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At least 127 records · Page 7

Exponentially-Biased Ground-State Sampling of Quantum Annealing Machines with Transverse-Field Driving Hamiltonians

We study the performance of the D-Wave 2X quantum annealing machine on systems with well-controlled ground-state degeneracy. While obtaining the ground state of a spin-glass benchmark instance represents a difficult task, the gold standard for any optimization algorithm or machine is to sample all solutions that minimize the Hamiltonian with more or less equal probability. Our results show that while naive transverse-field quantum annealing on the D-Wave 2X device can find the ground-state energy of the problems, it is not well suited in identifying all degenerate ground-state configurations associated to a particular instance. Even worse, some states are exponentially suppressed, in agreement with previous studies on toy model problems [New J. Phys. 11, 073021 (2009)]. These results suggest that more complex driving Hamiltonians are needed in future quantum annealing machines to ensure a fair sampling of the ground-state manifold.

Quantum Annealing

Quantum-Accelerated Distributed Algorithms for Approximate Steiner Trees and Directed Minimum Spanning Trees

We present two algorithms in the Quantum CONGEST-CLIQUE model of distributed computation that succeed with high probability; one for producing an approximately optimal Steiner Tree, and one for producing an exact spanning arborescence of minimum weight, the analog of a Minimum Spanning Tree in a directed graph, each of which uses O~(n^(1/4)) rounds of communication and O~(n^(9/4)) messages, achieving a lower round and message complexity than any known algorithms in the classical CONGEST-CLIQUE model. The CONGEST distributed computational model allows limited-sized messages to be transmitted within a network described by a communication graph of size n in a series of rounds to address a computational problem. The size limitation for such messages isO(log(n)) bits at each edge of the communication graph per round. The communication graph in the CONGEST-CLIQUE model is fully connected. In the Quantum CONGEST-CLIQUE model, at most O(log(n)) classical and quantum bits (qubits) can be communicated across each edge of the communication graph per round. At a high level, we achieve these results by combining classical algorithms with fast quantum subroutines. These speedups further contribute to understanding what problems can be solved more efficiently when we allow quantum communication in this CONGEST-CLIQUE model of distributed computation.

quantum distributed algorithms

Optimized Geometry for Superconducting Sensing Coils

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.

Eom, Byeong Ho

Performance and Radiation Tolerance of InAs/GaSb LWIR Detectors Based on CBIRD Design

We report our recent developments of antimonide based infrared photodetectors utilizing a complementary barrier infrared detector (CBIRD) design. The new generation of devices can operate close to zero bias with the same quantum efficiency as the initial design. 320x256 pixel long-wavelength infrared focal plane arrays utilizing optimized design have been demonstrated with 8.8 µm cutoff wavelength and noise equivalent differential temperature of 26 mK at operating temperature of 80 K for 300 K background and f/2 optics. As CBIRD detectors became valuable candidates for space-based instruments, question of their radiation tolerance became important. Here, we report our investigations of the proton irradiation effects on the photodetector performance.

heterostructure

Quantum Adiabatic Algorithms and Large Spin Tunnelling

We provide a theoretical study of the quantum adiabatic evolution algorithm with different evolution paths proposed in this paper. The algorithm is applied to a random binary optimization problem (a version of the 3-Satisfiability problem) where the n-bit cost function is symmetric with respect to the permutation of individual bits. The evolution paths are produced, using the generic control Hamiltonians H (r) that preserve the bit symmetry of the underlying optimization problem. In the case where the ground state of H(0) coincides with the totally-symmetric state of an n-qubit system the algorithm dynamics is completely described in terms of the motion of a spin-n/2. We show that different control Hamiltonians can be parameterized by a set of independent parameters that are expansion coefficients of H (r) in a certain universal set of operators. Only one of these operators can be responsible for avoiding the tunnelling in the spin-n/2 system during the quantum adiabatic algorithm. We show that it is possible to select a coefficient for this operator that guarantees a polynomial complexity of the algorithm for all problem instances. We show that a successful evolution path of the algorithm always corresponds to the trajectory of a classical spin-n/2 and provide a complete characterization of such paths.

Boulatov, A.

