Space Ghost: Quantum Ghost Imaging from Orbit
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The non-destructive readout capability of the Skipper Charge Coupled Device (CCD) has been demonstrated to reduce the noise limitation of conventional silicon devices to levels that allow single-photon or single-electron counting. The noise reduction is achieved by taking multiple measurements of the charge in each pixel. These multiple measurements come at the cost of extra readout time, which has been a limitation for the broader adoption of this technology in particle physics, quantum imaging, and astronomy applications. This work presents recent results of a novel sensor architecture that uses multiple non-destructive floating-gate amplifiers in series to achieve sub-electron readout noise in a thick, fully-depleted silicon detector to overcome the readout time overhead of the Skipper-CCD. This sensor is called the Multiple-Amplifier Sensing Charge-Coupled Device (MAS-CCD) can perform multiple independent charge measurements with each amplifier, and the measurements from multiple amplifiers can be combined to further reduce the readout noise. We will show results obtained for sensors with 8 and 16 amplifiers per readout stage in new readout operations modes to optimize its readout speed. The noise reduction capability of the new techniques will be demonstrated in terms of its ability to reduce the noise by combining the information from the different amplifiers, and to resolve signals in the order of a single photon per pixel. The first readout operation explored here avoids the extra readout time needed in the MAS-CCD to read a line of the sensor associated with the extra extent of the serial register. The second technique explore the capability of the MAS-CCD device to perform a region of interest readout increasing the number of multiple samples per amplifier in a targeted region of the active area of the device.
Nuclear forensic analysis techniques work to determine the contents of radiological samples with nondestructive and destructive analysis methods. Autoradiography is a nondestructive analysis method that creates an image of the distribution of radioactivity within the sample. These images allow the location of the radiological content within a sample to be ascertained, which can be used for further analysis. Autoradiography has been used since the discovery of radiation and has been continuously developed to better suit the needs of the medical, nuclear security, nuclear safeguards, and nuclear forensic communities. Recent developments in autoradiography have led to a higher spatial resolution down to a level of tens of microns, real-time capabilities that minimize the risk of overexposure, and the ability to discriminate particles. All of these developments in autoradiography would assist the nuclear forensics community in understanding the placement of radiological content within a sample and in understanding the locations of beta-particle interactions versus those for alpha-particle interactions. This article aims to discuss the history of autoradiography as well as multiple different autoradiographic technologies while focusing on imaging plates, the BeaQuant system, and the ionizing-radiation Quantum Imaging Detector system. This article reviews three autoradiographic techniques and detectors, discusses how they relate to nuclear forensics, and addresses the drawbacks and benefits of each detector.
Recently, optically active spin defects embedded in two-dimensional (2D) van der Waals (vdW) crystals have emerged as a transformative quantum sensing platform to explore cutting-edge materials science. Taking advantage of excellent solid-state integrability, this new class of spin defects can be readily arranged in nanoscale proximity to target materials, showing great promise for realizing in-situ quantum sensing of microscopic spin and charge behaviors in vdW heterostructures. Here we report hexagonal boron nitride-based quantum imaging of field-free deterministic magnetic switching and electric current distributions in an all-vdW spin-orbit torque (SOT) system. By visualizing variations of nanoscale magnetic stray field profile of room-temperature 2D magnet Fe 3 GaTe 2 under different SOT conditions, we show how the magnetic switching evolves from deterministic to stochastic behavior due to the interplay between spin orientations, anisotropy and Joule heating. Micromagnetic simulations rationalize our results well, revealing the role of field-like SOT in inhibiting thermal fluctuation driven stochastic switching and chaotic multi-domain competition. This understanding, which is otherwise difficult to access by conventional transport measurements, offers valuable insights into material design, testing, and performance evaluation of next-generation vdW spintronic devices.
We discuss advantages of using non-classical states of light for two aspects of optical imaging: creating of miniature images on photosensitive substrates, which constitutes the foundation for optical lithography, and conversely, imaging of micro objects. In both cases, the classical resolution limit given by the Rayleigh criterion is approximately a half of the optical wavelength. It has been shown, however, that by using multi-photon quantum states of the light field, and multi-photon sensitive material or detector, this limit can be surpassed. In the present work, we give a rigorous quantum mechanical treatment of this problem, address some particularly widespread misconceptions and discuss the requirements arising on the way of turning the research on quantum imaging into a practical technology.
