Motional state engineering for continuous-variable quantum computation
Thesis: S.B., Massachusetts Institute of Technology, Department of Physics, February, 2021 === Cataloged from PDF of thesis. === Includes bibliographical references (pages 61-63). === The standard approach to quantum computation uses qubits, which are well-described as a two-level system. An alterna...
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ndltd-MIT-oai-dspace.mit.edu-1721.1-1307282021-05-28T05:20:00Z Motional state engineering for continuous-variable quantum computation Mintzer, Gabriel L. Isaac L. Chuang. Massachusetts Institute of Technology. Department of Physics. Massachusetts Institute of Technology. Department of Physics Physics. Thesis: S.B., Massachusetts Institute of Technology, Department of Physics, February, 2021 Cataloged from PDF of thesis. Includes bibliographical references (pages 61-63). The standard approach to quantum computation uses qubits, which are well-described as a two-level system. An alternative approach to quantum computation is continuous-variable quantum computation (CVQC), which uses physical observables, such as the strength of an electromagnetic field or the position of a particle in space, whose numerical values belong to continuous intervals. Trapped ions are well-developed for quantum computation, and they possess both qubit and continuous degrees of freedom that can be precisely controlled, making them a good candidate for a realization of CVQC. Although there exist software frameworks capable of simulating CVQC experiments, these frameworks do not incorporate realistic noise sources and cannot be tailored to a specific trapped-ion setup. In this work, we develop a computational framework for simulating CVQC operations using trapped ions in a realistic system with realistic noise sources. We do so first with ideal Hamiltonians and then with Hamiltonians generated directly from the electric potential and fields that can be applied to the trapped ion in a representative Paul trap. This allows for the direct simulation of a squeezing operation that can be implemented through application of voltages in trapped-ion experiments. These methods can be applied to other CVQC operations in order to allow for their direct simulation as well. We package these tools into a usable application with which we can load information about an experimental configuration and then use this simulation procedure to design and test experiments in CVQC achievable with an ion-trap setup, thus facilitating the experimental design process and eventually allowing for prediction of system behavior and comparison with experimental results. by Gabriel L. Mintzer. S.B. S.B. Massachusetts Institute of Technology, Department of Physics 2021-05-24T19:53:12Z 2021-05-24T19:53:12Z 2021 2021 Thesis https://hdl.handle.net/1721.1/130728 1251804370 eng MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. http://dspace.mit.edu/handle/1721.1/7582 63 pages application/pdf Massachusetts Institute of Technology |
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Physics. Mintzer, Gabriel L. Motional state engineering for continuous-variable quantum computation |
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Thesis: S.B., Massachusetts Institute of Technology, Department of Physics, February, 2021 === Cataloged from PDF of thesis. === Includes bibliographical references (pages 61-63). === The standard approach to quantum computation uses qubits, which are well-described as a two-level system. An alternative approach to quantum computation is continuous-variable quantum computation (CVQC), which uses physical observables, such as the strength of an electromagnetic field or the position of a particle in space, whose numerical values belong to continuous intervals. Trapped ions are well-developed for quantum computation, and they possess both qubit and continuous degrees of freedom that can be precisely controlled, making them a good candidate for a realization of CVQC. Although there exist software frameworks capable of simulating CVQC experiments, these frameworks do not incorporate realistic noise sources and cannot be tailored to a specific trapped-ion setup. In this work, we develop a computational framework for simulating CVQC operations using trapped ions in a realistic system with realistic noise sources. We do so first with ideal Hamiltonians and then with Hamiltonians generated directly from the electric potential and fields that can be applied to the trapped ion in a representative Paul trap. This allows for the direct simulation of a squeezing operation that can be implemented through application of voltages in trapped-ion experiments. These methods can be applied to other CVQC operations in order to allow for their direct simulation as well. We package these tools into a usable application with which we can load information about an experimental configuration and then use this simulation procedure to design and test experiments in CVQC achievable with an ion-trap setup, thus facilitating the experimental design process and eventually allowing for prediction of system behavior and comparison with experimental results. === by Gabriel L. Mintzer. === S.B. === S.B. Massachusetts Institute of Technology, Department of Physics |
author2 |
Isaac L. Chuang. |
author_facet |
Isaac L. Chuang. Mintzer, Gabriel L. |
author |
Mintzer, Gabriel L. |
author_sort |
Mintzer, Gabriel L. |
title |
Motional state engineering for continuous-variable quantum computation |
title_short |
Motional state engineering for continuous-variable quantum computation |
title_full |
Motional state engineering for continuous-variable quantum computation |
title_fullStr |
Motional state engineering for continuous-variable quantum computation |
title_full_unstemmed |
Motional state engineering for continuous-variable quantum computation |
title_sort |
motional state engineering for continuous-variable quantum computation |
publisher |
Massachusetts Institute of Technology |
publishDate |
2021 |
url |
https://hdl.handle.net/1721.1/130728 |
work_keys_str_mv |
AT mintzergabriell motionalstateengineeringforcontinuousvariablequantumcomputation |
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1719407335019905024 |