Ghost imaging with atoms

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.

Non-local temporal interference

Although position and time have different mathematical roles in quantum mechanics, with one being an operator and the other being a parameter, there is a space-time duality in quantum phenomena-a lot of quantum phenomena that were first observed in the spatial domain were later observed in the temporal domain as well. In this context, we propose a modified version of the double-double-slit experiment using entangled atom pairs to observe a non-local interference in the arrival time distribution, which is analogous to the non-local interference observed in the arrival position distribution. However, computing the arrival time distribution in quantum mechanics is a challenging open problem, and so to overcome this problem we employ a Bohmian treatment. Based on this approach, we numerically demonstrate that there is a complementary relationship between the one-particle and two-particle interference visibilities in the arrival time distribution, which is analogous to the complementary relationship observed in the position distribution. These results can be used to test the Bohmian arrival time distribution in a strict manner, i.e., where the semiclassical approximation breaks down. Moreover, our approach to investigating this experiment can be applied to a wide range of phenomena, and it seems that the predicted non-local temporal interference and associated complementary relationship are universal behaviors of entangled quantum systems that may manifest in various phenomena.

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.

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.

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.

Ghost translation: an end-to-end ghost imaging approach based on the transformer network

Artificial intelligence has recently been widely used in computational imaging. The deep neural network (DNN) improves the signal-to-noise ratio of the retrieved images, whose quality is otherwise corrupted due to the low sampling ratio or noisy environments. This work proposes a new computational imaging scheme based on the sequence transduction mechanism with the transformer network. The simulation database assists the network in achieving signal translation ability. The experimental single-pixel detector's signal will be 'translated' into a 2D image in an end-to-end manner. High-quality images with no background noise can be retrieved at a sampling ratio as low as 2%. The illumination patterns can be either well-designed speckle patterns for sub-Nyquist imaging or random speckle patterns. Moreover, our method is robust to noise interference. This translation mechanism opens a new direction for DNN-assisted ghost imaging and can be used in various computational imaging scenarios.

Quantum ghost imaging of a transparent polarisation sensitive phase pattern

A transparent polarisation sensitive phase pattern exhibits a position and polarisation dependent phase shift of transmitted light and it represents a unitary transformation. A quantum ghost image of this pattern is produced with hyper-entangled photons consisting of Einstein-Podolsky-Rosen (EPR) and polarisation entanglement. In quantum ghost imaging, a single photon interacts with the pattern and is detected by a stationary detector and a non-interacting photon is imaged on a coincidence camera. EPR entanglement manifests spatial correlations between an object plane and a ghost image plane, whereas a polarisation dependent phase shift exhibited by the pattern is detected with polarisation entanglement. In this quantum ghost imaging, the which-position-polarisation information of a photon interacting with the pattern is not present in the experiment. A quantum ghost image is constructed by measuring correlations of the polarisation-momentum of an interacting photon with polarisation-position of a non-interacting photon. The experiment is performed with a coincidence single photon detection camera, where a non-interacting photon travels a long optical path length of 17.83 m from source to camera and a pattern is positioned at an optical distance of 19.16 m from the camera.

Extendible ghost imaging with high reconstruction quality in strong scattering medium

Ghost imaging (GI) possesses significant application prospects in scattering imaging, which is a classic example of underdetermined conversion problem in optical field. However, even under the framework of single-pixel imaging (SPI), a challenge remains unresolved, i.e., structured patterns may be damaged by scattering media in both the emissive and receiving optical paths. In this study, an extendible ghost imaging, a numerical reproduction of the qualitative process using deep learning (DL)-based GI is presented. First, we propose and experimentally verify a brief degradation-guided reconstruction (DR) approach with a neural network to demonstrate the degradation principle of scattering, including realistic dataset simulations and a new training structure in the form of a convolutional neural network (CNN). Then, a novel photon contribution model (PCM) with redundant parameters is proposed to generate intensity sequences from the forward direction through volumetric scattering media; the redundant parameters are constructed and relate to the special output configuration in a lightweight CNN with two branches, based on a reformulated atmospheric scattering model. The proposed scheme recovers the semantics of targets and suppresses the imaging noise in the strong scattering medium, and the obtained results are very satisfactory for applications to scattering media of more practical scenarios and are available for various scattering coefficients and work distances of an imaging prototype. After using DL methods in computational imaging, we conclude that strategies embedded in optics or broader physical factors can result in solutions with better effects for unanalyzable processes.

