Neural-network quantum states for solving few-body problems: application to Efimov physics
This paper extends neural-network quantum states to solve strongly interacting few-body problems in continuous space, successfully computing Efimov states and reproducing their key physical features for systems ranging from three to six identical bosons and mass-imbalanced fermions.