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A survey on the complexity of learning quantum states

Quantum Physics 2023-06-01 v1 Computational Complexity Machine Learning

Abstract

We survey various recent results that rigorously study the complexity of learning quantum states. These include progress on quantum tomography, learning physical quantum states, alternate learning models to tomography and learning classical functions encoded as quantum states. We highlight how these results are paving the way for a highly successful theory with a range of exciting open questions. To this end, we distill 25 open questions from these results.

Keywords

Cite

@article{arxiv.2305.20069,
  title  = {A survey on the complexity of learning quantum states},
  author = {Anurag Anshu and Srinivasan Arunachalam},
  journal= {arXiv preprint arXiv:2305.20069},
  year   = {2023}
}

Comments

Invited article by Nature Review Physics. 39 pages, 6 figures

R2 v1 2026-06-28T10:52:20.359Z