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.

Semantic ghost imaging based on recurrent-neural-network

Ghost imaging (GI) illuminates an object with a sequence of light patterns and obtains the corresponding total echo intensities with a bucket detector. The correlation between the patterns and the bucket signals results in the image. Due to such a mechanism different from the traditional imaging methods, GI has received extensive attention during the past two decades. However, this mechanism also makes GI suffer from slow imaging speed and poor imaging quality. In previous work, each sample, including an illumination pattern and its detected bucket signal, was treated independently with each other. The correlation is therefore a linear superposition of the sequential data. Inspired by human's speech, where sequential words are linked with each other by a certain semantic logic and an incomplete sentence could still convey a correct meaning, we here propose a different perspective that there is potentially a non-linear connection between the sequential samples in GI. We therefore built a system based on a recurrent neural network (RNN), called GI-RNN, which enables recovering high-quality images at low sampling rates. The test with MNIST's handwriting numbers shows that, under a sampling rate of 1.28%, GI-RNN have a 12.58 dB higher than the traditional basic correlation algorithm and a 6.61 dB higher than compressed sensing algorithm in image quality. After trained with natural images, GI-RNN exhibits a strong generalization ability. Not only does GI-RNN work well with the standard images such as "cameraman", but also it can recover the natural scenes in reality at the 3% sampling rate while the SSIMs are greater than 0.7.

Multi-Party Cryptographic Key Distribution Protocol over a Public Network Based on a Quick-Response Code

In existing cryptographic key distribution (CKD) protocols based on computational ghost imaging (CGI), the interaction among multiple legitimate users is generally neglected, and the channel noise has a serious impact on the performance. To overcome these shortcomings, we propose a multi-party interactive CKD protocol over a public network, which takes advantage of the cascade ablation of fragment patterns (FPs). The server splits a quick-response (QR) code image into multiple FPs and embeds different "watermark" labels into these FPs. By using a CGI setup, the server will acquire a series of bucket value sequences with respect to different FPs and send them to multiple legitimate users through a public network. The users reconstruct the FPs and determine whether there is an attack in the public channel according to the content of the recovered "watermark" labels, so as to complete the self-authentication. Finally, these users can extract their cryptographic keys by scanning the QR code (the cascade ablation result of FPs) returned by an intermediary. Both simulation and experimental results have verified the feasibility of this protocol. The impacts of different attacks and the noise robustness have also been investigated.

Quantum imaging of a polarisation sensitive phase pattern with hyper-entangled photons

A transparent polarisation sensitive phase pattern makes a polarisation dependent transformation of quantum state of photons without absorbing them. Such an invisible pattern can be imaged with quantum entangled photons by making joint quantum measurements on photons. This paper shows a long path experiment to quantum image a transparent polarisation sensitive phase pattern with hyper-entangled photon pairs involving momentum and polarisation degrees of freedom. In the imaging configuration, a single photon interacts with the pattern while the other photon, which has never interacted with the pattern, is measured jointly in a chosen polarisation basis and in a quantum superposition basis of its position which is equivalent to measure its momentum. Individual photons of each hyper-entangled pair cannot provide a complete image information. The image is constructed by measuring the polarisation state and position of the interacting photon corresponding to a measurement outcome of the non-interacting photon. This paper presents a detailed concept, theory and free space long path experiments on quantum imaging of polarisation sensitive phase patterns.

Color night vision ghost imaging based on a wavelet transform

Night vision imaging is a technology that converts objects not visible to the human eye into visible images for night scenes and other low-light environments. However, conventional night vision imaging can directly produce only grayscale images. Here, we report a novel, to the best of our knowledge, color night vision imaging method based on a ghost imaging framework and optimized coincidence measurement based on wavelet transformation. An interesting phenomenon is that color night vision image can be directly produced by this new method. To our knowledge, this is the first direct color night vision imaging method without any conventional pseudocolor image fusion techniques. The experimental results show that this method can restore color very well for some objects. Moreover, the color of the night vision image is more natural and friendly to the human eye than that of conventional color night vision images. Due to the advantages of wavelet transforms, this method has high reconstruction ability for distorted signals.

