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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
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Partially linearized, fully size-extensive, and reduced multireference coupled-cluster methods. II. Applications and

Xiangzhu Li1, Josef Paldus

  • 1Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada. xli@scienide.uwaterloo.ca

The Journal of Chemical Physics
|April 17, 2008
PubMed
Summary

Partially linearized multireference coupled-cluster (plMR CCSD) methods accurately model bond breaking. Reduced MR CCSD methods offer superior performance and ease of application, especially for challenging systems like N2.

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Area of Science:

  • Quantum Chemistry
  • Computational Chemistry
  • Theoretical Chemistry

Background:

  • Accurate modeling of bond breaking is crucial in computational chemistry.
  • Multireference coupled-cluster (MR CC) methods are essential for systems with strong electron correlation.
  • Standard single-reference (SR) CC methods often fail for bond dissociation processes.

Purpose of the Study:

  • To evaluate the performance of partially linearized (pl) MR CC methods, specifically plMR CCSD and plMR CCSD(T), for bond breaking.
  • To compare plMR CCSD/CCSD(T) with reduced MR (RMR) CCSD/CCSD(T) and standard SR CCSD/CCSD(T) methods.
  • To assess the impact of model space selection and size-extensivity on MR CC method accuracy.

Main Methods:

  • Application of plMR CCSD and plMR CCSD(T) methods to bond breaking in HF, F2, H2O, N2, and H4 models.
  • Utilized DZ and cc-pVDZ basis sets for comparison with Full Configuration Interaction (FCI) energies.
  • Comparative analysis with RMR CCSD/CCSD(T) and SR CCSD/CCSD(T) methods, including CR CC(2,3) for N2 and H4.

Main Results:

  • plMR CCSD/CCSD(T) methods provide accurate results for bond breaking, comparable to FCI.
  • RMR CCSD/CCSD(T) methods generally outperform plMR CCSD/CCSD(T) and are easier to implement for demanding cases.
  • The choice of model space significantly influences the accuracy of MR CC methods.

Conclusions:

  • plMR-type approaches are fully size-extensive, while RMR CCSD may slightly deviate.
  • RMR CCSD offers a better balance of accuracy and computational feasibility for challenging bond-breaking scenarios.
  • Proper model space definition is critical for reliable MR CC calculations.