Optical imaging by means of two-photon quantum entanglement

Polarization-entangled photon-pair source using beam displacers and thin crystals

We present an experimental implementation of a polarization-entangled photon-pair source based on beam displacers. The down-converted photons are emitted via spontaneous parametric downconversion in a non-degenerate and type-0 process. We obtain a state fidelity of F = 0.975 ± 0.004 and violate a Clauser-Horne-Shimony-Holt (CHSH) inequality with $\mathcal {S}=2.75\pm 0.01$. Our source also uses thin crystals for applications in quantum imaging, taking advantage of the large number of spatial modes. We estimate that our source could produce 550 ± 12 spatial modes.

SNR analysis of a multi-channel temporal correlation scheme in quantum-enhanced target detection

In lossy and noisy environments, quantum-enhanced target detection based on temporal quantum correlation encounters low signal-to-noise ratio (SNR), resulting in poor detection performance. To address these challenges, we propose a multi-channel temporal correlation scheme. In this scheme, signal photons from multiple independent entangled sources illuminate the target and arrive at the same detector. Coincidences are obtained by correlation measurements of the entangled photons on one signal path and different reference paths. We then propose a weighted average processing method for fusing the coincidences to obtain higher SNR. The relationship between the SNR and the number of sources is analyzed for different background noise levels. It is shown that the SNR increases as the number of sources increases, but eventually approaches a limit. Experimental results verify the correction of our theoretical analysis.

Simultaneous imaging and element differentiation by energy-resolved x-ray absorption ghost imaging

Based on the x-ray absorption edges of different elements, we simultaneously image and distinguish the composition of three differently shaped components of an object by using energy-resolved x-ray absorption ghost imaging (GI). The initial x-ray beam is spatially modulated by a series of Hadamard matrix masks, and the object is composed of three pieces of Mo, Ag, and Sn foil in the shape of a triangle, square, and circle, respectively. The transmitted x-ray intensity is measured by an energy-resolved single-pixel detector with a spectral resolution better than 0.8 keV. Through correlation of the transmission spectra with the corresponding Hadamard patterns, the spectral image of the sample is reconstructed, with a spatial resolution of 108 µm. Our experiment demonstrates a practical application of spectral ghost imaging, which has important potential for the noninvasive analysis of material composition and distribution in biology, medical science, and many other fields.

Scalable High-Resolution Single-Pixel Imaging via Pattern Reshaping

Single-pixel imaging (SPI) is an alternative method for obtaining images using a single photodetector, which has numerous advantages over the traditional matrix-based approach. However, most experimental SPI realizations provide relatively low resolution compared to matrix-based imaging systems. Here, we show a simple yet effective experimental method to scale up the resolution of SPI. Our imaging system utilizes patterns based on Hadamard matrices, which, when reshaped to a variable aspect ratio, allow us to improve resolution along one of the axes, while sweeping of patterns improves resolution along the second axis. This work paves the way towards novel imaging systems that retain the advantages of SPI and obtain resolution comparable to matrix-based systems.

Characterizing Biphoton Spatial Wave Function Dynamics with Quantum Wavefront Sensing

With an extremely high dimensionality, the spatial degree of freedom of entangled photons is a key tool for quantum foundation and applied quantum techniques. To fully utilize the feature, the essential task is to experimentally characterize the multiphoton spatial wave function including the entangled amplitude and phase information at different evolutionary stages. However, there is no effective method to measure it. Quantum state tomography is costly, and quantum holography requires additional references. Here, we introduce quantum Shack-Hartmann wavefront sensing to perform efficient and reference-free measurement of the biphoton spatial wave function. The joint probability distribution of photon pairs at the back focal plane of a microlens array is measured and used for amplitude extraction and phase reconstruction. In the experiment, we observe that the biphoton amplitude correlation becomes weak while phase correlation shows up during free-space propagation. Our work is a crucial step in quantum physical and adaptive optics and paves the way for characterizing quantum optical fields with high-order correlations or topological patterns.

Speckled-speckle field as a resource for imaging techniques

Correlated states of light, both classical and quantum, can find useful applications in the implementation of several imaging techniques. Among the employed sources, pseudo-thermal states, generated by the passage of a laser beam through a diffuser, represent the standard choice. To produce light with a higher level of correlation, in this work we consider and characterize the speckled-speckle field obtained with two diffusers using both a numerical simulation and an experimental implementation. In order to discuss the potential usefulness of super-thermal light in imaging protocols, we analyze the behavior of some figures of merit, namely the contrast, the signal-to-noise ratio and the image resolution. The obtained results clarify the possible advantages offered by this kind of light, and at the same time better emphasize the reasons why it does not outperform pseudo-thermal light.

A W-Shaped Self-Supervised Computational Ghost Imaging Restoration Method for Occluded Targets

We developed a novel method based on self-supervised learning to improve the ghost imaging of occluded objects. In particular, we introduced a W-shaped neural network to preprocess the input image and enhance the overall quality and efficiency of the reconstruction method. We verified the superiority of our W-shaped self-supervised computational ghost imaging (WSCGI) method through numerical simulations and experimental validations. Our results underscore the potential of self-supervised learning in advancing ghost imaging.

