Accelerating Optimal Elemental Configuration Search in Crystal using Ising Machine
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866910870603300864 |
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| author | Ichikawa, Kazuhide Ohuchi, Satoru Ueno, Koki Yokoyama, Tomoyasu |
| author_facet | Ichikawa, Kazuhide Ohuchi, Satoru Ueno, Koki Yokoyama, Tomoyasu |
| contents | This research demonstrates that Ising machines can effectively solve optimal elemental configuration searches in crystals, with Au-Cu alloys serving as an example. The energy function is derived using the cluster expansion method in the form of a QUBO function, enabling efficient problem-solving via Ising machines. We have successfully obtained reasonable solutions for crystal structures consisting of over 10,000 atoms. Notably, we have also obtained plausible solutions for optimization problems with constrained solutions, such as situations where the composition ratio of atomic species is predetermined. These findings suggest that Ising machines can be valuable tools for addressing materials science challenges. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2305_19625 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Accelerating Optimal Elemental Configuration Search in Crystal using Ising Machine Ichikawa, Kazuhide Ohuchi, Satoru Ueno, Koki Yokoyama, Tomoyasu Materials Science Computational Physics This research demonstrates that Ising machines can effectively solve optimal elemental configuration searches in crystals, with Au-Cu alloys serving as an example. The energy function is derived using the cluster expansion method in the form of a QUBO function, enabling efficient problem-solving via Ising machines. We have successfully obtained reasonable solutions for crystal structures consisting of over 10,000 atoms. Notably, we have also obtained plausible solutions for optimization problems with constrained solutions, such as situations where the composition ratio of atomic species is predetermined. These findings suggest that Ising machines can be valuable tools for addressing materials science challenges. |
| title | Accelerating Optimal Elemental Configuration Search in Crystal using Ising Machine |
| topic | Materials Science Computational Physics |
| url | https://arxiv.org/abs/2305.19625 |