Hamiltonian simulation with optimal sample complexity

dc.contributor.authorKimmel, Shelby
dc.contributor.authorLin, Cedric Yen-Yu
dc.contributor.authorLow, Guang Hao
dc.contributor.authorOzols, Maris
dc.contributor.authorYoder, Theodore J.
dc.date.accessioned2018-05-17T14:33:36Z
dc.date.available2018-05-17T14:33:36Z
dc.date.issued2017
dc.descriptionFunding for Open Access provided by the UMD Libraries Open Access Publishing Fund.en_US
dc.description.abstractWe investigate the sample complexity of Hamiltonian simulation: how many copies of an unknown quantum state are required to simulate a Hamiltonian encoded by the density matrix of that state? We show that the procedure proposed by Lloyd, Mohseni, and Rebentrost [Nat. Phys., 10(9):631–633, 2014] is optimal for this task. We further extend their method to the case of multiple input states, showing how to simulate any Hermitian polynomial of the states provided. As applications, we derive optimal algorithms for commutator simulation and orthogonality testing, and we give a protocol for creating a coherent superposition of pure states, when given sample access to those states. We also show that this sample-based Hamiltonian simulation can be used as the basis of a universal model of quantum computation that requires only partial swap operations and simple single-qubit states.en_US
dc.identifierhttps://doi.org/10.13016/M25T3G30R
dc.identifier.citationnpj Quantum Information (2017) 3:13; doi:10.1038/s41534-017-0013-7en_US
dc.identifier.urihttp://hdl.handle.net/1903/20599
dc.language.isoen_USen_US
dc.relation.isAvailableAtCollege of Computer, Mathematical & Natural Sciencesen_us
dc.relation.isAvailableAtComputer Scienceen_us
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_us
dc.relation.isAvailableAtUniversity of Maryland (College Park, MD)en_us
dc.titleHamiltonian simulation with optimal sample complexityen_US
dc.typeArticleen_US

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