A comparison between the measurement of quantum spatial correlations using qCMOS photon-number resolving and electron multiplying CCD camera technologies

Cameras with single-photon sensitivities can be used to measure the spatial correlations between the photon-pairs that are produced by parametric down-conversion. Even when pumped by a single-mode laser, the signal and idler photons are typically distributed over several thousand spatial modes yet strongly correlated with each other in their position and anti-correlated in their transverse momentum. These spatial correlations enable applications in imaging, sensing, communication, and optical processing. Here we show that, using a photon-number resolving camera, spatial correlations can be observed after only a few 10s of seconds of measurement time, thereby demonstrating comparable performance with previous single photon sensitive camera technologies but with the additional capability to resolve photon-number. Consequently, these photon-number resolving technologies are likely to find wide use in quantum, low-light, imaging systems.

Transmission of quantum-secured images

The secure transmission of an image can be accomplished by encoding the image information, securely communicating this information, and subsequently reconstructing the image. Alternatively, here we show how the image itself can be directly transmitted while ensuring that the presence of any eavesdropper is revealed in a way akin to quantum key distribution (QKD). We achieve this transmission using a photon-pair source with the deliberate addition of a thermal light source as background noise. One photon of the pair illuminates the object, which is masked from an eavesdropper by adding indistinguishable thermal photons, the other photon of the pair acts as a time reference with which the intended recipient can preferentially filter the image carrying photons from the background. These reference photons are themselves made sensitive to the presence of an eavesdropper by traditional polarisation-based QKD encoding. Interestingly the security verification is performed in the two-dimensional polarisation-basis, but the image information is encoded in a much higher-dimensional, hence information-rich, pixel basis. In our example implementation, our image comprises of 152 independent pixels. Beyond the secure transmission of images, our approach to the distribution of secure high-dimensional information may offer new high-bandwidth approaches to QKD.

Fast high quality computational ghost imaging based on saliency variable sampling detection

Fast computational ghost imaging with high quality and ultra-high-definition resolution reconstructed images has important application potential in target tracking, biological imaging and other fields. However, as far as we know, the resolution (pixels) of the reconstructed image is related to the number of measurements. And the limited resolution of reconstructed images at low measurement times hinders the application of computational ghost imaging. Therefore, in this work, a new computational ghost imaging method based on saliency variable sampling detection is proposed to achieve high-quality imaging at low measurement times. This method physically variable samples the salient features and realizes compressed detection of computational ghost imaging based on the salient periodic features of the bucket detection signal. Numerical simulation and experimental results show that the reconstructed image quality of our method is similar to the compressed sensing method at low measurement times. Even at 500 (sampling rate 0.76 % ) measurement times, the reconstructed image of the method still has the target features. Moreover, the 2160 × 4096 (4K) pixels ultra-high-definition resolution reconstructed images can be obtained at only a sampling rate of 0.11 % . This method has great potential value in real-time detection and tracking, biological imaging and other fields.

Robust bistatic ghost imaging with no physical synchronization

Ghost imaging (GI) requires each echo from the object being correctly matched with the corresponding illuminiation pattern. We proposed a way for such matching with no physical synchronization towards bistatic configuration. The illumination is dually encoded in spatial and time domain. With aperiodic waveform and progressive correlation, the echoes can be correctly located and images can be obtained. In the experiments, our scheme is verified under different levels of signal to noise ratios, as well as different intensity of crosstalk. Ghost imaging with two transmitters and one receiver is also demonstrated. With our method, it is also possible to improve the imaging speed with multiple sources.

Robust Classical and Quantum Polarimetry with a Single Nanostructured Metagrating

We formulate a new conceptual approach for one-shot complete polarization state measurement with nanostructured metasurfaces applicable to classical light and multiphoton quantum states by drawing on the principles of generalized quantum measurements based on positive operator-valued measures. Accurate polarization reconstruction from a combination of photon counts or correlations from several diffraction orders is robust with respect to even strong fabrication inaccuracies, requiring only a single classical calibration of the metasurface transmission. Furthermore, this approach operates with a single metagrating without interleaving, allowing for a reduction in metasurface size while preserving high transmission efficiency and output beam quality. We theoretically obtained original metasurface designs, fabricated the metasurface from amorphous silicon nanostructures deposited on glass, and experimentally confirmed accurate polarization reconstruction of laser beams. We also anticipate robust operation under changes in environmental conditions, opening new possibilities for space-based imaging and satellite optics.

Direct Observation of Sub-Poissonian Temporal Statistics in a Continuous Free-Electron Beam with Subpicosecond Resolution

We present a novel method to measure the arrival time statistics of continuous electron beams with subpicosecond resolution, based on the combination of an rf deflection cavity and fast single electron imaging. We observe Poissonian statistics within time bins from 100 to 2 ns and increasingly pronounced sub-Poissonian statistics as the time bin decreases from 2 ps to 340 fs. This 2D streak camera, in principle, enables femtosecond-level arrival time measurements, paving the way to observing Pauli blocking effects in electron beams and thus serving as an essential diagnostic tool toward degenerate electron beam sources for free-electron quantum optics.

