Autoregressive neural-network wavefunctions for ab initio quantum chemistry. (arXiv:2109.12606v2 [physics.chem-ph] UPDATED)

In recent years, neural network quantum states (NNQS) have emerged as
powerful tools for the study of quantum many-body systems. Electronic structure
calculations are one such canonical many-body problem that have attracted
significant research efforts spanning multiple decades, whilst only recently
being attempted with NNQS. However, the complex non-local interactions and high
sample complexity are significant challenges that call for bespoke solutions.
Here, we parameterise the electronic wavefunction with a novel autoregressive
neural network (ARN) that permits highly efficient and …

ab arxiv chemistry network physics