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Quantum Algorithm Implementations an...
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Zheng, Muqing.
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Quantum Algorithm Implementations and a Classical Look on Quantum Error Mitigation.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Quantum Algorithm Implementations and a Classical Look on Quantum Error Mitigation./
作者:
Zheng, Muqing.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2024,
面頁冊數:
210 p.
附註:
Source: Dissertations Abstracts International, Volume: 85-11, Section: B.
Contained By:
Dissertations Abstracts International85-11B.
標題:
Quantum physics. -
電子資源:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31240178
ISBN:
9798382338194
Quantum Algorithm Implementations and a Classical Look on Quantum Error Mitigation.
Zheng, Muqing.
Quantum Algorithm Implementations and a Classical Look on Quantum Error Mitigation.
- Ann Arbor : ProQuest Dissertations & Theses, 2024 - 210 p.
Source: Dissertations Abstracts International, Volume: 85-11, Section: B.
Thesis (Ph.D.)--Lehigh University, 2024.
Quantum computing holds great potential for reducing the time complexity of many problems in theory. However, there are many gaps waiting to be filled in the implementation. In the first part of this dissertation, we explore the performance and applications of several variational algorithms and a quantum linear solver, the HHL algorithm, on simulators. Specifically, we assess the use of the HHL algorithm in addressing scientific and engineering problems through quantum computing utilizing the NWQSim simulation package on high-performance computing. We demonstrate the influence of several tunable parameters of circuits and algorithms on the final solution in an iterative and a non-iterative numerical method. In the second part of this dissertation, we develop the quantum version of the Generator Coordinate Method. It is a hybrid quantum-classical approach for solving quantum chemistry problems without worrying about the barren plateau and the exactness of the ansatze by building the interconnection between constrained optimization and generalized eigenvalue problems through a unique class of Givens rotations. For practical applications, we propose an adaptive scheme for the robust construction of many-body states using these Givens rotations, with an emphasis on a linear expansion that balances accuracy and efficiency. In the final part of the dissertation, we focus on the unique problem in real quantum computers: quantum noise. To address this, we design a Bayesian inference approach that identifies posterior distributions of individual noise parameters for more elaborate characterization of device errors. Thus, we further improve the accuracy of quantum error mitigation. Our experiments on superconducting quantum computing devices show that our approach provides better error mitigation performance than existing techniques used by the vendor and outperforms the standard Bayesian inference method in some scenarios. In addition, our research on Kalman filter aims to simulate the quantum state evolution inside real quantum computers fully. In several multi-qubit experiments, our method has shown leading performance compared to the noise simulator in a popular software package.
ISBN: 9798382338194Subjects--Topical Terms:
726746
Quantum physics.
Subjects--Index Terms:
Bayesian inference
Quantum Algorithm Implementations and a Classical Look on Quantum Error Mitigation.
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Quantum computing holds great potential for reducing the time complexity of many problems in theory. However, there are many gaps waiting to be filled in the implementation. In the first part of this dissertation, we explore the performance and applications of several variational algorithms and a quantum linear solver, the HHL algorithm, on simulators. Specifically, we assess the use of the HHL algorithm in addressing scientific and engineering problems through quantum computing utilizing the NWQSim simulation package on high-performance computing. We demonstrate the influence of several tunable parameters of circuits and algorithms on the final solution in an iterative and a non-iterative numerical method. In the second part of this dissertation, we develop the quantum version of the Generator Coordinate Method. It is a hybrid quantum-classical approach for solving quantum chemistry problems without worrying about the barren plateau and the exactness of the ansatze by building the interconnection between constrained optimization and generalized eigenvalue problems through a unique class of Givens rotations. For practical applications, we propose an adaptive scheme for the robust construction of many-body states using these Givens rotations, with an emphasis on a linear expansion that balances accuracy and efficiency. In the final part of the dissertation, we focus on the unique problem in real quantum computers: quantum noise. To address this, we design a Bayesian inference approach that identifies posterior distributions of individual noise parameters for more elaborate characterization of device errors. Thus, we further improve the accuracy of quantum error mitigation. Our experiments on superconducting quantum computing devices show that our approach provides better error mitigation performance than existing techniques used by the vendor and outperforms the standard Bayesian inference method in some scenarios. In addition, our research on Kalman filter aims to simulate the quantum state evolution inside real quantum computers fully. In several multi-qubit experiments, our method has shown leading performance compared to the noise simulator in a popular software package.
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