Imaging with a small number of photons

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.

A Method to Correct the Temporal Drift of Single-Photon Detectors Based on Asynchronous Quantum Ghost Imaging

Single-photon detection and timing has attracted increasing interest in recent years due to their necessity in the field of quantum sensing and the advantages of single-quanta detection in the field of low-level light imaging. While simple bucket detectors are mature enough for commercial applications, more complex imaging detectors are still a field of research comprising mostly prototype-level detectors. A major problem in these detectors is the implementation of in-pixel timing circuitry, especially for two-dimensional imagers. One of the most promising approaches is the use of voltage-controlled ring resonators in every pixel. Each of these runs independently based on a voltage supplied by a global reference. However, this yields the problem that the supply voltage can change across the chip which, in turn, changes the period of the ring resonator. Due to additional parasitic effects, this problem can worsen with increasing measurement time, leading to drift in the timing information. We present here a method to identify and correct such temporal drifts in single-photon detectors based on asynchronous quantum ghost imaging. We also show the effect of this correction on recent quantum ghost imaging (QGI) measurement from our group.

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.

Quantum imaging of biological organisms through spatial and polarization entanglement

Quantum imaging holds potential benefits over classical imaging but has faced challenges such as poor signal-to-noise ratios, low resolvable pixel counts, difficulty in imaging biological organisms, and inability to quantify full birefringence properties. Here, we introduce quantum imaging by coincidence from entanglement (ICE), using spatially and polarization-entangled photon pairs to overcome these challenges. With spatial entanglement, ICE offers higher signal-to-noise ratios, greater resolvable pixel counts, and the ability to image biological organisms. With polarization entanglement, ICE provides quantitative quantum birefringence imaging capability, where both the phase retardation and the principal refractive index axis angle of an object can be remotely and instantly quantified without changing the polarization states of the photons incident on the object. Furthermore, ICE enables 25 times greater suppression of stray light than classical imaging. ICE has the potential to pave the way for quantum imaging in diverse fields, such as life sciences and remote sensing.

Three-dimensional quantum imaging of dynamic targets using quantum compressed sensing

Quantum imaging based on entangled light sources exhibits enhanced background resistance compared to conventional imaging techniques in low-light conditions. However, direct imaging of dynamic targets remains challenging due to the limited count rate of entangled photons. In this paper, we propose a quantum imaging method based on quantum compressed sensing that leverages the strong correlation characteristics of entangled photons and the randomness inherent in photon pair generation and detection. This approach enables the construction of a compressed sensing system capable of directly imaging high-speed dynamic targets. The results demonstrate that our system successfully achieves imaging of a target rotating at a frequency of 10 kHz, while maintaining an impressive data compression rate of 10-6. This proposed method introduces a pioneering approach for the practical implementation of quantum imaging in real-world scenarios.

Metasurface-Assisted Quantum Nonlocal Weak-Measurement Microscopy

In standard quantum weak measurements, preselection and postselection of quantum states are implemented in the same photon. Here we go beyond this restrictive setting and demonstrate that the preselection and postselection can be performed in two different photons, if the two photons are polarization entangled. The Pancharatnam-Berry phase metasurface is incorporated in the weak measurement system to perform weak coupling between probe wave function and spin observable. By introducing nonlocal weak measurement into the microscopy imaging system, it allows us to remotely switch different microscopy imaging modes of pure-phase objects, including bright-field, differential, and phase reconstruction. Furthermore, we demonstrate that the nonlocal weak-measurement scheme can prevent almost all environmental noise photons from detection and thus achieves a higher image contrast than the standard scheme at a low photon level. Our results provide the possibility to develop a quantum nonlocal weak-measurement microscope for label-free imaging of transparent biological samples.

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.

Study of computational sensing using frequency-domain compression

The computational sensing and imaging technique has been extended from spatial domain to temporal domain for capturing fast light signals with a slow photodetector. However, temporal computational sensing based on random source/modulation has to require a lot of measurements to reconstruct an object signal with acceptable SNR. In this paper, we study the frequency-domain acquisition technique for capturing a nanosecond temporal object with ten Hertz detection bandwidth. The frequency-domain acquisition technique offers a SNR gain of N, where N denotes the point number of Fourier spectrum. Because of the compressibility of data and the orthogonality and completeness of Fourier basis, it enables the reconstruction based on sub-Nyquist sampling. Because the slow detection only has low temporal resolution capability, the frequency-domain acquisition technique could provide robustness and is immune to the temporal distortion in experiments.

