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Paper describes status of program for developing integrated infrared detectors for astronomy. Program covers variety of detectors, including extrinsic silicon, extrinsic germanium, and indium antimonide devices with hybrid silicon multiplexers. Paper notes for arrays to reach background noise limit in cryogenic telescope, continued reductions in readout noise and dark current needed.
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This paper considers the control of a continuous linear plant disturbed by white plant noise when the control is constrained to be a piecewise constant function of time; i.e. a stochastic sampled-data system. The cost function is the integral of quadratic error terms in the state and control, thus penalizing errors at every instant of time while the plant noise disturbs the system continuously. The problem is solved by reducing the constrained continuous problem to an unconstrained discrete one. It is shown that the separation principle for estimation and control still holds for this problem when the plant disturbance and measurement noise are Gaussian.
Abstract Proper classification of nontectonic seismic signals is critical for detecting microearthquakes and developing an improved understanding of ongoing weak ground motions. We use unsupervised machine learning to label five classes of nonstationary seismic noise common in continuous waveforms. Temporal and spectral features describing the data are clustered to identify separable types of emergent and impulsive waveforms. The trained clustering model is used to classify every 1 s of continuous seismic records from a dense seismic array with 10–30 m station spacing. We show that dominate noise signals can be highly localized and vary on length scales of hundreds of meters. The methodology demonstrates the complexity of weak ground motions and improves the standard of analyzing seismic waveforms with a low signal‐to‐noise ratio. Application of this technique will improve the ability to detect genuine microseismic events in noisy environments where seismic sensors record earthquake‐like signals originating from nontectonic sources.
As part of a continuing study of possible methods of jet noise reduction, some tests have been made on a porous plug type noise suppressor. Very little information exists on the aeroacoustic performance of jet nozzles having porous elements designed to eliminate the shock wave in the exhaust stream and by so doing to eliminate the shock associated noise and screech. Some initial results on the aeroacoustic performance of a model porous plug type jet noise suppressor are presented. Included are shadowgraph pictures of the flow exhausting from the porous plug nozzle with the comparable acoustic far-field spectra and cross correlations which illustrate the benefits of the test device.
This work continues the analysis of data obtained during a 2017 NASA DGEN Aeropropulsion Research Turbofan (DART) core/combustor-noise baseline test in the NASA GRC Aero-Acoustic Propulsion Laboratory (AAPL). The DART is a cost-efficient testbed for the study of core-noise physics and mitigation. Acoustic data were simultaneously acquired using the AAPL overhead microphone array in the engine aft-quadrant farfield, a single midfield microphone, and two infinite-tube-probe sensors for unsteady pressures at the core-nozzle exit. The data are here examined on an 1/3-octave basis as a first step in extending and improving core-noise prediction capability.
This work continues the analysis of data obtained during a 2017 NASA DGEN Aeropropulsion Research Turbofan (DART) core/combustor-noise baseline test in the NASA GRC Aero-Acoustic Propulsion Laboratory (AAPL). The DART is a cost-efficient testbed for the study of core-noise physics and mitigation. Acoustic data were simultaneously acquired using the AAPL overhead microphone array in the engine aft-quadrant farfield, a single midfield microphone, and two infinite-tube-probe sensors for unsteady pressures at the core-nozzle exit. The data are here examined on an 1/3-octave basis as a first step in extending and improving core-noise prediction capability.
The quasi-continuous component of the magnetospheric noise observed by Imp 6, lying between 30 and 110 kHz, often exhibits a low-frequency cutoff when the spacecraft is in the interplanetary medium or the magnetosheath. A hypothesis is considered in which this low-frequency cutoff, f-co, is caused by overdense plasma situated somewhere along the noise-source-to-satellite path. The plasma is assumed to have a plasma frequency approximately equal to f-co, thus cutting off propagation below f-co.
Significant progress continues to be made with noise reduction for turbofan engines. NASA has conducted and sponsored research aimed at reducing noise from commercial aircraft. Since it takes many years for technologies to be developed and implemented, it is important to have aggressive technology goals that lead the target entry into service dates. Engine noise is one of the major contributors to the overall sound levels as aircraft operate near airports. Turbofan engines are commonly used on commercial transports due to their advantage for higher performance and lower noise. The noise reduction comes from combinations of changes to the engine cycle parameters and low noise design features. In this paper, an overview of major accomplishments from recent NASA research programs for engine noise will be given.