Quantum metrology takes advantage of quantum correlations to enhance the sensitivity of sensors and measurement techniques beyond their fundamental classical limit, given by the shot-noise limit. The use of both temporal and spatial correlations present in quantum states of light can extend quantum-enhanced sensing to a parallel configuration that can simultaneously probe an array of sensors or independently measure multiple parameters. To this end, we use multispatial-mode bright twin beams of light, which are characterized by independent quantum-correlated spatial subregions in addition to quantum temporal correlations, to probe a four-sensor quadrant plasmonic array. We show that it is possible to independently and simultaneously measure local changes in refractive index for all four sensors with a quantum enhancement in sensitivity in the range of 22% to 24% over the corresponding classical configuration. Finally, these results provide a first step toward highly parallel spatially resolved quantum-enhanced sensing techniques and pave the way toward more complex quantum sensing and quantum imaging platforms.
The multiple-amplifier sensing charge-coupled device (MAS-CCD) has emerged as a promising technology for astronomical observation, quantum imaging, and low-energy particle detection due to its ability to reduce the readout time for the same readout noise level compared with its predecessor, the skipper-CCD, by reading out the same charge packet through multiple inline amplifiers. Previous works identified a new parameter in this sensor, called node removal inefficiency (NRI), related to inefficiencies in charge transfer and residual charge removal from the sense node of each amplifier after readout. These inefficiencies can lead to distortions in the measured signals similar to those produced by the charge transfer inefficiencies in standard CCDs. We introduce more details in the mathematical model of the NRI mechanism and provide techniques to quantify its magnitude from the measured data. It also proposes a new operation strategy that significantly reduces its effect with minimal alterations of the timing sequences or voltage settings for the other signals of the sensor. The proposed technique is demonstrated experimentally on a 16-amplifier MAS-CCD. At the same time, the experimental data demonstrate that this approach minimizes the NRI effect to levels comparable with other sources of distortion such as the charge transfer inefficiency in scientific devices.
Classically there has existed an asymmetry between the computing and communicating sides of aerospace systems. Over the past few decades, this asymmetry has shifted to favoring communication link technologies, meaning that advancements in available central processing units (CPUs), storage devices, and internal data buses have stagnated. Indeed, the increased emphasis placed on refining subsystem performance such as with antenna bandwidth in phased arrays, amplifier power efficiency, software defined radio (SDR) flexibility and encoding for data compression and error correction has given rise to successful debuts of multi-gigabit-per-second data return from long space-link distances. These accomplishments are easily quantifiable through link budgets and illustrate what is possible, but also reveal the deficiencies in overall communications capabilities. In particular, the ever-accelerating presence of aerospace vehicles gives rise to newer and larger classes of challenges to address the needs of 21st century systems. Furthermore remote sensing and imaging capabilities have far outpaced our ability to transmit their products to the ground, so we are increasingly dependent on pre-processing and downselection to contend with the communications bottleneck. No longer may we depend upon the constrained logistics in delivering end-to-end data delivery through manual reconfigurations, static event scheduling and execution on a per-vehicle basis, for these methods do not scale and therefore must give way to dynamic, networked approaches with an overall systems view in mind. Emerging mission requirements exhibit a trend toward multiple smaller-scale vehicles working together to perform dissimilar observations. Such operations necessitate sensor fusion across a constellation, and where data processing may be distributed throughout a fairly disconnected network whose topology changes over time in non-deterministic manners. Individual communications link performance is still very relevant to deploying an effective communications system, but now must be embedded within a greater architecture of capability to optimally utilize the bandwidth available from each link to generate an ultimate end-to-end quality of service. The deleterious effects of timing uncertainty across the arrangement presents a challenge to measurement synchronization and delivery, so a successful deployed system needs to be tolerant to the delays inherent in time-of-light between elements and digital processing latencies existing at each node. In this presentation we share the flight test results from a high performance Gbps laser communications terminal evaluated with a suite of store and forward capabilities called High-rate Delay Tolerant Networking (HDTN). The communications payload is operated over Lake Erie across a range of configurations including several convergence layers, and is evaluated to determine recovery time after link disruptions, information loss, efficiency and speed. The