Number Of Signal Photons Research Articles

Heisenberg-Limited Quantum Lidar for Joint Range and Velocity Estimation.

We propose a quantum lidar protocol to jointly estimate the range and velocity of a target by illuminating it with a single beam of pulsed displaced squeezed light. In the lossless scenario, we show that the mean-squared errors of both range and velocity estimations are inversely proportional to the squared number of signal photons, simultaneously attaining the Heisenberg limit. This is achieved by engineering the multiphoton squeezed state of the temporal modes and adopting standard homodyne detection. To assess the robustness of the quantum protocol, we incorporate photon losses and detuning of the homodyne receiver. Our findings reveal a quantum advantage over the best-known classical strategy across a wide range of round-trip transmissivities. Particularly, the quantum advantage is substantial for sufficiently small losses, even when compared to the optimal-potentially unattainable-classical performance limit. The quantum advantage also extends to the practical case where quantum engineering is done on top of a strong classical coherent state with watts of power. This, together with the robustness against losses and the feasibility of the measurement with state-of-the-art technology, make the protocol highly promising for near-term implementation.

Implementation of large angle low error non-line-of-sight ultraviolet communication system

Due to the strong scattering of ultraviolet (UV) communication, it is particularly suitable for scenarios involving short distance and large angle scattering, such as communication between buildings and jungles. In this paper, a system based on a single scattering model and a discrete Poisson channel pulse counting signal processing algorithm is constructed, and the effects of the number of signal photons, noise photons, and elevation angle on the system's bit error rate (BER) are simulated and analyzed. The effect of sampling rate on the system's performance is numerically analyzed. The results show that the pulse counting algorithm is suitable for systems with a small number of signal photons and a high sampling rate. The BER of the system when the number of signal photons becomes large is more dependent on the sampling rate than the signal-to-noise ratio. Additionally, we designed an outdoor test system including hardware system, pulse counting, synchronization and data recovery algorithms. The test results are consistent with the simulation results. The communication rate of the outdoor system is designed to be 10 kbps at a distance of 50 m. The BER is 10-3 when the elevation angle is 85°, while the BER is 10-5 when the elevation angle is 50°.

Performance Analysis of Classical Data Transmission Over a Quantum Channel in the Presence of Atmospheric Turbulence

This paper presents the performance analysis of classical data transmission over a quantum channel in the presence of atmospheric turbulence. To transmit classical data, quantum coherent states are modulated over a log-normal turbulent channel for satellite-to-ground applications. The expression for the number of photons in the turbulent coherent state is approximated. Performance analysis is done in terms of error probability, channel capacity, and quantum bit error rate (QBER). The simulation results are presented using the Monte-Carlo simulation method. Numerical results show that the error performance improves with increasing the number of signal photons. However, for turbulence strength greater than 0.8, QBER increases more rapidly with a higher number of signal photons. Hence, a trade-off is essential between an achievable QBER and the number of signal photons.

Suppressing the influence of GM-APD coherent lidar saturation by signal modulation

Geiger-mode Avalanche Photo Diode (GM-APD) coherent lidar improves coherent detection sensitivity to single photon level, which is more suitable for remote target detection. However, due to the limited pixels, the photon count will be affected by the system saturation, resulting in low utilization of local oscillator (LO), reducing the system's signal-to-noise ratio (SNR). A GM-APD coherent lidar system based on signal modulation is proposed, the method uses an electro-optic modulator to modulate the slope of signal light, then GM-APD coherent detection. Firstly, the detection and optimal parameter model based on signal modulation are derived. Secondly, the effectiveness of this system is analyzed through simulation. Finally, GM-APD coherent detection experiment based on signal modulation is carried out to verify the effectiveness of the system. When the echo position is 2 μs, the pulse width is 200 ns, the number of signal photons is about 8000, LO photons is about 820, signal modulation improves the system SNR by more than two times. It is concluded that the greater influence of saturation on GM-APD coherent lidar, the better signal modulation effect. The proposed scheme improves the utilization rate of LO and SNR from equipment level, to further enhance system detection ability.

