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dc.contributor.advisorIsaac L. Chuang and Kevin M. Obenland.en_US
dc.contributor.authorRines, Richard Ellis.en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Physics.en_US
dc.date.accessioned2020-01-08T19:42:21Z
dc.date.available2020-01-08T19:42:21Z
dc.date.copyright2019en_US
dc.date.issued2019en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/123402
dc.descriptionThesis: Ph. D., Massachusetts Institute of Technology, Department of Physics, 2019en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 173-181).en_US
dc.description.abstractQuantum computers promise to extend the domain of the computable, performing calculations thought to be intractable on any classical device. Rapid experimental and technological progress suggests that this promise could soon be realized. However, these first quantum computers will inevitably be both small, faulty, and expensive, demanding implementations of quantum algorithms which are compact, fast, and error-resistant. As the complexity of realizable quantum computers accelerates toward the threshold of quantum supremacy, their capacity to demonstrate a meaningful quantum advantage when applied to real-world tasks depends on the high-performance design, implementation, and analysis of quantum circuits. The first half of the thesis is devoted to Shor's factoring algorithm, seeking to determine the most efficient quantum circuit implementation of a quantum modular multiplier.en_US
dc.description.abstractThree such implementations are introduced which outperform the best known exact reversible modular multiplier circuits for most practical problem sizes. Reformulated in the framework of quantum Fourier transform (QFT) based arithmetic, two of these circuits are further shown to reduce modular multiplication to a constant number of QFT-like circuits, which can then parallelized to a linear-depth circuit with just 2n + O(log n) qubits. Motivated by this deconstruction, the final result in this portion is an algorithm for a 'SIMD QFT' - demonstrating that the parallel QFT can be efficiently implemented on a topologically-limited distributed ion-trap architecture with just a single global shuttling instruction. The second half of this thesis focuses on quantum signal processing (QSP), specifically as applied to quantum Hamiltonian simulation.en_US
dc.description.abstractHamiltonian simulation promises to be one of the first practical applications for which a near-term device could demonstrate an advantage over all classical systems. We use high-performance classical tools to construct, optimize, and simulate quantum circuits subject to realistic error models in order to empirically determine the maximum tolerable error rate for a meaningful Hamiltonian simulation experiment on a near-term quantum computer. By exploiting symmetry inherent to the QSP circuit, we demonstrate that their capacity for quantum simulation can be increased by at least two orders of magnitude if errors are systematic and unitary. This portion concludes with a thorough description of the classical simulation software used for the this analysis.en_US
dc.description.statementofresponsibilityby Richard Ellis Rines.en_US
dc.format.extent181 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectPhysics.en_US
dc.titleDesign and evaluation of high-performance quantum circuit componentsen_US
dc.typeThesisen_US
dc.description.degreePh. D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Physicsen_US
dc.identifier.oclc1133618516en_US
dc.description.collectionPh.D. Massachusetts Institute of Technology, Department of Physicsen_US
dspace.imported2020-01-08T19:42:20Zen_US
mit.thesis.degreeDoctoralen_US
mit.thesis.departmentPhysen_US


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