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.

PI: Thomas Vuillaume
Contributors: 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).

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

The framework

To ease developments and experiments running, we have developed a complete environment allowing the user to:

• load datasets
• pre-process data (filter, augment, transform)
• train, validate and test networks
• monitor the training process
• visualize training results

Partners

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