Radiometric Correction Model and Land Cover Classification of Snow-Covered Terrains for ICESat-2 Photon-Counting Lidar

The signal strength is a fundamental parameter in radiometric applications for satellite lidars. Different from full-waveform lidars, photon-counting lidars cannot record the returned signal strength but only respond to the presence of the photon event and may miss some returned photons due to the dead time effect, i.e., introduce radiometric distortion. Based on the lidar equation and the response mechanism of photon-counting detectors, we propose a radiometric correction model to remove the impact of the nonlinear response and dead time of detectors for the photon-counting lidar borne on ICESat-2. The returned signal photon number is corrected by the proposed model with respect to the photon event number per shot (PNPS) and surface slope derived from ATL03/ATL08 products. Then, the optical throughput calibration factor of ICESat-2 is obtained from ATL06 products over high Antarctic plateau where has given reflectance and clear atmosphere, which is generally equal to 0.52. The atmospheric attenuation induced by the molecular, cloud, and aerosol is calculated from ATL09 products. In addition, the corrected radiometric parameters including the calculated surface reflectance and apparent surface reflectance (ASR) are applied to classify land cover types along laser tracks over snow-covered terrains. The results indicate that the signal strength and calibration constant are reliable after corrections, but the atmospheric attenuation is sometimes inaccurate, which further influences the derived surface reflectance. In classifications, the overall accuracy and Kappa coefficient based on the corrected ASR can achieve the best classification results with 88.80% and 0.69. The proposed radiometric correction model is very essential to radiometric applications for photon-counting lidars such as ICESat-2, especially for data captured on ice and bare land with relatively high reflectance.

Graph Neural Networks for low-energy event classification & reconstruction in IceCube

IceCube, a cubic-kilometer array of optical sensors built to detect atmospheric and astrophysical neutrinos between 1 GeV and 1 PeV, is deployed 1.45 km to 2.45 km below the surface of the ice sheet at the South Pole. The classification and reconstruction of events from the in-ice detectors play a central role in the analysis of data from IceCube. Reconstructing and classifying events is a challenge due to the irregular detector geometry, inhomogeneous scattering and absorption of light in the ice and, below 100 GeV, the relatively low number of signal photons produced per event. To address this challenge, it is possible to represent IceCube events as point cloud graphs and use a Graph Neural Network (GNN) as the classification and reconstruction method. The GNN is capable of distinguishing neutrino events from cosmic-ray backgrounds, classifying different neutrino event types, and reconstructing the deposited energy, direction and interaction vertex. Based on simulation, we provide a comparison in the 1 GeV–100 GeV energy range to the current state-of-the-art maximum likelihood techniques used in current IceCube analyses, including the effects of known systematic uncertainties. For neutrino event classification, the GNN increases the signal efficiency by 18% at a fixed background rate, compared to current IceCube methods. Alternatively, the GNN offers a reduction of the background (i.e. false positive) rate by over a factor 8 (to below half a percent) at a fixed signal efficiency. For the reconstruction of energy, direction, and interaction vertex, the resolution improves by an average of 13%–20% compared to current maximum likelihood techniques in the energy range of 1 GeV–30 GeV. The GNN, when run on a GPU, is capable of processing IceCube events at a rate nearly double of the median IceCube trigger rate of 2.7 kHz, which opens the possibility of using low energy neutrinos in online searches for transient events.

