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At least 703 records · Page 39

Sixteen multiple-amplifier sensing charge-coupled devices and characterization techniques targeting the next generation of astronomical instruments

We present a candidate sensor for future spectroscopic applications, such as a Stage-5 Spectroscopic Survey Experiment or the Habitable Worlds Observatory. This type of charge-coupled device (CCD) sensor features multiple in-line amplifiers at its output stage allowing multiple measurements of the same charge packet, either in each amplifier or in the different amplifiers. Recently, the operation of an eight-amplifier sensor has been experimentally demonstrated, and we present the operation of a 16-amplifier sensor. This new sensor enables a noise level of ∼1 erms− with a single sample per amplifier. In addition, it is shown that sub-electron noise can be achieved using multiple samples per amplifier. In addition to demonstrating the performance of the 16-amplifier sensor, we aim to create a framework for future analysis and performance optimization of this type of detectors. New models and techniques are presented to characterize specific parameters, which are absent in conventional CCDs and Skipper CCDs: charge transfer between amplifiers and independent and common noise in the amplifiers and their processing.

16 multiple-amplifer sensing CCD (MAS-CCD)↗

Avco Lycoming quiet clean general aviation turbofan engine

A fan module was developed using an existing turboshaft engine. The fan was designed using the latest in large engine noise control technology. A mixer was added to reduce the already low exhaust gas velocity. A nacelle incorporating sound treatment was provided for the test engine. A noise prediction model was used through the design process to evaluate the various design alternatives. Acoustic tests were then made to verify the prediction and identify the noise characteristics of the fan, core, jet, and sound treatment. Analysis of the recorded data yielded close agreement with the expected results. Core noise, as was expected, was the predominant source of noise for the quiet clean general aviation turbofan (QCGAT) engine. Flyover noise predictions were made which indicated that the Avco Lycoming QCGAT engine would meet the goals set for the QCGAT program.

Wilson, C. A.↗

On-board radiometric preprocessing for multispectral linear arrays /MLA/

A program that was undertaken to design, fabricate, and test a real-time hardwired data preprocessor is described, which applies a calibration normalization to each detector in a 576-element linear photodiode array. Various calibration problems were uncovered, such as those (1) due to system noise in recording the calibration tables, or (2) due to thermal drift and (3) due to the original quantization process. It was determined that in this experiment, noise and thermal drift led to fixed errors in the normalization of responses on the order of + or - 10 counts, out of 255 counts for many of the detectors.

Thompson, L. L.↗

SIS Mixer Design for a Broadband Millimeter Spectrometer Suitable for Rapid Line Surveys and Redshift Determinations

We present some detail of the waveguide probe and SIS mixer chip designs for a low-noise 180-300 GHz double- sideband receiver with an instantaneous RF bandwidth of 24 GHz. The receiver's single SIS junction is excited by a broadband, fixed-tuned waveguide probe on a silicon substrate. The IF output is coupled to a 6-18 GHz MMIC low- noise preamplifier. Following further amplification, the output is processed by an array of 4 GHz, 128-channel analog autocorrelation spectrometers (WASP 11). The single-sideband receiver noise temperature goal of 70 Kelvin will provide a prototype instrument capable of rapid line surveys and of relatively efficient carbon monoxide (CO) emission line searches of distant, dusty galaxies. The latter application's goal is to determine redshifts by measuring the frequencies of CO line emissions from the star-forming regions dominating the submillimeter brightness of these galaxies. Construction of the receiver has begun; lab testing should begin in the fall. Demonstration of the receiver on the Caltech Submillimeter Observatory (CSO) telescope should begin in spring 2003.

Rice, F.↗

Prediction-Based Auralization of a Multirotor Urban Air Mobility Vehicle

Recent advances in auralization methods applicable to rotary wing vehicles have made it possible to undertake a prediction-based auralization of a representative multirotor urban air mobility vehicle. These advances include a new capability for synthesizing loading and thickness noise directly from the prediction method and a new capability for predicting and synthesizing modulating broadband self noise within a unified system noise prediction-auralization framework. These capabilities are demonstrated for a six passenger quadrotor reference vehicle design using collective-pitch control. Propagation of the source noise to a ground observer completes the auralization process. The demonstrated capability serves as the basis for future work directed at perception-influenced design of low noise urban air mobility vehicles.

