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At least 937 records · Page 52

Skipper-in-CMOS: Nondestructive Readout With Subelectron Noise Performance for Pixel Detectors

The Skipper-in-CMOS image sensor integrates the nondestructive readout capability of skipper charge coupled devices (Skipper-CCDs) with the high conversion gain of a pinned photodiode (PPD) in a CMOS imaging process while taking advantage of in-pixel signal processing. This allows both single photon counting as well as high frame rate readout through highly parallel processing. The first results obtained from a ${15} \times {15}~\mu $ m2 pixel cell of a Skipper-in-CMOS sensor fabricated in Tower Semiconductor’s commercial 180-nm CMOS image sensor process are presented. Measurements confirm the expected reduction of the readout noise with the number of samples down to deep subelectron noise of $0.15\text {e}^ - $ , demonstrating the charge transfer operation from the PPD and the single photon counting operation when the sensor is exposed to light. This article also discusses new testing strategies employed for its operation and characterization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A platform to measure isentropes from proton-heated warm dense matter on short pulse laser facilities

We describe the development of an experimental platform that measures the release isentrope of materials heated isochorically to temperatures of a few electron volts, using short-pulse laser-produced protons to heat the sample and long-pulse laser-produced x rays to perform streaked x-ray radiography. The density profiles derived from the radiography data are integrated to generate pressure–density isentropes, independent of prior knowledge of the equation of state of the sample material. In order to understand the sensitivities of isentrope extraction from radiography data, we analyze synthetic radiographs generated by a radiation hydrodynamics code. Noise reduction and high spatial resolution are critical for isentrope reconstruction, as demonstrated by the analysis of a proof-of-principle shot day on the OMEGA-EP facility. In conclusion, the data demonstrate the feasibility of the platform for characterizing isentropes, and we discuss the necessary improvements to enhance precision in differentiating between equation-of-state models.

Equations of state↗

Radar optimization for sea surface and geodetic measurements

The efficient estimation of geoid and sea state parameters is discussed, and the optimum processing structures, including maximum likelihood estimators, and their accuracy limits are given for a model. The model accounts for random surface reflectivity, sea height, and additive noise, and allows for arbitrary radar system parameters, based on the assumption the received signal is a sample function of a normal random process. The integral equation associated with the Gaussian signal in Gaussian noise inference problem was solved. It is shown that the optimum processing is generally a mixture of coherent and incoherent integrations which may be viewed as a weighted summation of received power of the match-filtered received data. When estimates are correlated, the strongest correlation appears between geoid and asymmetry estimates, and between wave height standard deviation and reflectivity estimates.

Harger, R. O.↗

Reducing the Read Noise of HAWAII-2RG Detector Systems with Improved Reference Sampling and Subtraction (IRS2)

IRS2 is a Wiener-optimal approach to using all of the reference information that Teledyne's HAWAII-2RG detector arrays provide. Using a new readout pattern, IRS2 regularly interleaves reference pixels with the normal pixels during readout. This differs from conventional clocking, in which the reference pixels are read out infrequently, and only in a few rows and columns around the outside edges of the detector array. During calibration, the data are processed in Fourier space, which is <;:lose to the noise's eigenspace. Using IRS2, we have reduced the read noise of the James Webb Space Telescope Near Infrared Spectrograph by 15% compared to conventional readout. We are attempting to achieve further gains by calibrating out recently recognized non-stationary noise that appears at the frame rate.

Rauscher, Bernard J.↗

Upgrading and performance of the SAO laser ranging system in Matera

The performance of the SAO lasers was improved considerably in terms of accuracy, range noise, data yield, and reliability. With the narrower laser pulse (2.5-3.0 nsec) and a new analog pulse processing system, the systematic range errors were reduced to 3-5 cm and range noise has been reduced to 5-15 cm on low satellites and 10-18 cm on Lageos. Pulse repetition rate was increased to 30 ppm and considerable improvement has been made in signal-to-noise ratio by using a 3 Angstrom interference filter and by reducing the range gate window down to 200-400 nsec. The first upgraded system was installed in Arequipa, Peru in the spring of 1982. The second upgraded system is now in operation in Matera, Italy. The third system is expected to be installed in Israel during 1984.

