Single Photon Avalanche Detector Research Articles

Number-state reconstruction with a single single-photon avalanche detector

Single-photon avalanche detectors (SPADs) are crucial sensors of light for many fields and applications. However, they are not able to resolve photon number, so typically more complex and more expensive experimental setups or devices must be used to measure the number of photons in a pulse. Here, we present a methodology for performing photon number-state reconstruction with only one SPAD. The methodology, which is cost-effective and easy to implement, uses maximum-likelihood techniques with a detector model whose parameters are measurable. We achieve excellent agreement between known input pulses and their reconstructions for coherent states with up to ≈10 photons and peak input photon rates up to several Mcounts/s. When detector imperfections are small, we maintain good agreement for coherent pulses with peak input photon rates of over 40 Mcounts/s, greater than one photon per detector dead time. For anti-bunched light, the reconstructed and independently measured pulse-averaged values of g(2)(0) are also consistent with one another. Our algorithm is applicable to light pulses whose pulse width and correlation time scales are both at least a few detector dead times. These results, achieved with single commercially available SPADs, provide an inexpensive number-state reconstruction method and expand the capabilities of single-photon detectors.

An efficient modeling workflow for high-performance nanowire single-photon avalanche detector

Single-photon detector (SPD), an essential building block of the quantum communication system, plays a fundamental role in developing next-generation quantum technologies. In this work, we propose an efficient modeling workflow of nanowire SPDs utilizing avalanche breakdown at reverse-biased conditions. The proposed workflow is explored to maximize computational efficiency and balance time-consuming drift-diffusion simulation with fast script-based post-processing. Without excessive computational effort, we could predict a suite of key device performance metrics, including breakdown voltage, dark/light avalanche built-up time, photon detection efficiency, dark count rate, and the deterministic part of timing jitter due to device structures. Implementing the proposed workflow onto a single InP nanowire and comparing it to the extensively studied planar devices and superconducting nanowire SPDs, we showed the great potential of nanowire avalanche SPD to outperform their planar counterparts and obtain as superior performance as superconducting nanowires, i.e. achieve a high photon detection efficiency of 70% with a dark count rate less than 20 Hz at non-cryogenic temperature. The proposed workflow is not limited to single-nanowire or nanowire-based device modeling and can be readily extended to more complicated two-/three dimensional structures.

A 256 × 256 LiDAR Imaging System Based on a 200 mW SPAD-Based SoC with Microlens Array and Lightweight RGB-Guided Depth Completion Neural Network.

Light detection and ranging (LiDAR) technology, a cutting-edge advancement in mobile applications, presents a myriad of compelling use cases, including enhancing low-light photography, capturing and sharing 3D images of fascinating objects, and elevating the overall augmented reality (AR) experience. However, its widespread adoption has been hindered by the prohibitive costs and substantial power consumption associated with its implementation in mobile devices. To surmount these obstacles, this paper proposes a low-power, low-cost, single-photon avalanche detector (SPAD)-based system-on-chip (SoC) which packages the microlens arrays (MLAs) and a lightweight RGB-guided sparse depth imaging completion neural network for 3D LiDAR imaging. The proposed SoC integrates an 8 × 8 SPAD macropixel array with time-to-digital converters (TDCs) and a charge pump, fabricated using a 180 nm bipolar-CMOS-DMOS (BCD) process. Initially, the primary function of this SoC was limited to serving as a ranging sensor. A random MLA-based homogenizing diffuser efficiently transforms Gaussian beams into flat-topped beams with a 45° field of view (FOV), enabling flash projection at the transmitter. To further enhance resolution and broaden application possibilities, a lightweight neural network employing RGB-guided sparse depth complementation is proposed, enabling a substantial expansion of image resolution from 8 × 8 to quarter video graphics array level (QVGA; 256 × 256). Experimental results demonstrate the effectiveness and stability of the hardware encompassing the SoC and optical system, as well as the lightweight features and accuracy of the algorithmic neural network. The state-of-the-art SoC-neural network solution offers a promising and inspiring foundation for developing consumer-level 3D imaging applications on mobile devices.

Full two-dimensional ambipolar CFET-like architecture for switchable logic circuits

As the scaling of integrated circuits based on silicon semiconductors becomes increasingly challenging due to the minimum feature size being close to the physical limit, the urgent demand for alternative strategies has fuelled the rapid growth of techniques and material innovations. Here, we report on the fabrication of vertically stacked ambipolar complementary field-effect transistor that is fully composed of two-dimensional materials of WSe2/h-BN/graphene/h-BN/WSe2 heterostructures. The ambipolar feature of the top and bottom WSe2 FET enables a switchable inverter behavior with a favorable voltage gain of up to 75, which can work in both the first and third quadrants. Based on the switchable characteristics, a large voltage swing circuit for single photon avalanche detectors is proposed without any bulky negative-voltage components. This work could open a new pathway for future two-dimensional electronics and ultimate monolithic 3D high-density integration circuits.