High-quality coherent ghost imaging of a transmission target

When the test detector of ghost imaging (GI) is a point-like detector and the detector's transverse size is smaller than the transverse coherence length of the light field at the detection plane, this case is corresponding to coherent GI (CGI) and the imaging result recovered by traditional GI (TGI) reconstruction algorithm is usually bad for a transmission target. Here a CGI scheme of a transmission target is proposed and a corresponding CGI reconstruction algorithm is developed to stably recover the target's image. The validity of the proposed method is verified by both simulation and experiments. Both the simulation and experimental results demonstrate that the target's transmission function can be perfectly reconstructed by CGI. We also show that the imaging quality of CGI with a point-like detector is better than that of TGI with a bucket detector if detection noise exists in the sampling process. Performance comparisons between CGI reconstruction and TGI reconstruction are also discussed.

Vector-guided Fourier single-pixel imaging

The Fourier single-pixel imaging technique exhibits great potential for compressive imaging. However, the utilization of low sampling ratio can introduce unwanted ringing artifacts, thereby compromising the fidelity of reconstructed image detail. To address this issue, Vector guided Fourier single-pixel imaging (V-FSI) has been proposed. We analyze the statistical properties in the edge vector field derived from images with low sampling ratio. Based on this information, a tailored sampling map is designed to acquire the significant high-frequency components for image reconstruction. Experimental results demonstrate the remarkable effectiveness of the proposed V-FSI method in enhancing image quality. Notably, V-FSI exhibits exceptional capabilities in perceiving and preserving the details of the objects, particularly for objects characterized by pronounced periodicity and directionality.

Adaptive locating foveated ghost imaging based on affine transformation

Ghost imaging (GI) has been widely used in the applications including spectral imaging, 3D imaging, and other fields due to its advantages of broad spectrum and anti-interference. Nevertheless, the restricted sampling efficiency of ghost imaging has impeded its extensive application. In this work, we propose a novel foveated pattern affine transformer method based on deep learning for efficient GI. This method enables adaptive selection of the region of interest (ROI) by combining the proposed retina affine transformer (RAT) network with minimal computational and parametric quantities with the foveated speckle pattern. For single-target and multi-target scenarios, we propose RAT and RNN-RAT (recurrent neural network), respectively. The RAT network enables an adaptive alteration of the fovea of the variable foveated patterns spot to different sizes and positions of the target by predicting the affine matrix with a minor number of parameters for efficient GI. In addition, we integrate a recurrent neural network into the proposed RAT to form an RNN-RAT model, which is capable of performing multi-target ROI detection. Simulations and experimental results show that the method can achieve ROI localization and pattern generation in 0.358 ms, which is a 1 × 105 efficiency improvement compared with the previous methods and improving the image quality of ROI by more than 4 dB. This approach not only improves its overall applicability but also enhances the reconstruction quality of ROI. This creates additional opportunities for real-time GI.

Quantum ghost imaging of a vector field

Quantum ghost image technique utilizing position or momentum correlations between entangled photons can realize nonlocal reconstruction of the image of an object. In this work, based on polarization entanglement, we experimentally demonstrate quantum ghost imaging of vector images by using a geometric phase object. We also provide a corresponding theoretical analysis. Additionally, we offer a geometrical optics path explanation of ghost imaging for vector fields. The proposed strategy offers new insights into the fundamental development of ghost imaging and also holds great promise for developing complex structured ghost imaging techniques. Our work expanding the principle of ghost imaging to spatially varying vector beams will lead to interesting developments of this field.

Emission Ghost Imaging: reconstruction with data augmentation

Ghost Imaging enables 2D reconstruction of an object even though particles transmitted or emitted by the object of interest are detected with a single pixel detector without spatial resolution. This is possible because for the particular implementation of ghost imaging presented here, the incident beam is spatially modulated with a non-configurable attenuating mask whose orientation is varied (e.g. via transverse displacement or rotation) in the course of the ghost imaging experiment. Each orientation yields a distinct spatial pattern in the attenuated beam. In many cases, ghost imaging reconstructions can be dramatically improved by factoring the measurement matrix which consists of measured attenuated incident radiation for each of many orientations of the mask at each pixel to be reconstructed as the product of an orthonormal matrix Q and an upper triangular matrix R provided that the number of orientations of the mask (N ) is greater than or equal to the number of pixels (P ) reconstructed. For the N < P case, we present a data augmentation method that enables QR factorization of the measurement matrix. To suppress noise in the reconstruction, we determine the Moore-Penrose pseudoinverse of the measurement matrix with a truncated singular value decomposition approach. Since the resulting reconstruction is still noisy, we denoise it with the Adaptive Weights Smoothing method. In simulation experiments, our method outperforms a modification of an existing alternative orthogonalization method where rows of the measurement matrix are orthogonalized by the Gram-Schmidt method. We apply our ghost imaging methods to experimental X-ray fluorescence data acquired at Brookhaven National Laboratory.

Robust compressed ghost imaging against environmental influence factors

Ghost imaging based on sparse sampling is sensitive to the environmental influence factors frequently encountered in practice, such as instrumental drift and ambient light change, which could cause degradation of image quality. In this manuscript, we report a robust compressed sensing technique which could effectively reduce the influence of measurement errors on image quality. For demonstration purposes, we implement the proposed technique to ghost imaging, namely differential compressed sensing ghost imaging (DCSGI). By applying differential measurements n times, the first n Taylor expansion polynomials of the error could be eliminated in n-order DCSGI. It has been verified theoretically and experimentally that DCSGI works well with typical errors which exists in the realities of ghost imaging applications, while the conventional approach can hardly. In addition, the proposed technique may also replace conventional compressed sensing in other applications for anti-interference high-quality reconstruction.

