Quantum-enhanced radio-frequency photonic distributed imaging

• URL: http://arxiv.org/abs/2503.03075v1
• Date: Wed, 05 Mar 2025 00:29:50 GMT
• Title: Quantum-enhanced radio-frequency photonic distributed imaging
• Authors: Haowei Shi, Christopher M. Jones, Mengjie Yu, Zheshen Zhang, Quntao Zhuang,
• Abstract summary: We explore the quantum advantage of imaging in the weak coupling scenario of the RF-photonic receiver.<n>The proposed imaging receiver applies transducer to upconvert the RF signal to optical to enable high-efficiency connection via low-loss fiber networks.<n>We evaluate the quantum advantage in synthetic aperture radar imaging, where the images are generated from the standard resolution test chart.
• Score: 0.34952465649465553
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Quantum physics has brought enhanced capability in various sensing applications. Despite challenges from noise and loss in the radio-frequency (RF) domain, [Phys. Rev. Lett. 124, 150502 (2020)] demonstrates a route for enhanced RF-receiver empowered by quantum squeezing and entanglement. In this work, we further explore the quantum advantage of imaging in the weak coupling scenario of the RF-photonic receiver. The proposed imaging receiver applies transducer to upconvert the RF signal to optical to enable high-efficiency connection via low-loss fiber networks. The efficient connection therefore increases the synthetic aperture and improves the resolution of the distributed imaging system. To overcome the challenge from low transduction efficiency in existing devices limited by weak photon interaction, we propose the use of squeezed-state optical sources to suppress the noise. We numerically evaluate the quantum advantage in synthetic aperture radar imaging, where the images are generated from the standard resolution test chart via a Gaussian point spread function with added Gaussian noise. We apply the Wiener filter on the images to restore the objects and find that stronger squeezing significantly improves the quality of the restored image. Our findings push quantum squeezing advantage to real-world applications.

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