Optimal linear filter for continuous time-varying dynamic system, using measurements containing additive white noise
Abstract Significant imbalances in terrestrial water storage (TWS) and severe drought have been observed around the world as a consequence of climate changes. Improving our ability to monitor TWS and drought is critical for water‐resource management and water‐deficit estimation. We use continuous seismic ambient noise to monitor temporal evolution of near‐surface seismic velocity, dv / v , in central Oklahoma from 2013 to 2022. The derived dv / v is found to be negatively correlated with gravitational measurements and groundwater depths, showing the impact of groundwater storage on seismic velocities. The hydrological effects involving droughts and recharge of groundwater occur on a multi‐year time scale and dominate the overall derived velocity changes. The thermoelastic response to atmospheric temperature variations occurs primarily on a yearly timescale and dominates the superposed seasonal velocity changes in this study. The occurrences of droughts appear simultaneously with local peaks of dv / v , demonstrating the sensitivity of near‐surface seismic velocities to droughts.
Three categories of rotor noise (discrete frequency noise, impulsive noise, and broadband noise) are described and a study made of broadband noise is reported. Broadband noise has a continuous spectrum and is caused by disturbances which are not precisely repeated at each blade revolution but are basically due to some sort of turbulence-blade interactions. Source mechanisms include: inflow turbulence noise, boundary layer trailing edge noise, tip vortex noise, and several uncommon mechanisms. Broadband noise analyses are reviewed and calculations based on various analyses are compared to each other and to some available experimental data. Several satisfactory analyses are discussed and their limitations are delineated. Twenty-two references are cited.
Abstract Continuous quantum error correction has been found to have certain advantages over discrete quantum error correction, such as a reduction in hardware resources and the elimination of error mechanisms introduced by having entangling gates and ancilla qubits. We propose a machine learning algorithm for continuous quantum error correction that is based on the use of a recurrent neural network to identify bit-flip errors from continuous noisy syndrome measurements. The algorithm is designed to operate on measurement signals deviating from the ideal behavior in which the mean value corresponds to a code syndrome value and the measurement has white noise. We analyze continuous measurements taken from a superconducting architecture using three transmon qubits to identify three significant practical examples of non-ideal behavior, namely auto-correlation at temporal short lags, transient syndrome dynamics after each bit-flip, and drift in the steady-state syndrome values over the course of many experiments. Based on these real-world imperfections, we generate synthetic measurement signals from which to train the recurrent neural network, and then test its proficiency when implementing active error correction, comparing this with a traditional double threshold scheme and a discrete Bayesian classifier. The results show that our machine learning protocol is able to outperform the double threshold protocol across all tests, achieving a final state fidelity comparable to the discrete Bayesian classifier.
Observed Doppler noise (rms phase jitter) from the 1976 solar conjunctions of the Helios 1 and 2 and the Pioneer 10 and 11 spacecraft was processed with a recently developed Doppler noise model ISEDB. Good agreement is obtained between the observed data and the model. Correlation is shown between deviations from the ISEDB model and sunspot activity, but it is insufficient to be modeled. Correlation is also shown between ISEDB model deviations for (spacecraft) signal paths on the same side of the sun.
SUMMARY We examine the cyclic amplitude variation of seismic noise recorded by continuous three-component broad-band seismic data with durations spanning 91–713 d (2008–2011) from three different networks: Anza seismic network, IDA network and the transportable seismic array. These stations surround the San Jacinto Fault Zone (SJFZ) in southern California. We find the seismic noise amplitudes exhibit a cyclical variation between 0.3 and 7.2 Hz. The high-frequency (≥0.9 Hz) noise variations can be linked to human activity and are not a concern. Our primary interest is signals in the low frequencies (0.3–0.9 Hz), where the seismic noise is modulated by semi-diurnal tidal mode M2. These long-period (low-frequency) variations of seismic noise can be attributed to a temporal change of the ocean waves breaking at the shoreline, driven by ocean tidal loading. We focus on the M2 variation of seismic noise at f = 0.6 Hz, travelling distances of ∼92 km through the crust from offshore California to the inland Anza, California, region. Relative to the shoreline station, data from the inland stations show a phase lag of ∼ –12°, which we attribute to the cyclic change in M2 that can alter crustal seismic attenuation. We also find that for mode M2 at 0.6 Hz, the amplitude variations of the seismic quality factor (Q) depend on azimuth and varies from 0.22 per cent (southeast to northwest) to 1.28 per cent (northeast to southwest) with Q = 25 for Rayleigh waves. We propose the direction dependence of the Q variation at 0.6 Hz reflects the preferred orientation of subfaults parallel to the main faulting defined by the primarily N45°W strike of the SJFZ.