A dual-modality optical system for single-pixel imaging and transmission through scattering media

It is well recognized that it is difficult to develop an optical system to retrieve effective information when dynamic and turbid water exists in an optical channel. It could be more challenging to incorporate dual or multiple modalities in one optical system. In this Letter, we report a dual-modality optical system for single-pixel imaging (SPI) and transmission through scattering media. A series of mutually-orthogonal random illumination patterns are designed and adopted to realize high-resolution image recovery in SPI. The data to be transmitted are also encoded into random illumination patterns in a differential way, and high-fidelity free-space optical data transmission can be simultaneously realized. Experimental results validate feasibility of the proposed optical system and its high robustness against scattering. The developed dual-modality optical system realizes high-resolution SPI and high-fidelity data transmission in scattering media using only one set of realizations, offering an efficient implementation with reduced power and equipment requirements. The proposed method is promising toward the development of an integrated system with multiple modalities for optical information retrieval, especially in dynamic scattering media.

Efficient and noise-resistant single-pixel imaging based on Pseudo-Zernike moments

An efficient and noise-resistant single-pixel imaging (SPI) technique based on Pseudo-Zernike moments (PZ-SPI) is proposed. In this technique, the illumination light fields are modulated to satisfy the Pseudo-Zernike polynomials. Then the modulated light fields are projected onto the object. And the single-pixel detector is used to measure the reflected light intensities to calculate the Pseudo-Zernike moments. Finally, the object image is reconstructed by iterative summation of the product of the Pseudo-Zernike polynomials and the Pseudo-Zernike moments. Through the numerical simulation and experimental demonstration, PZ-SPI can effectively reconstruct image at low sampling ratios. Besides, comparing with the Fourier-SPI and Zernike-SPI, PZ-SPI has good robustness to background noise in SPI system. These advantages expand the application of PZ-SPI in complex environments.

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.

Fast object imaging and classification based on circular harmonic Fourier moment detection

Limited by the number of illumination fields and the speed of a spatial light modulator, single-pixel imaging (SPI) cannot realize real-time imaging and fast classification of an object. In this paper, we proposed the circular harmonic Fourier single-pixel imaging (CHF-SPI) for the first time to realize fast imaging and classification of objects. The light field distribution satisfies the circular harmonic Fourier formula, and the light intensity values of the single-pixel detector are equivalent to the circular harmonic Fourier moments. Then the target can be reconstructed under low sampling ratio by inverse transformation. Through simulation and experimental verification, clear imaging can be performed at a sampling ratio of 0.9%. In addition, circular harmonic Fourier moments are used to construct multi-distortion invariant to classify objects with rotation and scale change. The scale change multiples of objects can be calculated and the objects can be classified by using 10 light fields. It is of great significance to classify objects quickly without imaging.

Noise-resistant phase imaging with intensity correlation

Interferometric methods form the basis of highly sensitive measurement techniques from astronomy to bioimaging. Interferometry typically requires high stability between the measured and reference beams. The presence of rapid phase fluctuations washes out interference fringes, making phase profile recovery impossible. This challenge can be addressed by shortening the measurement time. However, such an approach reduces photon-counting rates, precluding applications in low-intensity imaging. We introduce a phase imaging technique which is immune to time-dependent phase fluctuations. Our technique, relying on intensity correlation instead of direct intensity measurements, allows one to obtain high interference visibility for arbitrarily long acquisition times. We prove the optimality of our method using the Cramér-Rao bound in the extreme case when no more than two photons are detected within the time window of phase stability. Our technique will broaden prospects in phase measurements, including emerging applications such as in infrared and x-ray imaging and quantum and matter-wave interferometry.

Experimental quantum imaging distillation with undetected light

Imaging based on the induced coherence effect makes use of photon pairs to obtain information of an object without detecting the light that probes it. While one photon illuminates the object, only its partner is detected, so no measurement of coincidence events is needed. The sought-after object's information is revealed, observing a certain interference pattern on the detected photon. Here, we demonstrate experimentally that this imaging technique can be made resilient to noise. We introduce an imaging distillation approach based on the interferometric modulation of the signal of interest. We show that our scheme can generate a high-quality image of an object even against noise levels up to 250 times the actual signal of interest. We also include a detailed theoretical explanation of our findings.

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.

Quantum enhanced non-interferometric quantitative phase imaging

Quantum entanglement and squeezing have significantly improved phase estimation and imaging in interferometric settings beyond the classical limits. However, for a wide class of non-interferometric phase imaging/retrieval methods vastly used in the classical domain, e.g., ptychography and diffractive imaging, a demonstration of quantum advantage is still missing. Here, we fill this gap by exploiting entanglement to enhance imaging of a pure phase object in a non-interferometric setting, only measuring the phase effect on the free-propagating field. This method, based on the so-called "transport of intensity equation", is quantitative since it provides the absolute value of the phase without prior knowledge of the object and operates in wide-field mode, so it does not need time-consuming raster scanning. Moreover, it does not require spatial and temporal coherence of the incident light. Besides a general improvement of the image quality at a fixed number of photons irradiated through the object, resulting in better discrimination of small details, we demonstrate a clear reduction of the uncertainty in the quantitative phase estimation. Although we provide an experimental demonstration of a specific scheme in the visible spectrum, this research also paves the way for applications at different wavelengths, e.g., X-ray imaging, where reducing the photon dose is of utmost importance.

