An efficient and near linear scaling pair natural orbital based local coupled cluster method

耦合簇 原子轨道 基准集 波函数 缩放比例 局域分子轨道 化学 线性比例尺 星团(航天器) 电子相关 物理 原子物理学 量子力学 统计物理学 密度泛函理论 分子 电子 数学 分子轨道理论 计算机科学 几何学 地理 程序设计语言 大地测量学
作者
Christoph Riplinger,Frank Neese
出处
期刊:Journal of Chemical Physics [American Institute of Physics]
卷期号:138 (3) 被引量:1675
标识
DOI:10.1063/1.4773581
摘要

In previous publications, it was shown that an efficient local coupled cluster method with single- and double excitations can be based on the concept of pair natural orbitals (PNOs) [F. Neese, A. Hansen, and D. G. Liakos, J. Chem. Phys. 131, 064103 (2009)10.1063/1.3173827]. The resulting local pair natural orbital-coupled-cluster single double (LPNO-CCSD) method has since been proven to be highly reliable and efficient. For large molecules, the number of amplitudes to be determined is reduced by a factor of 105–106 relative to a canonical CCSD calculation on the same system with the same basis set. In the original method, the PNOs were expanded in the set of canonical virtual orbitals and single excitations were not truncated. This led to a number of fifth order scaling steps that eventually rendered the method computationally expensive for large molecules (e.g., >100 atoms). In the present work, these limitations are overcome by a complete redesign of the LPNO-CCSD method. The new method is based on the combination of the concepts of PNOs and projected atomic orbitals (PAOs). Thus, each PNO is expanded in a set of PAOs that in turn belong to a given electron pair specific domain. In this way, it is possible to fully exploit locality while maintaining the extremely high compactness of the original LPNO-CCSD wavefunction. No terms are dropped from the CCSD equations and domains are chosen conservatively. The correlation energy loss due to the domains remains below <0.05%, which implies typically 15–20 but occasionally up to 30 atoms per domain on average. The new method has been given the acronym DLPNO-CCSD (“domain based LPNO-CCSD”). The method is nearly linear scaling with respect to system size. The original LPNO-CCSD method had three adjustable truncation thresholds that were chosen conservatively and do not need to be changed for actual applications. In the present treatment, no additional truncation parameters have been introduced. Any additional truncation is performed on the basis of the three original thresholds. There are no real-space cutoffs. Single excitations are truncated using singles-specific natural orbitals. Pairs are prescreened according to a multipole expansion of a pair correlation energy estimate based on local orbital specific virtual orbitals (LOSVs). Like its LPNO-CCSD predecessor, the method is completely of black box character and does not require any user adjustments. It is shown here that DLPNO-CCSD is as accurate as LPNO-CCSD while leading to computational savings exceeding one order of magnitude for larger systems. The largest calculations reported here featured >8800 basis functions and >450 atoms. In all larger test calculations done so far, the LPNO-CCSD step took less time than the preceding Hartree-Fock calculation, provided no approximations have been introduced in the latter. Thus, based on the present development reliable CCSD calculations on large molecules with unprecedented efficiency and accuracy are realized.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
充电宝应助smile采纳,获得10
刚刚
kittykitten发布了新的文献求助10
刚刚
1秒前
yyq发布了新的文献求助50
1秒前
willow完成签到,获得积分10
1秒前
1秒前
香蕉觅云应助LULU01采纳,获得10
1秒前
Three发布了新的文献求助10
2秒前
yul关闭了yul文献求助
2秒前
2秒前
3秒前
许鸣燕发布了新的文献求助10
3秒前
ryan发布了新的文献求助150
3秒前
zyzraylene完成签到,获得积分10
4秒前
英俊的铭应助cmh采纳,获得10
4秒前
5秒前
5秒前
5秒前
5秒前
神奇宝贝完成签到,获得积分10
6秒前
lili发布了新的文献求助10
6秒前
乐乐应助wangji采纳,获得10
7秒前
上官若男应助阔达的语海采纳,获得10
7秒前
秃头警告完成签到 ,获得积分10
7秒前
8秒前
默默苑博完成签到,获得积分10
8秒前
wanci应助成就的凡松采纳,获得10
8秒前
跑在颖发布了新的文献求助10
9秒前
元素搬运工完成签到,获得积分10
10秒前
10秒前
共享精神应助如约采纳,获得10
10秒前
Lujiokh完成签到,获得积分10
10秒前
秃头警告关注了科研通微信公众号
10秒前
10秒前
11秒前
自然的山柏完成签到,获得积分20
11秒前
彭于晏应助malaodi采纳,获得10
11秒前
天水碧完成签到,获得积分10
12秒前
12秒前
小小台yeah完成签到,获得积分10
12秒前
高分求助中
ФОРМИРОВАНИЕ АО "МЕЖДУНАРОДНАЯ КНИГА" КАК ВАЖНЕЙШЕЙ СИСТЕМЫ ОТЕЧЕСТВЕННОГО КНИГОРАСПРОСТРАНЕНИЯ 3000
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 2500
Future Approaches to Electrochemical Sensing of Neurotransmitters 1000
Electron microscopy study of magnesium hydride (MgH2) for Hydrogen Storage 1000
Finite Groups: An Introduction 800
Research on WLAN scenario optimisation policy based on IoT smart campus 500
生物降解型栓塞微球市场(按产品类型、应用和最终用户)- 2030 年全球预测 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3905605
求助须知:如何正确求助?哪些是违规求助? 3450824
关于积分的说明 10862710
捐赠科研通 3176226
什么是DOI,文献DOI怎么找? 1754740
邀请新用户注册赠送积分活动 848456
科研通“疑难数据库(出版商)”最低求助积分说明 791027