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A quantum well infrared photodetector (QWIP) that provides two-color image sensing. Two different quantum wells are configured to absorb two different wavelengths. The QWIPs are arrayed in a focal plane array (FPA). The two-color QWIPs are selected for readout by selective electrical contact with the two different QWIPs or by the use of two different wavelength sensitive gratings.
Over the last decade, the incidence of wildfires has surged, causing widespread destruction globally. To better comprehend and manage these incidents, remote sensing and aerial missions have been implemented in recent efforts. However, this has resulted in an exponential rise in the amount of remote sensing data utilization, leading to a need for intelligent automation of data extraction in wildfire studies. Machine learning provides an accurate automated approach for detecting these natural anomalies and facilitates decision-makers to take prompt actions. To make insightful decisions in wildfire management, it is imperative to move beyond simple detection and explore the potential of probabilistic generative machine learning for creating "what-if" scenarios for various wildfire conditions. Such models offer improved representation of the stochastic nature of wildfire events. However, the optimization of these models can be computationally expensive, especially when using classical computers. Quantum computers have recently emerged as a promising solution to reduce the computational cost of training such models and improve their performance. In this study, we aim to utilize quantum-compatible machine learning techniques to implement our probabilistic generative approach. To that end, we propose a supervised probabilistic variational model consisting of a U-NET-based image-to-image component along with encoder and decoder networks which work as a variational autoencoder (VAE) component. Additionally, we explore the type of latent distribution type in the VAE component and implement different means for modeling the prior distribution. We further investigate the quantum-compatible versions of the model compared to the classical counterpart and benchmark potential benefits of quantum compatibility over the classical model.
The recent FY 2020 federal Research and Development Budget Priorities memo addresses the leadership need in Quantum Information Science (QIS) directing agencies to “prioritize QIS research and development (R&D), which will build the technical and scientific base necessary to explore the next generation of QIS theory, devices, and applications.” Quantum Sensing (QS) is an integral part of QIS. NASA is a key part of the directive to forward American space exploration and commercialization by providing “capabilities that have broad potential applications in space and on Earth.” QS provides an arena for NASA to demonstrate leadership in both areas of the administrative directive. QS uses quantum properties to achieve unprecedented measurement sensitivity and performance, including quantum-enhanced methodologies that outperform their classical counterparts. Typical quantum sensors exploit techniques such as atomic systems, matter waves, quantum entanglement, quantum superposition of states, quantum illumination methods, and manipulation of photons and atoms, in general. Guided by advancements in our ability to generate, manipulate, and control quantum systems, the emerging quantum sensing technologies promise unrivalled sensitivity, resolution, and precision, potentially leading to game-changing applications. Significant gains include technologies important for a range of NASA missions such as remote sensing, in situ measurements, metrology, interferometry, quantum communication, ranging, imaging, radar and lidar receivers, and gravity measurements. NASA Engineering and Safety Center has convened an independent external panel, comprising of Quantum Sensing Experts from Government, DoD, academia, and Federally funded Research and Development Center to conduct an independent technical assessment of the agency's capabilities in Quantum Sensing to understand NASA's internal needs and competencies related to Quantum Sensing and compare agency capabilities with those available externally including industry, academia, and other government agencies. The outcomes of the assessment will help the agency in establishing appropriate strategies and investments to develop and maintain the state-of-the-art sensing competence and capabilities required to meet the agency’s future needs. The External Experts Panel (EEP) is collaborating with HQ, various NASA Center and the representatives in the NASA Quantum Sensing Community of Practice (QS CoP), a part of NASA Sensors and Instrumentation Technical Fellow Technical Discipline Team, in obtaining common, current understanding of agency mission needs where QS can be an important enabler for future needs, and any programs, projects, assets, and technologists working in QS. The EEP organized a Quantum Sensing Workshop of practitioners from industry, academia, other government agencies, external experts, and interested NASA personnel to gather the assessment information. EEP also conducted information gathering on the industry at large, educational institutions, and other government agency research efforts for capture in the assessment database. At the conclusion of this assessment, EEP team will develop findings and conclusions describing NASA’s capabilities for the mission needs, NASA's relative position on new, enabling technologies, and an analysis of the gaps that may present any risks to near-term or far-term mission needs. This presentation will give details of the NASA and External Quantum Sensing Assessment outcomes, findings, observations, and its recommendation to NASA as how it can advance Quantum Sensing technologies and techniques for its science and explorations related missions.
