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Data are presented from a range of operating conditions which include background photo flux, operating temperature, and frequency. Each detector is equipped with a load resistor, a cryogenic field effect transistor preamplifier, and a temperature sensor. Data are also presented of detector signal, noise spectra, noise equivalent power, and spectral response.
Second-order photon correlation measurements [g (2) (τ) functions] are widely used to classify single-photon emission purity in quantum emitters or to measure the multiexciton quantum yield of emitters that can simultaneously host multiple excitations – such as quantum dots – by evaluating the value of g (2) (τ = 0). Accumulating enough photons to accurately calculate this value is time consuming and could be accelerated by fitting of few-shot photon correlations. Here, we develop an uncertainty-aware, deep adversarial autoencoder ensemble (AAE) that reconstructs noise-free g (2) (τ) functions from noise-dominated, few-shot inputs. The model is trained with simulated g (2) (τ) functions that are facilely generated by Poisson sampling time bins. The AAE reconstructions are performed orders-of-magnitude faster, with reconstruction errors and estimates of g (2) (τ = 0) that are lower in variance and similar in accuracy compared to Maximum likelihood estimation and Levenberg-Marquardt least-squares fitting approaches, for simulated and experimentally measured few-shot g (2) (τ) functions (~100 two-photon events) of InP/ZnS/ZnSe and CdS/CdSe/CdS quantum dots. The deep-ensemble model comprises eight individual autoencoders, allowing for probabilistic reconstructions of noise-free g (2) (τ) functions, and we show that the predicted variance scales inversely with number of shots, with comparable uncertainties to computationally intensive Markov chain Monte Carlo sampling. Furthermore, this work demonstrates the advantage of machine learning models to perform uncertainty-aware, fast, and accurate reconstructions of simple Poisson-distributed photon correlation functions, allowing for on-the-fly reconstructions and accelerated materials characterization of solid-state quantum emitters.
The overall goal of this project was to understand in more detail how a pattern-forming system can adjust its spacing. "Pattern-forming systems," in this context, are nonequilibrium contina whose state is determined by experimentally adjustable control parameter. Below some critical value of the control system then has available to it a range of linearly stable, spatially periodic steady states, each characterized by a spacing which can lie anywhere within some band of values. These systems like directional solidification, where the solidification front is planar when the ratio of growth velocity to thermal gradient is below its critical value, but takes on a cellular shape above critical. They also include systems without interfaces, such as Benard convection, where it is the fluid velocity field which changes from zero to something spatially periodic as the control parameter is increased through its critical value. The basic question to be addressed was that of how the system chooses one of its myriad possible spacings when the control parameter is above critical, and in particular the role of noise in the selection process. Previous work on explosive crystallization had suggested that one spacing in the range should be preferred, in the sense that weak noise should eventually drive the system to that spacing. That work had also suggested a heuristic argument for identifying the preferred spacing. The project had three main objectives: to understand in more detail how a pattern-forming system can adjust its spacing; to investigate how noise drives a system to its preferred spacing; and to extend the heuristic argument for a preferred spacing in explosive crystallization to other pattern-forming systems.
An experiment was performed on the flap tip vortex shed from a half span Fowler flap. This flap was mounted on a 5 foot span NACA 63(2)-215 Mod B airfoil in the 7 by 10 foot wind tunnel at NASA Ames Research Center. Several noise reduction studies were performed with this model, and the addition of the Particle Image Velocimetry (PIV) research discussed here served as a proof case of large scale PIV. The measurement plane investigated here was a cross plane region. This is cross plane relative to the freestream flow direction. The measurement plane was located at a position 18 inches downstream of the flap trailing edge. This served to prove that measurements could also be made in the more difficult cross plane direction rather than in the downstream flow direction. Lastly the PIV data was used as a practical research tool that yielded important results that could not otherwise be obtained. The flow field area measured was 40 cm by 40 cm square, and served to characterize the downstream flow characteristics of the flap tip vortex under three configurations: the baseline configuration which was the flap and the wing only; the baseline with the addition of a 3/4 span slat; and the baseline with a Flap Edge Device which was designed to reduce the noise generated at the flap. All configurations were tested at a freestream velocity of 64.84 m/s. The test resulted in average velocity fields for the three configurations tested. The velocity fields aided in verifying other testing methods on this particular experiment, and also yielded further insight into the characteristics of the flap tip vortex under the three configurations considered. The velocity data was reduced, and we were able to calculate the vorticity of the flow field. From the position of minimum vorticity the location of the center of the vortex was determined. The circulation was also calculated and aided in comparing the effects of the three configurations on the lifting characteristics of the flap.
