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At least 19 records

Intensity dependent spread theory

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.

Holben, Richard↗

Quantum JPEG

The joint photographic expert group algorithm compresses a digital image by filtering its high spatial-frequency components. Similarly, we introduce a quantum algorithm that uses the quantum Fourier transform to discard the high spatial-frequency qubits of an image, downsampling it to a lower resolution. This allows one to capture, compress, and send images even with limited quantum resources for storage and communication. We show under which conditions this protocol is advantageous with respect to its classical counterpart.

97 MATHEMATICS AND COMPUTING↗

Generalized Quantum Convolution for Multidimensional Data

The convolution operation plays a vital role in a wide range of critical algorithms across various domains, such as digital image processing, convolutional neural networks, and quantum machine learning. In existing implementations, particularly in quantum neural networks, convolution operations are usually approximated by the application of filters with data strides that are equal to the filter window sizes. One challenge with these implementations is preserving the spatial and temporal localities of the input features, specifically for data with higher dimensions. In addition, the deep circuits required to perform quantum convolution with a unity stride, especially for multidimensional data, increase the risk of violating decoherence constraints. In this work, we propose depth-optimized circuits for performing generalized multidimensional quantum convolution operations with unity stride targeting applications that process data with high dimensions, such as hyperspectral imagery and remote sensing. We experimentally evaluate and demonstrate the applicability of the proposed techniques by using real-world, high-resolution, multidimensional image data on a state-of-the-art quantum simulator from IBM Quantum.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Quantum Leap for Dynamic Radiography

Dynamic radiography techniques have been instrumental in advancing the National Nuclear Security Administration's (NNSA) mission since WWII. This paper explores the transformative potential of quantum information science (QIS) to revolutionize dynamic radiography through enhanced image processing, tomographic reconstruction, statistics and uncertainty quantification (UQ), and artificial intelligence integration. By leveraging quantum algorithms to extract previously inaccessible information from existing datasets, this interdisciplinary approach promises unprecedented insights at the intersection of dynamic imaging, artificial intelligence, and quantum information technologies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Scintillating Quantum Dots for Imaging X-rays (SQDIX) for Aircraft Inspection

Scintillation is the process currently employed by conventional x-ray detectors to create x-ray images. Scintillating quantum dots or nano-crystals (StQDs) are a novel, nanometer-scale material that upon excitation by x-rays, re-emit the absorbed energy as visible light. StQDs theoretically have higher output efficiency than conventional scintillating materials and are more environmental friendly. This paper will present the characterization of several critical elements in the use of StQDs that have been performed along a path to the use of this technology in wide spread x-ray imaging. Initial work on the SQDIX system has shown great promise to create state-of-the-art sensors using StQDs as a sensor material. In addition, this work also demonstrates a high degree of promise using StQDs in microstructured fiber optics. Using the microstructured fiber as a light guide could greatly increase the capture efficiency a StQDs based imaging sensor.

Burke, Eric↗

Scintillating Quantum Dots for Imaging X-Rays (SQDIX) for Aircraft Inspection

Scintillation is the process currently employed by conventional X-ray detectors to create X-ray images. Scintillating quantum dots (StQDs) or nano-crystals are novel, nanometer-scale materials that upon excitation by X-rays, re-emit the absorbed energy as visible light. StQDs theoretically have higher output efficiency than conventional scintillating materials and are more environmentally friendly. This paper will present the characterization of several critical elements in the use of StQDs that have been performed along a path to the use of this technology in wide spread X-ray imaging. Initial work on the scintillating quantum dots for imaging X-rays (SQDIX) system has shown great promise to create state-of-the-art sensors using StQDs as a sensor material. In addition, this work also demonstrates a high degree of promise using StQDs in microstructured fiber optics. Using the microstructured fiber as a light guide could greatly increase the capture efficiency of a StQDs based imaging sensor.

Burke, E. R.↗

Thematic Mapper Image Processing System (TIPS) Processing Status

Radiometric and geometric correction performance is considered. A one quantum level requirement was met in all spectral bands with an occasional band 7 exception. Initial post launch calibration was accomplished. An absolute radiometric calibration is in progress including an investigation of low impact solution to scan striping. Initial and three downstream updates as well as coordination with LANDSAT D' instrument calibration are planned. Methods and problems in measuring geometric correction performance are examined with an emphasis on temporal registration, geodetic registrtion, and the modeling error budget. Planned efforts include eliminating band 2, band 5 chips; continued performance monitoring; calibration of profile, misalignment angles, and filer parameters; studying the need for seasonal geodetic control points; and improvement of the subpixel correlation technique.

