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An Integral-Direct Linear-Scaling Second-Order Møller-Plesset Approach
Péter R Nagy1, Gyula Samu1, Mihály Kállay1
1MTA-BME Lendület Quantum Chemistry Research Group, Department of Physical Chemistry and Materials Science, Budapest University of Technology and Economics , P.O. Box 91, Budapest H-1521, Hungary.
Journal of Chemical Theory and Computation
|September 13, 2016
Summary
A new computational method enables accurate and efficient second-order Møller-Plesset (MP2) calculations for very large molecules. This approach significantly reduces computational cost and memory requirements for quantum chemistry simulations.
Area of Science:
- Quantum Chemistry
- Computational Chemistry
- Theoretical Chemistry
Background:
- Accurate prediction of molecular properties is crucial in chemistry.
- Second-order Møller-Plesset perturbation theory (MP2) offers a good balance between accuracy and cost.
- Scaling limitations of traditional MP2 methods hinder application to large systems.
Purpose of the Study:
- To develop a linear-scaling, local MP2 method for large molecules.
- To enable efficient calculation of correlation energies and reaction energies.
- To facilitate MP2 calculations on systems previously inaccessible due to computational cost.
Main Methods:
- Integral-direct, iteration-free, local MP2 approach.
- Fragmentation approximation with localized orbitals and multipole expansions.
- Density fitting and natural auxiliary functions to reduce computational overhead.
Main Results:
- Recovers 99.9% of canonical MP2 correlation energy.
- Reproduces reaction energies with average error < 1 kJ/mol.
- Enables MP2 calculations for molecules with over 2300 atoms on a single processor.
Conclusions:
- The presented method offers a significant advancement in computational efficiency for MP2 calculations.
- This approach extends the applicability of accurate electronic structure methods to larger and more complex molecular systems.
- The method is also suitable for spin-scaled MP2 and double-hybrid density functional calculations.
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