Low-Scaling GW with Benchmark Accuracy and Application to Phosphorene Nanosheets

GW is an accurate method for computing electron addition and removal energies of molecules and solids. In a conventional GW implementation, however, its computational cost is O(N-4) in the system size N, which prohibits its application to many systems of interest. We present a low-scaling GW algorithm with notably improved accuracy compared to our previous algorithm [J. Phys. Chem. Lett. 2018, 9, 306-312]. This is demonstrated for frontier orbitals using the GW100 benchmark set, for which our algorithm yields a mean absolute deviation of only 6 meV with respect to canonical implementations. We show that also excitations of deep valence, semicore, and unbound states match conventional schemes within 0.1 eV. The high accuracy is achieved by using minimax grids with 30 grid points and the resolution of the identity with the truncated Coulomb metric. We apply the low-scaling GW algorithm with improved accuracy to phosphorene nanosheets of increasing size. We find that their fundamental gap is strongly size-dependent varying from 4.0 eV (1.8 nm x 1.3 nm, 88 atoms) to 2.4 eV (6.9 nm x 4.8 nm, 990 atoms) at the evGW(0)@PBE level.

Automated summary

GW is an accurate method for computing electron addition and removal energies, but its conventional implementation has high computational cost, limiting its application to many systems. A low-scaling GW algorithm with improved accuracy was presented, demonstrating strong size-dependent variation in the fundamental gap of phosphorene nanosheets when applied.