Brooks, J.↗

Reconfigurable unitary transformations of optical beam arrays

Spatial transformations of light are ubiquitous in optics, with examples ranging from simple imaging with a lens to quantum and classical information processing in waveguide meshes. Multi-plane light converter (MPLC) systems have emerged as a platform that promises completely general spatial transformations, i.e., a universal unitary. However, until now, MPLC systems have demonstrated transformations that are far from general, e.g., converting from a Gaussian to Laguerre-Gauss mode. Here, we demonstrate the promise of an MLPC, the ability to impose an arbitrary unitary transformation that can be reconfigured dynamically. Specifically, we consider transformations on superpositions of parallel free-space beams arranged in an array, which is a common information encoding in photonics. We experimentally test the full gamut of unitary transformations for a system of two parallel beams and make a map of their fidelity. We obtain an average transformation fidelity of 0.85 ± 0.03. This high-fidelity suggests that MPLCs are a useful tool for implementing the unitary transformations that comprise quantum and classical information processing.

47 OTHER INSTRUMENTATION↗

Fast quantum ghost imaging with a single-photon-sensitive time-stamping camera

Quantum ghost imaging (QGI) leverages correlations between entangled photon pairs to reconstruct an image using light that has never physically interacted with an object. Despite extensive research interest, this technique has long been hindered by slow acquisition speeds, due to the use of raster-scanned detectors or the slow response of intensified cameras. Here, we utilize a single-photon-sensitive time-stamping camera to perform QGI at ultra-low-light levels with rapid data acquisition and processing times, achieving high-resolution and high-contrast images in under 1 min. Our work addresses the trade-off between image quality, optical power, data acquisition time, and data processing time in QGI, paving the way for practical applications in biomedical and quantum-secured imaging.

Mavian, Alex (ORCID:0000000279448830)↗

Quantum Imaging with X-rays

Quantum imaging encompasses a broad range of methods that exploit the quantum properties of light to capture information about an object. One such approach involves using a two-photon quantum state, where only one photon interacts with the object being imaged while its entangled partner carries spatial or temporal information. To implement this technique, it is necessary to generate specific quantum states of light and detect photons at the single-photon level. While this method has been successfully demonstrated in the visible electromagnetic spectrum, extending it to X-rays has faced significant challenges due to the difficulties in producing a sufficient rate of X-ray photon pairs and detecting them with adequate resolution. Here, we demonstrate record high rates of correlated X-ray photon pairs produced via a spontaneous parametric down-conversion process and we employ these photons to perform quantum correlation imaging of several objects, including a biological sample (E. cardamomum seedpod). Notably, we report an unprecedented detection rate of about 6,300 pairs per hour and the observation of energy anti-correlation for the X-ray photon pairs. We also present a detailed analysis of the properties of the down-converted X-ray photons, as well as a comprehensive study of the correlation imaging formation, including a study of distortions and corrections. These results mark a substantial advancement in X-ray quantum imaging, expanding the possibilities of X-ray quantum optical technologies, and illustrating the pathway towards enhancing biological imaging with reduced radiation doses.

Gofron, Kaz [ORNL] (ORCID:0000000314415736)↗

X-ray Parametric Down Conversion at an XFEL

Understanding and harnessing X-ray quantum effects could open new frontiers in imaging and quantum optics. In this study, we measured the process of X-ray Parametric Down Conversion, where a single high-energy X-ray photon splits into two lower-energy photons. Using the SACLA X-ray Free Electron Laser in Japan at 9.83 keV, we found clear evidence that pairs of photons were produced along the energy-angle relationship that conserved both energy and momentum, as predicted for down-conversion, and consistent with quantum entanglement of X-ray photons. By matching specific photon pairs for energy and momentum conservation, we observe a signal rate of 1,250 pairs per hour, confirming that correlated photon pairs can be generated and observed in the absence of explicit time correlations. Our results show that with further refinement, the number of entangled photons produced per laser pulse could increase by an order of magnitude. This paves the way for demonstrating quantum-enhanced X-ray imaging, and confirmation of X-ray photon entanglement.

47 OTHER INSTRUMENTATION↗

Enhanced quantum efficiency of high-purity silicon imaging detectors by ultralow temperature surface modification using Sb doping

A low temperature process for Sb doping of silicon has been developed as a backsurface treatment for high-purity n-type imaging detectors. Molecular beam epitaxy (MBE) is used to achieve very high dopant incorporation in a thin, surface-confined layer. The growth temperature is kept below 450 (deg)C for compatibility with Al-metallized devices. Imaging with MBE-modified 1kx1k charge coupled devices (CCDs) operated in full depletion has been demonstrated. Dark current is comparable to the state-of-the-art process, which requires a high temperature step. Quantum efficiency is improved, especially in the UV, for thin doped layers placed closer to the backsurface. Near 100% internal quantum efficiency has been demonstrated in the ultraviolet for a CCD with a 1.5 nm silicon cap layer.

charged coupled devices (CCDs)↗

Enhanced quantum efficiency of high-purity silicon imaging detectors by ultralow temperature surface modification using Sb doping

A low temperature process for Sb doping of silicon has been developed as a backsurface treatment for high-purity n-type imaging detectors. Molecular beam epitaxy (MBE) is used to achieve very high dopant incorporation in a thin, surface-confined layer. The growth temperature is kept below 450 °C for compatibility with Al-metallized devices. Imaging with MBE-modified 1kx1k charge coupled devices ((CCDs) operated in full depletion has been demonstrated. Dark current is comparable to the state-of-the-art process, which requires a high temperature step. Quantum efficiency is improved, especially in the UV, for thin doped layers placed closer to the backsurface. Near 100% internal quantum efficiency has been demonstrated in the ultraviolet for a CCD with a 1.5 nm silicon cap layer.