Fundamental limits to depth imaging with single-photon detector array sensors

Single-Photon Avalanche Detector (SPAD) arrays are a rapidly emerging technology. These multi-pixel sensors have single-photon sensitivities and pico-second temporal resolutions thus they can rapidly generate depth images with millimeter precision. Such sensors are a key enabling technology for future autonomous systems as they provide guidance and situational awareness. However, to fully exploit the capabilities of SPAD array sensors, it is crucial to establish the quality of depth images they are able to generate in a wide range of scenarios. Given a particular optical system and a finite image acquisition time, what is the best-case depth resolution and what are realistic images generated by SPAD arrays? In this work, we establish a robust yet simple numerical procedure that rapidly establishes the fundamental limits to depth imaging with SPAD arrays under real world conditions. Our approach accurately generates realistic depth images in a wide range of scenarios, allowing the performance of an optical depth imaging system to be established without the need for costly and laborious field testing. This procedure has applications in object detection and tracking for autonomous systems and could be easily extended to systems for underwater imaging or for imaging around corners.

Pixels2Pose: Super-resolution time-of-flight imaging for 3D pose estimation.

Single-photon-sensitive depth sensors are being increasingly used in next-generation electronics for human pose and gesture recognition. However, cost-effective sensors typically have a low spatial resolution, restricting their use to basic motion identification and simple object detection. Here, we perform a temporal to spatial mapping that drastically increases the resolution of a simple time-of-flight sensor, i.e., an initial resolution of 4 × 4 pixels to depth images of resolution 32 × 32 pixels. The output depth maps can then be used for accurate three-dimensional human pose estimation of multiple people. We develop a new explainable framework that provides intuition to how our network uses its input data and provides key information about the relevant parameters. Our work greatly expands the use cases of simple single-photon avalanche detector time-of-flight sensors and opens up promising possibilities for future super-resolution techniques applied to other types of sensors with similar data types, i.e., radar and sonar.

Development of single photon avalanche detectors for NIR light detection

Near-infrared (NIR) light is used in several non-invasive biomedical techniques to measure the blood flow in deep tissues. The BIOSPAD project targets the development of SPAD arrays specifically designed for Diffuse Correlation Spectroscopy (DCS) in the NIR to measure deep tissue microvascular blood flow. In the first stage of the project, single SPADs with multiplication layers buried at different depths have been designed at IFAE and produced in a 150 nm CMOS technology. In this study, we present results of the characterization of SPAD devices with an area of 50 × 50 µm2 operated with an external passive quenching circuit. We compared properties, such as Dark Count Rate (DCR) and Photon Detection Efficiency (PDE) of the different SPAD designs. The PDE for 780 nm light of SPADs with a buried multiplication layer was observed to be in the range of 10–20% with a DCR of the order of 2 kHz. The results of these first prototypes are promising and are being followed up by the development of a new generation of CMOS SPADs designed to further improve the NIR light response.

Statistical Analysis of Silicon Photomultiplier Output Signals

Silicon photomultipliers are relatively new devices designed as a matrix of single-photon avalanche detectors, which have become popular for their miniature dimensions and low operating voltage. Their superior sensitivity allows detecting low-photon-count optical pulses, e.g., in ranging and LIDAR applications. The output signal of the photomultiplier is a non-stationary stochastic process, from which a weak periodic pulse can be extracted by means of statistical processing. Using the double-exponential approximation of output avalanche pulses the paper presents a simple analytical solution to the mean and variance of the stochastic process. It is shown that even for an ideal square optical pulse the rising edge of the statistically detected signal is longer than the edge of individual avalanche pulses. The knowledge of the detected waveform can be used to design an optimum laser pulse waveform or algorithms for estimating the time of arrival. The experimental section demonstrates the proposed procedure.

A high-precision detection method for laser time transfer based on a single-photon avalanche detector array.

Space-ground laser time transfer is of significant importance to effectively function a high-precision time synchronization system. Instead of the single-pixel single-photon avalanche detector (SPAD) commonly used in the laser time transfer system, the SPAD array device is capable of supporting the greater performance of the signal photon capture. In this paper, it is experimentally demonstrated that the detection precision and time deviation (TDEV) of the SPAD array can be extremely improved by an order of magnitude compared with those of a single-pixel SPAD. As a result, 2.4ps root mean square precision and 0.25ps over an averaging time of 1000s TDEV are achieved for the SPAD array, providing a new detection method for high-precision laser time transfer applications, such as space-ground optical clocks.

Deep-learning based photon-efficient 3D and reflectivity imaging with a 64 × 64 single-photon avalanche detector array.