Mid-infrared single-photon 3D imaging

Active mid-infrared (MIR) imagers capable of retrieving three-dimensional (3D) structure and reflectivity information are highly attractive in a wide range of biomedical and industrial applications. However, infrared 3D imaging at low-light levels is still challenging due to the deficiency of sensitive and fast MIR sensors. Here we propose and implement a MIR time-of-flight imaging system that operates at single-photon sensitivity and femtosecond timing resolution. Specifically, back-scattered infrared photons from a scene are optically gated by delay-controlled ultrashort pump pulses through nonlinear frequency upconversion. The upconverted images with time stamps are then recorded by a silicon camera to facilitate the 3D reconstruction with high lateral and depth resolutions. Moreover, an effective numerical denoiser based on spatiotemporal correlation allows us to reveal the object profile and reflectivity under photon-starving conditions with a detected flux below 0.05 photons/pixel/second. The presented MIR 3D imager features high detection sensitivity, precise timing resolution, and wide-field operation, which may open new possibilities in life and material sciences.

On-Chip Compressive Sensing with a Single-Photon Avalanche Diode Array

Single-photon avalanche diodes (SPADs) are novel image sensors that record photons at extremely high sensitivity. To reduce both the required sensor area for readout circuits and the data throughput for SPAD array, in this paper, we propose a snapshot compressive sensing single-photon avalanche diode (CS-SPAD) sensor which can realize on-chip snapshot-type spatial compressive imaging in a compact form. Taking advantage of the digital counting nature of SPAD sensing, we propose to design the circuit connection between the sensing unit and the readout electronics for compressive sensing. To process the compressively sensed data, we propose a convolution neural-network-based algorithm dubbed CSSPAD-Net which could realize both high-fidelity scene reconstruction and classification. To demonstrate our method, we design and fabricate a CS-SPAD sensor chip, build a prototype imaging system, and demonstrate the proposed on-chip snapshot compressive sensing method on the MINIST dataset and real handwritten digital images, with both qualitative and quantitative results.

Quantum ghost imaging based on a "looking back" 2D SPAD array

Quantum ghost imaging (QGI) is an intriguing imaging protocol that exploits photon-pair correlations stemming from spontaneous parametric down-conversion (SPDC). QGI retrieves images from two-path joint measurements, where single-path detection does not allow us to reconstruct the target image. Here we report on a QGI implementation exploiting a two-dimensional (2D) single-photon avalanche diode (SPAD) array detector for the spatially resolving path. Moreover, the employment of non-degenerate SPDC allows us to investigate samples at infrared wavelengths without the need for short-wave infrared (SWIR) cameras, while the spatial detection can be still performed in the visible region, where the more advanced silicon-based technology can be exploited. Our findings advance QGI schemes towards practical applications.

Video-rate Raman-based metabolic imaging by Airy light-sheet illumination and photon-sparse detection

Despite its massive potential, Raman imaging represents just a modest fraction of all research and clinical microscopy to date. This is due to the ultralow Raman scattering cross-sections of most biomolecules that impose low-light or photon-sparse conditions. Bioimaging under such conditions is suboptimal, as it either results in ultralow frame rates or requires increased levels of irradiance. Here, we overcome this tradeoff by introducing Raman imaging that operates at both video rates and 1,000-fold lower irradiance than state-of-the-art methods. To accomplish this, we deployed a judicially designed Airy light-sheet microscope to efficiently image large specimen regions. Further, we implemented subphoton per pixel image acquisition and reconstruction to confront issues arising from photon sparsity at just millisecond integrations. We demonstrate the versatility of our approach by imaging a variety of samples, including the three-dimensional (3D) metabolic activity of single microbial cells and the underlying cell-to-cell variability. To image such small-scale targets, we again harnessed photon sparsity to increase magnification without a field-of-view penalty, thus, overcoming another key limitation in modern light-sheet microscopy.

Mid-infrared single-pixel imaging at the single-photon level

Single-pixel cameras have recently emerged as promising alternatives to multi-pixel sensors due to reduced costs and superior durability, which are particularly attractive for mid-infrared (MIR) imaging pertinent to applications including industry inspection and biomedical diagnosis. To date, MIR single-pixel photon-sparse imaging has yet been realized, which urgently calls for high-sensitivity optical detectors and high-fidelity spatial modulators. Here, we demonstrate a MIR single-photon computational imaging with a single-element silicon detector. The underlying methodology relies on nonlinear structured detection, where encoded time-varying pump patterns are optically imprinted onto a MIR object image through sum-frequency generation. Simultaneously, the MIR radiation is spectrally translated into the visible region, thus permitting infrared single-photon upconversion detection. Then, the use of advanced algorithms of compressed sensing and deep learning allows us to reconstruct MIR images under sub-Nyquist sampling and photon-starving illumination. The presented paradigm of single-pixel upconversion imaging is featured with single-pixel simplicity, single-photon sensitivity, and room-temperature operation, which would establish a new path for sensitive imaging at longer infrared wavelengths or terahertz frequencies, where high-sensitivity photon counters and high-fidelity spatial modulators are typically hard to access.

