Tackling the Challenge of a Huge Materials Science Search Space with Quantum‐Inspired Annealing

• Main Authors: Kan Hatakeyama-Sato, Takahiro Kashikawa, Koichi Kimura, Kenichi Oyaizu
• Format: Article
• Language: English
• Published: Wiley 2021-04-01
• Series: Advanced Intelligent Systems
• Subjects: lithium-ion batteries; machine learning; materials informatics; organic functional materials; quantum-inspired annealing
• Online Access: https://doi.org/10.1002/aisy.202000209

Efficient screening of chemicals is essential for exploring new materials. However, the search space is astronomically large, making calculations with conventional computers infeasible. For example, an N‐component system of organic molecules generates >1060N candidates. Here, a quantum‐inspired annealing machine is used to tackle the challenge of the large search space. The prototype system extracts candidate chemicals and their composites with desirable parameters, such as melting temperature and ionic conductivity. The system can be at least 104–108 times faster than conventional approaches. Such dramatic acceleration is critical for exploring the enormous search space in virtual screening of materials.