Search for sub-eV axion-like particles in a stimulated resonant photon-photon collider with two laser beams based on a novel method to discriminate pressure-independent components

Sub-eV axion-like particles (ALPs) have been searched for by focusing two-color near-infrared pulse lasers into a vacuum along a common optical axis. Within the focused quasi-parallel collision system created by combining a creation field (2.5 mJ/47 fs Ti:Sapphire laser) and a background inducing field (1.5 mJ/9 ns Nd:YAG laser), the detection of signal photons via stimulated resonant photon-photon scattering by exchanging ALPs was attempted in a vacuum chamber. The signal wavelength can be determined via energy-momentum conservation in the vacuum, and it coincides with that determined from the atomic four-wave-mixing (aFWM) process. In this work, the pulse energies were one order of magnitude higher than those in the previous search, allowing aFWM from optical elements to be observed as a pressure-independent background for the first time, in addition to the residual-gas-originating aFWM following a quadratic pressure dependence. In principle the four-wave-mixing process in vacuum via ALP exchanges (vFWM) must also be pressure-independent, so the development of a new method for discriminating the optical-element aFWM is indispensable for increasing the pulse energies to the values needed for future upgraded searches. In this paper, we will present the established method for quantifying the yield from the optical-element aFWM process based on the beam cross- section dependence. With the new method, the number of signal photons was found to be consistent with zero. We then successfully obtained a new exclusion region in the relation between ALP-photon coupling, g/M, and the ALP mass m, reaching the most sensitive point g/M = 1.14 × 10−5 GeV−1 at m = 0.18 eV.

Analysis of the performance of a polarized LiDAR imager in fog.

This paper focuses on exploring ways to improve the performance of LiDAR imagers through fog. One of the known weaknesses of LiDAR technology is the lack of tolerance to adverse environmental conditions, such as the presence of fog, which hampers the future development of LiDAR in several markets. Within this paper, a LiDAR unit is designed and constructed to be able to apply temporal and polarimetric discrimination for detecting the number of signal photons received with detailed control of its temporal and spatial distribution under co-polarized and cross-polarized configurations. The system is evaluated using different experiments in a macro-scale fog chamber under controlled fog conditions. Using the complete digitization of the acquired signals, we analyze the natural light media response, to see that due to its characteristics it could be directly filtered out. Moreover, we confirm that there exists a polarization memory effect, which, by using a polarimetric cross-configuration detector, allows improvement of object detection in point clouds. These results are useful for applications related to computer vision, in fields like autonomous vehicles or outdoor surveillance where many variable types of environmental conditions may be present.

A photon-number-based systematic algorithm for range image recovery of GM-APD lidar under few-frames detection

The GM-APD lidar can detect the single-photon level echo signal and obtain three-dimensional range information, but the imaging results are greatly affected by noise and statistical frame number. Considering these problems, this paper proposes a photon-number systematic (PNS) algorithm under a few statistical frames in low SNR (signal-to-noise ratio). It includes three parts: (a) We realize range image recovery based on the signal photon number histogram with a match filtering algorithm by using the proposed normalized discrete waveform functions. (b) We propose a two-dimensional double-threshold approximation denoising algorithm, which is used for image-level denoising. (c) The neighborhood threshold smoothing algorithm is proposed to supplement the target missing pixels. It is verified by Monte Carlo simulation and experimental results that the proposed algorithm has a high recovery ratio, denoising, and fidelity performance under few-frames detection in different SNRs conditions. The experimental largest target recovery ratio of the proposed algorithm is about 92%, the peak signal-to-noise ratio exceeds 16.4, and the maximum average measure of structural similarity is more than 85% under 500 statistical frames. This paper provides a new processing scheme for GM-APD lidar range image recovery under few-frames detection and low SNR, it lays the foundation for real-time and all-day monitoring.

Coupling effects of the sum-frequency process and difference-frequency process on upconversion terahertz-wave detection via a DAST crystal.

Frequency upconversion technology with good performance including high sensitivity, fast response, and room-temperature operation is a promising method for terahertz-wave detection. The sum-frequency conversion and difference-frequency conversion jointly affect the detection ability for upconversion detection using organic crystals as nonlinear media. The concurrence of both processes has been ignored in past studies, which results in discrepancies between theoretical simulations and experimental results. In this paper, four-wave interaction equations involving two nonlinear conversion processes are proposed, and the effect of the sum-frequency process is analyzed in upconversion terahertz-wave detection via a 4-dimethylamino-N-methyl-4-stilbazolium tosylate (DAST) crystal. The ratio of the sum-frequency signal to the difference-frequency signal varies for different terahertz frequencies and crystal thicknesses. Experiments suggest that theoretical simulations are good at predicting physical processes. Under certain conditions, the detection efficiency can be improved by simultaneously utilizing the two signals. The total signal photon number is not sensitive to the crystal thickness. Furthermore, the theoretical exploration of terahertz single-photon detection provides a noteworthy reference for future experiments.

