Parameter estimation with limited access of measurements
Jianning Li, Dianzhen Cui, and X. X. Yi

TL;DR
This paper develops a theoretical framework for quantum parameter estimation when measurement access is limited, analyzing how non-optimal measurements affect precision and proposing optimization strategies to approach optimal bounds.
Contribution
It introduces a method to quantify and optimize measurement observables under limited access, enhancing estimation precision in quantum systems.
Findings
Shorter Euclidean distance to optimal observables improves estimation accuracy.
Optimizing accessible observables can approach the precision of fully accessible measurements.
The framework is demonstrated with examples involving a driven qubit and an NV-center system.
Abstract
Quantum parameter estimation holds the promise of quantum technologies, in which physical parameters can be measured with much greater precision than what is achieved with classical technologies. However, how to obtain a best precision when the optimal measurement is not accessible is still an open problem. In this work, we present a theoretical framework to explore the parameter estimation with limited access of measurements by analyzing the effect of non-optimal measurement on the estimation precision. We define a quantity to characterize the effect and illustrate how to optimize observables to attain a bound with limited accessibility of observables. On the other side, we introduce the minimum Euclidean distance to quantify the difference between an observable and the optimal ones in terms of Frobenius norm and find that the measurement with a shorter distance to the optimal ones…
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Taxonomy
TopicsControl Systems and Identification · Fault Detection and Control Systems · Structural Health Monitoring Techniques
