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Superconductor-Insulator-Superconductor (SIS) quantum mixers provide an approach to millimeter wave mixing - potentially offering conversion gain, a low local oscillator power demand, and potential mixer noise temperatures near the quantum limit. The development of a reliable fabrication technology for producing such high quality SIS devices for mixer applications in radio astronomy is the focus of the work.
A report discusses an algorithm for a new kind of dynamics based on a quantum- classical hybrid-quantum-inspired maximizer. The model is represented by a modified Madelung equation in which the quantum potential is replaced by different, specially chosen 'computational' potential. As a result, the dynamics attains both quantum and classical properties: it preserves superposition and entanglement of random solutions, while allowing one to measure its state variables, using classical methods. Such optimal combination of characteristics is a perfect match for quantum-inspired computing. As an application, an algorithm for global maximum of an arbitrary integrable function is proposed. The idea of the proposed algorithm is very simple: based upon the Quantum-inspired Maximizer (QIM), introduce a positive function to be maximized as the probability density to which the solution is attracted. Then the larger value of this function will have the higher probability to appear. Special attention is paid to simulation of integer programming and NP-complete problems. It is demonstrated that the problem of global maximum of an integrable function can be found in polynomial time by using the proposed quantum- classical hybrid. The result is extended to a constrained maximum with applications to integer programming and TSP (Traveling Salesman Problem).
We are developing software to explore the fault tolerance of quantum dot cellular automata gate architectures in the presence of manufacturing variations and device defects. The Topology Optimization Methodology using Applied Statistics (TOMAS) framework extends the capabilities of the A Quantum Interconnected Network Array Simulator (AQUINAS) by adding front-end and back-end software and creating an environment that integrates all of these components. The front-end tools establish all simulation parameters, configure the simulation system, automate the Monte Carlo generation of simulation files, and execute the simulation of these files. The back-end tools perform automated data parsing, statistical analysis and report generation.
In this tutorial we discuss the quantum alternating operator ansatz (QAOA), which is a variational algorithm that can be used for approximate optimization of combinatorial problems with soft and hard constraints.We go through the design of the quantum circuit and its actual implementation in real hardware, discussing compilation issues such as gate synthesis and scheduling of all the required gates and qubit-swapping overhead.
AlGaAsSb/InGaAsSb heterojunction phototransistors were developed at Astropower, Inc under Laser Risk Reduction Program (LRRP) for operation in the 2-micron region. These phototransistors were optimized for 2-micron detection and have high quantum efficiency (>60%), high gain (>10(exp 3)) and low noise-equivalent- power (<5x10(exp -14) W/Hz), while operating at low bias voltage. One of these phototransistors was tested in lidar mode using the 2-micron CO2 Differential Absorption Lidar (DIAL) system currently under development under the Instrument Incubator Program (IIP) at NASA Langley. Lidar measurements included detecting atmospheric structures consisting of thin clouds in the mid-altitude and near-field boundary layer. These test results are very promising for the application of phototransistors for the two-micron lidar remote sensing. In addition, HgCdTe avalanche photodiodes (APD) acquired from Raytheon were used in atmospheric testing at 2-microns. A discussion of these measurements is also presented in this paper.
Knowledge of the spatial and temporal distribution of atmospheric species such as CO2, O3, H2O, and CH4 is important for understanding the chemistry and physical cycles involving Earth s atmosphere. Although several remote sensing techniques are suitable for such measurements they are considered high cost techniques involving complicated instrumentation. Therefore, simultaneous measurement of atmospheric species using a single remote sensing instrument is significant for minimizing cost, size and complexity. While maintaining the instrument sensitivity and range, quality of multicolor detector, in terms of high quantum efficiency and low noise are vital for these missions. As the first step for developing multicolor focal plan array, the structure of a single element multicolor detector is presented in this paper. The detector consists of three p-n junction layers of Si, GaSb and InAs wafer bonded to cover the spectral range UV to 900 nm, 800 nm to 1.7 m, and 1.5 m to 3.4 m, respectively. Modeling of the absorption coefficient for each material was carried out for optimizing the layers thicknesses for maximum absorption. The resulted quantum efficiency of each layer has been determined except InAs layer. The optical and electrical characterization of each layer structure is reported including dark current and spectral response measurements of Si pin structure and of GaSb and InAs p-n junctions. The effect of the material processing is discussed.
