.png){kind=icon}
返回
Incremental embedding: A density matrix embedding scheme for molecules
.png){kind=icon}
OA
AI
DOI：10.1063/1.5053992.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The idea of using fragment embedding to circumvent the high computational scaling of accurate electronic structure methods while retaining high accuracy has been a long-standing goal for quantum chemists. Traditional fragment embedding methods mainly focus on systems composed of weakly correlated parts and are insufficient when division across chemical bonds is unavoidable. Recently, density matrix embedding theory and other methods based on the Schmidt decomposition have emerged as a fresh approach to this problem. Despite their success on model systems, these methods can prove difficult for realistic systems because they rely on either a rigid, non-overlapping partition of the system or a specification of some special sites (i.e., edge and center sites), neither of which is well-defined in general for real molecules. In this work, we present a new Schmidt decomposition-based embedding scheme called incremental embedding that allows the combination of arbitrary overlapping fragments without the knowledge of edge sites. This method forms a convergent hierarchy in the sense that higher accuracy can be obtained by using fragments involving more sites. The computational scaling for the first few levels is lower than that of most correlated wave function methods. We present results for several small molecules in atom-centered Gaussian basis sets and demonstrate that incremental embedding converges quickly with fragment size and recovers most static correlation in small basis sets even when truncated at the second lowest level. Published by AIP Publishing.
Keyword:
EXCHANGE-CORRELATION POTENTIALS
ELECTRON CORRELATION
PERTURBATION-THEORY
LARGE SYSTEMS
FORMULATION
INVARIANT
ALGORITHM
ORBITALS
STATES
MODEL
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.1
论文数:
7.2W
被引数:
23.2W
机构
暂无机构信息
引用论文
.png){kind=icon}
Modeling Li-ion batteries for automotive application: A trade-off between accuracy and complexityOAAI
OAAI分享收藏
查看更多内容