A new gradiometer scheme uses middle loops as sensing elements in lowfield superconducting quantum interference device (SQUID) magnetic resonance imaging (MRI). This design of a second order gradiometer increases its sensitivity and makes it more uniform, compared to the conventional side loop sensing scheme with a comparable matching SQUID. The space between the two middle loops becomes the imaging volume with the enclosing cryostat built accordingly.
Inexpensive far-infrared imaging radiometer contains 128 X 128-picture-element array of AlxGa1-xAs quantum-well detectors. Potentially useful in remote sensing from airborne platforms. Industrial applications include rapid thermal imaging of heat-sensitive components. Astronomical applications include imaging of planets and Sun.
The James Webb Space Telescope (JWST) is easily one of the most advanced devices ever created by humans, bridging a gap between the macroscopic and quantum worlds in terms of how accurately we can align mirrors. It is the product of exhaustive testing, countless innovations, and the international collaboration between 1000’s of people working tirelessly for more than 20 years. In this talk we discuss the physics of image-based wavefront sensing: one of the core technologies that was utilized to complete the final alignment of the segmented mirror.
An interdisciplinary quantum communications and sensing research effort has been underway at the NASA Glenn Research Center since the summer of 2000. Researchers in the Communications Technology, Instrumentation and Controls, and Propulsion and Turbomachinery Divisions have been working together to study and develop techniques that use the principle of quantum entanglement (QE). This work is supported principally by the Nanotechnology Base R&T program at Glenn. As applied to communications and sensing, QE is an emerging technology that holds promise as a new and innovative way to communicate faster and farther, and to sense, measure, and image environmental properties in ways that are not possible with existing technology. Quantum entangled photons are "inseparable" as described by a wave function formalism. For two entangled photons, the term "inseparable" means that one cannot describe one photon without completely describing the other. This inseparability gives rise to what appears as "spooky," or nonintuitive, behavior because of the quantum nature of the process. For example, two entangled photons of lower energy can be created simultaneously from a single photon of higher energy in a process called spontaneous parametric down-conversion. Our research is focused on the use of polarization-entangled photons generated by passing a high-energy (blue) photon through a nonlinear beta barium borate crystal to generate two red photons that have orthogonal, but entangled, polarization states. Although the actual polarization state of any one photon is not known until it is measured, the act of measuring the polarization of one photon completely determines the polarization state of its twin because of entanglement. This unique relationship between the photons provides extra information about the system. For example, entanglement makes it easy to distinguish entangled photons from other photons impinging on a detector. For many other applications, ranging from quantum computation and information to quantum sensing, the entanglement property is critical.
An optimized geometry has been proposed for superconducting sensing coils that are used in conjunction with superconducting quantum interference devices (SQUIDs) in magnetic resonance imaging (MRI), magnetoencephalography (MEG), and related applications in which magnetic fields of small dipoles are detected. In designing a coil of this type, as in designing other sensing coils, one seeks to maximize the sensitivity of the detector of which the coil is a part, subject to geometric constraints arising from the proximity of other required equipment. In MRI or MEG, the main benefit of maximizing the sensitivity would be to enable minimization of measurement time. In general, to maximize the sensitivity of a detector based on a sensing coil coupled with a SQUID sensor, it is necessary to maximize the magnetic flux enclosed by the sensing coil while minimizing the self-inductance of this coil. Simply making the coil larger may increase its self-inductance and does not necessarily increase sensitivity because it also effectively increases the distance from the sample that contains the source of the signal that one seeks to detect. Additional constraints on the size and shape of the coil and on the distance from the sample arise from the fact that the sample is at room temperature but the coil and the SQUID sensor must be enclosed within a cryogenic shield to maintain superconductivity.
