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dc.contributor.authorJena, Andrew
dc.date.accessioned2019-09-04 15:34:12 (GMT)
dc.date.available2019-09-04 15:34:12 (GMT)
dc.date.issued2019-09-04
dc.date.submitted2019-08-30
dc.identifier.urihttp://hdl.handle.net/10012/15017
dc.description.abstractMeasuring the expectation value of Pauli operators on prepared quantum states is a fundamental task in the variational quantum eigensolver. Simultaneously measuring sets of operators allows for fewer measurements and an overall speedup of the measurement process. In this thesis, we look both at the task of partitioning all Pauli operators of a xed length and of partitioning a random subset of these Pauli operators. We rst show how Singer cycles can be used to optimally partition the set of all Pauli operators, giving some insight to the structure underlying many constructions of mutually unbiased bases. Thereafter, we show how graph coloring algorithms promise to provide speedups linear with respect to the lengths of the operators over currently-implemented techniques in the measurement step of the variational quantum eigensolver.en
dc.language.isoenen
dc.publisherUniversity of Waterlooen
dc.subjectClifford groupen
dc.subjectPauli operatorsen
dc.subjectpartitioningen
dc.subjectgraph coloringen
dc.subjectSinger cyclesen
dc.subjectVQEen
dc.subjectvariational quantum eigensolveren
dc.subjectMUBsen
dc.subjectmutually unbiased basesen
dc.subjectsymplectic representationen
dc.subjectNP-harden
dc.titlePartitioning Pauli Operators: in Theory and in Practiceen
dc.typeMaster Thesisen
dc.pendingfalse
uws-etd.degree.departmentCombinatorics and Optimizationen
uws-etd.degree.disciplineCombinatorics and Optimization (Quantum Information)en
uws-etd.degree.grantorUniversity of Waterlooen
uws-etd.degreeMaster of Mathematicsen
uws.contributor.advisorMosca, Michele
uws.contributor.affiliation1Faculty of Mathematicsen
uws.published.cityWaterlooen
uws.published.countryCanadaen
uws.published.provinceOntarioen
uws.typeOfResourceTexten
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen


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