effectiveness of utilizing a flying laboratory to increase the Technology Readiness Level (TRL) of an integrated system in relevant environments is discussed, as well as the value of conducting aeronautics experiments to retire risk for technology infusion into space missions. Upcoming flight campaigns will be presented, including opportunities to demonstrate secure command and control, data intensive hyperspectral imaging, quantum link characterization, 4k High Definition (HD) video streaming and internetworked space-ground-aero relay operations. These experiments will pave the way for future missions which will depend upon interoperability across disparate government and privately owned networks, involve contention with uncertain and dynamic timing, and require agility to autonomously configure optimal parameters across networks of ever-increasing size and complexity to ensure data delivery. https://www1.grc.nasa.gov/space/scan/acs/tech-studies/dtn/
We theoretically investigate quantum-enhanced coherent anti-Stokes Raman scattering (CARS) using squeezed light to amplify vibrational transition rates at low photon flux. Quantum sensing approaches are needed for nondestructive nanometrology such as in bioimaging where reduced photodamage is desired while retaining resolution and sensitivity. We analyze both single-mode squeezing applied to the pump field and two-mode squeezing between the pump and Stokes fields. We also show that the ordering of displacement and squeezing operations—whether displacement precedes squeezing or squeezing precedes displacement—has an impact on the resulting CARS transition amplitudes due to a difference in the photon number and the quantum-enhancement coefficients, with the latter offering a stronger enhancement in the case of two modes squeezing of the pump and Stokes under experimentally accessible conditions. Furthermore, our calculations capture these quantum enhancements through the intrinsic photon-number correlations of squeezed light, eliminating the need for interferometric detection or higher pump powers that are otherwise required to reach comparable sensitivities in classical CARS. Finally, we outline a quantum plasmonic extension of our model in which local field enhancements caused by surface plasmon excitation in metallic nanoparticles can be incorporated via mode-selective field amplification factors, offering a pathway toward combining squeezed-light quantum optics with surface-enhanced nanoscale spectroscopy and imaging.
Measurements and comparisons have been made of the quantum efficiencies of microchannel plate (MCP) detectors in the far-UV (below 2000-A) wavelength range using CsI photocathodes (a) deposited on the front surfaces of microchannel plates and (b) deposited on solid substrates as opaque photocathodes with the resulting photoelectrons input to microchannel plates. The efficiences were measured in both pulse-counting and photodiode modes of operation. Typical efficiencies are about 15 percent at 1216 A for a CsI-coated MCP compared with 65 percent for an opaque CsI photocathode MCP detector. Special processing has yielded an efficiency as high as 20 percent for a CsI-coated MCP. This may possibly be further improved by optimization of the tilt angle of the MCP channels relative to the front face of the MCP and incident radiation. However, at present there still remains a factor of at least 3 quantum efficiency advantage in the separate opaque CsI photocathode configuration.
Graph and network theory play a fundamental role in quantum computer sciences, including quantum information and computation. Random graphs and complex network theory are pivotal in predicting novel quantum phenomena, where entangled links are represented by edges. Quantum algorithms have been developed to enhance solutions for various network problems, giving rise to quantum graph computing and quantum graph learning (QGL). Here, in this review, we explore graph theory and graph learning methods as powerful tools for quantum computers to generate efficient solutions to problems beyond the reach of classical systems. We delve into the development of quantum complex network theory and its applications in quantum computation, materials discovery, and research. We also discuss quantum machine learning (QML) methodologies for effective image classification using qubits, quantum gates, and quantum circuits. Additionally, the paper addresses the challenges of QGL and algorithms, emphasizing the steps needed to develop flexible QGL solvers. This review presents a comprehensive overview of the fields of QGL and QML, highlights recent advancements, and identifies opportunities for future research.
The Intensity Dependent Spread (IDS) procedure is an image-processing technique based on a model of the processing which occurs in the human visual system. IDS processing is relevant to many aspects of machine vision and image processing. For quantum limited images, it produces an ideal trade-off between spatial resolution and noise averaging, performs edge enhancement thus requiring only mean-crossing detection for the subsequent extraction of scene edges, and yields edge responses whose amplitudes are independent of scene illumination, depending only upon the ratio of the reflectance on the two sides of the edge. These properties suggest that the IDS process may provide significant bandwidth reduction while losing only minimal scene information when used as a preprocessor at or near the image plane.
