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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/2503.09356 |
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| _version_ | 1866916650855432192 |
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| author | Ichikawa, Kazuhide Hayashi, Genta Ohuchi, Satoru Yokoyama, Tomoyasu Okada, Ken N. Fujii, Keisuke |
| author_facet | Ichikawa, Kazuhide Hayashi, Genta Ohuchi, Satoru Yokoyama, Tomoyasu Okada, Ken N. Fujii, Keisuke |
| contents | Optimal elemental configuration search in crystal is a crucial task to discovering industrially important materials such as lithium-ion battery cathodes. In this paper we present application of quantum approximate optimization algorithm, the representative near-term quantum algorithm for combinatorial optimization, to finding the most stable elemental configuration in a crystal, using Au-Cu alloys as an example. After expressing the energy of the crystal in the form of the Ising model through the cluster expansion method combined with first-principles calculations, we numerically perform QAOA with three types of parameter optimization. As a result, we have demonstrated that the optimal solution can be sampled with a high probability for crystals containing up to 32 atoms. Our results could pave the way for optimal elemental configuration search in a crystal using a near-term quantum computer. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_09356 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Optimal elemental configuration search in crystal using quantum approximate optimization algorithm Ichikawa, Kazuhide Hayashi, Genta Ohuchi, Satoru Yokoyama, Tomoyasu Okada, Ken N. Fujii, Keisuke Quantum Physics Optimal elemental configuration search in crystal is a crucial task to discovering industrially important materials such as lithium-ion battery cathodes. In this paper we present application of quantum approximate optimization algorithm, the representative near-term quantum algorithm for combinatorial optimization, to finding the most stable elemental configuration in a crystal, using Au-Cu alloys as an example. After expressing the energy of the crystal in the form of the Ising model through the cluster expansion method combined with first-principles calculations, we numerically perform QAOA with three types of parameter optimization. As a result, we have demonstrated that the optimal solution can be sampled with a high probability for crystals containing up to 32 atoms. Our results could pave the way for optimal elemental configuration search in a crystal using a near-term quantum computer. |
| title | Optimal elemental configuration search in crystal using quantum approximate optimization algorithm |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2503.09356 |