Scattering loss in precision metrology due to mirror roughness.

Optical losses degrade the sensitivity of laser interferometric instruments. They reduce the number of signal photons and introduce technical noise associated with diffuse light. In quantum-enhanced metrology, they break the entanglement between correlated photons. Such decoherence is one of the primary obstacles in achieving high levels of quantum noise reduction in precision metrology. In this work, we compare direct measurements of cavity and mirror losses in the Caltech 40 m gravitational-wave detector prototype interferometer with numerical estimates obtained from semi-analytic intra-cavity wavefront simulations using mirror surface profile maps. We show a unified approach to estimating the total loss in optical cavities (such as the LIGO gravitational detectors) that will lead towards the engineering of systems with minimum decoherence for quantum-enhanced precision metrology.

Spatially modulated scene illumination for intensity-compensated two-dimensional array photon-counting LiDAR imaging

Photon-counting LiDAR using a two-dimensional (2D) array detector has the advantages of high lateral resolution and fast acquisition speed. The non-uniform intensity profile of the illumination beam and non-uniform quantum efficiency of the detectors in the 2D array deteriorate the imaging quality. Herein, we propose a photon-counting LiDAR system that uses a spatial light modulator to control the spatial intensity to compensate for both the non-uniform intensity profile of the illumination beam, and the variation in the quantum efficiency of the detectors in the 2D array. By using a 635 nm peak wavelength and 4 mW average power semiconductor laser, lab-based experiments at a 4.27 m stand-off distance are performed to verify the effectiveness of the proposed method. Compared with the unmodulated method, the standard deviation of the intensity image of the proposed method is reduced from 0.109 to 0.089 for a whiteboard target, with an average signal photon number of 0.006 per pixel.

Effects of ocean turbulence on photon orbital angular momentum quantum communication

The effect of the turbulent motion of ocean on the quantum communication based on the orbital angular momentum in an underwater quantum channel is studied in this work. Based on the power spectrum model of ocean turbulence proposed by Elamassie, the quantitative relationships of different ocean turbulence parameters with the single photon detection probability of orbital angular momentum photons, the channel capacity, the key generation rate, the concurrence of two entangled photons are proposed. The maximum entanglement distance of the orbital angular momentum entangled photon-pairs in the ocean turbulence is further studied by the universal entanglement decay of the concurrence of entangled photon-pairs in the ocean turbulence. The results show that the detection probability of single photon, the channel capacity, the key generation rate, and the concurrence of entangled photon-pairs decrease with the increase of the dissipation rate of turbulent kinetic energy and the decrease of the rate of dissipation of mean-squared temperature. The influence of the temperature and salinity balance parameter of ocean turbulence on the performance of underwater quantum communication are significantly different under the condition of whether the stable stratification of seawater is assumed or not. In the ocean turbulent environment, the increasing of the initial orbital angular momentum quantum number of signal photons can improve the key generation rate of quantum key distribution and the resistance of entangled photons to entanglement decay.

On‐Orbit Radiometric Performance on ICESat‐2

AbstractNASA's ICESat‐2 mission measures Earth's elevation with the Advanced Topographic Laser Altimeter System (ATLAS), a 6‐beam photon‐counting laser altimeter. The Global Geolocated Photon data product (ATL03) is the primary source of photon information used by surface‐type‐specific higher‐level products, along with the Atmospheric Layer Characteristics product (ATL09). ATL03 provides time‐tagged, geolocated photon heights referenced to the ellipsoid and a parameter providing an initial classification of photon events as signal or background. We use this classification to evaluate ATLAS radiometry (number of signal photons per transmitted laser pulse) over short time scales and over the mission to date. The radiometric performance of ATLAS will in part determine what differences in the signal and background photon rates are significant and indicate geophysical, rather than instrumental, changes. We find the ATLAS radiometry is very stable over short time scales and exhibits a long‐term decrease of ∼1 signal photon per laser pulse (∼−12%) in the strong spots over the first 1.5 years of the mission.

