Machine learning for quantum processes: from quantum technologies to taming complexity
Giorno 15 gennaio 2020, con inizio alle ore 16:30, presso l'Aula Magna del DFA, il Professor Mauro Paternostro (School of Mathematics and Physics, Queen’s University Belfast, UK) terrà uno Science Colloquium dal titolo Machine learning for quantum processes: from quantum technologies to taming complexity.
Il seminario appartiene al ciclo Science Colloquia del DFA, curato e coordinato dai Professori Rossella Caruso e Giuseppe Falci. Tutti gli interessati, in particolare gli Studenti dei corsi di laurea triennale in Fisica e magistrale in Physics, e i Dottorandi dei corsi di dottorato in Physics, in Materials Science and Nanotechnology, ed in Complex Systems, sono invitati a partecipare. Verrà offerto un piccolo rinfresco in antiaula alle ore 16:00.
Abstract. From face recognition to the development of autonomous vehicles, machine learning (ML) is permeating technology and science in an infectious manner, opening new perspectives for the management, mining and manipulation of Big Data. In this talk, I will review the applications of ML to quantum processes, highlighting the opportunities for advances in both fundamental and applied quantum physics that the ML-enhanced processing of quantum information is offering. I will address specific instances linked to quantum computing, quantum simulation and quantum dynamics of complex adaptive systems, discussing both theory and recent experimental endeavours.