Metasurfaces enabled polarization-multiplexing heralded single photon imaging

Quantum imaging has non-negligible advantages in terms of sensitivity, signal-to-noise ratio, and novel imaging schemes. Based on metasurfaces, the information density and stability of the quantum imaging system can be further improved. Here we experimentally demonstrate that two patterns, simultaneously and independently superimposed on a high-efficiency dielectric metasurface, can be remotely switched via polarization-entangled photon pairs. Furthermore, using the time-correlated property of entangled photon pairs, the information carried by quantum light can be remarkably discriminated from background noise. This work confirms that the phase manipulation of quantum light with metasurfaces has a huge potential in the field of quantum imaging, quantum state tomography, and also promises real-world quantum metasurface devices.

Quantum face recognition protocol with ghost imaging

Face recognition is one of the most ubiquitous examples of pattern recognition in machine learning, with numerous applications in security, access control, and law enforcement, among many others. Pattern recognition with classical algorithms requires significant computational resources, especially when dealing with high-resolution images in an extensive database. Quantum algorithms have been shown to improve the efficiency and speed of many computational tasks, and as such, they could also potentially improve the complexity of the face recognition process. Here, we propose a quantum machine learning algorithm for pattern recognition based on quantum principal component analysis, and quantum independent component analysis. A novel quantum algorithm for finding dissimilarity in the faces based on the computation of trace and determinant of a matrix (image) is also proposed. The overall complexity of our pattern recognition algorithm is [Formula: see text]-N is the image dimension. As an input to these pattern recognition algorithms, we consider experimental images obtained from quantum imaging techniques with correlated photons, e.g. "interaction-free" imaging or "ghost" imaging. Interfacing these imaging techniques with our quantum pattern recognition processor provides input images that possess a better signal-to-noise ratio, lower exposures, and higher resolution, thus speeding up the machine learning process further. Our fully quantum pattern recognition system with quantum algorithm and quantum inputs promises a much-improved image acquisition and identification system with potential applications extending beyond face recognition, e.g., in medical imaging for diagnosing sensitive tissues or biology for protein identification.

Single-pixel imaging using discrete Zernike moments

A novel single-pixel imaging (SPI) technique based on discrete orthogonal Zernike moments is proposed. In this technique, the target object is illuminated by two sets of Zernike basis patterns which satisfy the Zernike polynomials. The Zernike moments of object image are obtained by measuring the reflected light intensities through a single-pixel detector. And the object image is reconstructed by summing the product of Zernike polynomials and detected intensities iteratively. By theoretical and experimental demonstrations, an image with high quality is retrieved under compressive sampling. Moreover, the Zernike illuminating patterns are used for object classification due to the rotation invariant of Zernike moments. By measuring the amplitudes of a few specific Zernike moments through the SPI system, the rotated images with different angles and the same content are classified into the same class on experiment. This classification technique has the advantages of high efficiency and high accuracy due to the high modulation speed and high sensitivity of SPI system.

Physics-Based Noise Modeling for Extreme Low-Light Photography

Enhancing the visibility in extreme low-light environments is a challenging task. Under nearly lightless condition, existing image denoising methods could easily break down due to significantly low SNR. In this paper, we systematically study the noise statistics in the imaging pipeline of CMOS photosensors, and formulate a comprehensive noise model that can accurately characterize the real noise structures. Our novel model considers the noise sources caused by digital camera electronics which are largely overlooked by existing methods yet have significant influence on raw measurement in the dark. It provides a way to decouple the intricate noise structure into different statistical distributions with physical interpretations. Moreover, our noise model can be used to synthesize realistic training data for learning-based low-light denoising algorithms. In this regard, although promising results have been shown recently with deep convolutional neural networks, the success heavily depends on abundant noisy-clean image pairs for training, which are tremendously difficult to obtain in practice. Generalizing their trained models to images from new devices is also problematic. Extensive experiments on multiple low-light denoising datasets - including a newly collected one in this work covering various devices - show that a deep neural network trained with our proposed noise formation model can reach surprisingly-high accuracy. The results are on par with or sometimes even outperform training with paired real data, opening a new door to real-world extreme low-light photography.

