Solving the quantum many-body problem with artificial neural networks

@article{Carleo2017SolvingTQ,
  title={Solving the quantum many-body problem with artificial neural networks},
  author={Giuseppe Carleo and Matthias Troyer},
  journal={Science},
  year={2017},
  volume={355},
  pages={602 - 606}
}
Machine learning and quantum physics Elucidating the behavior of quantum interacting systems of many particles remains one of the biggest challenges in physics. Traditional numerical methods often work well, but some of the most interesting problems leave them stumped. Carleo and Troyer harnessed the power of machine learning to develop a variational approach to the quantum many-body problem (see the Perspective by Hush). The method performed at least as well as state-of-the-art approaches… 

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