mlsanityData to 7 Oct 2026

Tight Bounds for Quantum State Certification with Incoherent Measurements

arXiv 2204.07155 ↗First posted 14 Apr 2022quant-ph cs.CC cs.ITcited by 11

Not on the map. Why?

Abstract (arXiv)

We consider the problem of quantum state certification, where we are given the description of a mixed state σ ∈ mathbbCd × d, n copies of a mixed state ρ ∈ mathbbCd × d, and varepsilon > 0, and we are asked to determine whether ρ = σ or whether | ρ - σ |1 > varepsilon. When σ is the maximally mixed state frac1d Id, this is known as mixedness testing. We focus on algorithms which use incoherent measurements, i.e. which only measure one copy of ρ at a time. Unlike those that use entangled, multi-copy measurements, these can be implemented without persistent quantum memory and thus represent a large class of protocols that can be run on current or near-term devices. For mixedness testing, there is a folklore algorithm which uses incoherent measurements and only needs O(d3/2 / varepsilon2) copies. The algorithm is non-adaptive, that is, its measurements are fixed ahead of time, and is known to be optimal for non-adaptive algorithms. However, when the algorithm can make arbitrary incoherent measurements, the best known lower bound is only Omega (d4/3 / varepsilon2) [Bubeck-Chen-Li '20], and it has been an outstanding open problem to close this polynomial gap. In this work, 1) we settle the copy complexity of mixedness testing with incoherent measurements and show that Omega (d3/2 / varepsilon2) copies are necessary, and 2) we show the instance-optimal bounds for state certification to general σ first derived by [Chen-Li-O'Donnell '21] for non-adaptive measurements also hold for arbitrary incoherent measurements. Qualitatively, our results say that adaptivity does not help at all for these problems. Our results are based on new techniques that allow us to reduce the problem to understanding certain matrix martingales, which we believe may be of independent interest.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 8 of its 39 references that are in the map. First posted on arXiv 14 Apr 2022.

Builds on

8 of 39 references.

References · 8

  1. 2020Predicting Many Properties of a Quantum System from Very Few Measurementscited by 229
  2. 2021Quantum advantage in learning from experimentscited by 186
  3. 2021Information-theoretic bounds on quantum advantage in machine learningcited by 95
  4. 2021Exponential separations between learning with and without quantum memorycited by 50
  5. 2020Entanglement is Necessary for Optimal Quantum Property Testingcited by 22
  6. 2021A Hierarchy for Replica Quantum Advantagecited by 16
  7. 2017Quantum state certificationcited by 13
  8. 2021Toward Instance-Optimal State Certification With Incoherent Measurementscited by 12

Built on by

Cited by year

Citing papers per year: 2022: 3; 2023: 0; 2024: 4; 2025: 4.

11 papers.