Entanglement-Enhanced Neyman-Pearson Target Detection
ORAL
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. We achieve a 1.48 dB quantum advantage, quantified by an enhancement of the signal to noise ratio, over a classical illumination target detection system, despite the presence of additional noise in our experimental setup. This research highlights a critical advancement in utilizing quantum resources for entanglement-enhanced sensing in practical applications. Furthermore, this result serves to inspire investigation of quantum illumination for target detection in the microwave domain, facilitated by the integration of quantum transduction modules into hybrid quantum systems.
*We gratefully acknowledge support from Office of Naval Research Award no. N00014-23-1-2296, National Science Foundation Award no. 2326746, US Department of Energy, Office of Science, National Quantum Information Science Research Centers, Superconducting Quantum Materials and Systems Center (SQMS), under contract no. DE-AC02-07CH11359, and University of Michigan.
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Publication: arXiv:2410.07544 [quant-ph]
Presenters
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William Ward
- University of Michigan