In recent years, some remote-sensing applications require advanced airborne multi-sensor systems to provide high performance reflective and emissive spectral imaging measurement rapidly over large areas. The key or unique problem of characteristics is associated with a black box back-end system that operates a suite of cutting-edge imaging sensors to collect simultaneously the high throughput reflective and emissive spectral imaging data with precision georeference. This back-end system needs to be portable, easy-to-use, and reliable with advanced onboard processing. The innovation of the black box backend is a miniaturized airborne imaging central server system (MAICSS). MAICSS integrates a complex embedded system of systems with dedicated power and signal electronic circuits inside to serve a suite of configurable cutting-edge electro- optical (EO), long-wave infrared (LWIR), and medium-wave infrared (MWIR) cameras, a hyperspectral imaging scanner, and a GPS and inertial measurement unit (IMU) for atmospheric and surface remote sensing. Its compatible sensor packages include NASA s 1,024 1,024 pixel LWIR quantum well infrared photodetector (QWIP) imager; a 60.5 megapixel BuckEye EO camera; and a fast (e.g. 200+ scanlines/s) and wide swath-width (e.g., 1,920+ pixels) CCD/InGaAs imager-based visible/near infrared reflectance (VNIR) and shortwave infrared (SWIR) imaging spectrometer. MAICSS records continuous precision georeferenced and time-tagged multisensor throughputs to mass storage devices at a high aggregate rate, typically 60 MB/s for its LWIR/EO payload. MAICSS is a complete stand-alone imaging server instrument with an easy-to-use software package for either autonomous data collection or interactive airborne operation. Advanced multisensor data acquisition and onboard processing software features have been implemented for MAICSS. With the onboard processing for real time image development, correction, histogram-equalization, compression, georeference, and data organization, fast aerial imaging applications, including the real time LWIR image mosaic for Google Earth, have been realized for NASA fs LWIR QWIP instrument. MAICSS is a significant improvement and miniaturization of current multisensor technologies. Structurally, it has a complete modular and solid-state design. Without rotating hard drives and other moving parts, it is operational at high altitudes and survivable in high-vibration environments. It is assembled from a suite of miniaturized, precision-machined, standardized, and stackable interchangeable embedded instrument modules. These stackable modules can be bolted together with the interconnection wires inside for the maximal simplicity and portability. Multiple modules are electronically interconnected as stacked. Alternatively, these dedicated modules can be flexibly distributed to fit the space constraints of a flying vehicle. As a flexibly configurable system, MAICSS can be tailored to interface a variety of multisensor packages. For example, with a 1,024x1,024 pixel LWIR and a 8,984x6,732 pixel EO payload, the complete MAICSS volume is approximately 7x9x11 in. (=18x23x28 cm), with a weight of 25 lb (=11.4 kg).
Wildfire occurrences have been increasing for the past decade, leaving devastating traces across the world. In the recent efforts, remote sensing and airborne missions have been utilized to better understand and manage wildfires. This has resulted in an exponential increase in volume of remote sensing data, which has pushed the need for intelligent automation of data extraction for wildfire studies. Machine learning offers accurate automation in detecting such natural anomalies and enable decision-makers to take actions in a timely manner. Recent advances in machine learning algorithms, namely probabilistic generative methods, allow researchers and decisionmakers to step beyond detection and study “what-if” scenarios for wildfire occurrences. Additionally, they offer better imitations to the stochastic behavior of nature, and wildfire events. However, optimizing the performance of these probabilistic generative models is a computationally expensive process, specially using digital computers. On the other hand, quantum computers have recently shown a promise to reduce computationally costly training of such models and provide performance improvements. There is a body of research investigating the potential for improved machine learning methods in which key operations are performed on a quantum computer. In this study, we propose a probabilistic image-toimage segmentation approach combining a very well-known segmentation method, U-NET, with a Conditional Variational Auto-Encoder (CVAE) to not only detect wildfires but also describe the stochasticity of the phenomenon and be capable of running “what-if” scenarios. Our proposed model is compatible with training on quantum computers, which results in a quantum-assisted image-to-image segmentation approach and can be used to benchmark the potential benefit of quantum computing over the classical one.
