Learning quantum graph states with product measurements

@article{Ouyang2022LearningQG,
  title={Learning quantum graph states with product measurements},
  author={Yingkai Ouyang and Marco Tomamichel},
  journal={2022 IEEE International Symposium on Information Theory (ISIT)},
  year={2022},
  pages={2963-2968}
}
We consider the problem of learning N identical copies of an unknown n-qubit quantum graph state with product measurements. These graph states have corresponding graphs where every vertex has exactly d neighboring vertices. Here, we detail an explicit algorithm that uses product measurements on multiple identical copies of such graph states to learn them. When n ≫ d and N = O(d log(1/ϵ) + d2 log n), this algorithm correctly learns the graph state with probability at least 1 – ϵ. From channel… 

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