Optimal elemental configuration search in crystal using quantum approximate optimization algorithm
Year: 2025
Type: preprint
Abstract: 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.
Source: arXiv (Cornell University)
Authors: Ichikawa, Kazuhide, Hayashi, Genta, Ohuchi, Satoru, Yokoyama, Tomoyasu, Okada, Ken N., Fujii, Keisuke
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4415102452