Quantum Parametric Sorting Proposed to Separate between Signal and Noise

Nature paper "Noise-tolerant single photon sensitive three-dimensional imager" by Patrick Rehain, Yong Meng Sua, Shenyu Zhu, Ivan Dickson, Bharathwaj Muthuswamy, Jeevanandha Ramanathan, Amin Shahverdi, and Yu-Ping Huang from Stevens Institute of Technology, NJ, proposes to solve a fundamental problem of distinguishing between signal and and ambient photons:

"Active imagers capable of reconstructing 3-dimensional (3D) scenes in the presence of strong background noise are highly desirable for many sensing and imaging applications. A key to this capability is the time-resolving photon detection that distinguishes true signal photons from the noise. To this end, quantum parametric mode sorting (QPMS) can achieve signal to noise exceeding by far what is possible with typical linear optics filters, with outstanding performance in isolating temporally and spectrally overlapping noise. Here, we report a QPMS-based 3D imager with exceptional detection sensitivity and noise tolerance. With only 0.0006 detected signal photons per pulse, we reliably reconstruct the 3D profile of an obscured scene, despite 34-fold spectral-temporally overlapping noise photons, within the 6 ps detection window (amounting to 113,000 times noise per 20 ns detection period). Our results highlight a viable approach to suppress background noise and measurement errors of single photon imager operation in high-noise environments."