Balancing accuracy and efficiency in selecting vibrational configuration interaction basis states using vibrational perturbation theory

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This work describes the benchmarking of a vibrational configuration interaction (VCI) algorithm that combines the favourable computational scaling of VPT2 with the algorithmic robustness of VCI, in which VCI basis states are selected according to the magnitude of their contribution to the VPT2 energy, for the ground state and fundamental excited states. Particularly novel aspects of this work include: expanding the potential to 6th order in normal mode coordinates, using a double-iterative procedure in which configuration selection and VCI wavefunction updates are performed iteratively (micro-iterations) over a range of screening threshold values (macro-iterations), and characterisation of computational resource requirements as a function of molecular size. Computational costs may be further reduced by a priori truncation of the VCI wavefunction according to maximum extent of mode coupling, along with discarding negligible force constants and VCI matrix elements, and formulating the wavefunction in a harmonic oscillator product basis to enable efficient evaluation of VCI matrix elements. Combining these strategies, we define a series of screening procedures that scale as O(Nmode6)−O(Nmode9) in run time and O(Nmode6)−O(Nmode7) in memory, depending on the desired level of accuracy. Our open-source code is freely available for download from http://www.sourceforge.net/projects/pyvci-vpt2.