Auralization↗

Sonic environment of aircraft structure immersed in a supersonic jet flow stream

Test methods for determining the sonic environment of aircraft structure that is immersed in the flow stream of a high velocity jet or that is subjected to the noise field surrounding the jet, were investigated. Sonic environment test data measured on a SCAT 15-F model in the flow field of Mach 1.5 and 2.5 jets were processed. Narrow band, lateral cross correlation and noise contour plots are presented. Data acquisition and reduction methods are depicted. A computer program for scaling the model data is given that accounts for model size, jet velocity, transducer size, and jet density. Comparisons of scaled model data and full size aircraft data are made for the L-1011, S-3A, and a V/STOL lower surface blowing concept. Sonic environment predictions are made for an engine-over-the-wing SST configuration.

Guinn, W. A.↗

A Multilevel Approach For SolvingLarge-Scale QUBO Problems With Noisy Hybrid Quantum Approximate Optimization

Quantum approximate optimization is one ofthe promising candidates for useful quantum computation,particularly in the context of finding approximate solutionsto Quadratic Unconstrained Binary Optimization (QUBO)problems. However, the existing quantum processing units(QPUs) are of relatively small size, and canonical mappingsof QUBO via the Ising model require one qubit per vari-able, rendering direct large-scale optimization infeasible.In classical optimization, a general strategy for addressingmany large-scale problems is via multilevel/multigrid meth-ods, where the large target problem is iteratively coarsenedand the global solution is constructed from multiple small-scale optimization runs. In this work, we experimentallytest how existing QPUs perform when used as a sub-solverwithin such a multilevel strategy. To this aim, we com-bine and extend (via additional classical processing steps)the recently proposed Noise-Directed Adaptive Remapping(NDAR) and Quantum Relax&Round (QRR) algorithms.We first demonstrate the effectiveness of our heuristicextensions on Rigetti’s superconducting transmon deviceAnkaa-2. We find approximate solutions to10instances offully connected82-qubit Sherrington-Kirkpatrick graphswith random integer-valued coefficients obtaining normal-ized approximation ratios (ARs) in the range∼0.98−1.0,and the same class with real-valued coefficients (ARs∼0.94−1.0). Then, we implement the extended NDAR andQRR algorithms as subsolvers in the multilevel algorithmfor6large-scale graphs with at most∼27,000variables.In practice, the QPU (with classical post-processing steps)is used to find approximate solutions to dozens of at most82-qubit problems, which are iteratively used to constructthe global solution. We observe that quantum optimizationresults are competitive in terms of the quality of solutionswhen compared to classical heuristics used as subsolverswithin the multilevel approach.Reproducibility: source code and data are available at[TBA upon acceptance]

quantum computing↗

Noise and neuronal populations conspire to encode simple waveforms reliably

Sensory systems rely on populations of neurons to encode information transduced at the periphery into meaningful patterns of neuronal population activity. This transduction occurs in the presence of intrinsic neuronal noise. This is fortunate. The presence of noise allows more reliable encoding of the temporal structure present in the stimulus than would be possible in a noise-free environment. Simulations with a parallel model of signal processing at the auditory periphery have been used to explore the effects of noise and a neuronal population on the encoding of signal information. The results show that, for a given set of neuronal modeling parameters and stimulus amplitude, there is an optimal amount of noise for stimulus encoding with maximum fidelity.

Neurons/physiology↗

Joint Acceptance Attenuation Factor of Integrated Pressure with Unsteady Pressure-Sensitive Paint Measurements

