Deep reinforcement learning for efficient measurement of quantum devices

@article{Nguyen2021DeepRL,
  title={Deep reinforcement learning for efficient measurement of quantum devices},
  author={Vu Nguyen and S. B. Orbell and Dominic T. Lennon and H. Moon and Florian Vigneau and Leon C. Camenzind and L. Yu and Dominik M. Zumb{\"u}hl and G. Andrew D. Briggs and Michael A. Osborne and D. Sejdinovic and Natalia Ares},
  journal={npj Quantum Information},
  year={2021},
  volume={7},
  pages={1-9}
}
Deep reinforcement learning is an emerging machine-learning approach that can teach a computer to learn from their actions and rewards similar to the way humans learn from experience. It offers many advantages in automating decision processes to navigate large parameter spaces. This paper proposes an approach to the efficient measurement of quantum devices based on deep reinforcement learning. We focus on double quantum dot devices, demonstrating the fully automatic identification of specific… 
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