Hybrid quantum-classical approach to enhanced quantum metrology

TL;DR

This paper introduces a hybrid quantum-classical method with adjustable controls for optimizing quantum probes in metrology, demonstrated experimentally on an NMR processor, to improve measurement precision despite noise and complexity.

Contribution

It presents the first experimental implementation of an adaptive hybrid approach for quantum metrology that automatically optimizes probes without complex offline design.

Findings

Successfully optimized quantum probes for frequency estimation on NMR.

The scheme inherently corrects certain unitary errors during learning.

Demonstrated improved precision in quantum metrology tasks.

Abstract

Quantum metrology plays a fundamental role in many scientific areas. However, the complexity of engineering entangled probes and the external noise raise technological barriers for realizing the expected precision of the to-be-estimated parameter with given resources. Here, we address this problem by introducing adjustable controls into the encoding process and then utilizing a hybrid quantum-classical approach to automatically optimize the controls online. Our scheme does not require any complex or intractable off-line design, and it can inherently correct certain unitary errors during the learning procedure. We also report the first experimental demonstration of this promising scheme for the task of finding optimal probes for frequency estimation on a nuclear magnetic resonance (NMR) processor. The proposed scheme paves the way to experimentally auto-search optimal protocol for improving the metrology precision.