The Unsteady Pressure-Sensitive Paint (uPSP) is widely used to measure the surface pressure of the scaled model in the wind tunnel tests. Compared to the conventional pressure transducers, uPSP has the advantage of high spatial resolution. With multiple high-speed cameras, the uPSP data collected with the camera pixels are mapped to the surface grid of the scaled model and converted to pressure. The shot noise, which is associated with the quantum processes both in the generation of the photons by the luminescent uPSP and in the conversion of the photons into electrons within the camera, is the dominant component of the noise in the uPSP measurement. The integrated pressure is usually computed as an area-weighted average of the uPSP measured pressures on the grid nodes of a user-defined patch. The effect of the shot noise is reduced in the integrated pressure; however, the measurement of the aerodynamic pressure is also attenuated. This paper discusses the Joint Acceptance Attenuation Factor (JAAF) of the integrated pressure with uPSP measurements. The JAAF is defined as the ratio of the auto or cross Power Spectral Density (PSD) of the integrated aerodynamic pressure on the patch to the average auto PSD of the aerodynamic pressure on the grid nodes of the patch. Under the assumption that the cross spectrum of the aerodynamic pressure can be described with the Corcos model, the closed-form formula of the JAAF is derived for the integrated pressure on rectangular patches via the summation of uPSP measurements on discrete grid nodes. The closed-form formula is verified via the integration of the pressure field of Corcos model over continuous areas. The properties of the JAAF with different parameters are presented and the applications in the comparison of the spectrum of the pressure transducers and uPSP measurements, which were collected in the NASA Space Launch System (SLS) tests with the 11-by-11-foot transonic wind tunnel at NASA Ames Research Center in December 2017 and September 2019 respectively, are also discussed. The work described in this paper is a part of NASA’s development of a new state-of-the-art uPSP capability in production wind tunnels. Funding was provided by the NASA Aerosciences Evaluation and Test Capabilities(AETC) Portfolio Office.

Unsteady Pressure-Sensitive Paint↗

Application of Electromagnetic Methods for Reservoir Monitoring with Emphasis on Carbon Capture, Utilization, and Storage

The Controlled-Source ElectroMagnetic (CSEM) method provides crucial information about reservoir fluids and their spatial distribution. Carbon dioxide (CO2) storage, enhanced oil recovery (EOR), geothermal exploration, and lithium exploration are ideal applications for the CSEM method. The versatility of CSEM permits its customization to specific reservoir objectives by selecting the appropriate components of a multi-component system. To effectively tailor the CSEM approach, it is essential to determine whether the primary target reservoir is resistive or conductive. This task is relatively straightforward in CO2 monitoring, where the injected fluid is resistive. However, for scenarios involving brine-saturated (water-wet) or oil-wet (carbon capture, utilization, and storage—CCUS) reservoirs, consideration must also be given to conductive reservoir components. The optimization of data acquisition before the survey involves analyzing target parameters and the sensitivity of multi-component CSEM. This optimization process typically includes on-site noise measurements and 3D anisotropic modeling. Based on our experience, subsequent surveys tend to proceed smoothly, yielding robust measurements that align with scientific objectives. Other critical aspects to be considered are using magnetotelluric (MT) measurements to define the overall background resistivities and integrating real-time quality assurance during data acquisition with 3D modeling. This integration allows the fine tuning of acquisition parameters such as acquisition time and necessary repeats. As a result, data can be examined in real-time to assess subsurface information content while the acquisition is ongoing. Consequently, high-quality data sets are usually obtained for subsequent processing and initial interpretation with minimal user intervention. The implementation of sensitivity analysis during the inversion process plays a pivotal role in ensuring that the acquired data accurately respond to the target reservoirs’ expected depth range. To elucidate these concepts, we present an illustrative example from a CO2 storage site in North Dakota, USA, wherein the long-offset transient electromagnetic method (LOTEM), a variation of the CSEM method, and the MT method were utilized. This example showcases how surface measurements attain appropriately upscaled log-scale sensitivity. Furthermore, the sensitivity of the CSEM and MT methods was examined in other case histories, where the target reservoirs exhibited conductive properties, such as those encountered in enhanced oil recovery (EOR), geothermal, and lithium exploration applications. The same equipment specifications were utilized for CSEM and MT surveys across all case studies.

Barajas-Olalde, César↗

Computer image processing in marine resource exploration

Pictographic data or imagery is commonly used in marine exploration. Pre-existing image processing techniques (software) similar to those used on imagery obtained from unmanned planetary exploration were used to improve marine photography and side-scan sonar imagery. Features and details not visible by conventional photo processing methods were enhanced by filtering and noise removal on selected deep-sea photographs. Information gained near the periphery of photographs allows improved interpretation and facilitates construction of bottom mosaics where overlapping frames are available. Similar processing techniques were applied to side-scan sonar imagery, including corrections for slant range distortion, and along-track scale changes. The use of digital data processing and storage techniques greatly extends the quantity of information that can be handled, stored, and processed.

