The awarded funding of 600k eur for the period 2025-2029 will support networking and coordination activities such as workshops and short-Term Scientific Missions.
This COST Action aims to advance theoretical, experimental, and technological efforts for developing future particle colliders by leveraging cutting-edge computational technologies, including Machine Learning (ML) and Quantum Computing (QC). The action will bring together experts from High-Energy Physics (HEP), ML, and QC to form an interdisciplinary network that will explore and exploit synergies between emerging computing paradigms and HEP theory and experiments.
Future colliders pose complex challenges, from designing accelerators and experiments to managing and analyzing the enormous datasets they will produce. The large-scale data-taking and processing required in the next era of very-big-data physics will demand novel ML algorithms for efficient event selection, background reduction, pattern recognition, anomaly detection, and more. Additionally, QC offers possibilities for solving optimization problems related to collider design, simulating quantum systems, and improving theoretical predictions.