Maddox, J.↗

NASA progress in aircraft noise prediction

Langley Research Center efforts to develop a methodology for predicting the effective perceived noise level (EPNL) produced by jet-powered CTOL aircraft to an accuracy of + or - 1.5 dB are summarized with emphasis on the aircraft noise prediction program (ANOPP) which contains a complete set of prediction methods for CTOL aircraft including propulsion system noise sources, aerodynamic or airframe noise sources, forward speed effects, a layered atmospheric model with molecular absorption, ground impedance effects including excess ground attenuation, and a received noise contouring capability. The present state of ANOPP is described and its accuracy and applicability to the preliminary aircraft design process is assessed. Areas are indicated where further theoretical and experimental research on noise prediction are needed. Topics covered include the elements of the noise prediction problem which are incorporated in ANOPP, results of comparisons of ANOPP calculations with measured noise levels, and progress toward treating noise as a design constraint in aircraft system studies.

Raney, J. P.↗

Signal processing methodologies for an acoustic fetal heart rate monitor

Research and development is presented of real time signal processing methodologies for the detection of fetal heart tones within a noise-contaminated signal from a passive acoustic sensor. A linear predictor algorithm is utilized for detection of the heart tone event and additional processing derives heart rate. The linear predictor is adaptively 'trained' in a least mean square error sense on generic fetal heart tones recorded from patients. A real time monitor system is described which outputs to a strip chart recorder for plotting the time history of the fetal heart rate. The system is validated in the context of the fetal nonstress test. Comparisons are made with ultrasonic nonstress tests on a series of patients. Comparative data provides favorable indications of the feasibility of the acoustic monitor for clinical use.

Pretlow, Robert A., III↗

Performance of High-Resolution Mo/Cu Transition Edge Sensors Fabricated Using a Lift-Off Process

The soft X-ray band below ≈0.5 keV is expected to provide rich information on metallicity, temperature, and distribution of hot gas in our galaxy and the intergalactic medium. Resolving these densely spaced emission lines requires energy resolution on the order of 1--2 eV. The low count rates from diffuse astrophysical sources also necessitate large collection areas, particularly for a sounding rocket instrument with short exposure times and limited resources. This translates to large pixel sizes (about 1 mm 2 ) for a reasonable number of read-out channels. To achieve the required energy resolution with 200 nm thin Au absorbers (heat capacity C about 1 pJ/K), we are developing TES microcalorimeters with very high temperature sensitivity (αI), low enough current sensitivity (βI), and minimal excess noise (M). Out of the various fabrication approaches for the TES bilayer we have explored, the lift-off approach (as pioneered for Mo/Au TES by Joel Weber at NIST) so far is the simplest to execute. The simple square TES geometries we have tested to date show promising results for αI and βI. Measured complex impedance and noise for bare devices without absorbers are well described by two-body thermal models and their excess noise is found to be consistent with predictions for mixed-down Johnson noise by Wessels et al. More sensitive measurements with larger heat capacity are planned to accurately determine excess noise. In this paper, we give an overview of the process and summarize results of our detailed characterization measurements for thermal conductance G, αI, βI, and noise for several devices across a range of bias points.

Felix T Jaeckel↗

Synoptic scale wind field properties from the SEASAT SASS

Dealiased SEASAT SEASAT A Scatterometer System SASS vector winds obtained during the Gulf Of Alaska SEASAT Experiment GOASEX program are processed to obtain superobservations centered on a one degree by one degree grid. The grid. The results provide values for the combined effects of mesoscale variability and communication noise on the individual SASS winds. These superobservations winds are then processed further to obtain estimates of synoptic scale vector winds stress fields, the horizontal divergence of the wind, the curl of the wind stress and the vertical velocity at 200 m above the sea surface, each with appropriate standard deviations of the estimates for each grid point value. They also explain the concentration of water vapor, liquid water and precipitation found by means of the SMMR Scanning Multichannel Microwave Radiometer at fronts and occlusions in terms of strong warm, moist air advection in the warm air sector accompanied by convergence in the friction layer. Their quality is far superior to that of analyses based on conventional data, which are shown to yield many inconsistencies.