Nikzad, Shouleh↗

Quantum Image Denoising: A Framework via Boltzmann Machines, QUBO, and Quantum Annealing

We investigate a framework for binary image denoising via restricted Boltzmann machines (RBMs) that introduces a denoising objective in quadratic unconstrained binary optimization (QUBO) form and is well-suited for quantum annealing. The denoising objective is attained by balancing the distribution learned by a trained RBM with a penalty term for derivations from the noisy image. We derive the statistically optimal choice of the penalty parameter assuming the target distribution has been well-approximated, and further suggest an empirically supported modification to make the method robust to that idealistic assumption. We also show under additional assumptions that the denoised images attained by our method are, in expectation, strictly closer to the noise-free images than the noisy images are. While we frame the model as an image denoising model, it can be applied to any binary data. As the QUBO formulation is well-suited for implementation on quantum annealers, we test the model on a D-Wave Advantage machine, and also test on data too large for current quantum annealers by approximating QUBO solutions through classical heuristics.

restricted Boltzmann machine↗

Improved Starting Materials for Back-Illuminated Imagers

An improved type of starting materials for the fabrication of silicon-based imaging integrated circuits that include back-illuminated photodetectors has been conceived, and a process for making these starting materials is undergoing development. These materials are intended to enable reductions in dark currents and increases in quantum efficiencies, relative to those of comparable imagers made from prior silicon-on-insulator (SOI) starting materials. Some background information is prerequisite to a meaningful description of the improved starting materials and process. A prior SOI starting material, depicted in the upper part the figure, includes: a) A device layer on the front side, typically between 2 and 20 m thick, made of p-doped silicon (that is, silicon lightly doped with an electron acceptor, which is typically boron); b) A buried oxide (BOX) layer (that is, a buried layer of oxidized silicon) between 0.2 and 0.5 m thick; and c) A silicon handle layer (also known as a handle wafer) on the back side, between about 600 and 650 m thick. After fabrication of the imager circuitry in and on the device layer, the handle wafer is etched away, the BOX layer acting as an etch stop. In subsequent operation of the imager, light enters from the back, through the BOX layer. The advantages of back illumination over front illumination have been discussed in prior NASA Tech Briefs articles.

Pain, Bedabrata↗

A Comprehensive Analysis of the Physical Properties of Advanced GaAs/AlGaAs Junctions

Extensive studies have been performed on MQW junctions and structures because of their potential applications as avalanche photodetectors in optical communications and imaging systems. The role of the avalanche photodiode is to provide for the conversion of an optical signal into charge. Knowledge of junction physics, and the various carrier generation/recombination mechanisms, is crucial for effectively optimizing the conversion process and increasing the structure's quantum efficiency. In addition, the recent interest in the use of APDs in imaging systems has necessitated the development of semiconductor junctions with low dark currents and high gains for low light applications. Because of the high frame rate and high pixel density requirements in new imaging applications, it is necessary to provide some front-end gain in the imager to allow operation under reasonable light conditions. Understanding the electron/hole impact ionization process, as well as diffusion and surface leakage effects, is needed to help maintain low dark currents and high gains for such applications. In addition, the APD must be capable of operating with low power, and low noise. Knowledge of the effects of various doping configurations and electric field profiles, as well as the excess noise resulting from the avalanche process, are needed to help maintain low operating bias and minimize the noise output.

Menkara, Hicham M.↗

Random projection using random quantum circuits

The random sampling task performed by Google's Sycamore processor gave us a glimpse of the “quantum supremacy era.” This has definitely shed some light on the power of random quantum circuits in this abstract task of sampling outputs from the (pseudo)random circuits. In this paper, we explore a practical near-term use of local random quantum circuits in dimensional reduction of large low-rank data sets. We make use of the well-studied dimensionality reduction technique called the random projection method. This method has been extensively used in various applications such as image processing, logistic regression, entropy computation of low-rank matrices, etc. We prove that the matrix representations of local random quantum circuits with sufficiently shorter depths [ ∼ O ( n ) ] serve as good candidates for random projection. We demonstrate numerically that their projection abilities are not far off from the computationally expensive classical principal components analysis on MNIST and CIFAR-100 image datasets. We also benchmark the performance of quantum random projection against the commonly used classical random projection in the tasks of dimensionality reduction of image data sets and computing von Neumann entropies of large low-rank density matrices. And finally, using variational quantum singular value decomposition, we demonstrate a near-term implementation of extracting the singular vectors with dominant singular values after quantum random projecting a large low-rank matrix to lower dimensions. All such numerical experiments unequivocally demonstrate the ability of local random circuits to randomize a large Hilbert space at sufficiently shorter depths with robust retention of properties of large data sets in reduced dimensions. Published by the American Physical Society 2024

Kumaran, Keerthi (ORCID:0009000949125721)↗