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At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Probing axionlike particles with multimessenger observations of neutron star mergers

Axion-like particles (ALPs) can be copiously produced in binary neutron star (BNS) mergers through nucleon-nucleon bremsstrahlung if the ALP-nucleon couplings 𝑔 𝑎⁢𝑁 are sizable. The ALP-photon coupling 𝑔 𝑎⁢𝛾 may trigger conversions of ultralight ALPs into photons in the magnetic fields of the merger remnant and of the Milky Way. This effect would lead to a potentially observable short gamma-ray signal, in coincidence with the gravitational-wave signal produced during the merging process. This event could be detected through multimessenger observation of BNS mergers employing the synergy between gravitational-wave detectors and gamma-ray telescopes. Here, we study the sensitivity of current and proposed MeV gamma-ray experiments to detect such a signal. As an explicit example, we consider ALP couplings related as in the Kim-Shifman-Vainshtein-Zakharov axion model, and show that in this case the proposed instruments can reach a sensitivity down to 𝑔 𝑎⁢𝛾 ≳ few ×10 −13 GeV −1 for 𝑚 𝑎 ≲ 10 −9 eV, comparable with the SN 1987A limit.

Axion-like particles↗
DOE OSTI2020

Ultrafast, multiphoton-pump, multiphoton-probe spectroscopy

Methods for pump-probe spectroscopy are provided. In an embodiment, such a method comprises directing pump light having a frequency ωpump at a location in a sample to excite a transition between two quantum states of a target entity in the sample, directing probe light at the location to generate a coherent output signal having a frequency ωoutput and a wavevector koutput, and detecting the output signal as the probe light is scanned over a range of frequencies. In the method, either the transition excited by the pump light is a multiphoton transition corresponding to a frequency difference of n*ωpump, wherein n≥2; or the probe light is a set of m coherent light pulses, each coherent light pulse having a frequency ωm and a wavevector km, wherein m≥2; or both. Systems for carrying out the methods are also provided.

Morrow, Darien James↗
DOE OSTI2020

The promise of optical NMR spectroscopy for experimental aqueous geochemistry

Here, we discuss new quantum technologies being adapted to detect extraordinarily small magnetic fields. The signals are derived from the stimulated emission of light from single-atom defects in diamonds. The intensity of light reports the spin state of the electrons in the color center. The physics is relevant to geochemists because it points to a means of conducting NMR experiments on solutions in diamond-anvil cells. Because the method is so sensitive, it can detect signals in subnanoliter volumes, making work at elevated temperatures and pressures possible, and also on solutions that are dangerous in larger volumes.

58 GEOSCIENCES↗
NASA NTRS2020

EARLINET evaluation of the CATS Level 2 aerosol backscatter coefficient product

We present the evaluation activity of the European Aerosol Research Lidar Network (EARLINET) for the quantitative assessment of the Level 2 aerosol backscatter coefficient product derived by the Cloud-Aerosol Transport System (CATS) aboard the International Space Station (ISS; Rodier et al., 2015). The study employs correlative CATS and EARLINET backscatter measurements within a 50 km distance between the ground station and the ISS overpass and as close in time as possible, typically with the starting time or stopping time of the EARLINET performed measurement time window within 90 min of the ISS overpass, for the period from February 2015 to September 2016. The results demonstrate the good agreement of the CATS Level 2 backscatter coefficient and EARLINET. Three ISS overpasses close to the EARLINET stations of Leipzig, Germany; Évora, Portugal; and Dushanbe, Tajikistan, are analyzed here to demonstrate the performance of the CATS lidar system under different conditions. The results show that under cloud-free, relative homogeneous aerosol conditions, CATS is in good agreement with EARLINET, independent of daytime and nighttime conditions. CATS low negative biases are observed, partially attributed to the deficiency of lidar systems to detect tenuous aerosol layers of backscatter signal below the minimum detection thresholds; these are biases which may lead to systematic deviations and slight underestimations of the total aerosol optical depth (AOD) in climate studies. In addition, CATS misclassification of aerosol layers as clouds, and vice versa, in cases of coexistent and/or adjacent aerosol and cloud features, occasionally leads to non-representative, unrealistic, and cloud-contaminated aerosol profiles. Regarding solar illumination conditions, low negative biases in CATS backscatter coefficient profiles, of the order of 6.1 %, indicate the good nighttime performance of CATS. During daytime, a reduced signal-to-noise ratio by solar background illumination prevents retrievals of weakly scattering atmospheric layers that would otherwise be detectable during nighttime, leading to higher negative biases, of the order of 22.3 %.