Imaging privacy threats from an ambient light sensor

Embedded sensors in smart devices pose privacy risks, often unintentionally leaking user information. We investigate how combining an ambient light sensor with a device display can capture an image of touch interaction without a camera. By displaying a known video sequence, we use the light sensor to capture reflected light intensity variations partially blocked by the touching hand, formulating an inverse problem similar to single-pixel imaging. Because of the sensors' heavy quantization and low sensitivity, we propose an inversion algorithm involving an ℓp-norm dequantizer and a deep denoiser as natural image priors, to reconstruct images from the screen's perspective. We demonstrate touch interactions and eavesdropping hand gestures on an off-the-shelf Android tablet. Despite limitations in resolution and speed, we aim to raise awareness of potential security/privacy threats induced by the combination of passive and active components in smart devices and promote the development of ways to mitigate them.

Imaging objects hidden inside the strongly scattering media based on bidirectional ghost imaging

We demonstrate a novel, to the best of our knowledge, method for imaging objects hidden inside the strongly scattering media based on bidirectional ghost imaging (GI). In this method, GI is performed separately on both sides of the object, resulting in two GI results. Through an autocorrelation operation to the two GI results, the convolution between the autocorrelation of the object and the point spread function (PSF) of the strongly scattering media can be recovered. Therefore, the object can be recovered by obtaining the PSF of the strongly scattering media through noninvasive measurement or numerical calculation. Simulation and experimental results show that bidirectional ghost imaging (BGI) can reconstruct high-quality images, particularly when the thickness of the strongly scattering media greatly exceeds the scattering mean free path.

Generalized sub-Poissonian states of two-beam fields

Two-beam states obtained by partial photon-number-resolving detection in one beam of a multi-mode twin beam are experimentally investigated using an intensified CCD camera. In these states, sub-Poissonian photon-number distributions in one beam are accompanied by sub-shot-noise fluctuations in the photon-number difference of both beams. Multi-mode character of the twin beam implying the beam nearly Poissonian statistics is critical for reaching sub-Poissonian photon-number distributions, which contrasts with the use of a two-mode squeezed vacuum state. Relative intensities of both nonclassical effects as they depend on the generation conditions are investigated both theoretically and experimentally using photon-number distributions of these fields. Fano factor, noise-reduction parameter, local and global nonclassicality depths, degree of photon-number coherence, mutual entropy as a non-Gaussianity quantifier, and negative quasi-distributions of integrated intensities are used to characterize these fields. Spatial photon-pair correlations as means for improving the field properties are employed. These states are appealing for quantum metrology and imaging including the virtual-state entangled-photon spectroscopy.

Remote transport of high-dimensional orbital angular momentum states and ghost images via spatial-mode-engineered frequency conversion

The efficient transport and engineering of photonic orbital angular momentum (OAM) lie at the heart of various related classical and quantum applications. Here, by leveraging the spatial-mode-engineered frequency conversion, we realize the remote transport of high-dimensional orbital angular momentum (OAM) states between two distant parties without direct transmission of information carriers. We exploit perfect vortices for preparing high-dimensional yet maximal O AM entanglement. Based on nonlinear sum-frequency generation working with a strong coherent wave packet and a single photon, we conduct the Bell-like state measurements for high-dimensional perfect vortices. We experimentally achieve an average transport fidelity 0.879 ± 0.048 and 0.796 ± 0.066 for a complete set of 3-dimensional and 5-dimensional OAM mutually unbiased bases, respectively. Furthermore, by exploring the full transverse entanglement, we construct another strategy of quantum imaging with interaction-free light. It is expected that, with the future advances in nonlinear frequency conversion, our scheme will pave the way for realizing truly secure high-dimensional quantum teleportation in the upcoming quantum network.

Fast focusing method in ghost imaging with a tracking trajectory

The imaging environment is unstable for trembling disturbance, which is detrimental to object reconstruction. In this Letter, we experimentally investigated ghost imaging (GI) under a temporal trembling disturbance. The fast-focusing method based on imaging with small sampling measurements is proposed, and the theoretical model and algorithm are validated. It is demonstrated that the proposed method is effective to obtain a better-resolution image of the object under the strong trembling disturbance including a laboratory and a real trembling environment. The results provide a promising approach to deal with image degradation caused by an unstable environment and can find potential applications for ghost imaging in remote sensing.

Ghost imaging based on Fermat spiral laser array designed for remote sensing

We propose a Fermat spiral laser array as illumination source in ghost imaging. Due to the aperiodic structure, the Fermat spiral laser array generates illuminating light field without spatial periodicity on the normalized second-order intensity correlation function. A single-pixel detector is used to receive the signal light from object for image reconstruction. The effects of laser array parameters on the quality of ghost imaging are analyzed comprehensively. Through experimental demonstration, the Fermat spiral laser array successfully achieves ghost imaging with high quality by combining with the compressive sensing reconstruction algorithm. This method is expected to be applied in remote sensing by combining with phased and collimated fiber laser array equipped with the high emitting power and high-speed modulation frequency.

