Coherent transport of quantum states by deep reinforcement learning

@article{Porotti2019CoherentTO,
  title={Coherent transport of quantum states by deep reinforcement learning},
  author={Riccardo Porotti and Dario Tamascelli and Marcello Restelli and Enrico Prati},
  journal={Communications Physics},
  year={2019},
  volume={2},
  pages={1-9}
}
Some problems in physics can be handled only after a suitable ansatz solution has been guessed, proving to be resilient to generalization. The coherent transport of a quantum state by adiabatic passage through an array of semiconductor quantum dots is an excellent example of such a problem, where it is necessary to introduce a so-called counterintuitive control sequence. Instead, the deep reinforcement learning (DRL) technique has proven to be able to solve very complex sequential decision… 

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