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DTSTART:20240310T070000
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DTSTART:20231105T060000
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UID:69e49b4a03e3b
DTSTART;TZID=America/Toronto:20240416T150000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20240416T160000
URL:https://uwaterloo.ca/institute-for-quantum-computing/events/recent-prog
 ress-hamiltonian-learning
LOCATION:QNC - Quantum Nano Centre 200 University Avenue West Waterloo ON N
 2L 3G1 Canada
SUMMARY:Recent progress in Hamiltonian learning
CLASS:PUBLIC
DESCRIPTION:CS/MATH SEMINAR - YU TONG\, CALTECH\n\nQuantum-Nano Centre\, 20
 0 University Ave West\, Room QNC 1201 + ZOOM\nWaterloo\, ON CA N2L 3G1\n\n
 In the last few years a number of works have proposed and improved\nprovab
 ly efficient algorithms for learning the Hamiltonian from\nreal-time dynam
 ics. In this talk\, I will first provide an overview of\nthese development
 s\, and then discuss how the Heisenberg limit\, the\nfundamental precision
  limit imposed by quantum mechanics\, can be\nreached for this task. I wil
 l demonstrate how the Heisenberg limit\nrequires techniques that are funda
 mentally different from previous\nones\, and the important roles played by
  quantum control and\nthermalization. I will also discuss open problems th
 at are crucial to\nmaking these algorithms implementable on current device
 s.
DTSTAMP:20260419T090722Z
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