Optical authentication method based on correspondence ghost imaging

Ghost imaging technology has a great application potential in optical security because of its non-local characteristics. In this paper, on the basis of computational ghost imaging, an optical authentication scheme is proposed that utilizes the correspondence imaging technique for the preliminary reconstruction of the object image, and then authenticates the image by a nonlinear correlation algorithm. Different from the previous optical authentication schemes that usually adopted random selection of measurements, this authentication method consciously selects the bucket detector measurement values with large fluctuation and can achieve authentication using ultra-low data volumes less than 1% of the Nyquist limit. In brief, this scheme is easy to implement and has a simpler algorithm and higher stability, which is a tremendous advantage in practical optical authentication systems. The simulation and physical experimental results demonstrate the feasibility of the scheme.

Modeling the space-time correlation of pulsed twin beams

Entangled twin-beams generated by parametric down-conversion are among the favorite sources for imaging-oriented applications, due their multimodal nature in space and time. However, a satisfactory theoretical description is still lacking. In this work we propose a semi-analytic model which aims to bridge the gap between time-consuming numerical simulations and the unrealistic plane-wave pump theory. The model is used to study the quantum correlation and the coherence in the angle-frequency domain of the parametric emission, and demonstrates a [Formula: see text] growth of their size as the gain g increases, with a corresponding contraction of the space-time distribution. These predictions are systematically compared with the results of stochastic numerical simulations, performed in the Wigner representation, of the full model equations: an excellent agreement is shown even for parameters well outside the expected limit of validity of the model.

Probing exciton dynamics with spectral selectivity through the use of quantum entangled photons

Quantum light is increasingly recognized as a promising resource for developing optical measurement techniques. Particular attention has been paid to enhancing the precision of the measurements beyond classical techniques by using nonclassical correlations between quantum entangled photons. Recent advances in the quantum optics technology have made it possible to manipulate spectral and temporal properties of entangled photons, and photon correlations can facilitate the extraction of matter information with relatively simple optical systems compared to conventional schemes. In these respects, the applications of entangled photons to time-resolved spectroscopy can open new avenues for unambiguously extracting information on dynamical processes in complex molecular and materials systems. Here, we propose time-resolved spectroscopy in which specific signal contributions are selectively enhanced by harnessing nonclassical correlations of entangled photons. The entanglement time characterizes the mutual delay between an entangled twin and determines the spectral distribution of photon correlations. The entanglement time plays a dual role as the knob for controlling the accessible time region of dynamical processes and the degrees of spectral selectivity. In this sense, the role of the entanglement time is substantially equivalent to the temporal width of the classical laser pulse. The results demonstrate that the application of quantum entangled photons to time-resolved spectroscopy leads to monitoring dynamical processes in complex molecular and materials systems by selectively extracting desired signal contributions from congested spectra. We anticipate that more elaborately engineered photon states would broaden the availability of quantum light spectroscopy.

Advances in Ghost Imaging of Moving Targets: A Review

Ghost imaging is a novel imaging technique that utilizes the intensity correlation property of an optical field to retrieve information of the scene being measured. Due to the advantages of simple structure, high detection efficiency, etc., ghost imaging exhibits broad application prospects in the fields of space remote sensing, optical encryption transmission, medical imaging, and so on. At present, ghost imaging is gradually developing toward practicality, in which ghost imaging of moving targets is becoming a much-needed breakthrough link. At this stage, we can improve the imaging speed and improve the imaging quality to seek a more optimized ghost imaging scheme for moving targets. Based on the principle of moving target ghost imaging, this review summarizes and compares the existing methods for ghost imaging of moving targets. It also discusses the research direction and the technical challenges at the current stage to provide references for further promotion of the instantiation of ghost imaging applications.

High-fidelity and high-robustness free-space ghost transmission in complex media with coherent light source using physics-driven untrained neural network

It is well recognized that it is challenging to realize high-fidelity and high-robustness ghost transmission through complex media in free space using coherent light source. In this paper, we report a new method to realize high-fidelity and high-robustness ghost transmission through complex media by generating random amplitude-only patterns as 2D information carriers using physics-driven untrained neural network (UNN). The random patterns are generated to encode analog signals (i.e., ghost) without any training datasets and labeled data, and are used as information carriers in a free-space optical channel. Coherent light source modulated by the random patterns propagates through complex media, and a single-pixel detector is utilized to collect light intensities at the receiving end. A series of optical experiments have been conducted to verify the proposed approach. Experimental results demonstrate that the proposed method can realize high-fidelity and high-robustness analog-signal (ghost) transmission in complex environments, e.g., around a corner, or dynamic and turbid water. The proposed approach using the designed physics-driven UNN could open an avenue for high-fidelity free-space ghost transmission through complex media.

Learning-based correction with Gaussian constraints for ghost imaging through dynamic scattering media

In this Letter, we propose a learning-based correction method to realize ghost imaging (GI) through dynamic scattering media using deep neural networks with Gaussian constraints. The proposed method learns the wave-scattering mechanism in dynamic scattering environments and rectifies physically existing dynamic scaling factors in the optical channel. The corrected realizations obey a Gaussian distribution and can be used to recover high-quality ghost images. Experimental results demonstrate effectiveness and robustness of the proposed learning-based correction method when imaging through dynamic scattering media is conducted. In addition, only the half number of realizations is needed in dynamic scattering environments, compared with that used in the temporally corrected GI method. The proposed scheme provides a novel, to the best of our knowledge, insight into GI and could be a promising and powerful tool for optical imaging through dynamic scattering media.