Emmanouil Proestakis↗
DOE OSTI2020

Systems, methods and computer program products for self-tuning sensor data processing

Systems and methods are disclosed that include tools that utilize Dynamic Detector Tuning (DDT) software that identifies near-optimal parameter settings for each sensor using a neuro-dynamic programming (reinforcement learning) paradigm. DDT adapts parameter values to the current state of the environment by leveraging cooperation within a neighborhood of sensors. The key metric that guides the dynamic tuning is consistency of each sensor with its nearest neighbors: parameters are automatically adjusted on a per station basis to be more or less sensitive to produce consistent agreement of detections in its neighborhood. The DDT algorithm adapts in near real-time to changing conditions in an attempt to automatically self-tune a signal detector to identify (detect) only signals from events of interest. The disclosed systems and methods reduce the number of missed legitimate detections and the number of false detections, resulting in improved event detection.

Draelos, Timothy J.↗
NASA NTRS1992

Signal processing for airborne doppler radar detection of hazardous wind shear as applied to NASA 1991 radar flight experiment data

Radar data collected during the 1991 NASA flight tests have been selectively analyzed to support research directed at developing both improved as well as new algorithms for detecting hazardous low-altitude windshear. Analysis of aircraft attitude data from several flights indicated that platform stability bandwidths were small compared to the data rate bandwidths which should support an assumption that radar returns can be treated as short time stationary. Various approaches at detection of weather returns in the presence of ground clutter are being investigated. Non-coventional clutter rejection through spectrum mode tracking and classification algorithms is a subject of continuing research. Based upon autoregressive modeling of the radar return time sequence, this approach may offer an alternative to overcome errors in conventional pulse-pair estimates. Adaptive filtering is being evaluated as a means of rejecting clutter with emphasis on low signal-to-clutter ratio situations, particularly in the presence of discrete clutter interference. An analysis of out-of-range clutter returns is included to illustrate effects of ground clutter interference due to range aliasing for aircraft on final approach. Data are presented to indicate how aircraft groundspeed might be corrected from the radar data as well as point to an observed problem of groundspeed estimate bias variation with radar antenna scan angle. A description of how recorded clutter return data are mixed with simulated weather returns is included. This enables the researcher to run controlled experiments to test signal processing algorithms. In the summary research efforts involving improved modelling of radar ground clutter returns and a Bayesian approach at hazard factor estimation are mentioned.

Baxa, Ernest G., Jr.↗
DOE OSTI2025

Detecting anomalous SRF cavity behavior with unsupervised learning

We present an unsupervised learning framework for detecting anomalous superconducting radio-frequency (SRF) cavity behavior at the Continuous Electron Beam Accelerator Facility (CEBAF), emphasizing its initial performance and effectiveness. Key to the system’s success was the development of data acquisition systems (DAQs) that capture fast-sampled, information-rich signals, essential for detecting transient effects. The approach involves creating daily cavity-specific models using principal component analysis to handle variations in rf signal behavior and mitigate performance degradation from data drift. This unsupervised method eliminates the need for expensive labeling by continuously updating models with recent data. Deployed and operational for 3 months before a scheduled shutdown, the system successfully identified several issues with DAQ signals, confirming its effectiveness. Despite access to only a fraction of CEBAF’s SRF cavity signals, the framework efficiently detected several instances requiring intervention, demonstrating a significant improvement over traditional, labor-intensive methods of manual plot inspection. Published by the American Physical Society 2025

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Gravitational-wave and Gravitational-wave Memory Signatures of Core-collapse Supernovae