A heterogeneous material construction has been devised for sensing coils of superconducting quantum interference device (SQUID) magnetometers that are subject to a combination of requirements peculiar to some advanced applications, notably including low-field magnetic resonance imaging for medical diagnosis. The requirements in question are the following: The sensing coils must be large enough (in some cases having dimensions of as much as tens of centimeters) to afford adequate sensitivity; The sensing coils must be made electrically superconductive to eliminate Johnson noise (thermally induced noise proportional to electrical resistance); and Although the sensing coils must be cooled to below their superconducting- transition temperatures with sufficient cooling power to overcome moderate ambient radiative heat leakage, they must not be immersed in cryogenic liquid baths. For a given superconducting sensing coil, this combination of requirements can be satisfied by providing a sufficiently thermally conductive link between the coil and a cold source. However, the superconducting coil material is not suitable as such a link because electrically superconductive materials are typically poor thermal conductors. The heterogeneous material construction makes it possible to solve both the electrical- and thermal-conductivity problems. The basic idea is to construct the coil as a skeleton made of a highly thermally conductive material (typically, annealed copper), then coat the skeleton with an electrically superconductive alloy (typically, a lead-tin solder) [see figure]. In operation, the copper skeleton provides the required thermally conductive connection to the cold source, while the electrically superconductive coating material shields against Johnson noise that originates in the copper skeleton.
It is pointed out that the ambitious goals envisaged for the next generation of space-borne sensors challenge the state-of-the-art in solid-state imaging technology. Studies are being conducted with the aim to provide focal plane array technology suitable for use in future Multispectral Linear Array (MLA) earth resource instruments. An important new technology for IR-image sensors involves the use of monolithic Schottky barrier infrared charge-coupled device arrays. This technology is suitable for earth sensing applications in which moderate quantum efficiency and intermediate operating temperatures are required. This IR sensor can be fabricated by using standard integrated circuit (IC) processing techniques, and it is possible to employ commercial IC grade silicon. For this reason, it is feasible to construct Schottky barrier area and line arrays with large numbers of elements and high-density designs. A Pd2Si Schottky barrier sensor for multispectral imaging in the 1 to 3.5 micron band is under development.
The mid and thermal infrared (MTIR) for the Earth surface is defined between 3 and 14µm. In the outer solar system, objects are colder and their Planck response shifts towards longer wavelengths. Hence for these objects (e.g. icy moons, polar caps, comets, Europa), the thermal IR definition usually stretches out to 50µm and beyond. Spectroscopy has been a key part of this scientific exploration because of its ability to remotely determine elemental and mineralogical composition. Many key gas species such as methane, ammonia, sulfur, etc. also have vibrational bands which show up in the thermal infrared spectrum above the background response. Over the past few decades, the Jet Propulsion Laboratory has been building up a portfolio of technology to capture the MTIR for various scientific applications. Three recent sensors are briefly reviewed: The airborne Hyperspectral thermal emission spectrometer (HyTES), the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) and Mars Climate Sounder (MCS)/DIVINER. Each of these sensors utilize a different technology to provide a remote sensing product based on MTIR science. For example, HyTES is a push-brooming hyperspectral imager which utilizes a large format quantum well infrared photodetector (QWIP). The goal is to transition this to a new complementary barrier infrared photodetector (CBIRD) with a similar long wave cut-off and increased sensitivity. ECOSTRESS is a push-whisk Mercury Cadmium Telluride (MCT) based high speed, multi-band, imager which will eventually observe and characterize plant/vegetation functionality and stress index from the International Space Station (ISS) across the contiguous United States (CONUS). MCS/DIVINER utilizes thermopile technology to capture the thermal emission from the polar caps and shadow regions of the moon. Each sensor utilizes specific JPL technology to capture unique science. similar long wave cut-off and increased sensitivity. ECOSTRESS is a push-whisk Mercury Cadmium Telluride (MCT) based high speed, multi-band, imager which will eventually observe and characterize plant/vegetation functionality and stress index from the International Space Station (ISS) across the contiguous United States (CONUS). MCS/DIVINER utilizes thermopile technology to capture the thermal emission from the polar caps and shadow regions of the moon. Each sensor utilizes specific JPL technology to capture unique science.
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.
