Proof of avoidability of the quantum first-order transition in transverse magnetization in quantum annealing of finite-dimensional spin glasses
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arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866914579625279488 |
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| author | Yamaguchi, Mizuki Shiraishi, Naoto Hukushima, Koji |
| author_facet | Yamaguchi, Mizuki Shiraishi, Naoto Hukushima, Koji |
| contents | It is rigorously shown that an appropriate quantum annealing for any finite-dimensional spin system has no quantum first-order transition in transverse magnetization. This result can be applied to finite-dimensional spin-glass systems, where the ground state search problem is known to be hard to solve. Consequently, it is strongly suggested that the quantum first-order transition in transverse magnetization is not fatal to the difficulty of combinatorial optimization problems in quantum annealing. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2307_00791 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Proof of avoidability of the quantum first-order transition in transverse magnetization in quantum annealing of finite-dimensional spin glasses Yamaguchi, Mizuki Shiraishi, Naoto Hukushima, Koji Quantum Physics Disordered Systems and Neural Networks Statistical Mechanics It is rigorously shown that an appropriate quantum annealing for any finite-dimensional spin system has no quantum first-order transition in transverse magnetization. This result can be applied to finite-dimensional spin-glass systems, where the ground state search problem is known to be hard to solve. Consequently, it is strongly suggested that the quantum first-order transition in transverse magnetization is not fatal to the difficulty of combinatorial optimization problems in quantum annealing. |
| title | Proof of avoidability of the quantum first-order transition in transverse magnetization in quantum annealing of finite-dimensional spin glasses |
| topic | Quantum Physics Disordered Systems and Neural Networks Statistical Mechanics |
| url | https://arxiv.org/abs/2307.00791 |