Theoretical model considering optimal ranging performance and energy efficiency for photon-counting lidars with multiple detectors

With an orbital speed of several kilometers per second, space-borne photon-counting lidars can only perform several to a few tens of measurements on the same target. The ranging uncertainty can exceed tens of centimeters with a pulse width of several nanoseconds and has a great impact on the total ranging error. When multiple photons are recorded (using multiple detectors) in a single laser shot, the ranging uncertainty can be effectively suppressed by the average method. Higher signal levels (receiving more photons) introduce a better ranging uncertainty, but a worse ranging bias is caused by the dead time effect of photon-counting detectors. In this study, a theoretical ranging performance model is proposed to address that question: What signal levels and how many detectors are the optimum selection to achieve a better ranging performance? A photon-counting lidar system with four photomultiplier tubes is used to verify the proposed ranging performance model. Experiments are conducted under nine sets of different signal levels, and the ranging performance of experiment results agree well with the theoretical predictions. The average residual error is 0.31 cm and all error ratios are less than 10%. The energy efficiency and ranging uncertainty are further quantitatively analyzed. When multiple detectors are employed, the total ranging error (i.e., the root sum square of the ranging bias and ranging uncertainty) has the minimum value. For a space-borne photon-counting lidar, the expected signal photon number in each detector is recommended as 0.5∼1 (wasting a small part of the received energy). With a 4×4 detector array and a received pulse width of 1.5 ns, the total ranging error can reach approximately 5 cm when the expected signal photon number is close to 10. This theoretical model is essential in estimating the ranging performance for a give photon-counting lidar and in optimizing the design of lidar system parameters.

Signal Photon Extraction Method for Weak Beam Data of ICESat-2 Using Information Provided by Strong Beam Data in Mountainous Areas

The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) can measure the elevations of the Earth’s surface using a sampling strategy with unprecedented spatial detail. In the daytime of mountainous areas where the signal–noise ratio (SNR) of weak beam data is very low, current algorithms do not always perform well on extracting signal photons from weak beam data (i.e., many signal photons were missed). This paper proposes an effective algorithm to extract signal photons from the weak beam data of ICESat-2 in mountainous areas. First, a theoretical equation of SNR for ICESat-2 measured photons in mountainous areas was derived to prove that the available information provided by strong beam data can be used to assist the signal extraction of weak beam data (that may have very low SNR in mountainous areas). Then, the relationship between the along-track slope and the noise level was used as the bridge to connect the strong and weak beam data. To be specific, the along-track slope of the weak beam was inversed by the slope–noise relationship obtained from strong beam data, and then was used to rotate the direction of the searching neighborhood in the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. With the help of this process, the number of signal photons included in the searching neighborhood will significantly increase in mountainous areas and will be easily detected from the measured noisy photons. The proposed algorithm was tested in the Tibetan Plateau, the Altun Mountains, and the Tianshan Mountains in different seasons, and the extraction results were compared with the results from the ATL03 datasets, the ATL08 datasets, and the classical DBSCAN algorithm. Based on the ground-truth signal photons obtained by visual inspection, the parameters of the classification precision, recall, and F-score of our algorithm and three other algorithms were calculated. The modified DBSCAN could achieve a good balance between the classification precision (93.49% averaged) and recall (89.34% averaged), and its F-score (more than 0.91) was higher than that of the other three methods, which successfully obtained a continuous surface profile from weak beam data with very low SNRs. In the future, the detected signal photons from weak beam data are promising to assess the elevation accuracy achieved by ICESat-2, estimate the along-track and cross-track slope, and further obtain the ground control points (GCPs) for stereo-mapping satellites in mountainous areas.

