Continuous-variable neural-network quantum states and the quantum rotor model

Understand

We initiate the study of neural-network quantum state algorithms for analyzing continuous-variable lattice quantum systems in first quantization.

• A simple family of continuous-variable trial wavefunctons is introduced which naturally generalizes the restricted Boltzmann machine (RBM) wavefunction introduced for analyzing quantum spin systems.
• By virtue of its simplicity, the same variational Monte Carlo training algorithms that have been developed for ground state determination and time evolution of spin systems have natural analogues in the continuum.
• We offer a proof of principle demonstration in the context of ground state determination of a stoquastic quantum rotor Hamiltonian.