Entanglement-Enhanced Neyman-Pearson Target Detection

TL;DR

This paper demonstrates that entanglement-enhanced quantum illumination can provide a practical advantage in target detection by using the Neyman-Pearson criterion, making it more applicable to real-world scenarios where prior probabilities are unknown.

Contribution

It introduces a Neyman-Pearson-based approach to quantum illumination, showing an unconditional quantum advantage over classical protocols without relying on prior target probability assumptions.

Findings

Quantum advantage demonstrated using Neyman-Pearson criterion

Unconditional performance improvement over classical protocols

Applicable to practical scenarios with unknown prior probabilities

Abstract

Quantum illumination (QI) provides entanglement-enabled target-detection enhancement, despite operating in an entanglement-breaking environment. Existing experimental studies of QI have utilized a Bayesian approach, assuming that the target is equally likely to be present or absent before detection, to demonstrate an advantage over classical target detection. However, such a premise breaks down in practical operational scenarios in which the prior probability is unknown, thereby hindering QI's applicability to real-world target-detection scenarios. In this work, we adopt the Neyman-Pearson criterion in lieu of the error probability for equally likely target absence or presence as our figure of merit for QI. We demonstrate an unconditional quantum advantage over the optimal classical-illumination protocol as benchmarked by the receiver operating characteristic, which examines detection probability versus false-alarm probability without resorting to known prior probabilities. Our work represents a critical advancement in adapting quantum-enhanced sensing to practical operational settings.