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.

Single-pixel imaging with neutrons

Neutron imaging is an invaluable tool for noninvasive analysis in many fields. However, neutron facilities are expensive and inconvenient to access, while portable sources are not strong enough to form even a static image within an acceptable time frame using traditional neutron imaging. Here we demonstrate a new scheme for single-pixel neutron imaging of real objects, with spatial and spectral resolutions of 100 μm and 0.4% at 1 Å, respectively. Low illumination down to 1000 neutron counts per frame pattern was achieved. The experimental setup is simple, inexpensive, and especially suitable for low intensity portable sources, which should greatly benefit applications in biology, material science, and industry.

Dark-field ghost imaging

Ghost imaging is a promising technique for shape reconstruction using two spatially correlated beams: one beam interacts with a target and is collected with a bucket detector, and the other beam is measured with a pixelated detector. However, orthodox ghost imaging always provides unsatisfactory results for unstained samples, phase objects, or highly transparent objects. Here we present a dark-field ghost imaging technique that can work well for these "bad" targets. The only difference from orthodox ghost imaging is that the bucket signals rule out the target's unscattered beam. As experimental proof, we demonstrate images of fine copper wires, quartz fibers, scratched and damaged glass plates, a pure phase object, and biospecimens.

Ghost imaging enhancement for detections of the low-transmittance objects

The underwater environment is extremely complex and variable, which makes it difficult for underwater robots detecting or recognizing surroundings using images acquired with cameras. Ghost imaging as a new imaging technique has attracted much attention due to its special physical properties and potential for imaging of objects in optically harsh or noisy environments. In this work, we experimentally study three categories of image reconstruction methods of ghost imaging for objects of different transmittance. For high-transmittance objects, the differential ghost imaging is more efficient than traditional ghost imaging. However, for low-transmittance objects, the reconstructed images using traditional ghost imaging and differential ghost imaging algorithms are both exceedingly blurred and cannot be improved by increasing the number of measurements. A compressive sensing method named augmented Lagrangian and alternating direction algorithm (TVAL3) is proposed to reduce the background noise imposed by the low-transmittance. Experimental results show that compressive ghost imaging can dramatically subtract the background noise and enhance the contrast of the image. The relationship between the quality of the reconstructed image and the complexity of object itself is also discussed.

Single-pixel imaging 12 years on: a review

Modern cameras typically use an array of millions of detector pixels to capture images. By contrast, single-pixel cameras use a sequence of mask patterns to filter the scene along with the corresponding measurements of the transmitted intensity which is recorded using a single-pixel detector. This review considers the development of single-pixel cameras from the seminal work of Duarte et al. up to the present state of the art. We cover the variety of hardware configurations, design of mask patterns and the associated reconstruction algorithms, many of which relate to the field of compressed sensing and, more recently, machine learning. Overall, single-pixel cameras lend themselves to imaging at non-visible wavelengths and with precise timing or depth resolution. We discuss the suitability of single-pixel cameras for different application areas, including infrared imaging and 3D situation awareness for autonomous vehicles.

X-ray imaging of fast dynamics with single-pixel detector

We demonstrate experimentally the ability to use a single-pixel detector for two-dimensional high-resolution x-ray imaging of fast dynamics. We image the rotation of a spinning chopper at 100 kHz and at spatial resolution of about 40 microns by using the computational ghost imaging approach. The technique we develop can be used for the imaging of fast dynamics of periodic and periodically stimulated effects with a large field of view and at low dose.