Pierson, W. J., Jr.↗

Experimental Passive-State Preparation for Continuous-Variable Quantum Communications

In the Gaussian-modulated coherent state quantum key distribution (QKD) protocol, the sender first generates Gaussian-distributed random numbers and then encodes them on weak laser pulses actively by performing amplitude and phase modulations. Recently, an equivalent passive QKD scheme has been proposed by exploring the intrinsic field fluctuations of a thermal source [B. Qi, P. G. Evans, and W. P. Grice, Phys. Rev. A 97, 012317 (2018)]. This passive QKD scheme is especially appealing for chip-scale implementation since no active modulation is required. In this paper, we conduct an experimental study of the passively encoded QKD scheme using an off-the-shelf amplified spontaneous emission source operated in continuous-wave mode. Our results show that the excess noise introduced by the passive state preparation scheme can be effectively suppressed by applying optical attenuation and a secure key can be generated over metro-area distances.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Robust Decentralized Learning Using ADMM With Unreliable Agents

Many signal processing and machine learning problems can be formulated as consensus optimization problems which can be solved efficiently via a cooperative multi-agent system. However, the agents in the system can be unreliable due to a variety of reasons: noise, faults and attacks. Providing erroneous updates leads the optimization process in a wrong direction, and degrades the performance of distributed machine learning algorithms. This paper considers the problem of decentralized learning using ADMM in the presence of unreliable agents. First, we rigorously analyze the effect of erroneous updates (in ADMM learning iterations) on the convergence behavior of the multi-agent system. We show that the algorithm linearly converges to a neighborhood of the optimal solution under certain conditions and characterize the neighborhood size analytically. Next, we provide guidelines for network design to achieve a faster convergence to the neighborhood. Here, we also provide conditions on the erroneous updates for exact convergence to the optimal solution. Finally, to mitigate the influence of unreliable agents, we propose ROAD , a robust variant of ADMM, and show its resilience to unreliable agents with an exact convergence to the optimum.

97 MATHEMATICS AND COMPUTING↗

Full-scale experiments with an ejector to reduce jet engine exhaust noise

Experiments with a modified J65 turbojet engine and ejector resulted in noise power reductions as large as 13 decibels in the low-frequency range. High-frequency noise power, which appeared to originate mainly from the mixing processes within the ejector, increased. Peak velocities at the ejector exit were reduced by one-half to two-thirds, although survey rakes showed that mixing was not complete. Acoustical lining inside the ejector would reduce the perceived noise level (in PNdB) by removing much of the high-frequency noise.

Clark, B. J.↗

Models and error analyses in urban air quality estimation

Estimation theory has been applied to a wide range of aerospace problems. Application of this expertise outside the aerospace field has been extremely limited, however. This paper describes the use of covariance error analysis techniques in evaluating the accuracy of pollution estimates obtained from a variety of concentration measuring devices. It is shown how existing software developed for aerospace applications can be applied to the estimation of pollution through the processing of measurement types involving a range of spatial and temporal responses. The modeling of pollutant concentration by meandering Gaussian plumes is described in some detail. Time averaged measurements are associated with a model of the average plume, using some of the same state parameters and thus avoiding the problem of state memory. The covariance analysis has been implemented using existing batch estimation software. This usually involves problems in handling dynamic noise; however, the white dynamic noise has been replaced by a band-limited process which can be easily accommodated by the software.

Englar, T., Jr.↗

Correspondence between neuroevolution and gradient descent

Abstract We show analytically that training a neural network by conditioned stochastic mutation or neuroevolution of its weights is equivalent, in the limit of small mutations, to gradient descent on the loss function in the presence of Gaussian white noise. Averaged over independent realizations of the learning process, neuroevolution is equivalent to gradient descent on the loss function. We use numerical simulation to show that this correspondence can be observed for finite mutations, for shallow and deep neural networks. Our results provide a connection between two families of neural-network training methods that are usually considered to be fundamentally different.

