Surface-normal illuminated pseudo-planar Ge-on-Si avalanche photodiodes with high gain and low noise.

Germanium-on-Silicon (Ge-on-Si) avalanche photodiodes (APDs) are of considerable interest as low intensity light detectors for emerging applications. The Ge absorption layer detects light at wavelengths up to ≈ 1600 nm with the Si acting as an avalanche medium, providing high gain with low excess avalanche noise. Such APDs are typically used in waveguide configurations as growing a sufficiently thick Ge absorbing layer is challenging. Here, we report on a new vertically illuminated pseudo-planar Ge-on-Si APD design utilizing a 2 µm thick Ge absorber and a 1.4 µm thick Si multiplication region. At a wavelength of 1550 nm, 50 µm diameter devices show a responsivity of 0.41 A/W at unity gain, a maximum avalanche gain of 101 and an excess noise factor of 3.1 at a gain of 20. This excess noise factor represents a record low noise for all configurations of Ge-on-Si APDs. These APDs can be inexpensively manufactured and have potential integration in silicon photonic platforms allowing use in a variety of applications requiring high-sensitivity detectors at wavelengths around 1550 nm.

Experimental demonstration of a reconfigurable free-space receiver implementing polarization routing and filtering for daytime quantum key distribution.

Free-space quantum key distribution (QKD) systems are often designed to implement polarization-encoding protocols. Alternatively, time-bin/phase-encoding protocols are considerably more challenging to perform over a channel experiencing atmospheric turbulence. However, over the last decade, new and improved optical platforms have revived the interest in them. In this paper, we present a free-space multi-protocol receiver designed to work with three different time-bin/phase-encoding protocols highlighting its interoperability with different systems and architectures for potential satellite-based communications. We also present a detailed analysis of different experimental configurations when implementing the coherent one-way (COW) protocol in a free-space channel, as well as a polarization filtering technique showing how time-bin/phase-encoding protocols could be used for QKD applications in daylight conditions. We demonstrate secret key rates of several kbps for channels with a total 30 dB attenuation even with moderately high QBERs of ≈3.5%. Moreover, a 2.6 dB improvement in the signal to noise ratio is achieved by filtering background light in the polarization degree of freedom, a technique that could be used in daylight QKD.

Rapid single-photon color imaging of moving objects.

This paper outlines an experimental demonstration of a Bayesian image reconstruction approach to achieve rapid single-photon color imaging of moving objects. The capacity to extract the color of objects is important in a variety of target identification and computer vision applications. Nonetheless, it remains challenging to achieve high-speed color imaging of moving objects in low-photon flux environments. The low-photon regime presents particular challenges for efficient spectral separation and identification, while unsupervised image reconstruction algorithms are often slow and computationally expensive. In this paper, we address both of these difficulties using a combination of hardware and computational solutions. We demonstrate color imaging using a Single-Photon Avalanche Diode (SPAD) detector array for rapid, low-light-level data acquisition, with an integrated color filter array (CFA) for efficient spectral unmixing. High-speed image reconstruction is achieved using a bespoke Bayesian algorithm to produce high-fidelity color videos. The analysis is conducted first on simulated data allowing different pixel formats and photon flux scenarios to be investigated. Experiments are then performed using a plasmonic metasurface-based CFA, integrated with a 64 × 64 pixel format SPAD array. Passive imaging is conducted using white-light illumination of multi-colored, moving targets. Intensity information is recorded in a series of 2D photon-counting SPAD frames, from which accurate color information is extracted using the fast Bayesian method introduced herein. The per-frame reconstruction rate proves to be hundreds of times faster than the previous computational method. Furthermore, this approach yields additional information in the form of uncertainty measures, which can be used to assist with imaging system optimization and decision-making in real-world applications. The techniques demonstrated point the way towards rapid video-rate single-photon color imaging. The developed Bayesian algorithm, along with more advanced SPAD technology and utilization of time-correlated single-photon counting (TCSPC) will permit live 3D, color videography in extremely low-photon flux environments.