3D quantum ghost imaging

We present current results of a novel, to the best of our knowledge, type of setup for quantum ghost imaging based on asynchronous single photon timing using single photon avalanche diode (SPAD) detectors, first presented in [Appl. Opt.60, F66 (2021)APOPAI0003-693510.1364/AO.423634]. The scheme enables photon pairing without fixed delays and, thus, overcomes some limitations of the widely used heralded setups for quantum ghost imaging [Nat. Commun.6, 5913 (2015)NCAOBW2041-172310.1038/ncomms6913]. It especially allows three-dimensional (3D) imaging by direct time of flight methods, the first demonstration of which will be shown here. To our knowledge, it is also the first demonstration of 3D quantum ghost imaging at all.

Correlated-photon imaging at 10 volumetric images per second

The correlation properties of light provide an outstanding tool to overcome the limitations of traditional imaging techniques. A relevant case is represented by correlation plenoptic imaging (CPI), a quantum-inspired volumetric imaging protocol employing spatio-temporally correlated photons from either entangled or chaotic sources to address the main limitations of conventional light-field imaging, namely, the poor spatial resolution and the reduced change of perspective for 3D imaging. However, the application potential of high-resolution imaging modalities relying on photon correlations is limited, in practice, by the need to collect a large number of frames. This creates a gap, unacceptable for many relevant tasks, between the time performance of correlated-light imaging and that of traditional imaging methods. In this article, we address this issue by exploiting the photon number correlations intrinsic in chaotic light, combined with a cutting-edge ultrafast sensor made of a large array of single-photon avalanche diodes (SPADs). This combination of source and sensor is embedded within a novel single-lens CPI scheme enabling to acquire 10 volumetric images per second. Our results place correlated-photon imaging at a competitive edge and prove its potential in practical applications.

Approximating the uncertainty of deep learning reconstruction predictions in single-pixel imaging

Single-pixel imaging (SPI) has the advantages of high-speed acquisition over a broad wavelength range and system compactness. Deep learning (DL) is a powerful tool that can achieve higher image quality than conventional reconstruction approaches. Here, we propose a Bayesian convolutional neural network (BCNN) to approximate the uncertainty of the DL predictions in SPI. Each pixel in the predicted image represents a probability distribution rather than an image intensity value, indicating the uncertainty of the prediction. We show that the BCNN uncertainty predictions are correlated to the reconstruction errors. When the BCNN is trained and used in practical applications where the ground truths are unknown, the level of the predicted uncertainty can help to determine whether system, data, or network adjustments are needed. Overall, the proposed BCNN can provide a reliable tool to indicate the confidence levels of DL predictions as well as the quality of the model and dataset for many applications of SPI.

BER performance of an FSOC system over atmospheric turbulence channels based on computational temporal ghost imaging

In a free space optical communication (FSOC) system, atmospheric turbulence will increase the bit error ratio (BER) and impair FSOC link reliability. Since computational temporal ghost imaging (CTGI) has anti-interference, we present an FSOC system over atmospheric turbulence based on CTGI. The simulation results show that the BER performance of CTGI is better than on-off keying under different atmospheric turbulence regimes. To improve the performance of the CTGI scheme, the influence of the number of transmission samples and code length is analyzed. It is shown that BER performance improves with the increment of the number of samples, while code length has no impact. This scheme provides an idea for reliable communication over atmospheric turbulence and an important reference for improving wireless optical communication in an extreme environment.

High-quality and high-diversity conditionally generative ghost imaging based on denoising diffusion probabilistic model

Deep-learning (DL) methods have gained significant attention in ghost imaging (GI) as promising approaches to attain high-quality reconstructions with limited sampling rates. However, existing DL-based GI methods primarily emphasize pixel-level loss and one-to-one mapping from bucket signals or low-quality GI images to high-quality images, tending to overlook the diversity in image reconstruction. Interpreting image reconstruction from the perspective of conditional probability, we propose the utilization of the denoising diffusion probabilistic model (DDPM) framework to address this challenge. Our designed method, known as DDPMGI, can not only achieve better quality but also generate reconstruction results with high diversity. At a sampling rate of 10%, our method achieves an average PSNR of 21.19 dB and an SSIM of 0.64, surpassing the performance of other comparison methods. The results of physical experiments further validate the effectiveness of our approach in real-world scenarios. Furthermore, we explore the potential application of our method in color GI reconstruction, where the average PSNR and SSIM reach 20.055 dB and 0.723, respectively. These results highlight the significant advancements and potential of our method in achieving high-quality image reconstructions in GI, including color image reconstruction.

High-resolution self-corrected single-pixel imaging through dynamic and complex scattering media

Imaging with single-pixel detectors becomes attractive in many applications where pixelated detectors are not available or cannot work. Based on a correlation between the probing patterns and the realizations, optical imaging with single-pixel detector offers an indirect way to recover a sample. It is well recognized that single-pixel optical imaging through dynamic and complex scattering media is challenging, and dynamic scaling factors lead to serious mismatches between the probing patterns and the realizations. In this paper, we report self-corrected imaging to realize high-resolution object reconstruction through dynamic and complex scattering media using a parallel detection with dual single-pixel detectors. The proposed method can supervise and self-correct dynamic scaling factors, and can implement high-resolution object reconstruction through dynamic and complex scattering media where conventional methods could not work. Spatial resolution of 44.19 µm is achieved which approaches diffraction limit (40.0 µm) in the designed optical setup. The achievable spatial resolution is dependent on pixel size of spatial light modulator. It is experimentally validated that the proposed method shows unprecedented robustness against complex scattering. The proposed self-corrected imaging provides a solution for ghost recovery, enabling high-resolution object reconstruction in complex scattering environments.

