to retrieve events physical properties such as type, energy and incoming direction) based on the images or videos recorded by Cherenkov telescopes. To ease developments and experiments running, we have developed a complete framework to train and deploy deep learning networks, see code for more information.

Image credit: ctapipe, DOI:10.5281/zenodo.3372210.

Contributors:

Many thanks to everyone who contributed to this project, one way or another:

• Thomas Vuillaume (LAPP), Principal Investigator
• Mikaël Jacquemont (LAPP, LISTIC)
• Michaël Dell’aiera (LAPP, LISTIC)
• Alexandre Benoit (LISTIC)
• Patrick Lambert (LISTIC)
• Gilles Maurin (LAPP)
• Luca Antiga (Orobix)
• Filippo Quarenghi (Orobix)
• Daniele Ciriello (Orobix)
• Daniele Cortinovis (Orobix)
• Giorgia Silvestri (Orobix)
• Giovanni Lamanna (LAPP)
• Thomas Trivellato (LAPP)
• Brondon Waffa-Pagou (LAPP)
• Pierre Aubert (LAPP)
• Vincent Pollet (LAPP)
• Cyann Plard (LAPP)
• Sami Caroff (LAPP)

Partners

We gratefully acknowledge the support from the agencies and organizations listed here.