3D target detection and spectral classification for single-photon LiDAR data.

3D single-photon LiDAR imaging has an important role in many applications. However, full deployment of this modality will require the analysis of low signal to noise ratio target returns and very high volume of data. This is particularly evident when imaging through obscurants or in high ambient background light conditions. This paper proposes a multiscale approach for 3D surface detection from the photon timing histogram to permit a significant reduction in data volume. The resulting surfaces are background-free and can be used to infer depth and reflectivity information about the target. We demonstrate this by proposing a hierarchical Bayesian model for 3D reconstruction and spectral classification of multispectral single-photon LiDAR data. The reconstruction method promotes spatial correlation between point-cloud estimates and uses a coordinate gradient descent algorithm for parameter estimation. Results on simulated and real data show the benefits of the proposed target detection and reconstruction approaches when compared to state-of-the-art processing algorithms.

Submerged single-photon LiDAR imaging sensor used for real-time 3D scene reconstruction in scattering underwater environments.

We demonstrate a fully submerged underwater LiDAR transceiver system based on single-photon detection technologies. The LiDAR imaging system used a silicon single-photon avalanche diode (SPAD) detector array fabricated in complementary metal-oxide semiconductor (CMOS) technology to measure photon time-of-flight using picosecond resolution time-correlated single-photon counting. The SPAD detector array was directly interfaced to a Graphics Processing Unit (GPU) for real-time image reconstruction capability. Experiments were performed with the transceiver system and target objects immersed in a water tank at a depth of 1.8 meters, with the targets placed at a stand-off distance of approximately 3 meters. The transceiver used a picosecond pulsed laser source with a central wavelength of 532 nm, operating at a repetition rate of 20 MHz and average optical power of up to 52 mW, dependent on scattering conditions. Three-dimensional imaging was demonstrated by implementing a joint surface detection and distance estimation algorithm for real-time processing and visualization, which achieved images of stationary targets with up to 7.5 attenuation lengths between the transceiver and the target. The average processing time per frame was approximately 33 ms, allowing real-time three-dimensional video demonstrations of moving targets at ten frames per second at up to 5.5 attenuation lengths between transceiver and target.

Optical quantum super-resolution imaging and hypothesis testing.

Estimating the angular separation between two incoherent thermal sources is a challenging task for direct imaging, especially at lengths within the diffraction limit. Moreover, detecting the presence of multiple sources of different brightness is an even more severe challenge. We experimentally demonstrate two tasks for super-resolution imaging based on hypothesis testing and quantum metrology techniques. We can significantly reduce the error probability for detecting a weak secondary source, even for small separations. We reduce the experimental complexity to a simple interferometer: we show (1) our set-up is optimal for the state discrimination task, and (2) if the two sources are equally bright, then this measurement can super-resolve their angular separation. Using a collection baseline of 5.3 mm, we resolve the angular separation of two sources placed 15 µm apart at a distance of 1.0 m with a 1.7% accuracy - an almost 3-orders-of-magnitude improvement over shot-noise limited direct imaging.

Multichannel Superposition of Grafted Perfect Vortex Beams.

Inspired by plant grafting, grafted vortex beams can be formed through grafting two or more helical phase profiles of optical vortex beams. Recently, grafted perfect vortex beams (GPVBs) have attracted much attention due to their unique optical properties and potential applications. However, the current method to generate and manipulate GPVBs requires a complex and bulky optical system, hindering further investigation and limiting its practical applications. Here, a compact metasurface approach for generating and manipulating GPVBs in multiple channels is proposed and demonstrated, which eliminates the need for such a complex optical setup. A single metasurface is utilized to realize various superpositions of GPVBs with different combinations of topological charges in four channels, leading to asymmetric singularity distributions. The positions of singularities in the superimposed beam can be further modulated by introducing an initial phase difference in the metasurface design. The work demonstrates a compact metasurface platform that performs a sophisticated optical task that is very challenging with conventional optics, opening opportunities for the investigation and applications of GPVBs in a wide range of emerging application areas, such as singular optics and quantum science.