Securing 2D information carriers over dynamic and turbulent media in a free-space optical channel

In this Letter, a new, to the best of our knowledge, scheme is proposed to realize high-fidelity secured free-space optical information transmission through dynamic and turbulent media by encoding 2D information carriers. The data are transformed into a series of 2D patterns as information carriers. A novel differential method is developed to suppress noise, and a series of random keys are also generated. A different number of absorptive filters are arbitrarily combined to be placed in the optical channel to generate ciphertext with high randomness. It is experimentally demonstrated that the plaintext can be retrieved only when correct security keys are applied. Experimental results demonstrate that the proposed method is feasible and effective. The proposed method provides an avenue for securing high-fidelity optical information transmission over dynamic and turbulent media in a free-space optical channel.

Microscopy with heralded Fock states

We consider a microscopy setting where quantum light is used for illumination. Spontaneous parametric down conversion (SPDC) is used as a source of a heralded single photon, which is quantum light prepared in a Fock state. We present analytical formulas for the spatial mode tracking along with the heralded and non-heralded mode widths. The obtained analytical results are supported by numerical calculations and the following discussion taking into account realistic setup parameters such as finite-size optics and finite-size single-photon detectors. This allows us to observe that the diffraction limit can be approached with simultaneous alleviation of the photon loss leading to increased signal-to-noise ratio - a factor limiting practical applications of quantum light. Additionally, it is shown that the spatial resolution can be manipulated by carefully preparing the amplitude and phase of the spatial mode profile of the single photon at the input to the microscope objective. Here, the spatial entanglement of the biphoton wavefunction or adaptive optics can be applied for spatial mode shaping. Analytical dependencies between the incident and focused spatial mode profiles parameters are provided.

One-time readout temporal single-pixel imaging

Ghost imaging (GI) allows retrieval of the images of an uninterrogated object nonlocally based on cross correlation of photons. Central to GI is the integration of sparse detection events, i.e., bucket detection, even in the time domain. Here we report temporal single-pixel imaging of a non-integrating class as a viable GI variant that obviates the need for constant vigil. Mere division of the otherwise distorted waveforms by the known impulse response function of the detector makes the corrected waveforms readily available. This tempts us to use slow and as such less costly commercially available optoelectronic devices like light-emitting diodes and solar cells for imaging purposes on a one-time readout basis.

Time-to-space ghost imaging

Temporal ghost imaging is based on the temporal correlations of two optical beams and aims at forming a temporal image of a temporal object with a resolution, fundamentally limited by the photodetector resolution time and reaching 55 ps in a recent experiment. For further improvement of the temporal resolution, it is suggested to form a spatial ghost image of a temporal object relying on strong temporal-spatial correlations of two optical beams. Such correlations are known to exist between two entangled beams generated in type-I parametric downconversion. It is shown that a sub-picosecond-scale temporal resolution is accessible with a realistic source of entangled photons.

Performance evaluation of plastic optical fiber communication using micro-lens coupling and computational temporal ghost imaging algorithm

Plastic optical fiber communication (POFC) systems are particularly sensitive to signal performance and power budget. In this paper, we propose what we belive to be a novel scheme to jointly enhance the bit-error-ratio (BER) performance and coupling efficiency for multi-level pulse amplitude modulation (PAM-M) based POFC systems. The computational temporal ghost imaging (CTGI) algorithm is developed for PAM4 modulation for the first time to resist the system distortion. The simulation results reveal that enhanced BER performance and clear eye diagrams are acquired by using CTGI algorithm with an optimized modulation basis. Experimental results also investigate and show, with CTGI algorithm, the BER performance for 180 Mb/s PAM4 signals is enhanced from 2.2 × 10^-2 to 8.4 × 10^-4 over 10 m POF by using a 40 MHz photodetector. The POF link is equipped with micro-lenses at its end faces by using a ball-burning technique, which helps to increase the coupling efficiency from 28.64% to 70.61%. Both simulation and experimental results show that the proposed scheme is feasible to achieve a cost-effective and high-speed POFC system with short reach.

Learning-based adaptive under-sampling for Fourier single-pixel imaging

In this Letter, we present a learning-based method for efficient Fourier single-pixel imaging (FSI). Based on the auto-encoder, the proposed adaptive under-sampling technique (AuSamNet) manages to optimize a sampling mask and a deep neural network at the same time to achieve both under-sampling of the object image's Fourier spectrum and high-quality reconstruction from the under-sampled measurements. It is thus helpful in determining the best encoding and decoding scheme for FSI. Simulation and experiments demonstrate that AuSamNet can reconstruct high-quality natural color images even when the sampling ratio is as low as 7.5%. The proposed adaptive under-sampling strategy can be used for other computational imaging modalities, such as tomography and ptychography. We have released our source code.