In this paper we discuss the optimization of the detector design, material growth and processing that has culminated in realization of 15 micron cutoff 128x128 QWIP focal plane array camera, hand-held and palmsize 256x256 long wavelength QWIP cameras and 648x480 long-wavelength camera, holding forth great promise for myriad applications in 6-25 micron wavelength range in science, medicine, defense and industry.
There is a major need for long-wavelength-infrared (LWIR) detector arrays in the range of 8 to 16 microns which operate with close-cycle cryocoolers above 65 K. In addition, it would be very attractive to have Si-based infrared (IR) detectors that can be easily integrated with Si readout circuitry and have good pixel-to-pixel uniformity, which is critical for focal plane array (FPA) applications. Here, researchers report a novel Si(1-x)Ge(x)/Si heterojunction internal photoemission (HIP) detector approach with a tailorable long wavelength infrared cutoff wavelength, based on internal photoemission over the Si(1-x)Ge(x)/Si heterojunction. The HIP detectors were grown by molecular beam epitaxy (MBE), which allows one to optimize the device structure with precise control of doping profiles, layer thickness and composition. The feasibility of a novel Si(1-x)Ge(x)/Si HIP detector has been demonstrated with tailorable cutoff wavelength in the LWIR region. Photoresponse at wavelengths 2 to 10 microns are obtained with quantum efficiency (QE) above approx. 1 percent in these non-optimized device structures. It should be possible to significantly improve the QE of the HIP detectors by optimizing the thickness, composition, and doping concentration of the Si(1-x)Ge(x) layers and by configuring the detector for maximum absorption such as the use of a cavity structure. With optimization of the QE and by matching the barrier energy to the desired wavelength cutoff to minimize the thermionic current, researchers predict near background limited performance in the LWIR region with operating temperatures above 65K. Finally, with mature Si processing, the relatively simple device structure offers potential for low-cost producible arrays with excellent uniformity.
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.
We study both analytically and numerically the complexity of the adiabatic quantum evolution algorithm applied to random instances of combinatorial optimization problems. We use as an example the NP-complete set partition problem and obtain an asymptotic expression for the minimal gap separating the ground and exited states of a system during the execution of the algorithm. We show that for computationally hard problem instances the size of the minimal gap scales exponentially with the problem size. This result is in qualitative agreement with the direct numerical simulation of the algorithm for small instances of the set partition problem. We describe the statistical properties of the optimization problem that are responsible for the exponential behavior of the algorithm.
Superconductor-Insulator-Superconductor (SIS) quantum mixers provide a relatively new approach to millimeter wave mixing potentially offering conversion gain, a low local oscillator power demand and potential mixer temperatures near the quantum limit. This paper presents device modeling and fabrication development for NbCN lead-alloy submicron edge-contact SIS mixers for use at 115 GHz.