Ab initio molecular dynamics (AIMD) is a valuable technique for studying molecules and materials at finite temperatures where the nuclei evolve on potential energy surfaces obtained from accurate electronic structure calculations. In this work, we present an approach to running AIMD simulations on noisy intermediate-scale quantum (NISQ)-era quantum computers. The electronic energies are calculated on a quantum computer using the variational quantum eigensolver (VQE) method. Algorithms for computation of analytical gradients entirely on a quantum computer require quantum fault-tolerant hardware, which is beyond NISQ-era. Therefore, we compute the energy gradients numerically using finite differences, the Hellmann-Feynman theorem, and a correlated sampling technique. This method only requires additional classical calculations of electron integrals for each degree of freedom without any additional computations on a quantum computer beyond the initial VQE run. As a proof of concept, AIMD simulations are demonstrated for the H-2 molecule on IBM quantum devices. In addition, we demonstrate the validity of the method for larger molecules using full configuration interaction wave functions. As quantum hardware and noise mitigation techniques continue to improve, the method can be utilized for studying larger molecular systems.
Advanced satellite sensors are tasked with improving global observations of the Earth's atmosphere, clouds, and surface to enable enhancements in weather prediction, climate monitoring capability, and environmental change detection. Achieving such an improvement in geophysical information inferred from these observations requires optimal usage of data from current systems as well as instrument system enhancements for future sensors. This presentation addresses results of tradeoff studies evaluating the impact of spectral resolution, spectral coverage, instrument noise, and a priori knowledge on remote sensing system information content, with a specific emphasis on thermodynamic state and trace species information obtainable from advanced atmospheric sounders. Particular attention will be devoted toward information achievable from the Atmospheric InfraRed Sounder (AIRS) on the NASA EOS Aqua satellite in orbit since 2002, the Infrared Atmospheric Sounding Interferometer (IASI) aboard MetOp-A since 2006, and the Cross-track Infrared Sounder (CrIS) instrument to fly aboard the NPP and JPSS series of satellites expected to begin in late 2011. While all of these systems cover nearly the same infrared spectral extent, they have very different number of channels, instrument line shapes, coverage continuity, and instrument noise. AIRS is a grating spectrometer having 2378 discrete spectral channels ranging from about 0.4 to 2.2/cm resolution; IASI is a Michelson interferometer with 8461 uniformly-spaced spectral channels of 0.5/cm (apodized) resolution; and CrIS is a Michelson interferometer having 1305 spectral channels of 0.625, 1.250, and 2.50/cm (unapodized) spectral resolution, respectively, over its three continuous but non-overlapping bands. Results of tradeoff studies showing information content sensitivity to assumed measurement system characteristics will be presented.
Manipulating the quantum noise of continuous-wave lasers through squeezing has reshaped optical interferometry. However, progress in optical frequency comb interferometry with pulsed squeezed sources has been limited, despite the role of frequency combs in ultraprecise optical metrology. Here, we introduce a new time-domain approach to characterizing squeezed femtosecond light pulses using dual-comb interferometry. Time-domain interferograms are generated via multiheterodyne beating between the modes of a Kerr soliton-squeezed frequency comb and a coherent state comb. The interferogram noise reveals phase-dependent squeezing and antisqueezing, dipping as much as 3.8 ± 0.2 dB below the shot noise level at alternating zero crossings. We model this nonstationary quantum noise as a periodic optical displacement of the squeezed comb by the coherent comb. These results support a route toward quantum-enhanced dual-comb timing applications and high-speed quantum state tomography with dual-comb interferometers.