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Calculations of potential energy surfaces using Monte Carlo configuration interaction
Jeremy P Coe1, Daniel J Taylor, Martin J Paterson
1Institute of Chemical Sciences, School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh EH14 4AS, United Kingdom.
The Journal of Chemical Physics
|November 28, 2012
Summary
Monte Carlo Configuration Interaction (MCCI) accurately calculates molecular potential energy curves using a fraction of computational resources. This method offers improved accuracy over single-point energies for many molecular systems.
Area of Science:
- Computational Chemistry
- Quantum Chemistry
- Materials Science
Background:
- Accurate calculation of ground-state potential energy curves is crucial for understanding molecular behavior.
- Full Configuration Interaction (FCI) provides exact solutions but is computationally intractable for larger systems.
Purpose of the Study:
- To assess the accuracy of the Monte Carlo Configuration Interaction (MCCI) method for calculating potential energy curves.
- To evaluate MCCI's efficiency in terms of computational cost compared to FCI.
- To test MCCI on systems with basis sets exceeding FCI capabilities.
Main Methods:
- Application of the Monte Carlo Configuration Interaction (MCCI) method.
- Calculation of ground-state potential energy curves for small molecules.
- Comparison of MCCI results with Full Configuration Interaction (FCI) benchmarks.
- Quantification of accuracy using the non-parallelity error.
Main Results:
- MCCI accurately predicts potential energy curves using a small fraction of the FCI space.
- MCCI-derived potential curves often exhibit higher accuracy than individual single-point energies.
- MCCI results for ethylene align well with existing computational data.
- For a 50-hydrogen atom lattice, MCCI accuracy was limited by the considered fraction of the FCI space.
Conclusions:
- MCCI is a computationally efficient and accurate method for determining potential energy curves of molecules.
- The accuracy of MCCI is dependent on the fraction of the FCI space that can be explored.
- MCCI shows promise for larger systems where FCI is not feasible, with potential for further method development.
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