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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.20108 |
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| _version_ | 1866911021404258304 |
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| author | Endo, Seiya Kawakatsu, Shohei Matsuyama, Hiromichi Suzuki, Kohei Matsuzaki, Yuichiro |
| author_facet | Endo, Seiya Kawakatsu, Shohei Matsuyama, Hiromichi Suzuki, Kohei Matsuzaki, Yuichiro |
| contents | Quantum annealing is a method developed to solve combinatorial optimization problems by utilizing quantum bits. Solving such problems corresponds to minimizing a cost function defined over binary variables. However, in many practical cases, the cost function may also involve continuous variables. Representing continuous variables using quantum bits requires binary encoding, which demands a large number of qubits. To overcome this limitation, an approach using quantum resonators has been proposed, enabling the direct handling of continuous variables within the quantum annealing framework. On the other hand, certain optimization problems involve both binary and continuous variables simultaneously, and a quantum annealing method capable of efficiently solving such hybrid problems has not been established. Here, we propose a quantum annealing method based on a hybrid system composed of qubits and resonators, aiming to minimize cost functions that contain both binary and continuous variables. We present a general framework for hybrid quantum annealing using such systems, and investigate its feasibility and effectiveness through numerical simulations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_20108 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Quantum Annealing with Qubit-Resonator Systems for Simultaneous Optimization of Binary and Continuous Variables Endo, Seiya Kawakatsu, Shohei Matsuyama, Hiromichi Suzuki, Kohei Matsuzaki, Yuichiro Quantum Physics Quantum annealing is a method developed to solve combinatorial optimization problems by utilizing quantum bits. Solving such problems corresponds to minimizing a cost function defined over binary variables. However, in many practical cases, the cost function may also involve continuous variables. Representing continuous variables using quantum bits requires binary encoding, which demands a large number of qubits. To overcome this limitation, an approach using quantum resonators has been proposed, enabling the direct handling of continuous variables within the quantum annealing framework. On the other hand, certain optimization problems involve both binary and continuous variables simultaneously, and a quantum annealing method capable of efficiently solving such hybrid problems has not been established. Here, we propose a quantum annealing method based on a hybrid system composed of qubits and resonators, aiming to minimize cost functions that contain both binary and continuous variables. We present a general framework for hybrid quantum annealing using such systems, and investigate its feasibility and effectiveness through numerical simulations. |
| title | Quantum Annealing with Qubit-Resonator Systems for Simultaneous Optimization of Binary and Continuous Variables |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2506.20108 |