Zhiyang He, Anand Natarajan, et al.
APS March Meeting 2023
The variational simulation of electronic systems requires the parametrization of the wave function amplitudes on a given single-particle basis. Working in first (second) quantization, the parametrized wave function amplitudes must be anti-symmetric (symmetric) functions of the particle configurations, while being able to capture correlations beyond single-particle Slater determinants. To date, multiple candidates have been proposed in the space of neural-network (NN) parametrizations. While much progress has been made in the design of NN-based parametrizations, there are still open questions regarding their accuracy to describe the ground-state properties of ab-initio Hamiltonians.
In this talk I will discuss our recent work on the understanding of the choice of trial state defined by anti-symmetrix (symmetric) NN-wave function ansatzs for the study, in first (second) quantization, of molecular Hamiltonians projected onto a discrete basis. I will also discuss the challenges in optimazing certain families of NN-trial states and different approaches to improve the optimization behavior.
Zhiyang He, Anand Natarajan, et al.
APS March Meeting 2023
Pauline J. Ollitrault, Abhinav Kandala, et al.
PRResearch
Nathaniel Park
APS March Meeting 2023
Daniel Worledge
APS March Meeting 2023