mlsanityData to 13 Oct 2026

Efficient Tomography of Non-Interacting Fermion States

arXiv 2102.10458 ↗First posted 20 Feb 2021quant-ph cs.LGcited by 7

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Abstract (arXiv)

We give an efficient algorithm that learns a non-interacting fermion state, given copies of the state. For a system of n non-interacting fermions and m modes, we show that O(m3 n2 log(1/δ) / ε4) copies of the input state and O(m4 n2 log(1/δ)/ ε4) time are sufficient to learn the state to trace distance at most ε with probability at least 1 - δ. Our algorithm empirically estimates one-mode correlations in O(m) different measurement bases and uses them to reconstruct a succinct description of the entire state efficiently.

Key facts. Cited by 7 papers in the map (data through 13 Oct 2026). Builds on 2 of its 51 references that are in the map. First posted on arXiv 20 Feb 2021.

Builds on

2 of 51 references.

References · 2

  1. 2020Predicting Many Properties of a Quantum System from Very Few Measurementscited by 233
  2. 2016Efficient quantum tomography IIcited by 54

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Cited by year

Citing papers per year: 2023: 3; 2024: 1; 2025: 3.

7 papers.

  1. 2023A survey on the complexity of learning quantum statescited by 32
  2. 2025A Primer on Quantum Machine Learningcited by 9
  3. 2023Efficient Learning of Quantum States Prepared With Few Non-Clifford Gatescited by 7
  4. 2024Agnostic Tomography of Stabilizer Product Statescited by 4
  5. 2025Mildly-Interacting Fermionic Unitaries are Efficiently Learnablecited by 2
  6. 2025Efficient learning of bosonic Gaussian unitariescited by 1
  7. 2023Efficient Learning of Quantum States Prepared With Few Non-Clifford Gates II: Single-Copy Measurementscited by 0