Light detection and ranging (lidar): introduction.

In this introduction we provide an overview of the papers that were accepted for publication in the special issue on light detection and ranging (lidar). Four of the papers were published in JOSA A, and four were published in JOSA B. They represent different aspects of this important and fast-growing field while showing the relevant state-of-the-art achievements currently existing in the field of lidars in the world of science and engineering.

Custom-Technology Single-Photon Avalanche Diode Linear Detector Array for Underwater Depth Imaging.

We present an optical depth imaging system suitable for highly scattering underwater environments. The system used the time-correlated single-photon counting (TCSPC) technique and the time-of-flight approach to obtain depth profiles. The single-photon detection was provided by a linear array of single-photon avalanche diode (SPAD) detectors fabricated in a customized silicon fabrication technology for optimized efficiency, dark count rate, and jitter performance. The bi-static transceiver comprised a pulsed laser diode source with central wavelength 670 nm, a linear array of 16 × 1 Si-SPAD detectors, with a dedicated TCSPC acquisition module. Cylindrical lenses were used to collect the light scattered by the target and image it onto the sensor. These laboratory-based experiments demonstrated single-photon depth imaging at a range of 1.65 m in highly scattering conditions, equivalent up to 8.3 attenuation lengths between the system and the target, using average optical powers of up to 15 mW. The depth and spatial resolution of this sensor were investigated in different scattering conditions.

Robust real-time 3D imaging of moving scenes through atmospheric obscurant using single-photon LiDAR.

Recently, time-of-flight LiDAR using the single-photon detection approach has emerged as a potential solution for three-dimensional imaging in challenging measurement scenarios, such as over distances of many kilometres. The high sensitivity and picosecond timing resolution afforded by single-photon detection offers high-resolution depth profiling of remote, complex scenes while maintaining low power optical illumination. These properties are ideal for imaging in highly scattering environments such as through atmospheric obscurants, for example fog and smoke. In this paper we present the reconstruction of depth profiles of moving objects through high levels of obscurant equivalent to five attenuation lengths between transceiver and target at stand-off distances up to 150 m. We used a robust statistically based processing algorithm designed for the real time reconstruction of single-photon data obtained in the presence of atmospheric obscurant, including providing uncertainty estimates in the depth reconstruction. This demonstration of real-time 3D reconstruction of moving scenes points a way forward for high-resolution imaging from mobile platforms in degraded visual environments.

Simultaneous multi-spectral, single-photon fluorescence imaging using a plasmonic colour filter array.

We present the first realisation of simultaneous multi-spectral fluorescence imaging using a single-photon avalanche diode (SPAD) array, where the spectral unmixing is facilitated by a plasmonic metasurface mosaic colour filter array (CFA). A 64 × 64 pixel format silicon SPAD array is used to record widefield fluorescence and brightfield data from four biological samples. A plasmonic metasurface composed of an arrangement of circular and elliptical nanoholes etched into an aluminium thin film deposited on a glass substrate provides the high transmission efficiency CFA, enabling a bespoke spectral unmixing algorithm to reconstruct high fidelity, full colour images from as few as ∼3 photons per pixel. This approach points the way toward real-time, single-photon sensitive multi-spectral fluorescence imaging. Furthermore, this is possible without additional bulky components such as a filter wheel, prism or diffraction grating, nor the need for multiple sample exposures or multiple detectors.

Towards combined quantum bit detection and spatial tracking using an arrayed single-photon sensor.

Experimental quantum key distribution through free-space channels requires accurate pointing-and-tracking to co-align telescopes for efficient transmission. The hardware requirements for the sender and receiver could be drastically reduced by combining the detection of quantum bits and spatial tracking signal using two-dimensional single-photon detector arrays. Here, we apply a two-dimensional CMOS single-photon avalanche diode detector array to measure and monitor the single-photon level interference of a free-space time-bin receiver interferometer while simultaneously tracking the spatial position of the single-photon level signal. We verify an angular field-of-view of 1.28° and demonstrate a post-processing technique to reduce background noise. The experimental results show a promising future for two-dimensional single-photon detectors in low-light level free-space communications, such as quantum communications.

