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Quantum 3D imaging through multiscattering media of 10 optical depth

Yong Meng Sua, Shengyu Zhu, Patrick Rehain, Daniel Tafone, Bharathwaj Muthuswamy, Jeevanandha Ramanathan, Ivan Dickson, Yu‐Ping Huang

Published Apr 22, 2020• 8 citations
Publisher

Abstract

High resolution three dimensional (3D) optical imaging in the turbid underwater scenarios over extended length remains an outstanding challenge, primarily impeded by the absorption and scattering in turbid water, which result in substantial signal attenuation over short propagation distances. Overcoming water absorption by using optimum illumination wavelengths (480- 600 nm) of the visible spectrum, however, still requires one to address the strong scattering effects. To address the above challenge, we introduce a novel 3D imaging modality based on quantum parametric mode sorting (QPMS). It is a nascent quantum measurement technique that utilizes mode-selective quantum frequency conversion (QFC) in a χ2 nonlinear waveguide to up convert signal photons in a single spatiotemporal mode efficiently. Undesirable photons in other modes, even if they spectrally and temporally overlap with the signal, are converted with much less efficiency. This unique feature, combining with picosecond time gated detection as defined by the pump pulse width, can isolate signal photon backscattered by the target from multiscattered photons by the obstacle. It thus enables imaging through a strongly scattering medium, where the background photons are orders of magnitude stronger. With QPMS, we demonstrate 3D imaging of a target occluded by strongly scattering turbid media with optical depth < 9 (<18 round trip), while needing only 10􀀀5 detected photons/pulse to achieve sub-millimeters resolution. This makes our single photon sensitive 3D imager suitable for imaging and remote sensing applications in photon-starved natural water environments where it's high sensitivity and excellent temporal resolution can be exploited to its full extent.

