27 research outputs found
Low-Scaling Algorithm for the Random Phase Approximation using Tensor Hypercontraction with k-point Sampling
We present a low-scaling algorithm for the random phase approximation (RPA)
with \textbf{k}-point sampling in the framework of tensor hypercontraction
(THC) for electron repulsion integrals (ERIs). The THC factorization is
obtained via a revised interpolative separable density fitting (ISDF) procedure
with a momentum-dependent auxiliary basis for generic single-particle Bloch
orbitals. Our formulation does not require pre-optimized interpolating points
nor auxiliary bases, and the accuracy is systematically controlled by the
number of interpolating points. The resulting RPA algorithm scales linearly
with the number of \textbf{k}-points and cubically with the system size without
any assumption on sparsity or locality of orbitals. The errors of ERIs and RPA
energy show rapid convergence with respect to the size of the THC auxiliary
basis, suggesting a promising and robust direction to construct efficient
algorithms of higher-order many-body perturbation theories for large-scale
systems.Comment: 35 pages, 6 figure
QMCPACK: Advances in the development, efficiency, and application of auxiliary field and real-space variational and diffusion Quantum Monte Carlo
We review recent advances in the capabilities of the open source ab initio
Quantum Monte Carlo (QMC) package QMCPACK and the workflow tool Nexus used for
greater efficiency and reproducibility. The auxiliary field QMC (AFQMC)
implementation has been greatly expanded to include k-point symmetries,
tensor-hypercontraction, and accelerated graphical processing unit (GPU)
support. These scaling and memory reductions greatly increase the number of
orbitals that can practically be included in AFQMC calculations, increasing
accuracy. Advances in real space methods include techniques for accurate
computation of band gaps and for systematically improving the nodal surface of
ground state wavefunctions. Results of these calculations can be used to
validate application of more approximate electronic structure methods including
GW and density functional based techniques. To provide an improved foundation
for these calculations we utilize a new set of correlation-consistent effective
core potentials (pseudopotentials) that are more accurate than previous sets;
these can also be applied in quantum-chemical and other many-body applications,
not only QMC. These advances increase the efficiency, accuracy, and range of
properties that can be studied in both molecules and materials with QMC and
QMCPACK