Paluzzi, P. R.↗

Tone-excited jet: Theory and experiments

A detailed study to understand the phenomenon of broadband jet-noise amplification produced by upstream discrete-tone sound excitation has been carried out. This has been achieved by simultaneous acquisition of the acoustic, mean velocity, turbulence intensities, and instability-wave pressure data. A 5.08 cm diameter jet has been tested for this purpose under static and also flight-simulation conditions. An open-jet wind tunnel has been used to simulate the flight effects. Limited data on heated jets have also been obtained. To improve the physical understanding of the flow modifications brought about by the upstream discrete-tone excitation, ensemble-averaged schlieren photographs of the jets have also been taken. Parallel to the experimental study, a mathematical model of the processes that lead to broadband-noise amplification by upstream tones has been developed. Excitation of large-scale turbulence by upstream tones is first calculated. A model to predict the changes in small-scale turbulence is then developed. By numerically integrating the resultant set of equations, the enhanced small-scale turbulence distribution in a jet under various excitation conditions is obtained. The resulting changes in small-scale turbulence have been attributed to broadband amplification of jet noise. Excellent agreement has been found between the theory and the experiments. It has also shown that the relative velocity effects are the same for the excited and the unexcited jets.

Ahuja, K. K.↗

Multiplicative Shot-Noise: A New Route to Stability of Plastic Networks

Fluctuations of synaptic weights, among many other physical, biological, and ecological quantities, are driven by coincident events of two “parent” processes. Here we propose a multiplicative shot-noise model that can capture the behaviors of a broad range of such natural phenomena, and analytically derive an approximation that accurately predicts its statistics. We apply our results to study the effects of a multiplicative synaptic plasticity rule that was recently extracted from measurements in physiological conditions. Using mean-field theory analysis and network simulations, we investigate how this rule shapes the connectivity and dynamics of recurrent spiking neural networks. The multiplicative plasticity rule is shown to support efficient learning of input stimuli, and it gives a stable, unimodal synaptic-weight distribution with a large fraction of strong synapses. The strong synapses remain stable over long times but do not “run away.” Our results suggest that the multiplicative shot-noise offers a new route to understand the tradeoff between flexibility and stability in neural circuits and other dynamic networks.

59 BASIC BIOLOGICAL SCIENCES↗

The Mira-Titan Universe. III. Emulation of the Halo Mass Function

We construct an emulator for the halo mass function over group and cluster mass scales for a range of cosmologies, including the effects of dynamical dark energy and massive neutrinos. The emulator is based on the recently completed Mira-Titan Universe suite of cosmological N-body simulations. The main set of simulations spans 111 cosmological models with 2.1 Gpc boxes. We extract halo catalogs in the redshift range z = [0.0, 2.0] and for masses M-200c >= 10(13)M(circle dot)/h. The emulator covers an eight-dimensional hypercube spanned by {Omega(m)h(2), Omega(b)h(2), Omega(nu)h(2), sigma(8), h, n(s), w(0), w(a)}; spatial flatness is assumed. We obtain smooth halo mass functions by fitting piecewise second-order polynomials to the halo catalogs and employ Gaussian process regression to construct the emulator while keeping track of the statistical noise in the input halo catalogs and uncertainties in the regression process. For redshifts z less than or similar to 1, the typical emulator precision is better than 2% for 10(13)-10(14)M(circle dot)/h and <10<^> M similar or equal to 101(circle dot)(54)/h. For comparison, fitting functions using the traditional universal form for the halo mass function can be biased at up to 30% at M similar or equal to 10(144)M(circle dot)/h for z = 0. Our emulator is publicly available at https://github.com/SebastianBocquet/MiraTitanHMFemulator.

