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This research establishes the quantum U-statistic as the unique unbiased estimator for polynomial functionals of quantum states, achieving asymptotic efficiency at the multiparameter Cramér-Rao limit. By deriving a universal variance expansion, the study clarifies the scaling behavior of estimation errors and identifies conditions for bounded-variance estimation in specific divergences like Bures $\chi^2$. These theoretical advances provide foundational bounds for optimizing quantum state tomography and parameter inference protocols.
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Uniqueness and Cram\'er-Rao Efficiency of Quantum U-Statistics

arXiv2 min read

arXiv:2609.08745v1 Announce Type: new Abstract: We study unbiased estimation of scalar-valued polynomial functionals of quantum states from independent copies. We establish an equivalence between the first-order marginal of a permutation-invariant finite-copy observable and the functional gradient. We then prove that, among unbiased permutation-invariant estimators, the quantum U-statistic is the unique extension to an arbitrary number of copies. We further derive a universal variance expansion in which the leading $1/n$ term is determined by the variance of the functional gradient, while higher-order contributions are of order $O(1/n^2)$. This leading variance coincides with the multiparameter quantum Cram\'er-Rao limit, establishing asymptotic efficiency of quantum U-statistics. We also characterize the higher-order scaling at points where the variance of the first-order gradient vanishes. As an application, we analyze the Bures $\chi^2$-divergence and show that a spectral lower bound on the reference state is sufficient but not necessary for bounded-variance estimation.

Abstract:We study unbiased estimation of scalar-valued polynomial functionals of quantum states from independent copies. We establish an equivalence between the first-order marginal of a permutation-invariant finite-copy observable and the functional gradient. We then prove that, among unbiased permutation-invariant estimators, the quantum U-statistic is the unique extension to an arbitrary number of copies. We further derive a universal variance expansion in which the leading $1/n$ term is determined by the variance of the functional gradient, while higher-order contributions are of order $O(1/n^2)$. This leading variance coincides with the multiparameter quantum Cramér-Rao limit, establishing asymptotic efficiency of quantum U-statistics. We also characterize the higher-order scaling at points where the variance of the first-order gradient vanishes. As an application, we analyze the Bures $\chi^2$-divergence and show that a spectral lower bound on the reference state is sufficient but not necessary for bounded-variance estimation.

Quantum Physics (quant-ph); Statistics Theory (math.ST)

arXiv:2609.08745 [quant-ph]

(or arXiv:2609.08745v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2609.08745 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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Full text under the publisher's open licence · 237 words

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