Ghost imaging based on Y-net: a dynamic coding and decoding approach

Ghost imaging incorporating deep learning technology has recently attracted much attention in the optical imaging field. However, deterministic illumination and multiple exposure are still essential in most scenarios. Here we propose a ghost imaging scheme based on a novel dynamic decoding deep learning framework (Y-net), which works well under both deterministic and indeterministic illumination. Benefited from the end-to-end characteristic of our network, the image of a sample can be achieved directly from the data collected by the detector. The sample is illuminated only once in the experiment, and the spatial distribution of the speckle encoding the sample in the experiment can be completely different from that of the simulation speckle in training, as long as the statistical characteristics of the speckle remain unchanged. This approach is particularly important to high-resolution x-ray ghost imaging applications due to its potential for improving image quality and reducing radiation damage.

Adaptive ghost imaging

Traditional ghost imaging applies correlated algorithms to reconstruct the image of an object. However, it fundamentally requires some spatial distributions of the correlated light beam, e.g. random illumination, which hardly exists in reality. Here, different from the localized analysis used in the traditional ghost imaging, a spatial and temporal global analysis of the whole measurements is proposed. Therefore, we demonstrate a new ghost imaging modality, called adaptive ghost imaging (AGI), that utilizes the difference of successive frames as the correlation pattern to generate the image. As a result, AGI can work with any varying illuminations including, but not limited to, random illumination. We believe that AGI will make the ghost imaging easier, more applicable and closer to reality.

Ghost polarimetry using Stokes correlations

We present here a novel ghost polarimeter based on Stokes parameter correlations and a spatially incoherent classical source with adjustable polarization state and Gaussian statistics. The setup enables extracting the four amplitudes and three phase differences related to the spectral $ 2 \times 2 $2×2 complex Jones matrix of any transmissive polarization-sensitive object. Our work extends the ghost imaging methods from the traditional intensity correlation measurements to the detection of polarization state correlations.

All-Optical Naked-Eye Ghost Imaging

Ghost imaging is usually based on the optoelectronic process and electronic computing. A new ghost imaging approach is put forward in the paper that avoids any optoelectronic or electronic process. Instead, the proposed scheme exploits all-optical correlation and the vision persistence effect to generate images observed by naked eyes. To realize high contrast naked-eye ghost imaging, a special pattern-scanning architecture on a low-speed light-modulation disk is designed, which also enables high-resolution imaging with lower-order Hadamard vectors and boosts the imaging speed. With this approach, we realize high-contrast real-time naked-eye ghost imaging for moving colored objects.

Instant ghost imaging: algorithm and on-chip implementation

Ghost imaging (GI) is an imaging technique that uses the correlation between two light beams to reconstruct the image of an object. Conventional GI algorithms require large memory space to store the measured data and perform complicated offline calculations, limiting practical applications of GI. Here we develop an instant ghost imaging (IGI) technique with a differential algorithm and an implemented high-speed on-chip IGI hardware system. This algorithm uses the signal between consecutive temporal measurements to reduce the memory requirements without degradation of image quality compared with conventional GI algorithms. The on-chip IGI system can immediately reconstruct the image once the measurement finishes; there is no need to rely on post-processing or offline reconstruction. This system can be developed into a realtime imaging system. These features make IGI a faster, cheaper, and more compact alternative to a conventional GI system and make it viable for practical applications of GI.

Attosecond transient absorption spooktroscopy: a ghost imaging approach to ultrafast absorption spectroscopy

Recently demonstrated isolated attosecond XFEL pulses should allow the probing of ultrafast electron dynamics at X-ray wavelengths. The authors use ghost imaging to enable high-resolution transient absorption spectroscopy at fluctuating XFEL sources.

Bi-frequency 3D ghost imaging with Haar wavelet transform

Recently, ghost imaging has been attracting attention because its mechanism could lead to many applications inaccessible to conventional imaging methods. However, it is challenging for high-contrast and high-resolution imaging, due to its low signal-to-noise ratio (SNR) and the demand of high sampling rate in detection. To circumvent these challenges, we propose a ghost imaging scheme that exploits Haar wavelets as illuminating patterns with a bi-frequency light projecting system and frequency-selecting single-pixel detectors. This method provides a theoretically 100% image contrast and high-detection SNR, which reduces the requirement of high dynamic range of detectors, enabling high-resolution ghost imaging. Moreover, it can highly reduce the sampling rate (far below Nyquist limit) for a sparse object by adaptively abandoning unnecessary patterns during the measurement. These characteristics are experimentally verified with a resolution of 512×512 and a sampling rate lower than 5%. A high-resolution (1000×1000×1000) 3D reconstruction of an object is also achieved from multi-angle images.