cosmology: theory↗

InGaAsSb Detectors' Characterization for 2-Micron CO2 Lidar/DIAL Applications

Recent interest in monitoring atmospheric CO2 focuses attention on infrared remote sensing using the 2-micron lidar/differential absorption lidar (DIAL) technique. Quantum detectors are critical components in this technique, and many research efforts concentrate on developing such devices for the 2-micron wavelength. Characterization results of InGaAsSb quantum detectors for the 2-micron wavelength range are presented, including experimental setup and procedure. Detectors are prototype devices manufactured by using separate absorption and multiplication (SAM) structures. Characterization experiments include V-I measurements, spectral response and its variation with bias voltage and temperature, noise measurements, noise-equivalent-power (NEP) and detectivity calculations, and signal-to-noise ratio (SNR) estimation. A slight increase in the output signal occurred with increased bias voltage and was associated with a noise level increase. Cooling down the detectors reduces noise and shifts the cutoff wavelength to shorter values. Further improvement in the design and manufacturing process, by increasing the device gain and lowering its noise level, is necessary to meet the required CO2 lidar/DIAL specifications.

Refaat, Tamer F.↗

InGaAsSb Detectors Characterization for 2-Micron CO2 Lidar/DIAL Applications

Recent interest in monitoring atmospheric CO2 focuses attention on infrared remote sensing using the 2-micron lidar/differential absorption lidar (DIAL) technique. Quantum detectors are critical components in this technique, and many research efforts concentrate on developing such devices for the 2-micron wavelength. Characterization results of InGaAsSb quantum detectors for the 2-micron wavelength range are presented, including experimental setup and procedure. Detectors are prototype devices manufactured by using separate absorption and multiplication (SAM) structures. Characterization experiments include V-I measurements, spectral response and its variation with bias voltage and temperature, noise measurements, noise-equivalent-power (NEP) and detectivity calculations, and signal-to-noise ratio (SNR) estimation. A slight increase in the output signal occurred with increased bias voltage and was associated with a noise level increase. Cooling down the detectors reduces noise and shifts the cutoff wavelength to shorter values. Further improvement in the design and manufacturing process, by increasing the device gain and lowering its noise level, is necessary to meet the required CO2 lidar/DIAL specifications.

Refaat, Tamer F.↗

Analysis of the MUSIC 3 He Multiplicity Data

A measurement campaign called the Measurement of Uranium Subcritical and Critical (MUSiC) was performed on a range of configurations of highly-enriched uranium (HEU) from December 2020 through April of 2021. While part of the focus was to measure reactor kinetics parameters on delayed supercritical systems, an additional focus was performing neutron noise measurements on subcritical configurations from deeply subcritical to nearly delayed critical. Multiple detector systems were used to perform these measurements, such as a 3 He multiplicity detector called the Neutron Multiplicity Array Detector (NoMAD) and a liquid scintillator system called the Rossi-α Measurement Rapid Organic Discriminating Detector (RAM-RODD). Also included were a scintillator system from the University of Michigan and a set of small 3He tubes that have previously been used to measure Rossi-α values on near-critical systems. The focus of this paper will be a comparison of prospective analysis methods for the NoMAD measurements. Previous subcritical measurements at the National Criticality Experiments Research Center (NCERC) submitted to the International Criticality Safety Benchmark Evaluation Project (ICSBEP) used the Hage-Cifarelli formalism of the Feynman Variance-to-Mean method. This relies on the time correlations of neutron detections to infer the spontaneous fission rate and neutron multiplication of a system through binning the time tagged detections and analyzing resulting histograms of the numbers of counts. However, there are other neutron noise methods that rely on similar processes, such as the Hansen-Dowdy formalism which uses a slightly different methodology to extract multiplication from the neutron multiplicity counting moments. Comparisons can be made between these experimental results and those obtained through simulations to validate or identify deficiencies in analysis, detection methods, or the underlying nuclear data. Different time gating strategies and their effects on count rate uncertainties are also investigated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Removing Noise in BPM Measurements with Variational Autoencoders

Noise in beam measurements is an ever-present challenge in accelerator operations. In addition to the challenges presented by hardware and signal processing, new operational regimes, such as ultra-short bunches, create additional difficulties in routine beam measurements. Techniques in machine learning have been successfully applied in other domains to overcome challenges inherent in noisy data. Variational autoencoders (VAEs) are shown to be capable of removing significant leevels of noise. A VAE can be used as a pre-processing tool for noise removal before the de-noised data is analyzed via other methods, or the VAE can be directly used to make beam dynamics measurements. Here we present the use of VAEs as a tool for addressing noise in BPM measurements.

43 PARTICLE ACCELERATORS↗