X-ray Polarimetry with a Micro-Pattern Gas Detector

Topics covered include: Science drivers for X-ray polarimetry; Previous X-ray polarimetry designs; The photoelectric effect and imaging tracks; Micro-pattern gas polarimeter design concept. Further work includes: Verify results against simulator; Optimize pressure and characterize different gases for a given energy band; Optimize voltages for resolution and sensitivity; Test meshes with 80 micron pitch; Characterize ASIC operation; and Quantify quantum efficiency for optimum polarization sensitivity.

Hill, Joe

Quantum-Compatible Variational Segmentation for Image-to-Image Wildfire Detection Using Satellite Data

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.

quantum

Low-background InSb array development

Photovoltaic indium antimonide (PV InSb) detector technology has matured over the past several years to enable a wide variety of applications to use this high-performance detector material to advantage. The operating conditions for most of the applications to date for back-side illuminated PV InSb arrays have encompassed focal plane temperatures ranging from 40 to approximately 95 K, with the majority in the narrower range between 60 and 80 K. Background flux conditions have ranged from 10 to the 10th power ph/sq cm/sec to 10 to the 16th power ph/sq cm/sec, most typically between 10 to the 12th power and 10 to the 14th power ph/sq cm/sec. Appropriately, the array parameters were optimized for maximum performance over these temperature and background ranges. The key parameters which were peaked in this process were the resistance-area product of the detectors and their quantum efficiency. The Space Infrared Telescope Facility (SIRTF) Infrared Array Camera requirements, however, present very low temperature and background operating conditions, plus the need for very high signal to noise ratios. Preliminary analysis indicates that back-side illuminated PV InSb arrays can be optimized for operation under these conditions, and some performance projections will be presented.

Thom, R. D.

MDO can help resolve the designer's dilemma

Multidisciplinary design optimization (MDO) is presented as a rapidly growing body of methods, algorithms, and techniques that will provide a quantum jump in the effectiveness and efficiency of the quantitative side of design, and will turn that side into an environment in which the qualitative side can thrive. MDO borrows from CAD/CAM for graphic visualization of geometrical and numerical data, data base technology, and in computer software and hardware. Expected benefits from this methodology are a rational, mathematically consistent approach to hypersonic aircraft designs, designs pushed closer to the optimum, and a design process either shortened or leaving time available for different concepts to be explored.

Sobieszczanski-Sobieski, Jaroslaw

The Extreme Ultraviolet Explorer and the local interstellar medium

The EUV Explorer (EUVE) mission is described, with emphasis on the overall capabilities of the instrumentation and the relevance of the mission to determining parameters of the local interstellar medium. The primary purpose of the mission is to search the celestial sphere for astronomical sources of EUV radiation (100-1000 A). The search will be accomplished with the use of three EUV telescopes, sensitive to different segments of the EUV band. A fourth telescope will perform a high-sensitivity search of a limited sample of the sky in the shortest-wavelength bands. The all-sky survey will be carried out in the first six months of the mission. The second six months of the mission, conducted entirely by Guest Investigators selected by NASA, will be devoted to spectroscopic observations of selected EUV sources. The instrumentation is now well developed. The best mirror has full-width/half-energy spread of 8 arcsec and a surface finish of 20 A. Prototype thin-film bandpass filters have been flown on the Space Shuttle and their performance optimized. Prototype detectors have been developed which have 600 by 600-pixel imaging capability and up to 80-percent quantum efficiency in parts of the EUV band.

Bowyer, Stuart

Recent Developments and Applications of Quantum Well Infrared Photodetector Focal Plane Arrays

There are many applications that require long wavelength, large, uniform, reproducible, low cost, stable, and radiation-hard infrared (IR) focal plane arrays (FPAs). For example, the absorption lines of many gas molecules, such as ozone, water, carbon monoxide, carbon dioxide, and nitrous oxide occur in the wavelength region from 3 to 18 micron. Thus, IR imaging systems that operate in the long wavelength IR (LWIR) region (6 - 18 micron) are required in many space borne applications such as monitoring the global atmospheric temperature profiles, relative humidity profiles, cloud characteristics, and the distribution of minor constituents in the atmosphere which are being planned for future NASA Earth and planetary remote sensing systems. Due to higher radiation hardness, lower 1/f noise, and larger array size the GaAs based Quantum Well Infrared Photodetector (QWIP) FPAs are very attractive for such space borne applications compared to intrinsic narrow band gap detector arrays. In this presentation we will discuss the optimization of the detector design, material growth and processing that has culminated in realization of large format long-wavelength QWIP FPAs, portable and miniature LWIR cameras, holding forth great promise for myriad applications in 6-18 micron wavelength range in science, medicine, defense and industry. In addition, we will present some system demonstrations using broadband, two-color, and high quantum efficiency long-wavelength QWIP FPAs.