Photon-counting statistics-based support vector machine with multi-mode photon illumination for quantum imaging

We propose a photon-counting-statistics-based imaging process for quantum imaging where background photon noise can be distinguished and eliminated by photon mode estimation from the multi-mode Bose–Einstein distribution. Photon-counting statistics show multi-mode behavior in a practical, low-cost single-photon-level quantum imaging system with a short coherence time and a long measurement time interval. Different mode numbers in photon-counting probability distributions from single-photon illumination and background photon noise can be classified by a machine learning technique such as a support vector machine (SVM). The proposed photon-counting statistics-based support vector machine (PSSVM) learns the difference in the photon-counting distribution of each pixel to distinguish between photons from the source and the background photon noise to improve the image quality. We demonstrated quantum imaging of a binary-image object with photon illumination from a spontaneous parametric down-conversion (SPDC) source. The experiment results show that the PSSVM applied quantum image improves a peak signal-to-noise ratio (PSNR) gain of 2.89dB and a structural similarity index measure (SSIM) gain of 27.7% compared to the conventional direct single-photon imaging.

Using FADOF to eliminate the background light influence in ghost imaging

The high solar background during the day adversely affects the long distance daytime operations of ghost imaging. It is extremely hard to distinguish the signal light from the background noise light after they are both converted to voltage or current signals by the bucket detector, so spectral filtering before the detector is quite important. In this work, a Faraday anomalous dispersion optical filter (FADOF) is used in eliminating the background light influence in ghost imaging. Results of lab experiment show that the background light noise tolerance of the ghost imaging with FADOF is at least 18 times bigger than that with a 10 nm optical filter. The method has simple structure, great performance and great algorithms compatibility.

Weak thermal state quadrature-noise shadow imaging

In this work, we theoretically and experimentally demonstrate the possibility to create an image of an opaque object using a few-photon thermal optical field. We utilize the quadrature-noise shadow imaging (QSI) technique that detects the changes in the quadrature-noise statistics of the probe beam after its interaction with an object. We show that such a thermal QSI scheme has an advantage over the classical differential imaging when the effect of dark counts is considered. At the same time, the easy availability of thermal sources for any wavelength makes the method practical for broad range of applications, not accessible with, e.g., quantum squeezed light. As a proof of principle, we implement this scheme by two different light sources: a pseudo-thermal beam generated by rotating ground glass (RGG) method and a thermal beam generated by four-wave mixing (FWM) method. The RGG method shows simplicity and robustness of QSI scheme while the FWM method validates theoretical signal-to-noise ratio predictions. Finally, we demonstrate low-light imaging abilities with QSI by imaging a biological specimen on a CCD camera, detecting as low as 0.03 photons on average per pixel per 1.7 µs exposure.

High-resolution ghost imaging through complex scattering media via a temporal correction

In this Letter, we propose high-resolution ghost imaging (GI) through complex scattering media using temporal correction. We provide evidence that the theoretical description about GI based on spatially correlated beams is still incomplete and cannot work in complex scenarios. We complete the description of temporal correction of beam correlations in GI. The optical experiments demonstrate that high-resolution ghost images can always be retrieved by using the rectified temporally corrected beam correlation algorithm even in complex, dynamic, and highly strong scattering environments where conventional GI cannot work. By using the proposed method, the quality of the retrieved ghost images through complex scattering media can be enhanced effectively as the number of realizations increases, which cannot be achieved by conventional GI. The established general framework provides optical insights beyond the current understanding of GI, and the rectified theory and experimental results would represent a key step toward applications of GI over a wide range of free-space wave propagation environments.

Quantum imaging with a photon counting camera

Classical light sources emit a randomly-timed stream of individual photons, the spatial distribution of which can be detected with a camera to form an image. Quantum light sources, based on parametric down conversion, emit photons as correlated photon-pairs. The spatial correlations between the photons enables imaging systems where the preferential selection of photon-pairs allows for enhancements in the noise performance over what is possible using classical light sources. However, until now the technical challenge of measuring, and correlating both photons has led to system complexity. Here we show that a camera capable of resolving the number of individual photons in each pixel of the detector array can be used to record an image formed from these photon-pair events and hence achieve a greater contrast than possible using a classical light source. We achieve an enhancement in the ratio of two-photon events compared to one-photon events using spatially correlated SPDC light compared to uncorrelated illumination by a LED. These results indicate the potential advantages of using photon counting cameras in quantum imaging schemes and these advantages will further increase as the technology is developed. Operating in photon sparse regimes such systems have potential applications in low-light microscopy and covert imaging.

Intrinsic Optical Spatial Differentiation Enabled Quantum Dark-Field Microscopy

By solving the Maxwell's equations in Fourier space, we find that the cross-polarized component of the dipole scattering field can be written as the second-order spatial differentiation of the copolarized component. This differential operation can be regarded as intrinsic which naturally arises as consequence of the transversality of electromagnetic fields. By introducing the intrinsic spatial differentiation into heralded single-photon microscopy imaging technique, it makes the structure of pure-phase object clearly visible at low photon level, avoiding any biophysical damages to living cells. Based on the polarization entanglement, the switch between dark-field imaging and bright-field imaging is remotely controlled in the heralding arm. This research enriches both fields of optical analog computing and quantum microscopy, opening a promising route toward a nondestructive imaging of living biological systems.

