Performance Benchmarking of Quantum Algorithms for Hard Combinatorial Optimization Problems: A Comparative Study of non-FTQC Approaches
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| Main Authors: | , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866910678352134144 |
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| author | Kikuura, Santaro Igata, Ryoya Shingu, Yuta Watabe, Shohei |
| author_facet | Kikuura, Santaro Igata, Ryoya Shingu, Yuta Watabe, Shohei |
| contents | This study systematically benchmarks several non-fault-tolerant quantum computing algorithms across four distinct optimization problems: max-cut, number partitioning, knapsack, and quantum spin glass. Our benchmark includes noisy intermediate-scale quantum (NISQ) algorithms, such as the variational quantum eigensolver, quantum approximate optimization algorithm, quantum imaginary time evolution, and imaginary time quantum annealing, with both ansatz-based and ansatz-free implementations, alongside tensor network methods and direct simulations of the imaginary-time Schrödinger equation. For comparative analysis, we also utilize classical simulated annealing and quantum annealing on D-Wave devices. Employing default configurations, our findings reveal that no single non-FTQC algorithm performs optimally across all problem types, underscoring the need for tailored algorithmic strategies. This work provides an objective performance baseline and serves as a critical reference point for advancing NISQ algorithms and quantum annealing platforms. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2410_22810 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Performance Benchmarking of Quantum Algorithms for Hard Combinatorial Optimization Problems: A Comparative Study of non-FTQC Approaches Kikuura, Santaro Igata, Ryoya Shingu, Yuta Watabe, Shohei Quantum Physics This study systematically benchmarks several non-fault-tolerant quantum computing algorithms across four distinct optimization problems: max-cut, number partitioning, knapsack, and quantum spin glass. Our benchmark includes noisy intermediate-scale quantum (NISQ) algorithms, such as the variational quantum eigensolver, quantum approximate optimization algorithm, quantum imaginary time evolution, and imaginary time quantum annealing, with both ansatz-based and ansatz-free implementations, alongside tensor network methods and direct simulations of the imaginary-time Schrödinger equation. For comparative analysis, we also utilize classical simulated annealing and quantum annealing on D-Wave devices. Employing default configurations, our findings reveal that no single non-FTQC algorithm performs optimally across all problem types, underscoring the need for tailored algorithmic strategies. This work provides an objective performance baseline and serves as a critical reference point for advancing NISQ algorithms and quantum annealing platforms. |
| title | Performance Benchmarking of Quantum Algorithms for Hard Combinatorial Optimization Problems: A Comparative Study of non-FTQC Approaches |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2410.22810 |