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Compact and flexible basis functions for quantum Monte Carlo calculations.
F R Petruzielo1, Julien Toulouse, C J Umrigar
1Laboratory of Atomic and Solid State Physics, Cornell University, Ithaca, New York 14853, USA. frp3@cornell.edu
The Journal of Chemical Physics
|March 10, 2010
Summary
Reoptimizing Gaussian basis set exponents in quantum Monte Carlo (QMC) calculations creates more compact sets for higher accuracy. New Gauss-Slater functions further enhance energy and local energy fluctuations, enabling larger molecule simulations.
Area of Science:
- Computational Quantum Chemistry
- Quantum Monte Carlo Methods
Background:
- Quantum Monte Carlo (QMC) calculations commonly use mixed Gaussian basis sets.
- Existing literature provides standard basis sets of varying accuracy.
- Optimizing primitive Gaussian function exponents within QMC is underexplored.
Purpose of the Study:
- To demonstrate that reoptimizing primitive Gaussian function exponents in QMC yields more compact basis sets.
- To introduce and evaluate novel Gauss-Slater basis functions for QMC.
- To improve the efficiency and accuracy of QMC calculations for molecular systems.
Main Methods:
- Reoptimization of primitive Gaussian function exponents within the QMC framework.
- Development and implementation of Gauss-Slater basis functions.
- Application of optimized and novel basis sets to calculate ground and excited states of carbon, carbon dimer, and naphthalene.
Main Results:
- Exponent reoptimization led to more compact basis sets for a given accuracy, especially for excited states.
- Gauss-Slater basis functions improved energy and reduced local energy fluctuations.
- Basis set size reduction was achieved for systems like carbon, its dimer, and naphthalene.
Conclusions:
- Optimized Gaussian exponents and Gauss-Slater basis functions significantly enhance QMC efficiency and accuracy.
- These advancements enable the accurate, high-accuracy QMC treatment of larger molecular systems.
- Basis set optimization is a crucial step for advancing QMC applications in computational chemistry.
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