Pytorch Neural Quantum States

An implementation of ground-state variational search for input Hamiltonians using Neural Quantum States (NQS) ansatz with the Pytorch library. The primary class and method definitions are in NQS_Pytorch.py. A Hamiltonian can be input and run in Test_optimization_routine.py. Please note that this library is still a work in progress, it may throw unexpected errors and is not fully optimized. Future work in this library is on hold at the moment and a large update to the library will be made shortly now that complex backpropagation is supported in Pytorch.