DRF: Thesis subject SL-DRF-20-1004
After a very successful operation period crowned with the discovery of the Higgs boson, the Large Hadron Collider will undergo a luminosity upgrade where it is planned to increase the collision rate by a factor of ten. The CMS detector will also be upgraded to cope with these challenging environment and to enable a better event reconstruction, particularly with the new high-granularity calorimeters. Collecting, filtering and processing the data from these detectors will pose a significant challenge. In order to make the most out of it, the modern artificial intelligence techniques will be essential. We are looking for an enthusiastic student who will study the possible machine learning techniques that can be implemented in the Field Programable Gate Arrays (FPGA) to enable very high-speed reconstruction and filtering of this immense amount of data.
Département d’Electronique, des Détecteurs et d’Informatique pour la physique
Systèmes Temps Réel, Electronique d’Acquisition et Microélectronique
Start date of the thesis: 01/10/2020