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This research advances the theoretical understanding of classical shadows by establishing finite-sample bounds for their covariance spectra, which is critical for accurately estimating observables in quantum systems without scaling errors. The study demonstrates that dimension-independent estimation relies heavily on specific measurement protocols like local Pauli shadows rather than general theory alone, offering precise formulas for biased local cases.
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Finite-Sample Selected Covariance Spectra in Classical Shadows

arXiv2 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2606.00527v2 Announce Type: replace Abstract: Classical shadows use a single measurement snapshot to estimate many observables. These estimates are jointly distributed, and their covariance is not determined by their expectation values or individual variances. It also differs from physical correlations between observables because it depends on the measurement and reconstruction protocol. We study the covariance matrix for a fixed set of shadow estimates and its spectrum. For general shadow protocols, we give a finite-sample operator-norm bound for the empirical covariance computed using the sample mean. This bound also controls the eigenvalues and isolated spectral subspaces of the covariance matrix. For local product shadow protocols with fixed local dimension, observables supported on a bounded number of sites lead to bounds that do not depend on the total system size, provided that the number of selected observables and the relevant local reconstruction factors remain bounded. For biased local Pauli shadows, we obtain explicit finite-sample bounds and an exact covariance formula determined by Pauli compatibility and local basis probabilities. A comparison with global Clifford shadows shows that dimension-independent covariance estimation depends on the measurement protocol and does not follow from the general theory alone.

Abstract:Classical shadows use a single measurement snapshot to estimate many observables. These estimates are jointly distributed, and their covariance is not determined by their expectation values or individual variances. It also differs from physical correlations between observables because it depends on the measurement and reconstruction protocol. We study the covariance matrix for a fixed set of shadow estimates and its spectrum. For general shadow protocols, we give a finite-sample operator-norm bound for the empirical covariance computed using the sample mean. This bound also controls the eigenvalues and isolated spectral subspaces of the covariance matrix. For local product shadow protocols with fixed local dimension, observables supported on a bounded number of sites lead to bounds that do not depend on the total system size, provided that the number of selected observables and the relevant local reconstruction factors remain bounded. For biased local Pauli shadows, we obtain explicit finite-sample bounds and an exact covariance formula determined by Pauli compatibility and local basis probabilities. A comparison with global Clifford shadows shows that dimension-independent covariance estimation depends on the measurement protocol and does not follow from the general theory alone.

The title and the presentation were improved. The technical contents were not changed

arXiv:2606.00527 [quant-ph]

(or arXiv:2606.00527v2 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2606.00527 Focus to learn more arXiv-issued DOI via DataCite

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