Bell correlations between spatially separated pairs of atoms

Bell correlations are a foundational demonstration of how quantum entanglement contradicts the classical notion of local realism. Rigorous validation of quantum nonlocality have only been achieved between solid-state electron spins, internal states of trapped atoms, and photon polarisations, all weakly coupling to gravity. Bell tests with freely propagating massive particles, which could provide insights into the link between gravity and quantum mechanics, have proven to be much more challenging to realise. Here we use a collision between two Bose-Einstein condensates to generate spin entangled pairs of ultracold helium atoms, and measure their spin correlations along uniformly rotated bases. We show that correlations in the pairs agree with the theoretical prediction of a Bell triplet state, and observe a quantum mechanical witness of Bell correlations with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$6\sigma$$\end{document}6σ significance. Extensions to this scheme could find promising applications in quantum metrology, as well as for investigating the interplay between quantum mechanics and gravity.

Entangled particles some distance apart can be used to show the strikingly nonlocal nature of quantum mechanics. Here the authors generate spatially separated pairs of helium atoms by colliding Bose-Einstein condensates and show that they are entangled by observing nonlocal correlations.

Optimization of light fields in ghost imaging using dictionary learning

Ghost imaging (GI) is a novel imaging technique based on the second-order correlation of light fields. Due to limited number of samplings in practice, traditional GI methods often reconstruct objects with unsatisfactory quality. To improve the imaging results, many reconstruction methods have been developed, yet the reconstruction quality is still fundamentally restricted by the modulated light fields. In this paper, we propose to improve the imaging quality of GI by optimizing the light fields, which is realized via matrix optimization for a learned dictionary incorporating the sparsity prior of objects. A closed-form solution of the sampling matrix, which enables successive sampling, is derived. Through simulation and experimental results, it is shown that the proposed scheme leads to better imaging quality compared to the state-of-the-art optimization methods for light fields, especially at a low sampling rate.

Non-degenerate wavelength computational ghost imaging with thermal light

Non-degenerate wavelength computational ghost imaging with thermal light source is studied theoretically and experimentally. The acquired computational ghost images are of high quality when the wavelength of computed light is different from the light detected by bucket detector. Compared to the necessary light of short wavelength in previous ghost imaging, the use of longer wavelength light is demonstrated to bring about ghost images with higher spatial resolution, in strong atmospheric turbulence.

Higher-Order Quantum Ghost Imaging with Ultracold Atoms

Ghost imaging is a quantum optics technique that uses correlations between two beams to reconstruct an image from photons that do not interact with the object being imaged. While pairwise (second-order) correlations are usually used to create the ghost image, higher-order correlations can be utilized to improve the performance. In this Letter, we demonstrate higher-order atomic ghost imaging, using entangled ultracold metastable helium atoms from an s-wave collision halo. We construct higher-order ghost images up to fifth order and show that using higher-order correlations can improve the visibility of the images without impacting the resolution. This is the first demonstration of higher-order ghost imaging with massive particles and the first higher-order ghost imaging protocol of any type using a quantum source.

High-Contrast Interference of Ultracold Fermions

Many-body interference between indistinguishable particles can give rise to strong correlations rooted in quantum statistics. We study such Hanbury Brown-Twiss-type correlations for number states of ultracold massive fermions. Using deterministically prepared ^{6}Li atoms in optical tweezers, we measure momentum correlations using a single-atom sensitive time-of-flight imaging scheme. The experiment combines on-demand state preparation of highly indistinguishable particles with high-fidelity detection, giving access to two- and three-body correlations in fields of fixed fermionic particle number. We find that pairs of atoms interfere with a contrast close to 80%. We show that second-order density correlations arise from contributions from all two-particle pairs and detect intrinsic third-order correlations.