This work briefly discusses the potential applications of the Skipper-CCD technology in astronomy and reviews its current use in dark matter and neutrino experiments. An overview of the ongoing efforts to build multi-kilogram experiments with these sensors is given, in the context of the Oscura experiment. First results from the characterization of Oscura sensors from the first 200 mm wafer-fabrication run with a new vendor are presented. The overall yield of the electron counting capability of these sensors is 71%. In conclusion, a noise of 0.087 e - RMS, with 1225 samples/pix, and a dark current of (0.031±0.013) e - /pix/day at 140 K were measured.
Using P-wave seismograms, we trained a seismic source classifier using a Convolutional Neural Network. We trained for three classes: earthquake P-wave, underground nuclear explosion (UNE) P-wave, and noise. With the current absence of nuclear testing by countries that have signed the Comprehensive Test Ban Treaty, high quality seismic data from UNEs is limited. Even with limited training data, our model can accurately characterize most events recorded at regional and teleseismic distances, finding over 95% signals in the validation set. We applied the model on holdout datasets of the North Korean test explosions to evaluate the performance on unique region and station-source pairs, with promising results. Additionally, we tested on the Source Physics Experiment events to investigate the potential for chemical explosions to act as a surrogate for nuclear explosions. We anticipate that machine-learning models like our classifier system can have broad application for other seismic signals including volcanic and non-volcanic tremor, anomalous earthquakes, ice-quakes or landslide-quakes.
The use of automated, analytical techniques to aid medical support teams is suggested. Recommendations are presented for characterizing crew health in terms of: (1) wholebody function including physiological, psychological and performance factors; (2) a combination of critical performance indexes which consist of multiple factors of measurable parameters; (3) specific responses to low noise level stress tests; and (4) probabilities of future performance based on present and periodic examination of past performance. A concept is proposed for a computerized real time biomedical monitoring and health care system that would have the capability to integrate monitored data, detect off-nominal conditions based on current knowledge of spaceflight responses, predict future health status, and assist in diagnosis and alternative therapies. Mathematical models could play an important role in this approach, especially when operating in a real time mode. Recommendations are presented to update the present health monitoring systems in terms of recent advances in computer technology and biomedical monitoring systems.
General features of the quantum noise problem expressed as the equations of motion for a particle coupled to a set of oscillators are investigated analytically. Account is taken of the properties of the companion oscillators by formulating quantum statistical correlation Langevin equations (QSLE). The frequency of the oscillators is then retained as a natural cut-off for the quantum noise. The QSLE is further extended to encompass the particle trajectory and is bounded by initial and final states of the oscillator. The states are expressed as the probability of existence at the moment of particle collision that takes the oscillator into a final state. Two noise sources then exist: a statistical uncertainty of the initial state and the quantum dynamical uncertainty associated with a transition from the initial to final state. Feynman's path-integral formulation is used to characterize the functional of the particle trajectory, which slows the particle. It is shown that the energy loss may be attributed to friction, which satisfies energy conservation laws.
Results are reported of experiments with smoke-wire flow visualization applied to characterizing the conditions conducive to formation of a separation bubble on an airfoil in low Re flow. An airfoil was used which spanned the test channel of the wind tunnel designed for low turbulence and noise. A wire coated with mineral oil was stretched across the channel upstream of the airfoil and heated. The smoke it gave off was flash-illuminated and photographed with ASA 3000 film. Extending the airfoil over the entire section yielded photographs that gave an essentially two-dimensional perspective. Angles of attack from 0-10 deg were investigated at Re of 33,000, 66,000, 100,000 and 133,000. Sample photographs illustrate the usefulness of the technique and apparatus in the flow regimes examined, particularly when used in conjunction with pressure tap data from the airfoil surface.
"Smart" structures composed of piezoelectric materials may significantly improve the performance of aeropropulsion systems through a variety of vibration, noise, and shape-control applications. The development of analytical models for piezoelectric smart structures is an ongoing, in-house activity at the NASA Glenn Research Center at Lewis Field focused toward the experimental characterization of these materials. Research efforts have been directed toward developing analytical models that account for the coupled mechanical, electrical, and thermal response of piezoelectric composite materials. Current work revolves around implementing thermal effects into a curvilinear-shell finite element code. This enhances capabilities to analyze curved structures and to account for coupling effects arising from thermal effects and the curved geometry. The current analytical model implements a unique mixed multi-field laminate theory to improve computational efficiency without sacrificing accuracy. The mechanics can model both the sensory and active behavior of piezoelectric composite shell structures. Finite element equations are being implemented for an eight-node curvilinear shell element, and numerical studies are being conducted to demonstrate capabilities to model the response of curved piezoelectric composite structures (see the figure).