97 MATHEMATICS AND COMPUTING↗

Experimental demonstration of continuous quantum error correction

The storage and processing of quantum information are susceptible to external noise, resulting in computational errors. A powerful method to suppress these effects is quantum error correction. Typically, quantum error correction is executed in discrete rounds, using entangling gates and projective measurement on ancillary qubits to complete each round of error correction. Here we use direct parity measurements to implement a continuous quantum bit-flip correction code in a resource-efficient manner, eliminating entangling gates, ancillary qubits, and their associated errors. An FPGA controller actively corrects errors as they are detected, achieving an average bit-flip detection efficiency of up to 91%. Furthermore, the protocol increases the relaxation time of the protected logical qubit by a factor of 2.7 over the relaxation times of the bare comprising qubits. Our results showcase resource-efficient stabilizer measurements in a multi-qubit architecture and demonstrate how continuous error correction codes can address challenges in realizing a fault-tolerant system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Deep learning-driven super-resolution in Raman hyperspectral imaging: Efficient high-resolution reconstruction from low-resolution data

Deep learning (DL) has become an indispensable tool in hyperspectral data analysis, automatically extracting valuable features from complex, high-dimensional datasets. Super-resolution reconstruction, an essential aspect of hyperspectral data, involves enhancing spatial resolution, particularly relevant to low-resolution hyperspectral data. Yet, the pursuit of super-resolution in hyperspectral analysis is fraught with challenges, including acquiring ground truth high-resolution data for training, generalization, and scalability. The pressing issue of extended spectral acquisition times, notably for high-resolution scans, is a significant roadblock in hyperspectral imaging. Super-resolution methods offer a promising solution by providing higher spatial resolution data to expedite data collection and yield more efficient outcomes. This paper delves into a practical application of these concepts using Raman imaging, where spectral acquisition times can be prohibitively long. In this context, DL-based super-resolution models demonstrate their efficacy by predicting and reconstructing high-resolution Raman data from low-resolution input, eliminating the need for resource-intensive high-resolution scans. While previous work often relied on substantial high-resolution datasets, this study showcases the ability to achieve similar outcomes even with limited data, presenting a more practical and cost-effective approach. In conclusion, the results offer a glimpse into the transformative potential of this technology to streamline hyperspectral imaging applications by saving valuable time and resources through the successful generation of high-resolution data from low-resolution inputs.

42 ENGINEERING↗

Sensitivity Enhancement and Random Telegraph Noise in Magnetic Tunnel Junctions with Compensated Anisotropy

We demonstrate the manipulation of perpendicular magnetic anisotropy (PMA) in magnetic tunnel junctions (MTJs) by varying the layer stacks and temperature. PMA is tuned to compensate the shape anisotropy, giving a nonhysteretic magnetic response, a noteworthy sensitivity enhancement, and a field detectability of 1.8 nT/$\sqrt{Hz}$ at 100 kHz. Such a method is further exemplified in multiple MTJs, providing a solution to obtain desired sensitivities and operating temperatures. Additionally, the electronic noise of this MTJ is revealed as a random telegraph noise (RTN) due to a generation-recombination process. In conclusion, the observed voltage-dependent RTN could potentially be applied to true random number generators.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Source noise suppression in attosecond transient absorption spectroscopy by edge-pixel referencing

Attosecond transient absorption spectroscopy (ATAS) is used to observe photoexcited dynamics with outstanding time resolution. The main experimental challenge of this technique is that high-harmonic generation sources show significant instabilities, resulting in sub-par sensitivity when compared to other techniques. This paper proposes edge-pixel referencing as a means to suppress this noise. Two approaches are introduced: the first is deterministic and uses a correlation analysis, while the second relies on singular value decomposition. Each method is demonstrated and quantified on a noisy measurement taken on WS 2 and results in a fivefold increase in sensitivity. The combination of the two methods ensures the fidelity of the procedure and can be implemented on live data collection but also on existing datasets. The results show that edge-referencing methods bring the sensitivity of ATAS near the detector noise floor. An implementation of the post-processing code is provided to the reader.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