Entanglement is Necessary for Optimal Quantum Property Testing
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Abstract (arXiv)
There has been a surge of progress in recent years in developing algorithms for testing and learning quantum states that achieve optimal copy complexity. Unfortunately, they require the use of entangled measurements across many copies of the underlying state and thus remain outside the realm of what is currently experimentally feasible. A natural question is whether one can match the copy complexity of such algorithms using only independent---but possibly adaptively chosen---measurements on individual copies. We answer this in the negative for arguably the most basic quantum testing problem: deciding whether a given d-dimensional quantum state is equal to or ε-far in trace distance from the maximally mixed state. While it is known how to achieve optimal O(d/ε2) copy complexity using entangled measurements, we show that with independent measurements, Omega(d4/3/ε2) is necessary, even if the measurements are chosen adaptively. This resolves a question of Wright. To obtain this lower bound, we develop several new techniques, including a chain-rule style proof of Paninski's lower bound for classical uniformity testing, which may be of independent interest.
Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Apr 2020.
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Citing papers per year: 2021: 5; 2022: 4; 2023: 4; 2024: 4; 2025: 5.
22 papers.
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- 2021Quantum advantage in learning from experimentscited by 186
- 2021Information-theoretic bounds on quantum advantage in machine learningcited by 95
- 2021Exponential separations between learning with and without quantum memorycited by 50
- 2021A Hierarchy for Replica Quantum Advantagecited by 16
- 2022The Complexity of NISQcited by 13
- 2021Toward Instance-Optimal State Certification With Incoherent Measurementscited by 12
- 2022When Does Adaptivity Help for Quantum State Learning?cited by 12
- 2022Tight Bounds for Quantum State Certification with Incoherent Measurementscited by 11
- 2023Tight bounds on Pauli channel learning without entanglementcited by 7
- 2022Lower Bounds for Learning Quantum States with Single-Copy Measurementscited by 6
- 2023On the Role of Entanglement and Statistics in Learningcited by 5
- 2023Transition Role of Entangled Data in Quantum Machine Learningcited by 5
10 more
- 2024On the sample complexity of purity and inner product estimationcited by 4
- 2023Spacetime-Efficient Low-Depth Quantum State Preparation with Applicationscited by 2
- 2024An optimal tradeoff between entanglement and copy complexity for state tomographycited by 2
- 2025Instance-Optimal Quantum State Certification with Entangled Measurementscited by 1
- 2024New Bounds on Quantum Sample Complexity of Measurement Classescited by 0
- 2024Adaptivity can help exponentially for shadow tomographycited by 0
- 2025Purest Quantum State Identificationcited by 0
- 2025Sample-optimal learning of quantum states using gentle measurementscited 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
- 2025Sample-optimal learning of quantum states using gentle measurements30 May 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
- 2024New Bounds on Quantum Sample Complexity of Measurement Classes22 Aug 2024
- 2024An optimal tradeoff between entanglement and copy complexity for state tomography26 Feb 2024
- 2023Tight bounds on Pauli channel learning without entanglement23 Sep 2023
- 2023Transition Role of Entangled Data in Quantum Machine Learning6 Jun 2023
- 2023On the Role of Entanglement and Statistics in Learning5 Jun 2023
10 more
- 2023Spacetime-Efficient Low-Depth Quantum State Preparation with Applications3 Mar 2023
- 2022The Complexity of NISQ13 Oct 2022
- 2022Lower Bounds for Learning Quantum States with Single-Copy Measurements29 Jul 2022
- 2022When Does Adaptivity Help for Quantum State Learning?10 Jun 2022
- 2022Tight Bounds for Quantum State Certification with Incoherent Measurements14 Apr 2022
- 2021Quantum advantage in learning from experiments1 Dec 2021
- 2021Exponential separations between learning with and without quantum memory10 Nov 2021
- 2021A Hierarchy for Replica Quantum Advantage10 Nov 2021
- 2021Toward Instance-Optimal State Certification With Incoherent Measurements25 Feb 2021
- 2021Information-theoretic bounds on quantum advantage in machine learning7 Jan 2021
- 2021Quantum advantage in learning from experimentscited by 186
- 2021Information-theoretic bounds on quantum advantage in machine learningcited by 95
- 2021Exponential separations between learning with and without quantum memorycited by 50
- 2021A Hierarchy for Replica Quantum Advantagecited by 16
- 2022The Complexity of NISQcited by 13
- 2021Toward Instance-Optimal State Certification With Incoherent Measurementscited by 12
- 2022When Does Adaptivity Help for Quantum State Learning?cited by 12
- 2022Tight Bounds for Quantum State Certification with Incoherent Measurementscited by 11
- 2023Tight bounds on Pauli channel learning without entanglementcited by 7
- 2022Lower Bounds for Learning Quantum States with Single-Copy Measurementscited by 6
- 2023On the Role of Entanglement and Statistics in Learningcited by 5
- 2023Transition Role of Entangled Data in Quantum Machine Learningcited by 5
12 most cited of 22 All 22 (JSON)
- 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
- 2025Sample-optimal learning of quantum states using gentle measurements30 May 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
- 2024New Bounds on Quantum Sample Complexity of Measurement Classes22 Aug 2024
- 2024An optimal tradeoff between entanglement and copy complexity for state tomography26 Feb 2024
- 2023Tight bounds on Pauli channel learning without entanglement23 Sep 2023
- 2023Transition Role of Entangled Data in Quantum Machine Learning6 Jun 2023
- 2023On the Role of Entanglement and Statistics in Learning5 Jun 2023
12 newest of 22 All 22 (JSON)