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Correcting Basis Set Incompleteness in Wave Function Correlation Energy by Dressing Electronic Hamiltonian with an
Michał Hapka1, Aleksandra Tucholska2, Marcin Modrzejewski1
1Faculty of Chemistry, University of Warsaw, ul. L. Pasteura 1, 02-093 Warsaw, Poland.
We present a new method to reduce basis set errors in electron correlation energy calculations. This approach improves accuracy in computational chemistry, achieving high precision with smaller basis sets.
Area of Science:
- Computational Chemistry
- Quantum Chemistry
- Theoretical Chemistry
Background:
- Basis set incompleteness is a significant error source in electronic structure calculations.
- Accurate computation of electron correlation energy is crucial for predicting molecular properties.
Purpose of the Study:
- To develop a general and efficient method for reducing basis set incompleteness error in electron correlation energy calculations.
- To introduce a novel approach that computes corrections within a single calculation.
Main Methods:
- Modification of the electron interaction operator with an effective short-range interaction.
- Local mapping of the Coulomb operator to a long-range interaction using a range-separated parameter.
- Application with complete active space wave functions and linearized adiabatic connection (AC0) or n-electron valence state second-order perturbation theory (NEVPT2).
Main Results:
- The proposed method effectively reduces basis set incompleteness error.
- Calculations in a triple-ζ basis set achieved accuracy comparable to or exceeding uncorrected methods in a quintuple-ζ basis set.
- Encouraging results were obtained for the relative energies of test molecules.
Conclusions:
- The developed approach offers a computationally efficient way to improve the accuracy of electron correlation energy calculations.
- This method provides a viable alternative to traditional basis set extrapolation or augmentation techniques.
- The findings suggest a significant advancement in achieving high-accuracy electronic structure calculations with reduced computational cost.
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