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This paper establishes the first limit distribution theory for quantum relative entropy estimators, characterizing asymptotic fluctuations via Fréchet derivatives of operator-valued functions. By proving that estimators based on Pauli tomography converge to a centered normal distribution, the work provides rigorous variance bounds essential for multi-hypothesis testing in quantum information protocols. These theoretical advances directly enhance the statistical reliability and error analysis capabilities required for scalable quantum computing applications.
Limit Distribution Theory for Quantum Divergences
arXiv:2311.13694v4 Announce Type: replace Abstract: Estimation of quantum relative entropy and its R\'{e}nyi generalizations is a fundamental statistical task in quantum information theory, physics, and beyond. While several estimators of these divergences have been proposed in the literature along with their computational complexities explored, a limit distribution theory which characterizes the asymptotic fluctuations of the estimation error is still premature. As our main contribution, we characterize these asymptotic distributions in terms of Fr\'{e}chet derivatives of elementary operator-valued functions. We achieve this by leveraging an operator version of Taylor's theorem and identifying the regularity conditions needed. As an application of our results, we consider an estimator of quantum relative entropy based on Pauli tomography of quantum states and show that the resulting asymptotic distribution is a centered normal, with its variance characterized in terms of the Pauli operators and states. We utilize the knowledge of the aforementioned limit distribution to obtain asymptotic performance guarantees for a multi-hypothesis testing problem.
Abstract:Estimation of quantum relative entropy and its Rényi generalizations is a fundamental statistical task in quantum information theory, physics, and beyond. While several estimators of these divergences have been proposed in the literature along with their computational complexities explored, a limit distribution theory which characterizes the asymptotic fluctuations of the estimation error is still premature. As our main contribution, we characterize these asymptotic distributions in terms of Fréchet derivatives of elementary operator-valued functions. We achieve this by leveraging an operator version of Taylor's theorem and identifying the regularity conditions needed. As an application of our results, we consider an estimator of quantum relative entropy based on Pauli tomography of quantum states and show that the resulting asymptotic distribution is a centered normal, with its variance characterized in terms of the Pauli operators and states. We utilize the knowledge of the aforementioned limit distribution to obtain asymptotic performance guarantees for a multi-hypothesis testing problem.
Quantum Physics (quant-ph); Information Theory (cs.IT); Statistics Theory (math.ST)
arXiv:2311.13694 [quant-ph]
(or arXiv:2311.13694v4 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2311.13694 Focus to learn more arXiv-issued DOI via DataCite
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Full text under the publisher's open licence · 251 words
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