Symmetries and Many-Body Excitations with Neural-Network Quantum States.

@article{Choo2018SymmetriesAM,
  title={Symmetries and Many-Body Excitations with Neural-Network Quantum States.},
  author={Kenny Choo and Giuseppe Carleo and Nicolas Regnault and Titus Neupert},
  journal={Physical review letters},
  year={2018},
  volume={121 16},
  pages={
          167204
        }
}
Artificial neural networks have been recently introduced as a general ansatz to represent many-body wave functions. In conjunction with variational Monte Carlo calculations, this ansatz has been applied to find Hamiltonian ground states and their energies. Here, we provide extensions of this method to study excited states, a central task in several many-body quantum calculations. First, we give a prescription that allows us to target eigenstates of a (nonlocal) symmetry of the Hamiltonian… 

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