HubbardNet: Efficient Predictions of the Bose-Hubbard Model Spectrum with Deep Neural Networks

Ziyan Zhu, Marios Mattheakis, Weiwei Pan +1

We present a deep neural network (DNN)-based model (HubbardNet) to variationally find the ground state and excited state wavefunctions of the one-dimensional and two-dimensional Bo…