Flexible resources for quantum metrology

TL;DR

This paper introduces a method using 2D cluster states as flexible resources in quantum metrology, enabling efficient state preparation and measurement with preserved quantum advantage across various sensing tasks.

Contribution

It demonstrates that 2D cluster states can serve as versatile, resource-efficient tools for quantum sensing, maintaining quantum scaling advantages with minimal overhead.

Findings

Efficient preparation of sensing states using 2D cluster states.

Achieved optimal scaling in phase and frequency estimation.

Applicable to Bayesian estimation with Gaussian priors.

Abstract

Quantum metrology offers a quadratic advantage over classical approaches to parameter estimation problems by utilizing entanglement and nonclassicality. However, the hurdle of actually implementing the necessary quantum probe states and measurements, which vary drastically for different metrological scenarios, is usually not taken into account. We show that for a wide range of tasks in metrology, 2D cluster states (a particular family of states useful for measurement-based quantum computation) can serve as flexible resources that allow one to efficiently prepare any required state for sensing, and perform appropriate (entangled) measurements using only single qubit operations. Crucially, the overhead in the number of qubits is less than quadratic, thus preserving the quantum scaling advantage. This is ensured by using a compression to a logarithmically sized space that contains all relevant information for sensing. We specifically demonstrate how our method can be used to obtain optimal scaling for phase and frequency estimation in local estimation problems, as well as for the Bayesian equivalents with Gaussian priors of varying widths. Furthermore, we show that in the paradigmatic case of local phase estimation 1D cluster states are sufficient for optimal state preparation and measurement.