A family of polymer/carbon films has been developed for use as sensory films in electronic noses for detecting SO2 gas at concentrations as low as 1 part per million (ppm). Most previously reported SO2 sensors cannot detect SO2 at concentrations below tens of ppm; only a few can detect SO2 at 1 ppm. Most of the sensory materials used in those sensors (especially inorganic ones that include solid oxide electrolytes, metal oxides, and cadmium sulfide) must be used under relatively harsh conditions that include operation and regeneration at temperatures greater than 100 C. In contrast, the present films can be used to detect 1 ppm of SO2 at typical opening temperatures between 28 and 32 C and can be regenerated at temperatures between 36 and 40 C. The basic concept of making sensing films from polymer/carbon composites is not new. The novelty of the present family of polymer/carbon composites lies in formulating the polymer components of these composites specifically to optimize their properties for detecting SO2. First-principles quantum-mechanical calculations of the energies of binding of SO2 molecules to various polymer functionalities are used as a guide for selecting polymers and understanding the role of polymer functionalities in sensing. The polymer used in the polymer-carbon composite is a copolymer of styrene derivative units with vinyl pyridine or substituted vinyl pyridine derivative units. To make a substituted vinyl pyridine for use in synthesizing such a polymer, poly(2-vinyl pyridine) that has been dissolved in methanol is reacted with 3-chloropropylamine that has been dissolved in a solution of methanol. The methanol is then removed to obtain the copolymer. Later, the copolymer can be dissolved in an appropriate solvent with a suspension of carbon black to obtain a mixture that can be cast and then dried to obtain a sensory film.
One of the simplest device realizations of the classic particle-in-the-box problem of basic quantum mechanics is the Quantum Well Infrared Photodetector (QWIP). In this paper we discuss the optimization of the detector design, material growth and processing that has culminated in realization of 15 micron cutoff 128x128 QWIP focal plane array camera, hand-held and palmsize 256x256 long-wavelength QWIP cameras and 648x480 long-wavelength cameras, holding forth great promise for myriad applications in 6-25 micron wavelength range in science, medicine, defense and industry.
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 Minimum Directed Spanning tree. These use O(n1/4) rounds of communication and O(n9/4) messages, leading to a quantum speedup in round and message complexity compared to any known algorithms in the classical CONGEST-CLIQUE model (vs O(n1/3) and O(n7/3)). At a high level, we achieve these results by combining classical algorithms with fast quantum subroutines. Further, these problems can not be sped up in the CONGEST (non-clique) setting, and we characterize the constants involved.
Improved techniques and well-optimized basis sets are presented for application of the outgoing wave variational principle to calculate converged quantum mechanical reaction probabilities. They are illustrated with calculations for the reactions D + H2 yields HD + H with total angular momentum J = 3 and F + H2 yields HF + H with J = 0 and 3. The optimization involves the choice of distortion potential, the grid for calculating half-integrated Green's functions, the placement, width, and number of primitive distributed Gaussians, and the computationally most efficient partition between dynamically adapted and primitive basis functions. Benchmark calculations with 224-1064 channels are presented.
Topics covered include: Hybrid Architecture Active Wavefront Sensing and Control; Carbon-Nanotube-Based Chemical Gas Sensor; Aerogel-Positronium Technology for the Detection of Small Quantities of Organic and/or Toxic Materials; Graphene-Based Reversible Nano-Switch/Sensor Schottky Diode; Inductive Non-Contact Position Sensor; High-Temperature Surface-Acoustic-Wave Transducer; Grid-Sphere Electrodes for Contact with Ionospheric Plasma; Enabling IP Header Compression in COTS Routers via Frame Relay on a Simplex Link; Ka-Band SiGe Receiver Front-End MMIC for Transponder Applications; Robust Optimization Design Algorithm for High-Frequency TWTs; Optimal and Local Connectivity Between Neuron and Synapse Array in the Quantum Dot/Silicon Brain; Method and Circuit for In-Situ Health Monitoring of Solar Cells in Space; BGen: A UML Behavior Network Generator Tool; Platform for Post-Processing Waveform-Based NDE; Electrochemical Hydrogen Peroxide Generator; Fabrication of Single, Vertically Aligned Carbon Nanotubes in 3D Nanoscale Architectures; Process to Create High-Fidelity Lunar Dust Simulants; Lithium-Ion Electrolytes Containing Phosphorous-Based, Flame-Retardant Additives; InGaP Heterojunction Barrier Solar Cells; Straight-Pore Microfilter with Efficient Regeneration; Determining Shear Stress Distribution in a Laminate; Self-Adjusting Liquid Injectors for Combustors; Handling Qualities Prediction of an F-16XL-Based Reduced Sonic Boom Aircraft; Tele-Robotic ATHLETE Controller for Kinematics - TRACK; Three-Wheel Brush-Wheel Sampler; Heterodyne Interferometer Angle Metrology; Aligning Astronomical Telescopes via Identification of Stars; Generation of Optical Combs in a WGM Resonator from a Bichromatic Pump; Large-Format AlGaN PIN Photodiode Arrays for UV Images; Fiber-Coupled Planar Light-Wave Circuit for Seed Laser Control in High Spectral Resolution Lidar Systems; On Calculating the Zero-Gravity Surface Figure of a Mirror; Optical Modification of Casimir Forces for Improved Function of Micro- and Nano-Scale Devices; Analysis, Simulation, and Verification of Knowledge-Based, Rule-Based, and Expert Systems; Core and Off-Core Processes in Systems Engineering; Digital Reconstruction Supporting Investigation of Mishaps; and Template Matching Approach to Signal Prediction.