Abstract In this paper, we calculate the energy, signal-to-noise ratio (SNR), detection range, and angular anisotropy of the matter, matter memory, and neutrino memory gravitational-wave (GW) signatures of 21 three-dimensional initially nonrotating core-collapse supernova (CCSN) models carried to late times. We find that inferred energy, SNR, and detection range are angle-dependent quantities, and that the spread of possible energy, signal to noise, and detection ranges across all viewing angles generally increases with progenitor mass. When examining the low-frequency matter memory and neutrino memory components of the signal, we find that the neutrino memory is the most detectable component of a CCSN GW signal, and that DECIGO is best equipped to detect both matter memory and neutrino memory. Moreover, we find that the polarization angle between the h + and h × strains serves as a unique identifier of matter and neutrino memory. Finally, we develop a Galactic density- and stellar mass-weighted formalism to calculate the rate at which we can expect to detect CCSN GW signals with the Advanced Laser Interferometer Gravitational-Wave Observatory (aLIGO). When considering only the matter component of the signal, the aLIGO detection rate is around 65% of the total Galactic supernova rate, but increases to 90% when incorporating the neutrino memory component. We find that all future detectors (Einstein Telescope, Cosmic Explorer, DECIGO) will be able to detect CCSN GW signals from the entire Galaxy, and for the higher-mass progenitors even into the Local Group of galaxies.

Choi, Lyla (ORCID:0000000153860133)↗
NASA NTRS1992

Fault detection and bypass in a sequence information signal processor

The invention comprises a plurality of scan registers, each such register respectively associated with a processor element; an on-chip comparator, encoder and fault bypass register. Each scan register generates a unitary signal the logic state of which depends on the correctness of the input from the previous processor in the systolic array. These unitary signals are input to a common comparator which generates an output indicating whether or not an error has occurred. These unitary signals are also input to an encoder which identifies the location of any fault detected so that an appropriate multiplexer can be switched to bypass the faulty processor element. Input scan data can be readily programmed to fully exercise all of the processor elements so that no fault can remain undetected.

Peterson, John C.↗
NASA NTRS2021

All-sky search in early O3 LIGO data for continuous gravitational-wave signals from unknown neutron stars in binary systems

Rapidly spinning neutron stars are promising sources of continuous gravitational waves. Detecting such a signal would allow probing of the physical properties of matter under extreme conditions. A significant fraction of the known pulsar population belongs to binary systems. Searching for unknown neutron stars in binary systems requires specialized algorithms to address unknown orbital frequency modulations. We present a search for continuous gravitational waves emitted by neutron stars in binary systems in early data from the third observing run of the Advanced LIGO and Advanced Virgo detectors using the semicoherent, GPU-accelerated, binaryskyhough pipeline. The search analyzes the most sensitive frequency band of the LIGO detectors, 50–300 Hz. Binary orbital parameters are split into four regions, comprising orbital periods of three to 45 days and projected semimajor axes of two to 40 light seconds. No detections are reported. We estimate the sensitivity of the search using simulated continuous wave signals, achieving the most sensitive results to date across the analyzed parameter space.

Gravitation↗
NASA NTRS1998

Effectiveness of an Expert System for Astronaut Assistance on a Sleep Experiment

Principal Investigator-in-a-Box ([PI]) is an expert system designed to train and assist astronauts with the performance of an experiment outside their field of expertise, particularly when contact with the Principal Investigators on the ground is limited or impossible. In the current case, [PI] was designed to assist with the calibration and troubleshooting procedures of the Neurolab Sleep and Respiration Experiment during the pre-sleep period of no ground contact. It displays physiological signals in real time during the pre-sleep instrumentation period, and alerts the astronauts when a poor signal quality is detected. Results of the first study indicated a beneficial effect of [PI] and training in reducing anomaly detection time and the number of undetected anomalies. For the in-flight performance, excluding the saturated signals, the expert system had an 84.2% detection accuracy, and the questionnaires filled out by the astronauts showed positive crew reactions to the expert system.

Heher, Dennis↗
NASA NTRS1991

Coincidence probabilities for spacecraft gravitational wave experiments - Massive coalescing binaries

Massive coalescing binary systems are candidate sources of gravitational radiation in the millihertz frequency band accessible to spacecraft Doppler tracking experiments. This paper discusses signal processing and detection probability for waves from coalescing binaries in the regime where the signal frequency increases linearly with time, i.e., 'chirp' signals. Using known noise statistics, thresholds with given false alarm probabilities are established for one- and two-spacecraft experiments. Given the threshold, the detection probability is calculated as a function of gravitational wave amplitude for both one- and two-spacecraft experiments, assuming random polarization states and under various assumptions about wave directions. This allows quantitative statements about the detection efficiency of these experiments and the utility of coincidence experiments. In particular, coincidence probabilities for two-spacecraft experiments are insensitive to the angle between the directions to the two spacecraft, indicating that near-optical experiments can be done without constraints on spacecraft trajectories.

