Toward Instance-Optimal State Certification With Incoherent Measurements
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Abstract (arXiv)
We revisit the basic problem of quantum state certification: given copies of unknown mixed state ρ∈mathbbCd× d and the description of a mixed state σ, decide whether σ = ρ or |σ - ρ|_mathsftr ≥ ε. When σ is maximally mixed, this is mixedness testing, and it is known that Omega(dTheta(1)/ε2) copies are necessary, where the exact exponent depends on the type of measurements the learner can make [OW15, BCL20], and in many of these settings there is a matching upper bound [OW15, BOW19, BCL20]. Can one avoid this dTheta(1) dependence for certain kinds of mixed states σ, e.g. ones which are approximately low rank? More ambitiously, does there exist a simple functional f:mathbbCd× d→ℝ≥ 0 for which one can show that Theta(f(σ)/ε2) copies are necessary and sufficient for state certification with respect to any σ? Such instance-optimal bounds are known in the context of classical distribution testing, e.g. [VV17]. Here we give the first bounds of this nature for the quantum setting, showing (up to log factors) that the copy complexity for state certification using nonadaptive incoherent measurements is essentially given by the copy complexity for mixedness testing times the fidelity between σ and the maximally mixed state. Surprisingly, our bound differs substantially from instance optimal bounds for the classical problem, demonstrating a qualitative difference between the two settings.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 4 of its 53 references that are in the map. First posted on arXiv 25 Feb 2021.
Builds on
4 of 53 references.
References · 4
- 2021Information-theoretic bounds on quantum advantage in machine learningcited by 95
- 2016Efficient quantum tomography IIcited by 54
- 2020Entanglement is Necessary for Optimal Quantum Property Testingcited by 22
- 2017Quantum state certificationcited by 13
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Citing papers per year: 2021: 2; 2022: 2; 2023: 0; 2024: 4; 2025: 4.
12 papers.
- 2021Exponential separations between learning with and without quantum memorycited by 50
- 2021A Hierarchy for Replica Quantum Advantagecited by 16
- 2022When Does Adaptivity Help for Quantum State Learning?cited by 12
- 2022Tight Bounds for Quantum State Certification with Incoherent Measurementscited by 11
- 2024Certifying almost all quantum states with few single-qubit measurementscited by 7
- 2024On the sample complexity of purity and inner product estimationcited by 4
- 2024An optimal tradeoff between entanglement and copy complexity for state tomographycited by 2
- 2025Instance-Optimal Quantum State Certification with Entangled Measurementscited by 1
- 2024Adaptivity can help exponentially for shadow tomographycited by 0
- 2025Purest Quantum State Identificationcited by 0
- 2025Efficient learning of bosonic Gaussian unitariescited by 0
- 2025Non-iid hypothesis testing: from classical to quantumcited by 0
- 2025Non-iid hypothesis testing: from classical to quantum7 Oct 2025
- 2025Efficient learning of bosonic Gaussian unitaries7 Oct 2025
- 2025Instance-Optimal Quantum State Certification with Entangled Measurements8 Jul 2025
- 2025Purest Quantum State Identification20 Feb 2025
- 2024Adaptivity can help exponentially for shadow tomography26 Dec 2024
- 2024On the sample complexity of purity and inner product estimation16 Oct 2024
- 2024Certifying almost all quantum states with few single-qubit measurements10 Apr 2024
- 2024An optimal tradeoff between entanglement and copy complexity for state tomography26 Feb 2024
- 2022When Does Adaptivity Help for Quantum State Learning?10 Jun 2022
- 2022Tight Bounds for Quantum State Certification with Incoherent Measurements14 Apr 2022
- 2021Exponential separations between learning with and without quantum memory10 Nov 2021
- 2021A Hierarchy for Replica Quantum Advantage10 Nov 2021