Interferometric speckle visibility spectroscopy (ISVS) for human cerebral blood flow monitoring

Infrared light scattering methods have been developed and employed to non-invasively monitor human cerebral blood flow (CBF). However, the number of reflected photons that interact with the brain is low when detecting blood flow in deep tissue. To tackle this photon-starved problem, we present and demonstrate the idea of interferometric speckle visibility spectroscopy (ISVS). In ISVS, an interferometric detection scheme is used to boost the weak signal light. The blood flow dynamics are inferred from the speckle statistics of a single frame speckle pattern. We experimentally demonstrated the improvement in the measurement of fidelity by introducing interferometric detection when the signal photon number is low. We apply the ISVS system to monitor the human CBF in situations where the light intensity is ∼100-fold less than that in common diffuse correlation spectroscopy (DCS) implementations. Due to the large number of pixels (∼2 × 105) used to capture light in the ISVS system, we are able to collect a similar number of photons within one exposure time as in normal DCS implementations. Our system operates at a sampling rate of 100 Hz. At the exposure time of 2 ms, the average signal photoelectron number is ∼0.95 count/pixel, yielding a single pixel interferometric measurement signal-to-noise ratio (SNR) of ∼0.97. The total ∼2 × 105 pixels provide an expected overall SNR of 436. We successfully demonstrate that the ISVS system is able to monitor the human brain pulsatile blood flow, as well as the blood flow change when a human subject is doing a breath-holding task.

Enhancing quantum vacuum signatures with tailored laser beams

We demonstrate that tailored laser beams provide a powerful means to make quantum vacuum signatures in strong electromagnetic fields accessible in experiment. Typical scenarios aiming at the detection of quantum vacuum nonlinearities at the high-intensity frontier envision the collision of focused laser pulses. The effective interaction of the driving fields mediated by vacuum fluctuations gives rise to signal photons encoding the signature of quantum vacuum nonlinearity. Isolating a small number of signal photons from the large background of the driving laser photons poses a major experimental challenge. The main idea of the present work is to modify the far-field properties of a driving laser beam to exhibit a fieldfree hole in its center, thereby allowing for an essentially backgroundfree measurement of the signal scattered in the forward direction. Our explicit construction makes use of a peculiar far-field/focus duality.

Closed-Form Density Matrices of Free-Space Optical Quantum Communications in Turbulent Channels

A closed-form expression is derived for the received density matrix of the free-space optical quantum communication over the gamma-gamma turbulence channels. A truncation method based on root-mean-square error is proposed to facilitate the calculation of the received density matrix. The required minimum matrix size and minimum number of terms for calculating the received density matrix under various channel conditions are obtained. These results can provide a benchmark for choosing these two parameters in practical implementations. The computation efficiency of the proposed truncation method can be more than 30 times higher than that of the integration method. Besides, we find a convergent property of the required minimum number of terms in the truncation method as the number of signal photons increases.

Sensitive Infrared Photon Counting Detection by Nondegenerate Two-Photon Absorption in Si APD

We report on the sensitive detection of photons at broadband infrared wavelengths based on the nondegenerate two-photon absorption in the Si avalanche photodiodes. The detected 1700~1850 nm infrared photon energy is lower than Si band gap and the energy difference is complemented by a high intensity pump laser field at 1550 nm. It is thus possible to capitalize on the low noise property of large band gap materials for detecting low energy photons. And the linear intensity response of the detector to the incident infrared photons was observed when the power of pump laser was about $12.42\mu $ W, indicating the dominance of nondegenerate two-photon absorption in the infrared photon detection. An enhancement factor of 20 was observed for the incident signal photon numbers of $\sim 0.14\times 10^{\mathbf {6}}$ photons per pulse. We offer an alternative to sensitive detection of infrared light. This may also provide new ideas for broadband infrared photon detection in different applications such as optical comb laser ranging, infrared bio-image and so forth.