Gunapala, S. D.

Theoretical study of the nitrogen atom hyperfine coupling constant

The nitrogen-atom isotropic hyperfine coupling constant A(iso) is studied as a function of improvements in both the one-particle and n-particle basis sets. The study underscores the importance of diffuse basis functions. For example, the (9s 5p) primitive set of Huzinaga (1965) augmented with an even-tempered diffuse s function yields values for A(iso) that are virtually identical to an energy-optimized (23s 12p) even-tempered set. The A(iso) constant is found to converge relatively quickly with increasing l quantum numbers: d, f, and g functions are estimated to contribute 2.5 + or - 0.2, 0.4 + or - 0.1, and 0.05 + or - 0.05 MHz, respectively. Full CI calibration calculations indicate that very high levels of correlation treatment are required for quantitative results. In addition, a strong coupling is observed between the one-particle and n-particle requirements. The best result, 10.4 MHz, is in excellent agreement with the accurate experimental value of 10.4509 MHz.

Bauschlicher, Charles W., Jr.

Quantum state transfer in double-quantum-well devices

A Monte Carlo simulation of double-quantum-well (DQW) devices is presented in view of analyzing the quantum state transfer (QST) effect. Different structures, based on the AlGaAs/GaAs system, were simulated at 77 and 300 K and optimized in terms of electron transfer and device speed. The analysis revealed the dominant role of the impurity scattering for the QST. Different approaches were used for the optimization of QST devices and basic physical limitations were found in the electron transfer between the QWs. The maximum transfer of electrons from a high to a low mobility well was at best 20%. Negative differential resistance is hampered by the almost linear rather than threshold dependent relation of electron transfer on electric field. By optimizing the doping profile the operation frequency limit could be extended to 260 GHz.

Jakumeit, Jurgen

A Holistic DSMC Transport Database for Re-Entry and Ablation Modeling

Hybrid simulation frameworks combining Computational Fluid Dynamics (CFD) and Direct Simulation Monte Carlo (DSMC) are frequently employed to efficiently perform high-fidelity solutions of environments containing combined continuum/rarified flow. The use of DSMC, a stochastic, particle-based method, is necessary for high-Knudsen flow where continuum-based assumptions governing CFD break down. However, the DSMC methodology is generally very computationally inefficient to model the continuum regime. In a CFD/DSMC hybrid approach, obtaining an accurate, high-fidelity solution hinges on the consistent treatment of transport properties and the used thermo-chemical models employed within the two solvers. In principle, in regions where CFD and DSMC are both employed, the same gas mixture under the same conditions should have the same properties, regardless of simulation type. Observed differences should be due to non-equilibrium processes, rather than differences in physical models. While the transport models governing CFD and DSMC simulations are starkly different, they can effectively be linked via their use of reduced Chapman-Enskog collision integrals. In CFD, these integrals are typically stored as fitted polynomial expressions and used to directly compute gas transport properties via mixing rules or the full Chapman-Enskog formulation. In DSMC, they can be used to derive the collision parameters needed for the phenomenological collision cross-section models that govern particle interactions, via a Nelder-Mead optimization scheme. The goal of this work is to provide a unified DSMC transport database encompassing the vast majority of known gas species encountered during atmospheric entry, on Earth or any other Solar body. This goal is largely possible due to recently performed ab-initio quantum chemistry calculations. Combined with other high-fidelity literature sources, the planned database will consist of collision integral data for over 200 neutral and ionized species and over 17000 binary collisions. From these collision integrals, Nelder-Mead optimization is used to compute Variable Soft Sphere (VSS) collision model parameters for DSMC, fitted from 300 K to 20000 K. Initial comparisons of transport properties of relevant equilibrium gas mixtures show great agreement between CFD and DSMC-derived results. The completed database will be able to be readily applied to model binary collisions of any gas mixture containing the included species over the specified temperature range, making it a valuable tool for future planetary probe modeling efforts. An example is shown below. Equilibrium mixture transport properties for a 19-species Titan atmospheric model [4] are computed using both fitted VSS parameters and the original CFD collision integral values. Deviations in computed properties between the two approaches is less than 5% for the entire temperature range.

