SparseMaps—A systematic infrastructure for reduced scaling electronic structure methods. V. Linear scaling explicitly correlated coupled-cluster method with pair natural orbitals

2017 ◽  
Vol 146 (17) ◽  
pp. 174108 ◽  
Author(s):  
Fabijan Pavošević ◽  
Chong Peng ◽  
Peter Pinski ◽  
Christoph Riplinger ◽  
Frank Neese ◽  
...  
Keyword(s):  
Electronic Structure ◽  
Cluster Method ◽  
Coupled Cluster ◽  
Linear Scaling ◽  
Coupled Cluster Method ◽  
Natural Orbitals ◽  
Electronic Structure Methods ◽  
Explicitly Correlated

Perturbative triples correction for explicitly correlated Mukherjee’s state-specific coupled cluster method

2013 ◽  
Vol 111 (16-17) ◽  
pp. 2477-2488 ◽  
Author(s):  
Ondřej Demel ◽  
Stanislav Kedžuch ◽  
Jozef Noga ◽  
Jiří Pittner
Keyword(s):  
Cluster Method ◽  
Coupled Cluster ◽  
Coupled Cluster Method ◽  
Explicitly Correlated

Linear scaling coupled cluster method with correlation energy based error control

2010 ◽  
Vol 133 (1) ◽  
pp. 014107 ◽  
Author(s):  
Marcin Ziółkowski ◽  
Branislav Jansík ◽  
Thomas Kjærgaard ◽  
Poul Jørgensen
Keyword(s):  
Error Control ◽  
Correlation Energy ◽  
Cluster Method ◽  
Coupled Cluster ◽  
Linear Scaling ◽  
Coupled Cluster Method

An explicitly correlated Mukherjee's state specific coupled cluster method: development and pilot applications

2012 ◽  
Vol 14 (14) ◽  
pp. 4753 ◽  
Author(s):  
Ondřej Demel ◽  
Stanislav Kedžuch ◽  
Matej Švaňa ◽  
Seiichiro Ten-no ◽  
Jiří Pittner ◽  
...  
Keyword(s):  
Method Development ◽  
Cluster Method ◽  
Coupled Cluster ◽  
Coupled Cluster Method ◽  
Explicitly Correlated

A global coupled cluster potential energy surface for HCl + OH ↔ Cl + H2O

2017 ◽  
Vol 19 (15) ◽  
pp. 9770-9777 ◽  
Author(s):  
Junxiang Zuo ◽  
Bin Zhao ◽  
Hua Guo ◽  
Daiqian Xie
Keyword(s):  
Neural Network ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Energy Surface ◽  
Cluster Method ◽  
Coupled Cluster ◽  
Invariant Polynomial ◽  
Coupled Cluster Method ◽  
Polynomial Neural Network ◽  
Explicitly Correlated

A new and more accurate full-dimensional global potential energy surface (PES) for the ground electronic state of the ClH2O system is developed by using the permutation invariant polynomial-neural network (PIP-NN) method to fit 15 777 points obtained using an explicitly correlated unrestricted coupled-cluster method with single, double, and perturbative triple excitations (UCCSD(T)-F12b).

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