Multi-Object Positioning and Imaging Based on Single-Pixel Imaging Using Binary Patterns

Single-pixel imaging (SPI) is a new type of imaging technology that uses a non-scanning single-pixel detector to image objects and has important application prospects and value in many fields. Most of the modulators currently used in SPI systems are digital micromirror device (DMD) modulators, which use a higher frequency for binary modulation than other alternatives. When modulating grayscale information, the modulation frequency is significantly reduced. This paper conducts research on multiple discrete objects in a scene and proposes using binary patterns to locate and image these objects. Compared with the existing methods of using gray patterns to locate and image multiple objects, the method proposed in this paper is more suitable for DMD-type SPI systems and has wider applicability and greater prospects. The principle of the proposed method is introduced, and the effectiveness of the method is experimentally verified. The experimental results show that, compared to traditional SPI methods, the number of patterns required by the proposed method is reduced by more than 85%.

Image-enhanced single-pixel imaging using fractional calculus

Recent years, image enhancement for single-pixel imaging has developed rapidly and provides an image-free way for extracting image information. However, the conventional image enhancement approaches for single-pixel imaging are still based on the discontinuously adjustable operations such as integer-order derivatives, which are frequently used in edge detection but sensitive to the image noise. Therefore, how to balance between two conflicting demands, i.e. edge detection and noise suppression, is a new challenge. To address this issue, we introduce arbitrary-order fractional operations into single-pixel imaging. In experiment, the proposed technique has the capacity to detect image edges with high quality. Compared with integer-order derivative method which amplifies noise significantly while extracting edges, it offers a nice tradeoff between image SNR and performance of edge enhancement. In addition, it also shows good performance of image smoothing and improvement of image quality, if fractional order is negative. The proposed technique provides the adjustable fractional order as a new degree of freedom for edge extraction and image de-noising and therefore makes up for the shortcomings of traditional method for image enhancement.

Self-healing of a heralded single-photon Airy beam

Self-healing of an Airy beam during propagation is of fundamental interest and also promises important applications. Despite many studies of Airy beams in the quantum regime, it is unclear whether an Airy beam only including a single photon can heal after passing an obstacle because the photon may be blocked. Here we experimentally observe self-healing of a heralded single-photon Airy beam. Our observation implies that an Airy wave packet is robust against obstacle caused distortion and can restore even at the single-photon level.

Single-pixel neural network object classification of sub-Nyquist ghost imaging

A single-pixel neural network object classification scenario in the sub-Nyquist ghost imaging system is proposed. Based on the neural network, objects are classified directly by bucket measurements without reconstructing images. Classification accuracy can still be maintained at 94.23% even with only 16 measurements (less than the Nyquist limit of 1.56%). A parallel computing scheme is applied in data processing to reduce the object acquisition time significantly. Random patterns are used as illumination patterns to illuminate objects. The proposed method performs much better than existing methods for both binary and grayscale images in the sub-Nyquist condition, which is also robust to environment noise turbulence. Benefiting from advantages of ghost imaging, it may find applications for target recognition in the fields of remote sensing, military defense, and so on.

Airy light-sheet Raman imaging

Light-sheet fluorescence microscopy has greatly improved the speed and overall photostability of optically sectioning cellular and multi-cellular specimens. Similar gains have also been conferred by light-sheet Raman imaging; these schemes, however, rely on diffraction limited Gaussian beams that hinder the uniformity and size of the imaging field-of-view, and, as such, the resulting throughput rates. Here, we demonstrate that a digitally scanned Airy beam increases the Raman imaging throughput rates by more than an order of magnitude than conventional diffraction-limited beams. Overall, this, spectrometer-less, approach enabled 3D imaging of microparticles with high contrast and 1 µm axial resolution at 300 msec integration times per plane and orders of magnitude lower irradiation density than coherent Raman imaging schemes. We detail the apparatus and its performance, as well as its compatibility with fluorescence light-sheet and quantitative-phase imaging towards rapid and low phototoxicity multimodal imaging.

Effectiveness of the Heads-Up Surgery System for Retinal Surgery in a Patient with Severe Photophobia

Background

The reported features and effectiveness of heads-up surgery (HUS) for ophthalmic surgery include greater resolution, teaching, and significantly reduced endoillumination power.

Objective

To report how to care for severe intraoperative photophobia using the HUS system during bilateral rhegmatogenous retinal detachment (RD) surgery in a patient with severe photophobia.

