Accelerating the Convergence of Auxiliary-Field Quantum Monte Carlo inSolids with Optimized Gaussian Basis Sets

TL;DR

This paper develops optimized Gaussian basis sets for AFQMC in solids, significantly improving convergence speed and accuracy, and demonstrates their effectiveness on various insulating materials with results aligning well with experimental data.

Contribution

The authors introduce a novel basis set optimization method that accelerates AFQMC convergence in solids and reduces computational costs compared to existing approaches.

Findings

Optimized basis sets improve AFQMC energy convergence in solids.

The method reduces basis set size requirements for accurate results.

Results show excellent agreement with experimental data for studied systems.

Abstract

We investigate the use of optimized correlation consistent gaussian basis sets for the study of insulating solids with auxiliary-field quantum Monte Carlo (AFQMC). The exponents of the basis set are optimized through the minimization of the second order M{\o}ller--Plesset perturbation theory (MP2) energy in a small unit cell of the solid. We compare against other alternative basis sets proposed in the literature, namely calculations in the Kohn--Sham basis and in the natural orbitals of an MP2 calculation. We find that our optimized basis sets accelerate the convergence of the AFQMC correlation energy compared to a Kohn--Sham basis, and offer similar convergence to MP2 natural orbitals at a fraction of the cost needed to generate them. We also suggest the use of an improved, method independent, MP2-based basis set correction that significantly reduces the required basis set sizes needed to converge the correlation energy. With these developments, we study the relative performance of these basis sets in LiH, Si and MgO, and determine that our optimized basis sets yield the most consistent results as a function of volume. Using these optimized basis sets, we systematically converge the AFQMC calculations to the complete basis set and thermodynamic limit and find excellent agreement with experiment for systems studied. Although we focus on AFQMC, our basis set generation procedure is independent of the subsequent correlated wavefunction method used.