论文标题
通过数据挖掘确定候选宿主的量子缺陷
Identifying candidate hosts for quantum defects via data mining
论文作者
论文摘要
固态宿主中的原子状缺陷是量子信息系统开发的有前途的候选人,但是尽管它们的重要性,但目前正在研究的宿主底物/缺陷组合几乎完全偶然发现了。在这里,我们通过在材料项目数据库中的所有条目中应用四阶段数据挖掘和手动筛选过程来系统地评估宿主材料的适用性,并对频带隙值进行基于文献的实验确认。我们确定580个可行的宿主基板,用于量子缺陷引入和使用量子信息系统。尽管这构成已知和潜在可行的物质系统的数量显着增加,但它仍然是已知无机阶段总数的显着减少(99.54%),并且在特定应用中应用其他选择标准将进一步减少其数量。概述的筛选原则很容易应用于以前未实现的阶段和其他重要的材料系统。
Atom-like defects in solid-state hosts are promising candidates for the development of quantum information systems, but despite their importance, the host substrate/defect combinations currently under study have almost exclusively been found serendipitously. Here we systematically evaluate the suitability of host materials by applying a combined four-stage data mining and manual screening process to all entries in the Materials Project database, with literature-based experimental confirmation of band gap values. We identify 580 viable host substrates for quantum defect introduction and use in quantum information systems. While this constitutes a significant increase in the number of known and potentially viable material systems, it nonetheless represents a significant (99.54%) reduction from the total number of known inorganic phases, and the application of additional selection criteria for specific applications will reduce their number even further. The screening principles outlined may easily be applied to previously unrealized phases and other technologically important materials systems.