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VERSION:2.0
CALSCALE:GREGORIAN
PRODID:UW-Madison-Physics-Events
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SEQUENCE:0
UID:UW-Physics-Event-6959
DTSTART:20220518T153000Z
DTEND:20220518T163000Z
DTSTAMP:20260414T114411Z
LAST-MODIFIED:20220516T213309Z
LOCATION:For full info: https://www.anl.gov/event/variational-quantum-
 algorithms-for-nonlinear-problems
SUMMARY:Variational Quantum Algorithms for Nonlinear Problems\, Wiscon
 sin Quantum Institute\, Michael Lubasch\, Cambridge Quantum Computing\
 , Ltd.
DESCRIPTION:We show that nonlinear problems including nonlinear partia
 l differential equations can be efficiently solved by variational quan
 tum computing. We achieve this by utilizing multiple copies of variati
 onal quantum states to treat nonlinearities efficiently and by introdu
 cing tensor networks as a programming paradigm. The key concepts of th
 e algorithm are demonstrated for the nonlinear Schrödinger equation a
 s a canonical example. We numerically show that the variational quantu
 m ansatz can be exponentially more efficient than matrix product state
 s and present experimental proof-of-principle results obtained on an I
 BM Q device.
URL:https://www.physics.wisc.edu/events/?id=6959
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