In this project we plan to address the opportunities offered by Quantum Machine Learning for event classification and event simulation at nuclear physics, high-energy physics and gravitational wave experiments. We draw on already developed work in the area of jet-tagging in events from the LHCb experiment and develop further more advanced algorithms, evaluating the cost-benefit tradeoff of a larger number of qbits and comparing results of the quantum algorithms with the state-of-the-art offered by well-established classical algorithms.
Relatori:
Cristiano Palomba
(Istituto Nazionale di Fisica Nucleare),
Davide Zuliani
(Istituto Nazionale di Fisica Nucleare),
Donatella Lucchesi
(Istituto Nazionale di Fisica Nucleare),
Lorenzo Sestini
(Istituto Nazionale di Fisica Nucleare),
Pia Astone
(Istituto Nazionale di Fisica Nucleare),
Stefano Giagu
(Istituto Nazionale di Fisica Nucleare)