Compact, highly efficient, 3.0 to 3.4 m light emitters are in demand for spectroscopic analysis and identification of chemical substances (including methane and formaldehyde), infrared countermeasures technologies, and development of advanced infrared scene projectors. The need for these light emitters can be currently addressed either by bulky solid-state light emitters with limited power conversion efficiency, or cooled Interband Cascade (IC) semiconductor lasers. Researchers here have developed a breakthrough approach to fabrication of diode mid-IR lasers that have several advantages over IC lasers used for the Mars 2009 mission. This breakthrough is due to a novel design utilizing the strain-engineered quantum-well (QW) active region and quinternary barriers, and due to optimization of device material composition and growth conditions (growth temperatures and rates). However, in their present form, these GaSb-based laser diodes cannot be directly used as a part of sensor systems. The device spectrum is too broad to perform spectroscopic analysis of gas species, and operating currents and voltages are too high. In the current work, the emitters were fabricated as narrow-ridge waveguide index-guided lasers rather than broad stripe-gain guided multimode Fabry-Perot (FP) lasers as was done previously. These narrow-ridge waveguide mid-IR lasers exhibit much lower power consumptions, and can operate in a single spatial mode that is necessary for demonstration of single-mode distributed feedback (DBF) devices for spectroscopic applications. These lasers will enable a new generation of compact, tunable diode laser spectrometers with lower power consumption, reduced complexity, and significantly reduced development costs. These lasers can be used for the detection of HCN, C2H2, methane, and ethane.
The accurate first-principles description of strongly-correlated materials is an important and challenging problem in condensed matter physics. Ab initio downfolding has emerged as a way of deriving accurate many-body Hamiltonians including strong correlations, representing a subspace of interest of a material, using density functional theory calculations as a starting point. However, the solution of these material-specific models can scale exponentially on classical computers, constituting a challenge. Here we propose that utilizing quantum computers for obtaining the properties of downfolded Hamiltonians yields an accurate description of the ground state properties of strongly-correlated systems, while circumventing the exponential scaling problem. We benchmark the solution of Hubbard-like models obtained through downfolding by utilizing a classical tensor network implementation of variational quantum eigensolvers (VQE), and we reveal a strategy for driving the optimization through a hybrid minimization of the energy and maximization of the overlap with an approximate solution obtained through low-cost computational methods. This results in a reduction of the energy error by orders of magnitude compared to conventional VQE approaches, and allows us to reproduce long-range correlations for the first time. We demonstrate our first-principles approach for diverse strongly-correlated materials, correctly predicting the antiferromagnetic state of one-dimensional cuprate Ca 2 CuO 3 , the excitonic ground state of monolayer WTe2, and the charge-ordered state of correlated metal SrVO 3 . Our efficient computational implementation allows us to simulate large systems with up to 54 qubits and encompassing up to four correlated bands, which is indicative of the complexity that our framework can address.