# Entanglement-enhanced Neyman-Pearson target detection using quantum illumination

## TL;DR

This paper demonstrates how entanglement-enhanced quantum illumination can be optimized for Neyman-Pearson target detection, improving detection performance in environments where classical methods struggle, using a novel SFG and feedforward architecture.

## Contribution

It introduces a Neyman-Pearson optimized quantum illumination receiver architecture based on sum-frequency generation and feedforward processing, extending previous Bayesian-based approaches.

## Key findings

- Achieves improved detection probability versus false-alarm rate trade-offs.
- Provides a theoretical framework for quantum illumination under Neyman-Pearson criterion.
- Demonstrates the potential for quantum advantage in practical radar scenarios.

## Abstract

Quantum illumination (QI) provides entanglement-based target detection---in an entanglement-breaking environment---whose performance is significantly better than that of optimum classical-illumination target detection. QI's performance advantage was established in a Bayesian setting with the target presumed equally likely to be absent or present and error probability employed as the performance metric. Radar theory, however, eschews that Bayesian approach, preferring the Neyman-Pearson performance criterion to avoid the difficulties of accurately assigning prior probabilities to target absence and presence and appropriate costs to false-alarm and miss errors. We have recently reported an architecture---based on sum-frequency generation (SFG) and feedforward (FF) processing---for minimum error-probability QI target detection with arbitrary prior probabilities for target absence and presence. In this paper, we use our results for FF-SFG reception to determine the receiver operating characteristic---detection probability versus false-alarm probability---for optimum QI target detection under the Neyman-Pearson criterion.