Machine learning enjoys widespread success in High Energy Physics (HEP) analysis at LHC. However the ambitious HL-LHC program will require much more computing resources in the next two decades. Quantum computing may offer speed-up for HEP physics analysis at HL-LHC, and can be a new computational

With the commissioning of the upgraded LHC-HL machine, High Energy Physics will face a large shortage of computing resources that has been evaluated between a factor 10 and 100. It is therefore necessary to explore all avenues that can lead to an improvement of the performance of HEP software

The ambitious upgrade programme for CERN’s Large Hadron Collider (LHC) will result in significant challenges related to information and communications technologies (ICTs) over the next decade and beyond. It is therefore vital that we — members of the high-energy physics (HEP) research community and