A superconducting hot-electron bolometer has been built and tested as a prototype of high-sensitivity, rapid-response detectors of submillimeter-wavelength radiation. There are diverse potential applications for such detectors, a few examples being submillimeter spectroscopy for scientific research; detection of leaking gases; detection of explosive, chemical, and biological weapons; and medical imaging. This detector is a superconducting-transition- edge device. Like other such devices, it includes a superconducting bridge that has a low heat capacity and is maintained at a critical temperature (T(sub c)) at the lower end of its superconducting-transition temperature range. Incident photons cause transient increases in electron temperature through the superconducting-transition range, thereby yielding measurable increases in electrical resistance. In this case, T(sub c) = 6 K, which is approximately the upper limit of the operating-temperature range of silicon-based bolometers heretofore used routinely in many laboratories. However, whereas the response speed of a typical silicon- based laboratory bolometer is characterized by a frequency of the order of a kilohertz, the response speed of the present device is much higher characterized by a frequency of the order of 100 MHz. For this or any bolometer, a useful figure of merit that one seeks to minimize is (NEP)(tau exp 1/2), where NEP denotes the noise-equivalent power (NEP) and the response time. This figure of merit depends primarily on the heat capacity and, for a given heat capacity, is approximately invariant. As a consequence of this approximate invariance, in designing a device having a given heat capacity to be more sensitive (to have lower NEP), one must accept longer response time (slower response) or, conversely, in designing it to respond faster, one must accept lower sensitivity. Hence, further, in order to increase both the speed of response and the sensitivity, one must make the device very small in order to make its heat capacity very small; this is the approach followed in developing the present device.
A fabrication process is reported for prototype emitters of THz radiation, which operate cryogenically, and should provide a fast, stable blackbody source suitable for characterization of THz devices. The fabrication has been demonstrated and, at the time of this reporting, testing was underway. The emitter is similar to a monolithic silicon bolometer in design, using both a low-noise thermometer and a heater element on a thermally isolated stage. An impedance-matched, high-emissivity coat ing is also integrated to tune the blackbody properties. This emitter is designed to emit a precise amount of power as a blackbody spectrum centered on terahertz frequencies. The emission is a function of the blackbody temperature. An integrated resistive heater and thermometer system can control the temperature of the blackbody with greater precision than previous incarnations of calibration sources that relied on blackbody emission. The emitter is fabricated using a silicon- on-insulator substrate wafer. The buried oxide is chosen to be less than 1 micron thick, and the silicon device thickness is 1-2 microns. Layers of phosphorus compensated with boron are implanted into and diffused throughout the full thickness of the silicon device layer to create the thermometer and heater components. Degenerately doped wiring is implanted to connect the devices to wire-bondable contact pads at the edge of the emitter chip. Then the device is micromachined to remove the thick-handle silicon behind the thermometer and heater components, and to thermally isolate it on a silicon membrane. An impedance- matched emissive coating (ion assisted evaporated Bi) is applied to the back of the membrane to enable high-efficiency emission of the blackbody spectrum.
Hot-Electron Bolometer (HEB) mixers have proven to be the best tool for high-resolution spectroscopy at the Terahertz frequencies. However, the current state of the art NbN mixers suffer from a small intermediate frequency (IF) bandwidth as well as a low operating temperature. MgB2 is a promising material for HEB mixer technology in view of its high critical temperature and fast thermal relaxation allowing for a large IF bandwidth. In this work, we have fabricated and characterized thin-film (approximately 15 nanometers) MgB2-based spiral antenna-coupled HEB mixers on SiC substrate. We achieved the IF bandwidth greater than 8 gigahertz at 25 degrees Kelvin and the device noise temperature less than 4000 degrees Kelvin at 9 degrees Kelvin using a 600 gigahertz source. Using temperature dependencies of the radiation power dissipated in the device we have identified the optical loss in the integrated microantenna responsible as a cause of the limited sensitivity of the current mixer devices. From the analysis of the current-voltage (IV) characteristics, we have derived the effective thermal conductance of the mixer device and estimated the required local oscillator power in an optimized device to be approximately 1 microwatts.
Fully-depleted thick silicon Skipper-charge-coupled devices (Skipper-CCDs) have achieved sub-electron read-out noise and are an important technology to probe neutrino and light dark matter interactions. However, the successful search for rare neutrino or dark-matter events requires the signal and all backgrounds to be fully characterized. In particular, a measurement of the electron-hole pair creation energy below 150 eV and the Fano factor are necessary for characterizing the dark matter and neutrino signals. Moreover, photons from background radiation may Compton scatter in the silicon bulk, producing events that can mimic a dark matter or neutrino signal. We present a measurement of the Compton spectrum using a Skipper-CCD and a $^{241}$Am source. With these data, we measure the electron-hole pair-creation energy to be $\left(3.71 \pm 0.08\right)$ eV at 130 K in the energy range between 99.3 eV and 150 eV. By measuring the widths of the steps at 99.3 eV and 150 eV in the Compton spectrum, we introduce a novel technique to measure the Fano factor, setting an upper limit of 0.31 at 90% C.L. These results prove the potential of Skipper-CCDs to characterize the Compton spectrum and to measure precisely the Fano factor and electron-hole pair creation energy below 150 eV.
