Sprecher
Beschreibung
CERN has started its second phase of the Quantum Technology Initiative with 5year-term plan aligned with the CERN research and collaboration objectives. This effort is designed to build specific capacity and technology platforms, and support a longer-term strategy to use quantum technology at CERN and in HEP in the future.
After a preliminary introduction about the initiative, we will discuss the integration of Quantum Machine Learning (QML) into the High Energy Physics (HEP) pipeline to address computational challenges in the analysis of vast and complex datasets. This talk will walk through main research directions and results from theoretical foundations of quantum machine learning algorithms to application in several areas of HEP and will outline future directions for incorporating quantum technologies into the broader HEP research framework and beyond.