M R Gosma

Development of FIR arrays with integrating amplifiers

The development of optimized photoconductor arrays suitable for far infrared space astronomical applications are described. Although the primary impetus is the production of a 16 by 16 element Ge:Ga demonstration array for SIRTF, the extension of this technology to Large Deployable Reflector (LDR) is considered. The optimization of Ge:Ga and Ge:Be photoconductor materials is discussed. In collaboration with Lawrence Berkeley Laboratory, measurements of FIR photoconductors with quantum efficiencies greater than 20 percent at 100 micrometers, and dark currents below 300 electrons/s are presented. Integrating J-FET amplifier technology is discussed. The current generation of integrating amplifiers has a demonstrated read noise of less than 20 electrons for an integration time of 100 s. The design is shown for a stackable 16 x n Ge:Ga array that utilizes a 16-channel monolithic version of the J-FET integrator. A part of the design is the use of a thin, thermally insulating substrate that allows the electronics to operate at the optimum temperature of 50 K while maintaining thermal and optical isolation from the detectors at 2 K. The power dissipation for the array is less than 16 mW. The array design may particularly be applicable to high resolution imaging spectrometers for LDR.

Young, Erick T.

NASA Tech Briefs, April 2009

Topics covered include: Direct-Solve Image-Based Wavefront Sensing; Use of UV Sources for Detection and Identification of Explosives; Using Fluorescent Viruses for Detecting Bacteria in Water; Gradiometer Using Middle Loops as Sensing Elements in a Low-Field SQUID MRI System; Volcano Monitor: Autonomous Triggering of In-Situ Sensors; Wireless Fluid-Level Sensors for Harsh Environments; Interference-Detection Module in a Digital Radar Receiver; Modal Vibration Analysis of Large Castings; Structural/Radiation-Shielding Epoxies; Integrated Multilayer Insulation; Apparatus for Screening Multiple Oxygen-Reduction Catalysts; Determining Aliasing in Isolated Signal Conditioning Modules; Composite Bipolar Plate for Unitized Fuel Cell/Electrolyzer Systems; Spectrum Analyzers Incorporating Tunable WGM Resonators; Quantum-Well Thermophotovoltaic Cells; Bounded-Angle Iterative Decoding of LDPC Codes; Conversion from Tree to Graph Representation of Requirements; Parallel Hybrid Vehicle Optimal Storage System; and Anaerobic Digestion in a Flooded Densified Leachbed.

Source record

Advances in Detector-Integrated Filter Coatings for the Far Ultraviolet

We report on the continued development of multilayer optical coatings on back-illuminated silicon imaging sensors in order to enhance the functionality of such systems at ultraviolet wavelengths. This includes the development metal-dielectric filter structures to enable solar-blind operation, and graded thickness coatings to tune the spatial response of a detector system to the dispersion of a spectrometer. Such systems can maintain the high internal quantum efficiency afforded by the delta-doping process utilized at NASA JPL, while also providing long-wavelength rejection or a spatially optimized efficiency (or both). We present the characterization of CCD and CMOS image sensors incorporating these processes, and describe the atomic layer deposition coating processes. Such detectors are currently being developed for ground-based high energy physics applications as well as NASA orbital astrophysics instruments operating at wavelengths shorter than 200 nm.

Nikzad, Shouleh

Optimization of Noise Performance of Low-Back Ground Detector Arrays

The performance of the 2k x 2k Teledyne H2RG detectors is key to the success of the JWST mission. For broadband imaging, where background limited sensitivity is quickly reached, the key parameter is the quantum efficiency of the detectors, which is, in general, very good. For near infrared spectroscopy and narrow band imaging, we cannot generally reach the back-round limit, so instrument sensitivity is directly dependent on the read noise of the detector. We have initiated a program to analyze the noise characteristics of the H2RG detectors, studying the correlations among the detector outputs and with the reference output, as well as the temporal correlations in a given detector section. Lasing the measured characteristics of the noise correlations, we can determine the optimal coefficients for the removal of correlated noise as a function of frequency. By using available reference sources and adding more frequent references, we have been able to reduce the noise by a factor of two. We find that the detectors have significantly lower noise that observed in prior tests, and can offer significant improvements in the performance of the JWST instruments. We will present the analysis and mitigation techniques, discuss prospects for further improvements with existing detectors, and describe considerations for improvements in next-generation detectors.

Rauscher, Bernard J.