Enhancing Neural-Network Variational Monte Carlo

Enhancing Neural-Network Variational Monte Carlo through Basis Transformation

arXiv:2604.15888v2 Announce Type: replace-cross Abstract: Neural-network variational Monte Carlo (NNVMC) has emerged as a powerful tool for solving quantum many-body problems, yet systematic pathways for improving its accuracy remain largely heuristic. Here, we introduce a physically motivated basis transformation for NNVMC that enhances variational expressivity without increasing the complexity of the neural-network ansatz itself. By formulating the many-body wave function in a Gaussian...