Survey on the Improvement and Application of HHL Algorithm
Quantum computing is a new computing mode that follows the laws of quantum mechanics to control quantum information units for computation. In terms of computational efficiency, due to the existence of quantum mechanical superposition, some known quantum algorithms can process problems faster than tr...
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| Vydáno v: | Journal of physics. Conference series Ročník 2333; číslo 1; s. 12023 - 12034 |
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Bristol
IOP Publishing
01.08.2022
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| ISSN: | 1742-6588, 1742-6596 |
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| Abstract | Quantum computing is a new computing mode that follows the laws of quantum mechanics to control quantum information units for computation. In terms of computational efficiency, due to the existence of quantum mechanical superposition, some known quantum algorithms can process problems faster than traditional general-purpose computers. HHL algorithm is an algorithm for solving linear system problems. Compared with classical algorithms in solving linear equations, it has an exponential acceleration effect in certain cases and as a sub-module, it is widely used in some machine learning algorithms to form quantum machines learning algorithms. However, there are some limiting factors in the use of this algorithm, which affect the overall effect of the algorithm. How to improve it to make the algorithm perform better has become an important issue in the field of quantum computing. This paper summarizes the optimization and improvement of HHL algorithm since it was proposed, and the application of HHL algorithm in machine learning, and discusses some possible future improvements of some subroutines in HHL algorithm. |
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| AbstractList | Quantum computing is a new computing mode that follows the laws of quantum mechanics to control quantum information units for computation. In terms of computational efficiency, due to the existence of quantum mechanical superposition, some known quantum algorithms can process problems faster than traditional general-purpose computers. HHL algorithm is an algorithm for solving linear system problems. Compared with classical algorithms in solving linear equations, it has an exponential acceleration effect in certain cases and as a sub-module, it is widely used in some machine learning algorithms to form quantum machines learning algorithms. However, there are some limiting factors in the use of this algorithm, which affect the overall effect of the algorithm. How to improve it to make the algorithm perform better has become an important issue in the field of quantum computing. This paper summarizes the optimization and improvement of HHL algorithm since it was proposed, and the application of HHL algorithm in machine learning, and discusses some possible future improvements of some subroutines in HHL algorithm. |
| Author | Liu, Xiaonan Zhao, Chenyan Xie, Haoshan Liu, Zhengyu |
| Author_xml | – sequence: 1 givenname: Xiaonan surname: Liu fullname: Liu, Xiaonan organization: State Key Laboratory of Mathematical Engineering and Advanced Computing, Information Engineering University , China – sequence: 2 givenname: Haoshan surname: Xie fullname: Xie, Haoshan organization: State Key Laboratory of Mathematical Engineering and Advanced Computing, Information Engineering University , China – sequence: 3 givenname: Zhengyu surname: Liu fullname: Liu, Zhengyu organization: School of Computer and Artificial Intelligence, ZhengZhou University , China – sequence: 4 givenname: Chenyan surname: Zhao fullname: Zhao, Chenyan organization: State Key Laboratory of Mathematical Engineering and Advanced Computing, Information Engineering University , China |
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| DOI | 10.1088/1742-6596/2333/1/012023 |
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| SubjectTerms | Algorithms HHL Algorithm Linear equations LinearSystems Machine learning Optimization Physics Quantum Computing Quantum Machine-Learning Quantum mechanics Quantum phenomena Superposition (mathematics) |
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