The 10-micron intersubband absorption in quantum wells made of the silicon-based system, Si/Si(1-x)Ge(x), has been calculated. The necessary details of the effective-mass anisotropy are included in the present analysis. It is found that it is readily possible to achieve an absorption constant of order of 10,000/cm in Si quantum wells with current doping technology. For 110-line and 111-line growth directions, a further advantage of Si quantum wells is pointed out, namely, an allowed absorption at normal incidence due to the anisotropic effective mass in Si.
The theory of partial coherence has a long and storied history in classical statistical optics. the vast majority of this work addresses fields that are statistically stationary in time, hence their complex envelopes only have phase-insensitive correlations. The quantum optics of squeezed-state generation, however, depends on nonlinear interactions producing baseband field operators with phase-insensitive and phase-sensitive correlations. Utilizing quantum light to enhance imaging has been a topic of considerable current interest, much of it involving biphotons, i.e., streams of entangled-photon pairs. Biphotons have been employed for quantum versions of optical coherence tomography, ghost imaging, holography, and lithography. However, their seemingly quantum features have been mimicked with classical-sate light, questioning wherein lies the classical-quantum boundary. We have shown, for the case of Gaussian-state light, that this boundary is intimately connected to the theory of phase-sensitive partial coherence. Here we present that theory, contrasting it with the familiar case of phase-insensitive partial coherence, and use it to elucidate the classical-quantum boundary of ghost imaging. We show, both theoretically and experimentally, that classical phase-sensitive light produces ghost imaging most closely mimicking those obtained in biphotons, and we derived the spatial resolution, image contrast, and signal-to-noise ratio of a standoff-sensing ghost imager, taking into account target-induced speckle.
Quantum sensing promises to revolutionize sensing applications by employing quantum states of light or matter as sensing probes. Photons are the clear choice as quantum probes for remote sensing because they can travel to and interact with a distant target. Existing schemes are mainly based on the quantum illumination framework, which requires quantum memory to store a single photon of an initially entangled pair until its twin reflects off a target and returns for final correlation measurements. Existing demonstrations are limited to tabletop experiments, and expanding the sensing range faces various roadblocks, including long-time quantum storage and photon loss and noise when transmitting quantum signals over long distances. We propose a novel quantum sensing framework that addresses these challenges using quantum frequency combs with path identity for remote sensing of signatures (“qCOMBPASS”). The combination of one key quantum phenomenon and two quantum resources—namely, quantum-induced coherence by path identity, quantum frequency combs, and two-mode squeezed light—allows for quantum remote sensing without requiring quantum memory. The proposed scheme is akin to a quantum radar based on entangled frequency-comb pairs that uses path identity to detect, range, or sense a remote target of interest by measuring pulses of one comb in the pair that never traveled to the target but that contains target information “teleported” by quantum-induced coherence by path identity from the other comb in the pair that traveled to the target but is not detected. We develop the basic qCOMBPASS theory, analyze the properties of the qCOMBPASS transceiver, and introduce the qCOMBPASS equation—a quantum analog of the well-known LIDAR equation in classical remote sensing. We also describe an experimental scheme to demonstrate the concept using two-mode squeezed quantum combs. qCOMBPASS can strongly impact various applications in remote quantum sensing, imaging, metrology, and communications. These applications include detection and ranging of low-reflectivity objects, measurement of small displacements of a remote target with precision beyond the standard quantum limit (SQL), standoff hyperspectral quantum imaging, discreet surveillance from space with low detection probability (detect without being detected), very-long-baseline interferometry, quantum Doppler sensing, quantum clock synchronization, and networks of distributed quantum sensors. Published by the American Physical Society 2024
Quantum well infrared photodetector technology has shown remarkable success by realizing large-format focal plane arrays in both broad-bands and in multi-bands. The spectral response of these detectors based on the III-V material system are tailorable within the mid and long wavelength IR bands (similar to 3-25 mu m) and possibly beyond. Multi-band and broad-band detector arrays have been developed by vertically integrating stacks of multi quantum wells tailored for response in different wavelengths bands. Each detector stack absorbs photons within the specified wavelength band while allowing the transmission other photons, thus efficiently permitting multiband detection. Flexibility in many design parameters of these detectors allows for tuning and tailoring the spectral shape according to application requirements, specifically for spectral imaging instruments.
Long wavelength Quantum Well Infrared Photodetector (QWIP) cameras developed at the Jet Propulsion Laboratory demonstrate the potential of GaAs/A1xGa1-xAs QWIP technology for highly sensitive, low power, low cost, and highly uniform large format FPA imaging systems.
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