A single photon avalanche diode (SPAD) is a high sensitivity detector that can work under weak echo signal conditions (≤1 photon per pixel). The measured digital signals can be used to invert the range and reflectivity images of the target with photon-efficient imaging reconstruction algorithm. However, the existing photon-efficient imaging reconstruction algorithms are susceptible to noise, which leads to poor quality of the reconstructed range and reflectivity images of target. In this paper, a non-local sparse attention encoder (NLSA-Encoder) neural network is proposed to extract the 3D information to reconstruct both the range and reflectivity images of target. The proposed network model can effectively reduce the influence of noise in feature extraction and maintain the capability of long-range correlation feature extraction. In addition, the network is optimized for reconstruction speed to achieve faster reconstruction without performance degradation, compared with other existing deep learning photon-efficient imaging reconstruction methods. The imaging performance is verified through numerical simulation, near-field indoor and far-field outdoor experiments with a 64 × 64 SPAD array. The experimental results show that the proposed network model can achieve better results in terms of the reconstruction quality of range and reflectivity images, as well as reconstruction speed.

Review of Quanta Image Sensors for Ultralow-Light Imaging

The quanta image sensor (QIS) is a photon-counting image sensor that has been implemented using different electron devices, including impact ionization-gain devices, such as the single-photon avalanche detectors (SPADs), and low-capacitance, high conversion-gain devices, such as modified CMOS image sensors (CIS) with deep subelectron read noise and/or low noise readout signal chains. This article primarily focuses on CIS QIS, but recent progress of both types is addressed. Signal processing progress, such as denoising, critical to improving apparent signal-to-noise ratio, is also reviewed as an enabling coinnovation.

Breaking the diffraction limit using fluorescence quantum coherence.

The classical optical diffraction limit can be overcome by exploiting the quantum properties of light in several theoretical studies; however, they mostly rely on an entangled light source. Recent experiments have demonstrated that quantum properties are preserved in many fluorophores, which makes it possible to add a new dimension of information for super-resolution fluorescence imaging. Here, we developed a statistical quantum coherence model for fluorescence emitters and proposed a new super-resolution method using fluorescence quantum coherence in fluorescence microscopy. In this study, by exploiting a single-photon avalanche detector (SPAD) array with a time-correlated single-photon-counting technique to perform spatial-temporal photon statistics of fluorescence coherence, the subdiffraction-limited spatial separation of emitters is obtained from the determined coherence. We numerically demonstrate an example of two-photon interference from two common fluorophores using an achievable experimental procedure. Our model provides a bridge between the macroscopic partial coherence theory and the microscopic dephasing and spectral diffusion mechanics of emitters. By fully taking advantage of the spatial-temporal fluctuations of the emitted photons as well as coherence, our quantum-enhanced imaging method has the significant potential to improve the resolution of fluorescence microscopy even when the detected signals are weak.

Finite-key analysis of practical time-bin high-dimensional quantum key distribution with afterpulse effect

High-dimensional quantum resources provide the ability to encode several bits of information on a single photon, which can particularly increase the secret key rate rate of quantum key distribution (QKD) systems. Recently, a practical four-dimensional QKD scheme based on time-bin quantum photonic state, only with two single-photon avalanche detectors as measurement setup, has been proven to have a superior performance than the qubit-based one. In this paper, we extend the results to our proposed eight-dimensional scheme. Then, we consider two main practical factors to improve its secret key bound. Concretely, we take the afterpulse effect into account and apply a finite-key analysis with the intensity fluctuations. Our secret bounds give consideration to both the intensity fluctuations and the afterpulse effect for the high-dimensional QKD systems. Numerical simulations show the bound of eight-dimensional QKD scheme is more robust to the intensity fluctuations but more sensitive to the afterpulse effect than the four-dimensional one.

Room temperature photon-counting lidar at 3 µm.

A midinfrared single-photon-counting lidar at 3 µm is presented. The 3 µm photons were upconverted to 790 nm in a periodically poled rubidium-doped KTiOPO4 crystal through intracavity mixing inside a 1064 nm Nd:YVO4 laser and detected using a conventional silicon single-photon avalanche detector (SPAD). The lidar system could distinguish 1 mm deep features on a diffusely reflecting target, limited by the SPAD and time-tagging electronics. This technique could easily be extended to longer wavelengths within the transparency of the nonlinear crystal.

