Tensor Network Based HOBO Solver
Fuente:
arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866929432228265984 |
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| author | Minato, Yuichiro |
| author_facet | Minato, Yuichiro |
| contents | In the field of quantum computing, combinatorial optimization problems are typically addressed using QUBO (Quadratic Unconstrained Binary Optimization) solvers. However, these solvers are often insufficient for tackling higher-order problems. In this paper, we introduce a novel and efficient solver designed specifically for HOBO (Higher-Order Binary Optimization) problem settings. Our approach leverages advanced techniques to effectively manage the complexity and computational demands associated with high-dimensional optimization tasks. The proposed solver is a promising tool with significant potential for future extensions in terms of formulation. This solver holds promising potential for a wide range of applications in quantum computing. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_16106 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Tensor Network Based HOBO Solver Minato, Yuichiro Quantum Physics In the field of quantum computing, combinatorial optimization problems are typically addressed using QUBO (Quadratic Unconstrained Binary Optimization) solvers. However, these solvers are often insufficient for tackling higher-order problems. In this paper, we introduce a novel and efficient solver designed specifically for HOBO (Higher-Order Binary Optimization) problem settings. Our approach leverages advanced techniques to effectively manage the complexity and computational demands associated with high-dimensional optimization tasks. The proposed solver is a promising tool with significant potential for future extensions in terms of formulation. This solver holds promising potential for a wide range of applications in quantum computing. |
| title | Tensor Network Based HOBO Solver |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2407.16106 |