Case Report

A man in his 50s, who had been followed up for photophobia and visual impairment underwent five ophthalmic surgeries for bilateral RD. In his early 40s, he had been referred to our hospital because of a complaint of bilateral visual impairment, including severe photophobia, approximately 2 years prior. His decimal best-corrected visual acuities were 0.7 and 0.6 in his right and left eyes, respectively. Optical coherence tomography showed diffuse thinning of the entire retinal layer in the macula of both eyes, which was considered to be a cause of the decrement of visual acuity and photophobia. Twelve years after his first visit, he noticed multiple floaters in his left eye. For RD excluding the macular area, we planned cataract and retinal surgery under retrobulbar anesthesia. However, as we could not continue retinal surgery after cataract surgery due to severe photophobia, we performed general anesthesia (GA) during the second surgery. Seventeen months after the surgery, he underwent the third surgery for RD in his right eye under GA. For RD recurring twice, we performed surgery with the HUS system under retrobulbar anesthesia for the fourth and fifth surgeries, which avoided photophobia due to the significantly reduced light stimulation of the HUS system.

Conclusion

Lower light intensity achieved by the HUS system enabled us to eliminate the patient’s intraoperative discomfort. Consequently, we could perform the surgery under local anesthesia in this patient with RD who complained of severe photophobia that required GA using a conventional surgical system.

Quantum enhanced multiple-phase estimation with multi-mode N00N states

Quantum metrology can achieve enhanced sensitivity for estimating unknown parameters beyond the standard quantum limit. Recently, multiple-phase estimation exploiting quantum resources has attracted intensive interest for its applications in quantum imaging and sensor networks. For multiple-phase estimation, the amount of enhanced sensitivity is dependent on quantum probe states, and multi-mode N00N states are known to be a key resource for this. However, its experimental demonstration has been missing so far since generating such states is highly challenging. Here, we report generation of multi-mode N00N states and experimental demonstration of quantum enhanced multiple-phase estimation using the multi-mode N00N states. In particular, we show that the quantum Cramer-Rao bound can be saturated using our two-photon four-mode N00N state and measurement scheme using a 4 × 4 multi-mode beam splitter. Our multiple-phase estimation strategy provides a faithful platform to investigate multiple parameter estimation scenarios.

Fractional Fourier single-pixel imaging

Single-pixel imaging technology has a number of advantages over conventional imaging approaches, such as wide operation wavelength region, compressive sampling, low light radiation dose and insensitivity to distortion. Here, we report on a novel single-pixel imaging based on fractional Fourier transform (FRFT), which captures images by acquiring the fractional-domain information of targets. With the use of structured illumination of two-dimensional FRFT base patterns, FRFT coefficients of the object could be measured by single-pixel detection. Then, the object image is achieved by performing inverse FRFT on the measurements. Furthermore, the proposed method can reconstruct the object image from sub-Nyquist measurements because of the sparsity of image data in fractional domain. In comparison with traditional single-pixel imaging, it provides a new degree of freedom, namely fractional order, and therefore has more flexibility and new features for practical applications. In experiments, the proposed method has been applied for edge detection of object, with an adjustable parameter as a new degree of freedom.

Quantum ghost imaging using asynchronous detection

We present first results of a novel type of setup for quantum ghost imaging based on asynchronous single photon timing using single photon avalanche diode (SPAD) detectors. This scheme enables photon pairing with arbitrary path length difference and does, therefore, obviate the dependence on optical delay lines of current quantum ghost imaging setups [Nat. Commun.6, 5913 (2015)NCAOBW2041-172310.1038/ncomms6913]. It is also, to our knowledge, the first quantum ghost imaging setup to allow three-dimensional imaging.

Direct Tomography of High-Dimensional Density Matrices for General Quantum States of Photons

Quantum-state tomography is the conventional method used to characterize density matrices for general quantum states. However, the data acquisition time generally scales linearly with the dimension of the Hilbert space, hindering the possibility of dynamic monitoring of a high-dimensional quantum system. Here, we demonstrate a direct tomography protocol to measure density matrices of photons in the position basis through the use of a polarization-resolving camera, where the dimension of density matrices can be as large as 580×580 in our experiment. The use of the polarization-resolving camera enables parallel measurements in the position and polarization basis and as a result, the data acquisition time of our protocol does not increase with the dimension of the Hilbert space and is solely determined by the camera exposure time (on the order of 10 ms). Our method is potentially useful for the real-time monitoring of the dynamics of quantum states and paves the way for the development of high-dimensional, time-efficient quantum metrology techniques.

Efficient Interaction of Heralded X-Ray Photons with a Beam Splitter

We report the experimental demonstration of efficient interaction of multi-kilo-electron-volt heralded x-ray photons with a beam splitter. The measured heralded photon rate at the outputs of the beam splitter is about 0.01  counts/s which is comparable to the rate in the absence of the beam splitter. We use this beam splitter together with photon number and photon energy resolving detectors to show directly that when a single x-ray photon interacts with a beam splitter it can only be detected at either of the ports of the beam splitter but not at both simultaneously, leading to a strong anticorrelation between the detection events at the two output ports. Our experiment demonstrates the major advantage of x rays for quantum optics-the possibility to observe experimental results with high fidelity and with negligible background.

