Bayesian error regions in quantum estimation I: analytical reasonings

TL;DR

This paper derives analytical formulas for Bayesian error regions in quantum estimation, enabling efficient asymptotic error certification for high-dimensional parameters, validated through simulations in quantum state tomography.

Contribution

It provides the first analytical expressions for the size and credibility of quantum Bayesian error regions under general conditions, improving practical error certification.

Findings

Analytical formulas match numerical results in simulations

Formulas applicable to high-dimensional quantum parameter estimation

Enhanced efficiency in quantum error certification

Abstract

Results concerning the construction of quantum Bayesian error regions as a means to certify the quality of parameter point estimators have been reported in recent years. This task remains numerically formidable in practice for large dimensions and so far, no analytical expressions of the region size and credibility (probability of any given true parameter residing in the region) are known, which form the two principal region properties to be reported alongside a point estimator obtained from collected data. We first establish analytical formulas for the size and credibility that are valid for a uniform prior distribution over parameters, sufficiently large data samples and general constrained convex parameter-estimation settings. These formulas provide a means to an efficient asymptotic error certification for parameters of arbitrary dimensions. Next, we demonstrate the accuracies of these analytical formulas as compared to numerically computed region quantities with simulated examples in qubit and qutrit quantum-state tomography where computations of the latter are feasible.