Robust 3D Reconstruction of Dynamic Scenes From Single-Photon Lidar Using Beta-Divergences.

In this article, we present a new algorithm for fast, online 3D reconstruction of dynamic scenes using times of arrival of photons recorded by single-photon detector arrays. One of the main challenges in 3D imaging using single-photon lidar in practical applications is the presence of strong ambient illumination which corrupts the data and can jeopardize the detection of peaks/surface in the signals. This background noise not only complicates the observation model classically used for 3D reconstruction but also the estimation procedure which requires iterative methods. In this work, we consider a new similarity measure for robust depth estimation, which allows us to use a simple observation model and a non-iterative estimation procedure while being robust to mis-specification of the background illumination model. This choice leads to a computationally attractive depth estimation procedure without significant degradation of the reconstruction performance. This new depth estimation procedure is coupled with a spatio-temporal model to capture the natural correlation between neighboring pixels and successive frames for dynamic scene analysis. The resulting online inference process is scalable and well suited for parallel implementation. The benefits of the proposed method are demonstrated through a series of experiments conducted with simulated and real single-photon lidar videos, allowing the analysis of dynamic scenes at 325 m observed under extreme ambient illumination conditions.

High sensitivity Ge-on-Si single-photon avalanche diode detectors.

The performance of planar geometry Ge-on-Si single-photon avalanche diode detectors of 26µm diameter is presented. Record low dark count rates are observed, remaining less than 100 K counts per second at 6.6% excess bias and 125 K. Single-photon detection efficiencies are found to be up to 29.4%, and are shown to be temperature insensitive. These performance characteristics lead to a significantly reduced noise equivalent power (NEP) of 7.7×10-17WHz-12 compared to prior planar devices, and represent a two orders of magnitude reduction in NEP compared to previous Ge-on-Si mesa devices of a comparable diameter. Low jitter values of 134±10ps are demonstrated.

High concentration factor diffractive microlenses integrated with CMOS single-photon avalanche diode detector arrays for fill-factor improvement.

Large-format single-photon avalanche diode (SPAD) arrays often suffer from low fill-factors-the ratio of the active area to the overall pixel area. The detection efficiency of these detector arrays can be vastly increased with the integration of microlens arrays designed to concentrate incident light onto the active areas and may be refractive or diffractive in nature. The ability of diffractive optical elements (DOEs) to efficiently cover a square or rectangular pixel, combined with their capability of working as fast lenses (i.e., ∼f/3) makes them versatile and practical lens designs for use in sparse photon applications using microscale, large-format detector arrays. Binary-mask-based photolithography was employed to fabricate fast diffractive microlenses for two designs of 32×32 SPAD detector arrays, each design having a different pixel pitch and fill-factor. A spectral characterization of the lenses is performed, as well as analysis of performance under different illumination conditions from wide- to narrow-angle illumination (i.e., f/2 to f/22 optics). The performance of the microlenses presented exceeds previous designs in terms of both concentration factor (i.e., increase in light collection capability) and lens speed. Concentration factors greater than 33× are achieved for focal lengths in the substrate material as short as 190µm, representing a microlens f-number of 3.8 and providing a focal spot diameter of <4µm. These results were achieved while retaining an extremely high degree of performance uniformity across the 1024 devices in each case, which demonstrates the significant benefits to be gained by the implementation of DOEs as part of an integrated detector system using SPAD arrays with very small active areas.

3D LIDAR imaging using Ge-on-Si single-photon avalanche diode detectors.

We present a scanning light detection and ranging (LIDAR) system incorporating an individual Ge-on-Si single-photon avalanche diode (SPAD) detector for depth and intensity imaging in the short-wavelength infrared region. The time-correlated single-photon counting technique was used to determine the return photon time-of-flight for target depth information. In laboratory demonstrations, depth and intensity reconstructions were made of targets at short range, using advanced image processing algorithms tailored for the analysis of single-photon time-of-flight data. These laboratory measurements were used to predict the performance of the single-photon LIDAR system at longer ranges, providing estimations that sub-milliwatt average power levels would be required for kilometer range depth measurements.

