Numerical Exploration of the Pythagorean Theorem Using HOBO Algorithm
Fuente:
arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866913474238480384 |
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| author | Yasuda, Shoya Mochida, Naoaki Sotobayashi, Shunsuke Garg, Devanshu Minato, Yuichiro |
| author_facet | Yasuda, Shoya Mochida, Naoaki Sotobayashi, Shunsuke Garg, Devanshu Minato, Yuichiro |
| contents | This paper introduces a novel method for finding integer sets that satisfy the Pythagorean theorem by leveraging the Higher-Order Binary Optimization (HOBO) formulation. Unlike the Quadratic Unconstrained Binary Optimization (QUBO) formulation, which struggles to express complex mathematical equations, HOBO's ability to model higher-order interactions between binary variables makes it well-suited for addressing more complex and expressive problem settings. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_11076 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Numerical Exploration of the Pythagorean Theorem Using HOBO Algorithm Yasuda, Shoya Mochida, Naoaki Sotobayashi, Shunsuke Garg, Devanshu Minato, Yuichiro Optimization and Control This paper introduces a novel method for finding integer sets that satisfy the Pythagorean theorem by leveraging the Higher-Order Binary Optimization (HOBO) formulation. Unlike the Quadratic Unconstrained Binary Optimization (QUBO) formulation, which struggles to express complex mathematical equations, HOBO's ability to model higher-order interactions between binary variables makes it well-suited for addressing more complex and expressive problem settings. |
| title | Numerical Exploration of the Pythagorean Theorem Using HOBO Algorithm |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2408.11076 |