Tinto, Massimo↗
DOE OSTI2024

Improving Robustness of Spectrogram Classifiers with Neural Stochastic Differential Equations

Signal analysis and classification is fraught with high levels of noise and perturbation. Computer-vision-based deep learning models applied to spectrograms have proven useful in the field of signal classification and detection; however, these methods aren't designed to handle the low signal-to-noise ratios inherent within non-vision signal processing tasks. While they are powerful, they are currently not the method of choice in the inherently noisy and dynamic critical infrastructure domain, such as smart-grid sensing, anomaly detection, and non-intrusive load monitoring. Currently, these models can be brittle, which makes them susceptible to noisy input. This also means they have sub-optimal stability of explanation outputs. Experts and technicians using these models to make decisions in real world scenarios need assurance that a model is performing as it is supposed to. The classification or prediction outputs it generates should be sound and grounded, not likely to change in the presence of shifting noise landscapes. In this work, we explore the idea of Neural Stochastic Differential Equations (NSDE's) to improve the robustness of models trained to classify time series data and the effect of NSDE's on the explainability of outputs. We then test the effectiveness of these approaches by applying them to a non-intrusive load monitoring (NILM) dataset that consists of simulated harmonic signals injected into a real building.

Brogan, Joel↗
NASA NTRS2000

Information Theoretic Extraction of EEG Features for Monitoring Subject Attention

The goal of this project was to test the applicability of information theoretic learning (feasibility study) to develop new brain computer interfaces (BCI). The difficulty to BCI comes from several aspects: (1) the effective data collection of signals related to cognition; (2) the preprocessing of these signals to extract the relevant information; (3) the pattern recognition methodology to detect reliably the signals related to cognitive states. We only addressed the two last aspects in this research. We started by evaluating an information theoretic measure of distance (Bhattacharyya distance) for BCI performance with good predictive results. We also compared several features to detect the presence of event related desynchronization (ERD) and synchronization (ERS), and concluded that at least for now the bandpass filtering is the best compromise between simplicity and performance. Finally, we implemented several classifiers for temporal - pattern recognition. We found out that the performance of temporal classifiers is superior to static classifiers but not by much. We conclude by stating that the future of BCI should be found in alternate approaches to sense, collect and process the signals created by populations of neurons. Towards this goal, cross-disciplinary teams of neuroscientists and engineers should be funded to approach BCIs from a much more principled view point.

Principe, Jose C.↗
DOE OSTI2023

Truncated non-linear interferometer-based sensor system

A truncated non-linear interferometer-based sensor system includes an input that receives an optical beam and a non-linear amplifier that generates a probe beam and a conjugate beam from the optical beam. The system's local oscillators are related to the probe beam and the conjugate beam. The system includes a sensor that transduces an input with the probe beam and the conjugate beam. The transduction detects changes in the phase of each of the probe beam and the conjugate beam. The system's phase sensitive detectors detect phase modulations between the respective local oscillators, the probe beam, and the conjugate beam and outputs phase signals based on detected phase modulations. The system measures phase signals indicative of the sensor's input resulting from a sum or difference of the phase signals. The measurement exhibits a quantum noise reduction in an intensity difference, a phase sum, or an amplitude difference quadrature.

47 OTHER INSTRUMENTATION↗
NASA NTRS1981

Wedge-and-strip anodes for centroid-finding position-sensitive photon and particle detectors

The paper examines geometries employing position-dependent charge partitioning to obtain a two-dimensional position signal from each detected photon or particle. Requiring three or four anode electrodes and signal paths, images have little distortion and resolution is not limited by thermal noise. An analysis of the geometrical image nonlinearity between event centroid location and the charge partition ratios is presented. In addition, fabrication and testing of two wedge-and-strip anode systems are discussed. Images obtained with EUV radiation and microchannel plates verify the predicted performance, with further resolution improvements achieved by adopting low noise signal circuitry. Also discussed are the designs of practical X-ray, EUV, and charged particle image systems.

