BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//talks.cam.ac.uk//v3//EN
BEGIN:VTIMEZONE
TZID:Europe/London
BEGIN:DAYLIGHT
TZOFFSETFROM:+0000
TZOFFSETTO:+0100
TZNAME:BST
DTSTART:19700329T010000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0100
TZOFFSETTO:+0000
TZNAME:GMT
DTSTART:19701025T020000
RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
CATEGORIES:Lennard-Jones Centre
SUMMARY:A quantum computing algorithm to speed up Metropol
 is sampling - Prof. Guglielmo Mazzola\, Institute 
 for Computational Science\, University of Zurich
DTSTART;TZID=Europe/London:20230515T140000
DTEND;TZID=Europe/London:20230515T143000
UID:TALK201007AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/201007
DESCRIPTION:The task of sampling from a multidimensional finit
 e-temperature classical Boltzmann probability dist
 ribution is a central problem in numerical simulat
 ions of physics\, chemistry\, and beyond the tradi
 tional boundaries of natural sciences. In this tal
 k\, I will introduce a recent algorithm that can b
 e executed on quantum computers\, offering a scali
 ng advantage compared to state-of-the-art Metropol
 is schemes. In practice\, we can leverage the fact
  that the collapses of a wave function are uncorre
 lated and use them as trial updates to obtain non-
 local but effective moves in the configuration spa
 ce. The algorithm was invented in 2021 for continu
 ous systems\, where a rigorous justification can b
 e found.[1] Subsequently\, it was adapted to spin 
 systems amenable to hardware implementation\, wher
 e it has been experimentally demonstrated.[2]\n\n[
 1] Mazzola\, PRA\, 104\, 022431 (2021)\n[2] Layden
 \, Mazzola et al\,  arXiv:2203.12497 (2022)
LOCATION:Zoom link: https://zoom.us/j/92447982065?pwd=RkhaY
 kM5VTZPZ3pYSHptUXlRSkppQT09
CONTACT:Dr Venkat Kapil
END:VEVENT
END:VCALENDAR