DOI
10.1117/12.2560535

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High resolution three dimensional (3D) optical imaging in the turbid underwater scenarios over extended length remains an outstanding challenge, primarily impeded by the absorption and scattering in turbid water, which result in substantial signal attenuation over short propagation distances. Overcoming water absorption by using optimum illumination wavelengths (480- 600 nm) of the visible spectrum, however, still requires one to address the strong scattering effects. To address the above challenge, we introduce a novel 3D imaging modality based on quantum parametric mode sorting (QPMS). It is a nascent quantum measurement technique that utilizes mode-selective quantum frequency conversion (QFC) in a χ2 nonlinear waveguide to up convert signal photons in a single spatiotemporal mode efficiently. Undesirable photons in other modes, even if they spectrally and temporally overlap with the signal, are converted with much less efficiency. This unique feature, combining with picosecond time gated detection as defined by the pump pulse width, can isolate signal photon backscattered by the target from multiscattered photons by the obstacle. It thus enables imaging through a strongly scattering medium, where the background photons are orders of magnitude stronger. With QPMS, we demonstrate 3D imaging of a target occluded by strongly scattering turbid media with optical depth < 9 (<18 round trip), while needing only 10􀀀5 detected photons/pulse to achieve sub-millimeters resolution. This makes our single photon sensitive 3D imager suitable for imaging and remote sensing applications in photon-starved natural water environments where it's high sensitivity and excellent temporal resolution can be exploited to its full extent.
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.
Selective detection of signal over noise is essential to measurement and signal processing. Time-frequency filtering has been the standard approach for the optimal detection of non-stationary signals. However, there is a fundamental tradeoff between the signal detection efficiency and the amount of undesirable noise detected simultaneously, which restricts its uses under weak signal yet strong noise conditions. Here, we demonstrate quantum parametric mode sorting based on nonlinear optics at the edge of phase matching to improve the tradeoff. By tailoring the nonlinear process in a commercial lithium-niobate waveguide through optical arbitrary waveform generation, we demonstrate highly selective detection of picosecond signals overlapping temporally and spectrally but in orthogonal time-frequency modes as well as against broadband noise, with performance well exceeding the theoretical limit of the optimized time-frequency filtering. We also verify that our device does not introduce any significant quantum noise to the detected signal and demonstrate faithful detection of pico-second single photons. Together, these results point to unexplored opportunities in measurement and signal processing under challenging conditions, such as photon-starving quantum applications.
Detection signal to noise ratio lies at the heart of any remote sensing task. Matched filters have long been deployed as the optimal devices for radio and microwave receiving. However, their implements in the optics domain are challenging due to a much higher bandwidth and the intensity-only measurement by incoherent detectors. For applications involving high noise and low signal, their utilities are overly restricted by a fundamental trade-off between the signal detection efficiency and noise rejection. In this talk, I will describe a nascent approach, quantum parametric mode sorting, to addressing these practical and fundamental challenges. It is realized via quantum frequency conversion at the phase matching edge, where the signal distillation, picosecond timing tagging, and wavelength transduction are accomplished during a single pass through a nonlinear waveguide or crystal. I will report our experimental progress on using it a variety of single photon sensing and imaging tasks.
The temporal shape of single photons provides a high-dimensional basis of temporal modes, and can therefore support quantum computing schemes that go beyond the qubit. However, the lack of linear optical components to act as quantum gates has made it challenging to efficiently address specific temporal-mode components from an arbitrary superposition. Recent progress towards realizing such a "quantum pulse gate," has been proposed using nonlinear optical signal processing to add coherently the effect of multiple stages of quantum frequency conversion. This scheme, called temporal-mode interferometry [D. V. Reddy, Phys. Rev. A 91, 012323 (2015)], has been shown in the case of three-wave mixing to promise near-unity mode-sorting efficiency. Here we demonstrate that it is also possible to achieve high mode-sorting efficiency using four-wave mixing, if one pump pulse is long and the other short - a configuration we call asymmetrically-pumped Bragg scattering.
Quantum frequency conversion (QFC) of photonic signals preserves quantum information while simultaneously changing the signal wavelength. A common application of QFC is to translate the wavelength of a signal compatible with the current fiber-optic infrastructure to a shorter wavelength more compatible with high quality single-photon detectors and optical memories. Recent work has investigated the use of QFC to manipulate and measure specific temporal modes (TMs) through tailoring of the pump pulses. Such a scheme holds promise for multidimensional quantum state manipulation that is both low loss and re-programmable on a fast time scale. We demonstrate the first QFC temporal mode sorting system in a four-dimensional Hilbert space, achieving a conversion efficiency and mode separability as high as 92% and 0.84, respectively. A 20-GHz pulse train is projected onto 6 different TMs, including superposition states, and mode separability with weak coherent signals is verified via photon counting. Such ultrafast high-dimensional photonic signals could enable long-distance quantum communication with high rates.
Random phase perturbations in dynamic media fundamentally limit a broad class of conventional optical imaging, causing severe motion artifacts and resolution degradation in applications from in vivo biomedical tomography to remote sensing. Here, we demonstrate that quantum optical coherence tomography (QOCT), leveraging Hong–Ou–Mandel interference of entangled photons, achieves unprecedented resilience against these disturbances and provides quantitative formulas characterizing this robustness. Theoretically, QOCT exhibits >10-fold slower visibility decay than classical optical coherence tomography (OCT) under random phase fluctuations. Experimentally, it maintains >90 % baseline visibility through turbulent media—conditions where OCT fails. Crucially, this robustness stems from intrinsic quantum properties: interference detection between indistinguishable paths of frequency-entangled identical photons eliminates random path length perturbations and provides native axial resolution doubling (versus classical OCT at identical bandwidth), with neither post-processing nor system modifications required. We validate QOCT’s capability by performing micron-scale 3D tomography of structured targets through dynamic turbid liquids, achieving high-fidelity reconstructions under strong flow turbulence (Reynolds number >5600). This work establishes a paradigm for quantum-enhanced imaging, enabling high-precision volumetric tomography in scenarios from motion artifact-free biological diagnosis to non-contact subaquatic mapping through turbulent air–water interfaces.