Progress towards a more efficient denisty matrix quantum Monte Carlo method

In this talk, we will present our work in modifying the density matrix quantum Monte Carlo (DMQMC) algorithm, which samples the density matrix for the electronic Hamiltonian across a range of temperatures. The DMQMC algorithm is modified to propagate the density matrix in a semi-stochastic (partly stochastic and partly deterministic) fashion. This work is based on and inspired by the semi-stochastic projector modification to full configuration interaction quantum Monte Carlo (FCIQMC). This work was motivated to provide high accuracy finite temperature electronic structure results with fewer required simulations, which we refer to as increasing the method's efficiency. We evaluated the accuracy of this modification through comparisons with finite temperature full configuration interaction (ft-FCI), as well as the original DMQMC and its interaction picture variant (IP-DMQMC). We investigated the impact the size of and selection scheme for the deterministic space has on the efficiency of the semi-stochastic DMQMC algorithm. We believe that this modification will allow for increases in the systems sizes with which we can treat with finite temperature.