Robustness of Quantum-Enhanced Adaptive Phase Estimation

TL;DR

This paper evaluates the robustness of adaptive quantum-enhanced phase estimation policies under various noise models, proposing a test to compare their efficacy and resource usage in noisy conditions.

Contribution

It introduces a robustness testing framework for AQEM policies and compares different control strategies under diverse noise scenarios.

Findings

Control policies devised by evolutionary algorithms perform well under unknown noise.

Bayesian-based feedback methods are effective even without noise assumptions.

The proposed test helps select the most robust policy for noisy quantum metrology.

Abstract

As all physical adaptive quantum-enhanced metrology schemes operate under noisy conditions with only partially understood noise characteristics, so a practical control policy must be robust even for unknown noise. We aim to devise a test to evaluate the robustness of AQEM policies and assess the resource used by the policies. The robustness test is performed on QEAPE by simulating the scheme under four phase-noise models corresponding to normal-distribution noise, random-telegraph noise, skew-normal-distribution noise, and log-normal-distribution noise. Control policies are devised either by an evolutionary algorithm under the same noisy conditions, albeit ignorant of its properties, or a Bayesian-based feedback method that assumes no noise. Our robustness test and resource comparison method can be used to determining the efficacy and selecting a suitable policy.