A strategy for quantum algorithm design assisted by machine learning

@article{Bang2014ASF,
  title={A strategy for quantum algorithm design assisted by machine learning},
  author={Jeongho Bang and Junghee Ryu and Seokwon Yoo and M. Pawlowski and Jinhyoung Lee},
  journal={New Journal of Physics},
  year={2014},
  volume={16},
  pages={073017}
}
We propose a method for quantum algorithm design assisted by machine learning. The method uses a quantum–classical hybrid simulator, where a 'quantum student' is being taught by a 'classical teacher'. In other words, in our method, the learning system is supposed to evolve into a quantum algorithm for a given problem, assisted by a classical main-feedback system. Our method is applicable for designing quantum oracle-based algorithms. We chose, as a case study, an oracle decision problem, called… Expand

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References

SHOWING 1-10 OF 46 REFERENCES
Quantum algorithm design using dynamic learning
Quantum Learning Machine
Machine learning for precise quantum measurement.
Quantum learning speedup in binary classification
...
1
2
3
4
5
...