Martin, C.↗
NASA NTRS1994

Crossflow instability control on a swept-wing: Preliminary studies

The pressure distribution on a swept wing causes the streamlines at the edge of the boundary layer to be curved. This pressure gradient normal to the external streamline creates a velocity component normal to the external streamline within the boundary layer which is referred to as the crossflow velocity. Because the crossflow velocity profile perpendicular to the wing surface has an inflection point, the profile is unstable. The stationary instability mode takes the form of crossflow vortices. Under these conditions, the boundary layer on the wing is extremely unstable and transition to turbulent flow takes place much closer to the leading edge of the wing than it would on an unswept wing. Higher skin friction drag is associated with turbulent flow, and so better aircraft performance could be obtained if the crossflow could be eliminated One method of controlling crossflow that is being investigated is boundary-layer suction. An extensive airfoil suction experiment in the 8 feet Transonic Pressure Tunnel (TPT) at NASA Langley Research Center will begin late in 1994. Because of the size, complexity, and expense associated with this test, a number of 'risk-reduction' tests are currently being conducted. The 20 x 28 in. Shear Flow Control Tunnel at NASA Langley is being used for some of these tests. Prior to the summer of 1994, a flat plate with a swept leading edge was installed in the 20 x 28 in. tunnel, with a displacement body mounted on the tunnel ceiling that created a pressure distribution on the plate similar to the pressure distribution on a swept wing. The flow over the plate was investigated during the summer of 1994 using a laser Doppler velocimeter (LDV) system. The LDV measurements indicated the possible presence of multiple disturbance modes, a rarely-seen phenomena since, in most tests, one disturbance mode dominates. The possible existence of multiple disturbance modes in the flat plate boundary layer, however, means that the flow in the 20 x 28 in. tunnel is of interest itself, and will be investigated more thoroughly in the future. With a view to these investigations, the boundary layer traverse mechanism in the 20 x 28 in. tunnel was modified to improve its performance, and strain gauges were mounted on the traverse in order to monitor its deflection during a test. Other preliminary work conducted in the 20 x 28 in. tunnel included the use of an infrared camera system. Previous work with this system showed that transition indeed could be detected, but the signal produced by the crossflow vortices was too weak to be detected. It was hoped that spraying the flat plate with naphthalene would augment the heat transfer associated with the crossflow vortices so that they would show up in a IR image; however, experiments showed that this would not work. Another set of tests was conducted in the 20 x 28 in. tunnel to determine the tripping requirements for a set of airfoil-shaped struts that will be used in the 8 feet TPT experiment. Since the Reynolds number associated with these struts is small, a laminar boundary layer would separate early, causing large fluctuations in the flow field. A turbulent boundary layer would remain attached further back, but tripping from laminar to turbulent flow at low Reynolds number is very difficult. However, trip strip configurations were found that should effectively trip the boundary layer at the required conditions. Currently underway is an investigation of the data acquisition requirements for the 8 feet TPT experiment, with the purpose of the finding the minimum amount of data needed to characterize sufficiently the swept-wing boundary layer. This study is being conducted using a numerically generated data set.

Bridges, David H.↗
NASA NTRS1999

Chemometric analysis for extraction of individual fluorescence spectrum and lifetimes from a target mixture

The present invention is a system for chemometric analysis for the extraction of the individual component fluorescence spectra and fluorescence lifetimes from a target mixture. The present invention combines a processor with an apparatus for generating an excitation signal to transmit at a target mixture and an apparatus for detecting the emitted signal from the target mixture. The present invention extracts the individual fluorescence spectrum and fluorescence lifetime measurements from the frequency and wavelength data acquired from the emitted signal. The present invention uses an iterative solution that first requires the initialization of several decision variables and the initial approximation determinations of intermediate matrices. The iterative solution compares the decision variables for convergence to see if further approximation determinations are necessary. If the solution converges, the present invention then determines the reduced best fit error for the analysis of the individual fluorescence lifetime and the fluorescence spectrum before extracting the individual fluorescence lifetime and fluorescence spectrum from the emitted signal of the target mixture.

Hallidy, William H.↗