Considerable interest lies in the ability to characterize the onset of spontaneous instabilities within liquid propellant rocket engine (LPRE) combustion devices. Linear techniques, such as fast Fourier transforms, various correlation parameters, and critical damping parameters, have been used at great length for over fifty years. Recently, nonlinear time series methods have been applied to deduce information pertaining to instability incipiency hidden in seemingly stochastic combustion noise. A technique commonly used in biological sciences known as the Multifractal Detrended Fluctuation Analysis has been extended to the combustion dynamics field, and is introduced here as a data analysis approach complementary to linear ones. Advancing, a modified technique is leveraged to extract artifacts of impending combustion instability that present themselves a priori growth to limit cycle amplitudes. Analysis is demonstrated on data from J-2X gas generator testing during which a distinct spontaneous instability was observed. Comparisons are made to previous work wherein the data were characterized using linear approaches. Verification of the technique is performed by examining idealized signals and comparing two separate, independently developed tools.
Researchers fabricated and characterized several AlGaAs/GaAs multiple quantum well infrared detectors to evaluate the ultimate performance of these devices for low infrared background applications. The detectors were designed to have a single bound state in the quantum well and the first excited state in the continuum above the AlGaAs conduction band edge. The difference in energy between the two levels, as determined by the quantum well width and aluminum mole fraction in the barrier, was chosen such that peak absorption would occur near 8 microns. The initial structures studied comprised 50 periods with 40 A well widths and 300 A Al(0.28)Ga(0.72)As barriers. The performance of these detectors are summarized. To better interpret these results and design optimized detectors, researchers modeled both the detector noise and tunneling currents. The noise model correctly predicts that multiple quantum well detectors will, indeed, exhibit noise lower than full shot noise. The tunneling current model predicts the dark current versus bias for any choice of design parameters in a multiple quantum well detector. This model predicts a substantially reduced dark current (x 10(exp 04)) for samples with 400 A barriers. To evaluate structures with thicker barriers, researchers fabricated and characterized detectors with 400 A and 500 A barriers; a comparison of detector dark currents is shown. These results are consistent with the predictions of the dark current model.
Monte Carlo simulations are at the heart of many high-fidelity simulations and analyses for radiation transport systems. As is the case with any complex computational model, it is important to propagate sources of input uncertainty and characterize how they affect model output. Unfortunately, uncertainty quantification (UQ) is made difficult by the stochastic variability that Monte Carlo transport solvers introduce. The standard method to avoid corrupting the UQ statistics with the transport solver noise is to increase the number of particle histories, resulting in very high computational costs. In this contribution, we propose and analyze a sampling estimator based on the law of total variance to compute UQ variance even in the presence of residual noise from Monte Carlo transport calculations. Here, we rigorously derive the statistical properties of the new variance estimator, compare its performance to that of the standard method, and demonstrate its use on neutral particle transport model problems involving both attenuation and scattering physics. We illustrate, both analytically and numerically, the estimator’s statistical performance as a function of available computational budget and the distribution of that budget between UQ samples and particle histories. We show analytically and corroborate numerically that the new estimator is unbiased, unlike the standard approach, and is more accurate and precise than the standard estimator for the same computational budget.
A Cosmic Muon Veto (CMV) detector using extruded scintillators is being designed around the mini-Iron Calorimeter detector at the transit campus of the India-based Neutrino Observatory, Madurai for measuring its efficiency at shallow depth underground experiments. The scintillation signal is transmitted through a Wavelength Shifting (WLS) fibre and readout by Hamamatsu Silicon-Photomultipliers (SiPMs). A Light Emitting Diode (LED) system is included on the front-end readout for in-situ calibration of the gain of each SiPM. A characterization system was developed for the measurement of gain and choice of the overvoltage (V ov ) of SiPMs using the LED as well as a cosmic muon telescope. The V ov is obtained by studying the noise rate, the gain of the SiPM, and the muon detection efficiency. In case of any malfunction of the LED system during the operation, the SiPM can also be calibrated with the noise data as well as using radioactive sources. Furthermore, this paper describes the basic characteristics of the SiPM and the comparison of the calibration results using all three methods, as well as the V ov of the SiPMs and muon selection criteria for the veto detector.