BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Richard Kueng (Johannes Kepler University Linz) DTSTART:20210527T060000Z DTEND:20210527T070000Z DTSTAMP:20260423T041751Z UID:UTSQSI/24 DESCRIPTION:Title: The classical shadow formalism and (some) implications for quantum machine learning\nby Richard Kueng (Johannes Kepler University Linz) as part of Centre for Quantum Software and Information Seminar Series\n\n\nAbstrac t\nExtracting important information from a quantum system as efficiently a nd tractably as possible is an important subroutine in most near-term appl ications of quantum hardware.\nWe present an efficient method for construc ting an approximate classical description of a quantum state using very fe w measurements of the state. This description\, called a classical shadow\ , can be used to predict many different properties. The required number of measurements is independent of the system size and saturates information- theoretic lower bounds.\nIf time permits\, I will also illustrate how one can combine classical shadows with machine learning (ML). This combination showcases that training data obtained from quantum experiments can be ver y empowering for classical ML methods. \n\nThis is joint work with Robert Huang and John Preskill (both Caltech).\n\nTo request the zoom link\, plea se send a message cqsiadmin@uts.edu.au using your institution/organisation /business email address.\n\nHOSTED BY: Dr Mária Kieferová\, Centre for Q uantum Software and Information\, University of Technology Sydney\, Austra lia\n LOCATION:https://researchseminars.org/talk/UTSQSI/24/ END:VEVENT END:VCALENDAR