• Corpus ID: 250334828

Optimal quantum control via genetic algorithms for quantum state engineering

@inproceedings{Brown2022OptimalQC,
  title={Optimal quantum control via genetic algorithms for quantum state engineering},
  author={Jonathon Brown and Mauro Paternostro and Alessandro Ferraro},
  year={2022}
}
We employ a machine learning-enabled approach to quantum state engineering based on evolutionary algorithms. In particular, we focus on superconducting platforms and consider a network of qubits – encoded in the states of artificial atoms with no direct coupling – interacting via a common single-mode driven microwave resonator. The qubit-resonator couplings are assumed to be in the resonant regime and tunable in time. A genetic algorithm is used in order to find the functional time-dependence… 

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