Stochastic multi-reference perturbation theory with application to linearized coupled cluster method

TL;DR

This paper introduces a stochastic approach to multireference perturbation theory that efficiently combines static and dynamic correlation treatments, demonstrated on benchmark molecules with promising accuracy.

Contribution

It presents a novel fully stochastic method for multireference perturbation theory that enables large active space calculations with improved accuracy.

Findings

Successfully applied to benchmark systems like the carbon dimer and aromatic molecules.

Accurately computed singlet-triplet gaps for benzene and m-xylylene.

Achieved good agreement with experimental data for challenging cases.

Abstract

In this article we report a stochastic evaluation of the recently proposed LCC multireference perturbation theory [Sharma S., and Alavi A., J. Chem. Phys. 143, 102815, (2015)]. In this method both the zeroth order and first order wavefunctions are sampled stochastically by propagating simultaneously two populations of signed walkers. The sampling of the zeroth order wavefunction follows a set of stochastic processes identical to the one used in the FCIQMC method. To sample the first order wavefunction, the usual FCIQMC algorithm is augmented with a source term that spawns walkers in the sampled first order wavefunction from the zeroth order wavefunction. The second order energy is also computed stochastically but requires no additional overhead outside of the added cost of sampling the first order wavefunction. This fully stochastic method opens up the possibility of simultaneously treating large active spaces to account for static correlation and recovering the dynamical correlation using perturbation theory. This method is used to study a few benchmark systems including the carbon dimer and aromatic molecules. We have computed the singlet-triplet gaps of benzene and m-xylylene. For m-xylylene, which has proved difficult for standard CASSCF+PT, we find the singlet-triplet gap to be in good agreement with the experimental values.