Towards Integrated Single Photon Avalanche Detectors for Visible Light (Invited)

Integrated avalanche photodetectors (APDs) are essential and ubiquitous devices in quantum photonics applications. While free-space APDs are a mature technology, the development of integrated APDs for visible light is still in its infancy. In this invited talk, we review our work on integrated photodetectors – the Germanium photodetector for O band, and the first integrated silicon (Si) APD for visible light. A unique feature of the integrated Si APD system for visible light is the end-fire coupling between the silicon nitride (SiN) waveguide and the Si APD in the same layer. This allows for broadband and high-efficiency coupling of light from the SiN waveguide to the Si APD for light detection, without the drawbacks of conventional interlayer coupling. Our work on integrated Si APDs based on Geiger-mode and our progress towards achieving single photon detection for visible light is discussed in the talk.

Design and implementation of silicon single-photon avalanche photodiode modeling tool for QKD systems

Single-photon detection concept is the most crucial factor that determines the performance of quantum key distribution (QKD) systems. In this paper, a simulator with time domain visualizers and configurable parameters using continuous time simulation approach is presented for modeling and investigating the performance of single-photon detectors operating in Gieger mode at the wavelength of 830 nm. The widely used C30921S silicon avalanche photodiode was modeled in terms of avalanche pulse, the effect of experiment conditions such as excess voltage, temperature and average photon number on the photon detection efficiency, dark count rate and afterpulse probability. This work shows a general repeatable modeling process for significant performance evaluation. The most remarkable result emerged from the simulated data generated and detected by commercial devices is that the modeling process provides guidance for single-photon detectors design and characterization. The validation and testing results of the single-photon avalanche detectors (SPAD) simulator showed acceptable results with the theoretical and experimental results reported in related references and the device's data sheets.

Faceting of Si and Ge crystals grown on deeply patterned Si substrates in the kinetic regime: phase-field modelling and experiments

The development of three-dimensional architectures in semiconductor technology is paving the way to new device concepts for various applications, from quantum computing to single photon avalanche detectors. In most cases, such structures are achievable only under far-from-equilibrium growth conditions. Controlling the shape and morphology of the growing structures, to meet the strict requirements for an application, is far more complex than in close-to-equilibrium cases. The development of predictive simulation tools can be essential to guide the experiments. A versatile phase-field model for kinetic crystal growth is presented and applied to the prototypical case of Ge/Si vertical microcrystals grown on deeply patterned Si substrates. These structures, under development for innovative optoelectronic applications, are characterized by a complex three-dimensional set of facets essentially driven by facet competition. First, the parameters describing the kinetics on the surface of Si and Ge are fitted on a small set of experimental results. To this goal, Si vertical microcrystals have been grown, while for Ge the fitting parameters have been obtained from data from the literature. Once calibrated, the predictive capabilities of the model are demonstrated and exploited for investigating new pattern geometries and crystal morphologies, offering a guideline for the design of new 3D heterostructures. The reported methodology is intended to be a general approach for investigating faceted growth under far-from-equilibrium conditions.

Absolute calibration of a single-photon avalanche detector using a bright triggered single-photon source based on an InGaAs quantum dot.

We apply an InGaAs quantum dot based single-photon source for the absolute detection efficiency calibration of a silicon single-photon avalanche diode operating in Geiger mode. The single-photon source delivers up to (2.55 ± 0.02) × 106 photons per second inside a multimode fiber at the wavelength of 929.8 nm for above-band pulsed excitation with a repetition rate of 80 MHz. The purity of the single-photon emission, expressed by the value of the 2nd order correlation function g(2)(τ = 0), is between 0.14 and 0.24 depending on the excitation power applied to the quantum dot. The single-photon flux is sufficient to be measured with an analog low-noise reference detector, which is traceable to the national standard for optical radiant flux. The measured detection efficiency using the single-photon source remains constant within the measurement uncertainty for different photon fluxes. The corresponding weighted mean thus amounts to 0.3263 with a standard uncertainty of 0.0022.

Intensity-corrected 4D light-in-flight imaging.

Light-in-flight (LIF) imaging is the measurement and reconstruction of light's path as it moves and interacts with objects. It is well known that relativistic effects can result in apparent velocities that differ significantly from the speed of light. However, less well known is that Rayleigh scattering and the effects of imaging optics can lead to observed intensities changing by several orders of magnitude along light's path. We develop a model that enables us to correct for all of these effects, thus we can accurately invert the observed data and reconstruct the true intensity-corrected optical path of a laser pulse as it travels in air. We demonstrate the validity of our model by observing the photon arrival time and intensity distribution obtained from single-photon avalanche detector (SPAD) array data for a laser pulse propagating towards and away from the camera. We can then reconstruct the true intensity-corrected path of the light in four dimensions (three spatial dimensions and time).

Method for calibration of SPAD detectors using photon time of arrival statistics

Single-photon Avalanche Detectors (SPAD) are widely used in modern quantum optics experiments and applications. This work proposes an alternative method for calibrating SPADs by optical attenuation, based on the recognition of the statistical distribution of time intervals between consecutive detections.