On the Power and Limitations of Shallow Quantum Circuits

dc.contributor.authorParham, Natalie
dc.date.accessioned2022-09-01T18:59:07Z
dc.date.available2022-09-01T18:59:07Z
dc.date.issued2022-09-01
dc.date.submitted2022-08-20
dc.description.abstractConstant-depth quantum circuits, or shallow quantum circuits, have been shown to exhibit behavior that is uniquely quantum. This thesis explores the power and limitations of constant-depth quantum circuits, in particular as they compare to constant-depth classical circuits. We start with a gentle introduction to shallow quantum and classical circuit complexity, and we review the hardness of sampling from the output distribution of a constant-depth quantum circuit. We then give an overview of the shallow circuit advantage from the 1D Magic Square Problem from [Bravyi, Gosset, Koenig, Tomamichel 2020]. The first novel contribution is an investigation into the limitations of shallow quantum circuits for local optimization problems. We prove that if a shallow quantum circuit's input/output relation is exactly that of a local optimization problem, then we can construct a shallow classical circuit that also solves the optimization problem. We also prove an approximate version of this statement. Finally, we introduce a novel sampling task over an n-bit distribution D_n such that there exists a shallow quantum circuit that takes as input the state \ket{\GHZ_n} = \frac{1}{\sqrt{2}}(\ket{0^n} + \ket{1^n}) and produces a distribution close to D_n whereas, any constant-depth classical circuit with bounded fan-in and n + n^\delta random input bits for some \delta<1, will produce a distribution that is not close to D_n.en
dc.identifier.urihttp://hdl.handle.net/10012/18702
dc.language.isoenen
dc.pendingfalse
dc.publisherUniversity of Waterlooen
dc.subjectquantumen
dc.subjectshallow quantum circuitsen
dc.subjectcomplexity theoryen
dc.subjectmathen
dc.titleOn the Power and Limitations of Shallow Quantum Circuitsen
dc.typeMaster Thesisen
uws-etd.degreeMaster of Mathematicsen
uws-etd.degree.departmentCombinatorics and Optimizationen
uws-etd.degree.disciplineCombinatorics and Optimization (Quantum Information)en
uws-etd.degree.grantorUniversity of Waterlooen
uws-etd.embargo.terms0en
uws.contributor.advisorGosset, David
uws.contributor.advisorLaflamme, Raymond
uws.contributor.affiliation1Faculty of Mathematicsen
uws.peerReviewStatusUnrevieweden
uws.published.cityWaterlooen
uws.published.countryCanadaen
uws.published.provinceOntarioen
uws.scholarLevelGraduateen
uws.typeOfResourceTexten

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