论文标题
通过量子启发的退火来应对巨大材料科学搜索空间的挑战
Tackling the challenge of a huge materials science search space with quantum-inspired annealing
论文作者
论文摘要
化学物质的有效筛选对于探索新材料至关重要。但是，搜索空间在天文学上很大，可以使用常规计算机进行计算。例如，有机分子的$ n $组成系统生成> $ 10^{60n} $候选。在这里，使用量子启发的退火机来应对大型搜索空间的挑战。原型系统提取具有理想参数的候选化学物质及其复合材料，例如熔化温度和离子电导率。该系统至少可以比传统方法快$ 10^4 $ - $ 10^7 $倍。这种指数加速对于探索虚拟筛选中的巨大搜索空间至关重要。
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 >$10^{60N}$ 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 $10^4$-$10^7$ times faster than conventional approaches. Such exponential acceleration is critical for exploring the enormous search space in virtual screening.