Feature ghost imaging for color identification

On the basis of computational ghost imaging (CGI), we present a new imaging technique, feature ghost imaging (FGI), which can convert the color information into distinguishable edge features in retrieved grayscale images. With the edge features extracted by different order operators, FGI can obtain the shape and the color information of objects simultaneously in a single-round detection using one single-pixel detector. The feature distinction of rainbow colors is presented in numerical simulations and the verification of FGI's practical performance is conducted in experiments. Furnishing a new perspective to the imaging of colored objects, our FGI extends the function and the application fields of traditional CGI while sustaining the simplicity of the experimental setup.

Background-Free Near-Infrared Biphoton Emission from Single GaAs Nanowires

The generation of photon pairs from nanoscale structures with high rates is still a challenge for the integration of quantum devices, as it suffers from parasitic signals from the substrate. In this work, we report type-0 spontaneous parametric down-conversion at 1550 nm from individual bottom-up grown zinc-blende GaAs nanowires with lengths of up to 5 μm and diameters of up to 450 nm. The nanowires were deposited on a transparent ITO substrate, and we measured a background-free coincidence rate of 0.05 Hz in a Hanbury-Brown-Twiss setup. Taking into account transmission losses, the pump fluence, and the nanowire volume, we achieved a biphoton generation of 60 GHz/Wm, which is at least 3 times higher than that of previously reported single nonlinear micro- and nanostructures. We also studied the correlations between the second-harmonic generation and the spontaneous parametric down-conversion intensities with respect to the pump polarization and in different individual nanowires.

Target Velocity Ghost Imaging Using Slice Difference Method

Ghost imaging is a technique that uses the correlation between reference and signal arms to obtain intensity images of targets. Compared with the existing laser active imaging methods, ghost imaging can improve the signal-to-noise ratio and resolution. In this paper, through the use of the slice difference method, we propose a new scheme that allows a velocity image of moving targets to be obtained. We conduct a complete theoretical analysis and provide a proof-of-principle experiment. The experimental results are in good agreement with those of the theoretical analysis, and a velocity image with 64 × 64 resolution is obtained. This protocol achieves a great increase in the signal-to-noise ratio over what would be achievable using direct imaging. The results show a fully functional instance of velocity imaging, which is a key advancement on the path towards the multi-dimensional information acquisition of moving targets. Our scheme fulfils an urgent need for the detection of moving targets and may thus find use in fields such as target attitude perception and security monitoring.

Dual-mode adaptive-SVD ghost imaging

In this paper, we present a dual-mode adaptive singular value decomposition ghost imaging (A-SVD GI), which can be easily switched between the modes of imaging and edge detection. It can adaptively localize the foreground pixels via a threshold selection method. Then only the foreground region is illuminated by the singular value decomposition (SVD) - based patterns, consequently retrieving high-quality images with fewer sampling ratios. By changing the selecting range of foreground pixels, the A-SVD GI can be switched to the mode of edge detection to directly reveal the edge of objects, without needing the original image. We investigate the performance of these two modes through both numerical simulations and experiments. We also develop a single-round scheme to halve measurement numbers in experiments, instead of separately illuminating positive and negative patterns in traditional methods. The binarized SVD patterns, generated by the spatial dithering method, are modulated by a digital micromirror device (DMD) to speed up the data acquisition. This dual-mode A-SVD GI can be applied in various applications, such as remote sensing or target recognition, and could be further extended for multi-modality functional imaging/detection.

High-fidelity ghost diffraction through complex scattering media using a modified Gerchberg-Saxton algorithm

In this paper, we propose a modified Gerchberg-Saxton (GS) algorithm to generate random amplitude-only patterns as information carriers in ghost diffraction. With the generated random patterns, high-fidelity ghost diffraction through complex scattering media can be realized with a single-pixel detector. The modified GS algorithm adopts a support constraint in the image plane, which is divided into a target region and a support region. In the Fourier plane, amplitude of the Fourier spectrum is scaled to regulate the sum of the image function. A random amplitude-only pattern can be generated to encode a pixel of the data to be transmitted using the modified GS algorithm. Optical experiments are conducted to verify the proposed method in complex scattering environments, e.g., dynamic and turbid water with non-line-of-sight (NLOS). Experimental results demonstrate that the proposed ghost diffraction is of high fidelity and high robustness against complex scattering media. It is expected that an avenue could be opened up for ghost diffraction and transmission in complex media.

Ghost imaging lidar system for remote imaging

Research towards practical applications of ghost imaging lidar system especially in longer sensing distance has been urgent in recent years. In this paper we develop a ghost imaging lidar system to boost an extension of remote imaging, where the transmission distance of the collimated pseudo-thermal beam can be improved hugely over long range and just shifting the adjustable lens assembly generates wide field of view suiting for short-range imaging. Based on the proposed lidar system, the changing tendency of illuminating field of view, energy density, and reconstructed images is analyzed and verified experimentally. Some considerations on the improvement of this lidar system are also discussed.

Ghost images with controllable visibility and spatial resolution

We designed a kind of speckle field with controllable visibility and speckle grain size through a modified Gerchberg-Saxton algorithm based on Fresnel diffraction. Ghost images with independently controllable visibility and spatial resolution were demonstrated based on the designed speckle fields, which could be of much higher visibility and spatial resolution than those with pseudothermal light. In addition, speckle fields capable of reconstructing ghost images simultaneously on multiple different planes were customized. These results could be of potential applications on optical encryption and optical tomography.