Structured-Pump-Enabled Quantum Pattern Recognition

We report a new scheme of ghost imaging by using a spatially structured pump in the Fourier domain of spontaneous parametric down-conversion for quantum-correlation-based pattern recognition. We exploit the mathematical feature of Laguerre-Gaussian mode's Fourier transform to describe the pump-modulated formation of a ghost image. Of particular interest is the experimental demonstration of a quantum equivalence of a Vander Lugt filter, based on which the nonlocal spiral phase contrast for vortex mapping and quantum-correlation-based human face recognition are implemented successfully. The photons used for probing a test object, scanning the database, and producing a correlation signal can belong to three different light beams, which suggests some security applications where low-light-level illumination and covert operation are desired.

Approaching the adiabatic timescale with machine learning

The control and manipulation of quantum systems without excitation are challenging, due to the complexities in fully modeling such systems accurately and the difficulties in controlling these inherently fragile systems experimentally. For example, while protocols to decompress Bose-Einstein condensates (BECs) faster than the adiabatic timescale (without excitation or loss) have been well developed theoretically, experimental implementations of these protocols have yet to reach speeds faster than the adiabatic timescale. In this work, we experimentally demonstrate an alternative approach based on a machine-learning algorithm which makes progress toward this goal. The algorithm is given control of the coupled decompression and transport of a metastable helium condensate, with its performance determined after each experimental iteration by measuring the excitations of the resultant BEC. After each iteration the algorithm adjusts its internal model of the system to create an improved control output for the next iteration. Given sufficient control over the decompression, the algorithm converges to a solution that sets the current speed record in relation to the adiabatic timescale, beating out other experimental realizations based on theoretical approaches. This method presents a feasible approach for implementing fast-state preparations or transformations in other quantum systems, without requiring a solution to a theoretical model of the system. Implications for fundamental physics and cooling are discussed.

Electron Ghost Imaging

In this Letter we report a demonstration of electron ghost imaging. A digital micromirror device directly modulates the photocathode drive laser to control the transverse distribution of a relativistic electron beam incident on a sample. Correlating the structured illumination pattern to the total sample transmission then retrieves the target image, avoiding the need for a pixelated detector. In our example, we use a compressed sensing framework to improve the reconstruction quality and reduce the number of shots compared to raster scanning a small beam across the target. Compressed electron ghost imaging can reduce both acquisition time and sample damage in experiments for which spatially resolved detectors are unavailable (e.g., spectroscopy) or in which the experimental architecture precludes full frame direct imaging.

Orthonormalization method in ghost imaging

Ghost imaging system requires a large number of samples to reconstruct the object. Computational ghost imaging can use well-designed pre-modulated orthogonal patterns to reduce the requirement of sampling number and increase the imaging quality, while the rotating ground glass (RGG) scheme cannot. Instead of the pre-modulation method, a post-processing method using Gram-Schmidt process to orthonormalize the patterns in a RGG scheme is introduced. Reconstructed ghost image after the Gram-Schmidt process (SGI) are tested using the quality indicators such as the Contrast-to-Noise (CNR), the Peak Signal to Noise Ratio (PSNR), the Correlation Coefficient (CC) and reducing the Mean Square Error (MSE). Simulation results show that this method has obvious advantage on enhancing the efficiency of image acquisition, and the sampling number requirement drops from several thousands to a few hundreds in ideal condition. However, in actual system with noise, the image quality from SGI declines in large sampling number, for noise and errors accumulate in the orthonormalization process. So an improved Group SGI method is then developed to avoid this error accumulation, which behaves effectively in reconstructing the image from experimental data and show good performances in large sampling number too. Since this method do not change the relationship between the reference patterns and the bucket values, it can easily combine with most of reconstruction algorithms and improve their reconstruction efficiency.

Quantum lidar based on a random interleaved optical pulse sequence consisting of wavelength-time quantum states

Based on a random interleaved optical pulse sequence consisting of wavelength-time quantum states, we have established a quantum lidar model. Multiple quantum states are used as a detection tool for the interception and interference of a target, and multiple wavelengths spanning the ultraviolet to near-infrared waveband are used to avoid interference and improve the detection efficiency. We elaborate upon the working principle of the entire quantum lidar detection system and demonstrate its feasibility through simulations, thereby establishing a foundation for the application of quantum lidar systems aboard satellite platforms at long distances from the high-precision detection of targets.

