Compressed Sensing and Entanglement

Gregory A. Howland, John C. Howell

Gregory A. Howland, John C. Howell

We use compressive sensing to efficiently image spatial correlations from spontaneous parametric downconversion at high resolution and witness entanglement. This technique efficiently scales to large dimensions and efficiently handles very low flux signals.

Samuel H. Knarr, Gregory A. Howland, James Schneeloch +2 more

We use compressive sensing in the image and Fourier planes of a spontaneous parametric downconversion source to simultaneously gather the joint position and momentum distributions. We witness entanglement by violating a continuous variable steering inequality.

Shengjun Wu

Aditi Sen

Yang Liu, Jianyong Hu, Hongqi Niu +9 more

Quantum imaging based on entangled light sources exhibits enhanced background resistance compared to conventional imaging techniques in low-light conditions. However, direct imaging of dynamic targets remains challenging due to the limited count rate of entangled photons. In this paper, we propose a quantum imaging method based on quantum compressed sensing that leverages the strong correlation characteristics of entangled photons and the randomness inherent in photon pair generation and detection. This approach enables the construction of a compressed sensing system capable of directly imaging high-speed dynamic targets. The results demonstrate that our system successfully achieves imaging of a target rotating at a frequency of 10 kHz, while maintaining an impressive data compression rate of 10 −6 . This proposed method introduces a pioneering approach for the practical implementation of quantum imaging in real-world scenarios.