Optical quantum technologies with hexagonal boron nitride single photon sources

Single photon quantum emitters are important building blocks of optical quantum technologies. Hexagonal boron nitride (hBN), an atomically thin wide band gap two dimensional material, hosts robust, optically active luminescent point defects, which are known to reduce phonon lifetimes, promises as a stable single-photon source at room temperature. In this Review, we present the recent advances in hBN quantum light emission, comparisons with other 2D material based quantum sources and analyze the performance of hBN quantum emitters. We also discuss state-of-the-art stable single photon emitter's fabrication in UV, visible and near IR regions, their activation, characterization techniques, photostability towards a wide range of operating temperatures and harsh environments, Density-functional theory predictions of possible hBN defect structures for single photon emission in UV to IR regions and applications of single photon sources in quantum communication and quantum photonic circuits with associated potential obstacles.

Photon quantum entanglement in the MeV regime and its application in PET imaging

Positron Emission Tomography (PET) is a widely-used imaging modality for medical research and clinical diagnosis. Imaging of the radiotracer is obtained from the detected hit positions of the two positron annihilation photons in a detector array. The image is degraded by backgrounds from random coincidences and in-patient scatter events which require correction. In addition to the geometric information, the two annihilation photons are predicted to be produced in a quantum-entangled state, resulting in enhanced correlations between their subsequent interaction processes. To explore this, the predicted entanglement in linear polarisation for the two photons was incorporated into a simulation and tested by comparison with experimental data from a cadmium zinc telluride (CZT) PET demonstrator apparatus. Adapted apparati also enabled correlation measurements where one of the photons had undergone a prior scatter process. We show that the entangled simulation describes the measured correlations and, through simulation of a larger preclinical PET scanner, illustrate a simple method to quantify and remove the unwanted backgrounds in PET using the quantum entanglement information alone.

Restoration of Two-Photon Ca2+ Imaging Data Through Model Blind Spatiotemporal Filtering

Two-photon Ca²⁺ imaging is a leading technique for recording neuronal activities in vivo with cellular or subcellular resolution. However, during experiments, the images often suffer from corruption due to complex noises. Therefore, the analysis of Ca²⁺ imaging data requires preprocessing steps, such as denoising, to extract biologically relevant information. We present an approach that facilitates imaging data restoration through image denoising performed by a neural network combining spatiotemporal filtering and model blind learning. Tests with synthetic and real two-photon Ca²⁺ imaging datasets demonstrate that the proposed approach enables efficient restoration of imaging data. In addition, we demonstrate that the proposed approach outperforms the current state-of-the-art methods by evaluating the qualities of the denoising performance of the models quantitatively. Therefore, our method provides an invaluable tool for denoising two-photon Ca²⁺ imaging data by model blind spatiotemporal processing.

Single-pixel ptychography

Ptychography is a predominant non-interferometric technique to image large complex fields but with quite a narrow working spectrum, because diffraction measurements require dense array detection with an ultra-high dynamic range. Here we report a single-pixel ptychography technique that realizes non-interferometric and non-scanning complex-field imaging in a wide waveband, where 2D dense detector arrays are not available. A single-pixel detector is placed in the far field to record the DC-only component of the diffracted wavefront scattered from the target field, which is illuminated by a sequence of binary modulation patterns. This decreases the measurements' dynamic range by several orders of magnitude. We employ an efficient single-pixel phase-retrieval algorithm to jointly recover the field's 2D amplitude and phase maps from the 1D intensity-only measurement sequence. No a priori object information is needed in the recovery process. We validate the technique's quantitative phase imaging nature using both calibrated phase objects and biological samples and demonstrate its wide working spectrum with both 488-nm visible light and 980-nm near-infrared light.

Entangled photon-pair sources based on three-wave mixing in bulk crystals

Entangled photon pairs are a critical resource in quantum communication protocols ranging from quantum key distribution to teleportation. The current workhorse technique for producing photon pairs is via spontaneous parametric down conversion (SPDC) in bulk nonlinear crystals. The increased prominence of quantum networks has led to a growing interest in deployable high performance entangled photon-pair sources. This manuscript provides a review of the state-of-the-art bulk-optics-based SPDC sources with continuous wave pump and discusses some of the main considerations when building for deployment.

Ghost imaging influenced by a supersonic wind-induced random environment

Near field airflow induced by wind is an important factor influencing imaging quality when the imaging system is placed on a moving platform with high speed, such as airborne imaging. In this Letter, ghost imaging through an airflow environment is experimentally and numerically investigated. The experiment is performed with a wind tunnel, and imaging quality decreases with wind velocity. The simulation model of ghost imaging through this kind of environment is proposed, and simulation results match well with experiments. With the model, imaging results are extended into the supersonic wind region with the effects of airflow factors discussed in detail, and a comparison between airflow and atmosphere turbulence is presented. The results can find potential applications in optical imaging and may be a powerful tool to estimate the effect of airflow on performance of the imaging system.