Accelerating Optimal Elemental Configuration Search in Crystal using Ising Machine

TL;DR

This paper demonstrates that Ising machines can efficiently solve large-scale optimal elemental configuration problems in crystals, including constrained cases, by formulating the problem as a QUBO derived from cluster expansion.

Contribution

The study introduces a method to apply Ising machines to crystal configuration problems, including constrained optimization, with successful solutions for structures over 10,000 atoms.

Findings

Successfully solved large crystal configuration problems with over 10,000 atoms.

Obtained plausible solutions for constrained atomic composition scenarios.

Validated Ising machines as effective tools for materials science optimization.

Abstract

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.