The paper describes an X-ray detector using microchannel plates as a photocathode surface and imaging photoelectron multiplier, and a crossed wire grid as a two-dimensional position-sensitive detector. The position resolution is 10 microns. The crossed wire grid consists of 100-micron-diam wires on 200-micron centers. Position sensing is accomplished by electronic interpolation to 1/20 of the wire spacing. The quantum efficiency of the microchannel plates varies from 29% at 0.28 keV to 5% at 3 keV. This detector will provide second-of-arc X-ray imaging in the focal plane of the 342.9-cm focal length grazing-incidence telescope being prepared for the HEAO-B observatory. By addition of suitable photocathodes, it can be used for single-photon imaging light detection in the UV, visible, and near-IR-ranges. In all cases, it gives a very low dark counting rate, allows timing of individual events to 1 microsec or less, and can handle counting rates up to 10,000 per sec.
Topics covered include: Optoelectronic Tool Adds Scale Marks to Photographic Images; Compact Interconnection Networks Based on Quantum Dots; Laterally Coupled Quantum-Dot Distributed-Feedback Lasers; Bit-Serial Adder Based on Quantum Dots; Stabilized Fiber-Optic Distribution of Reference Frequency; Delay/Doppler-Mapping GPS-Reflection Remote-Sensing System; Ladar System Identifies Obstacles Partly Hidden by Grass; Survivable Failure Data Recorders for Spacecraft; Fiber-Optic Ammonia Sensors; Silicon Membrane Mirrors with Electrostatic Shape Actuators; Nanoscale Hot-Wire Probes for Boundary-Layer Flows; Theodolite with CCD Camera for Safe Measurement of Laser-Beam Pointing; Efficient Coupling of Lasers to Telescopes with Obscuration; Aligning Three Off-Axis Mirrors with Help of a DOE; Calibrating Laser Gas Measurements by Use of Natural CO2; Laser Ranging Simulation Program; Micro-Ball-Lens Optical Switch Driven by SMA Actuator; Evaluation of Charge Storage and Decay in Spacecraft Insulators; Alkaline Capacitors Based on Nitride Nanoparticles; Low-EC-Content Electrolytes for Low-Temperature Li-Ion Cells; Software for a GPS-Reflection Remote-Sensing System; Software for Building Models of 3D Objects via the Internet; "Virtual Cockpit Window" for a Windowless Aerospacecraft; CLARAty Functional-Layer Software; Java Library for Input and Output of Image Data and Metadata; Software for Estimating Costs of Testing Rocket Engines; Energy-Absorbing, Lightweight Wheels; Viscoelastic Vibration Dampers for Turbomachine Blades; Soft Landing of Spacecraft on Energy-Absorbing Self-Deployable Cushions; Pneumatically Actuated Miniature Peristaltic Vacuum Pumps; Miniature Gas-Turbine Power Generator; Pressure-Sensor Assembly Technique; Wafer-Level Membrane-Transfer Process for Fabricating MEMS; A Reactive-Ion Etch for Patterning Piezoelectric Thin Film; Wavelet-Based Real-Time Diagnosis of Complex Systems; Quantum Search in Hilbert Space; Analytic Method for Computing Instrument Pointing Jitter; and Semiselective Optoelectronic Sensors for Monitoring Microbes.
An interdisciplinary quantum communications and sensing research effort for application in microdevices has been underway at the NASA Glenn Research Center since 2000. Researchers in Glenn's Instrumentation and Controls, Communications Technology, and Propulsion and Turbomachinery Divisions have been working together to study and develop techniques that utilize quantum effects for sensing and communications. The emerging technology provides an innovative way to communicate faster and farther using less power and to sense, measure, and image environmental properties in ways that are not possible with existing technology.
Sensors based on quantum mechanical properties of electromagnetic radiation and matter offer unique capabilities and performance sometimes difficult to achieve using classical approaches. This report assesses the suitability of quantum sensing for current and future NASA needs, with a specific focus on NASA’s Science Mission Directorate (SMD). Measurement and sensing needs across NASA SMD are reviewed as a driver for the possible incorporation of existing quantum sensors into the NASA portfolio and the development of next-generation quantum sensors. A range of quantum sensing modalities is then described and the current state of the art for each sensor is presented. Current research and development activities on quantum sensing within NASA are compared with the range of activities ongoing throughout the broader scientific community, both within the United States and internationally. In conclusion, there is considerable advantage to be gained by NASA from quantum sensors through the growth of internal programs and collaboration with outside entities.