Bell Inequality, Einstein-Podolsky-Rosen Steering, and Quantum Metrology with Spinor Bose-Einstein Condensates

We propose an experiment, where the Bell inequality is violated in a many-body system of massive particles. The source of correlated atoms is a spinor F=1 Bose-Einstein condensate residing in an optical lattice. We characterize the complete procedure-the local operations, the measurements, and the inequality-necessary to run the Bell test. We show how the degree of violation of the Bell inequality depends on the strengths of the two-body correlations and on the number of scattered pairs. We show that the system can be used to demonstrate the Einstein-Podolsky-Rosen paradox. Also, the scattered pairs are an excellent many-body resource for the quantum-enhanced metrology. Our results apply to any multimode system where the spin-changing collision drives the scattering into separate regions. The presented inquiry shows that such a system is versatile as it can be used for the tests of nonlocality, quantum metrology, and quantum information.

Sub-Rayleigh resolution ghost imaging by spatial low-pass filtering

A sub-Rayleigh resolution ghost imaging experiment is performed via post-detection spatial low-pass filtering of the instantaneous intensity. A super-resolution reconstructed image has been achieved, in which the spatial resolution can exceed the Rayleigh diffraction limit by more than a factor of two. The resolution depends on the filter threshold, and the Rayleigh limit can be exceeded for a wide choice of threshold values. The setup is simple and easy to implement, which is an advantage for practical applications.

Single-pixel computational ghost imaging with helicity-dependent metasurface hologram

Different optical imaging techniques are based on different characteristics of light. By controlling the abrupt phase discontinuities with different polarized incident light, a metasurface can host a phase-only and helicity-dependent hologram. In contrast, ghost imaging (GI) is an indirect imaging modality to retrieve the object information from the correlation of the light intensity fluctuations. We report single-pixel computational GI with a high-efficiency reflective metasurface in both simulations and experiments. Playing a fascinating role in switching the GI target with different polarized light, the metasurface hologram generates helicity-dependent reconstructed ghost images and successfully introduces an additional security lock in a proposed optical encryption scheme based on the GI. The robustness of our encryption scheme is further verified with the vulnerability test. Building the first bridge between the metasurface hologram and the GI, our work paves the way to integrate their applications in the fields of optical communications, imaging technology, and security.

Classical ghost-imaging spectral ellipsometer

We introduce a novel approach for the spectral characterization of inhomogeneous thin films and interfaces by means of an imaging ghost ellipsometer operating with classical light of Gaussian statistics. We show that the device output in general provides the ellipsometric information associated with the fractional Fourier transforms of the sample's reflection coefficients, which in special cases reduce to the Fourier transforms or images. The formalisms for both one-dimensional and two-dimensional samples are presented. The method is insensitive to instrumentation errors and, unlike in traditional ellipsometry, no source or detector calibration is needed.

X-ray ghost imaging with a laboratory source

We describe an experiment demonstrating ghost imaging with an incoherent low brightness X-ray tube source. We reconstruct the images of 10 μm and 100 μm slits with very high contrast. Our results advance the possibilities that the high-resolution method of ghost diffraction will be utilized with tabletop X-ray sources.

Solving the Quantum Many-Body Problem via Correlations Measured with a Momentum Microscope

In quantum many-body theory, all physical observables are described in terms of correlation functions between particle creation or annihilation operators. Measurement of such correlation functions can therefore be regarded as an operational solution to the quantum many-body problem. Here, we demonstrate this paradigm by measuring multiparticle momentum correlations up to third order between ultracold helium atoms in an s-wave scattering halo of colliding Bose-Einstein condensates, using a quantum many-body momentum microscope. Our measurements allow us to extract a key building block of all higher-order correlations in this system-the pairing field amplitude. In addition, we demonstrate a record violation of the classical Cauchy-Schwarz inequality for correlated atom pairs and triples. Measuring multiparticle momentum correlations could provide new insights into effects such as unconventional superconductivity and many-body localization.