Learning Non-Local Spatial Correlations To Restore Sparse 3D Single-Photon Data.

This paper presents a new algorithm for the learning of spatial correlation and non-local restoration of single-photon 3-Dimensional Lidar images acquired in the photon starved regime (fewer or less than one photon per pixel) or with a reduced number of scanned spatial points (pixels). The algorithm alternates between three steps: (i) extract multi-scale information, (ii) build a robust graph of non-local spatial correlations between pixels, and (iii) the restoration of depth and reflectivity images. A non-uniform sampling approach, which assigns larger patches to homogeneous regions and smaller ones to heterogeneous regions, is adopted to reduce the computational cost associated with the graph. The restoration of the 3D images is achieved by minimizing a cost function accounting for the multi-scale information and the non-local spatial correlation between patches. This minimization problem is efficiently solved using the alternating direction method of multipliers (ADMM) that presents fast convergence properties. Various results based on simulated and real Lidar data show the benefits of the proposed algorithm that improves the quality of the estimated depth and reflectivity images, especially in the photon-starved regime or when containing a reduced number of spatial points.

On-chip implementation of the probabilistic quantum optical state comparison amplifier.

Propagation losses in transmission media limit the transmission distance of optical signals. In the case where the signal is made up of quantum optical states, conventional deterministic optical amplification schemes cannot be used to increase the transmission distance as the copying of an arbitrary and unknown quantum state is forbidden. One strategy that can offset propagation loss is the use of probabilistic, or non-deterministic, amplification schemes - an example of which is the state comparison amplifier. Here we report a state comparison amplifier implemented in a compact, fiber-coupled femtosecond laser-written waveguide chip as opposed to the large, bulk-optical components of previous designs. This pathfinder on-chip implementation of the quantum amplifier has resulted in several performance improvements: the polarization integrity of the written waveguides has resulted in improved visibility of the amplifier interferometers; the potential of substantially-reduced losses throughout the amplifier configuration; and a more compact and environmentally-stable amplifier which is scalable to more complex networks.

Three-dimensional imaging of stationary and moving targets in turbid underwater environments using a single-photon detector array.

Three-dimensional imaging in underwater environments was investigated using a picosecond resolution silicon single-photon avalanche diode (SPAD) detector array fabricated in complementary metal-oxide semiconductor (CMOS) technology. Each detector in the 192  × 128 SPAD array had an individual time-to-digital converter allowing rapid, simultaneous acquisition of data for the entire array using the time-correlated single-photon counting approach. A picosecond pulsed laser diode source operating at a wavelength of 670 nm was used to illuminate the underwater scenes, emitting an average optical power up to 8 mW. Both stationary and moving targets were imaged under a variety of underwater scattering conditions. The acquisition of depth and intensity videos of moving targets was demonstrated in dark laboratory conditions through scattering water, equivalent to having up to 6.7 attenuation lengths between the transceiver and target. Data were analyzed using a pixel-wise approach, as well as an image processing algorithm based on a median filter and polynomial approximation.

Real-time 3D reconstruction from single-photon lidar data using plug-and-play point cloud denoisers.

Single-photon lidar has emerged as a prime candidate technology for depth imaging through challenging environments. Until now, a major limitation has been the significant amount of time required for the analysis of the recorded data. Here we show a new computational framework for real-time three-dimensional (3D) scene reconstruction from single-photon data. By combining statistical models with highly scalable computational tools from the computer graphics community, we demonstrate 3D reconstruction of complex outdoor scenes with processing times of the order of 20 ms, where the lidar data was acquired in broad daylight from distances up to 320 metres. The proposed method can handle an unknown number of surfaces in each pixel, allowing for target detection and imaging through cluttered scenes. This enables robust, real-time target reconstruction of complex moving scenes, paving the way for single-photon lidar at video rates for practical 3D imaging applications.