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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Detection prospects for the second-order weak decays of 124 Xe in multi-tonne xenon time projection chambers

We investigate the detection prospects for two-neutrino and neutrinoless second-order weak decays of 124 Xe – double-electron capture (0/2νECEC), electron capture with positron emission (0/2νECβ + ) and double-positron emission (0/2νβ + β + ) – in multi-tonne xenon time projection chambers. We simulate the decays in a liquid xenon medium and develop a reconstruction algorithm which uses the multi-particle coincidence in these decays to separate signal from background. This is used to compute the expected detection efficiencies as a function of position resolution and energy threshold for planned experiments. In addition, we consider an exhaustive list of possible background sources and find that they are either negligible in rate or can be greatly reduced using our topological reconstruction criteria. In particular, we draw two conclusions: First, with a theoretical half-life of $T^{2νECβ^+}_{1/2}$= (1.7 ± 0.6) ∙10 23 year, the 2νECβ + decay of 124 Xe will likely be detected in upcoming Dark Matter experiments (e.g. XENONnT or LZ), and their major background will be γ-rays from detector construction materials. Second, searches for the 0νECβ + decay mode will likely be background-free, and new parameter space may be within reach. To this end we investigate two different scenarios of existing experimental constraints on the effective neutrino mass. The necessary 500 kg-year exposure of 124 Xe could be achieved by the baseline design of the DARWIN observatory, or by extracting and using the 124 Xe from the tailings of the nEXO experiment. We demonstrate how a combination of 124 Xe results with those from 0νβ - β - searches in 136 Xe could help to identify the neutrinoless decay mechanism.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Observation of four-top-quark production in the multilepton final state with the ATLAS detector

This paper presents the observation of four-top-quark ($t$$\overline{t}$$t$$\overline{t}$) production in proton-proton collisions at the LHC. The analysis is performed using an integrated luminosity of 140 fb -1 at a centre-of-mass energy of 13 TeV collected using the ATLAS detector. Events containing two leptons with the same electric charge or at least three leptons (electrons or muons) are selected. Event kinematics are used to separate signal from background through a multivariate discriminant, and dedicated control regions are used to constrain the dominant backgrounds. The observed (expected) significance of the measured $t$$\overline{t}$$t$$\overline{t}$ signal with respect to the standard model (SM) background-only hypothesis is 6.1 (4.3) standard deviations. The $t$$\overline{t}$$t$$\overline{t}$ production cross section is measured to be ${22.5}^{+6.6}_{-5.5}$, consistent with the SM prediction of 12.0 ± 2.4 fb within 1.8 standard deviations. Data are also used to set limits on the three-top-quark production cross section, being an irreducible background not measured previously, and to constrain the top-Higgs Yukawa coupling and effective field theory operator coefficients that affect $t$$\overline{t}$$t$$\overline{t}$ production.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Application of deep learning to single-shot gas-phase laser-induced breakdown spectroscopy

Single-shot fs laser-induced breakdown spectroscopy (LIBS) has the potential to capture ns-scale electrode desorption phenomena in pulsed power fusion drivers. However, the successful implementation of the diagnostic for this purpose is challenging, as it requires interpreting single-shot measurements collected from low-density gas mixtures. In this work, we demonstrate the efficacy of a Bayesian-optimized convolutional neural network (CNN) to interpret these measurements. We generated 256 distinct measurement conditions at relevant gas pressures ranging from 80–530 mTorr by mixing 100–250 sccm H 2 and 50–200 sccm CH 4 in increments of 10 sccm. Despite the considerable overlap between signals separated by 20 sccm, the CNN is able to predict the H 2 flow rate with a root-mean-square error (RMSE) of 15.9 sccm and the CH 4 flow rate with an RMSE of 12.0 sccm. The average relative prediction error is <9% for each gas and largely remains below or near 10%.

Brown, Nathan Parnell [Sandia National Lab. (SNL-N↗
DOE OSTI2025

Using Neural Networks for Low Energy Reconstruction and Neutron Identification in the MicroBooNE LArTPC

Identifying and reconstructing final-state neutrons from neutrino interactions in Liquid Argon Time Projection Chambers (LArTPCs) will enhance future oscillation measurements by recovering missing energy and improving neutrino interaction channel identification. However, neutrons are challenging to reconstruct as the majority leave only small, isolated charge signatures known as blips. Here we present initial efforts to identify neutrons in the MicroBooNE LArTPC with low energy protons from neutron-argon inelastic interactions that present as blips below the traditional tracking threshold in the TPC. Unlike for tracks, there is no algorithmic method to determine direction for blips since they span only a few wires. Therefore, we developed and trained a Recurrent Neural Network (RNN) to reconstruct the directionality of proton-induced blips, allowing us to separate signal from background by selecting blips that point back to the neutrino vertex. The model achieves a preliminary average angular resolution of 17 degrees when tested on a simulated sample of protons over 6 MeV in kinetic energy. This novel tool will enhance neutron detection in LArTPCs and expand a broad range of other low-energy physics searches such as for solar and supernova neutrinos.

Silva, Liani Isabel [Unlisted, US]↗
NASA NTRS1975

Recent developments in density, temperature and momentum fluctuation measurement

Attention is drawn to recent advancements in the fluctuating line-reversal temperature measurement, the development of the two-dimensional drag-sensing probe into a three-dimensional drag-sensing probe, and the fluctuating density gradient cross beam Schlieren technique. An experimental apparatus is explained whereby the temperature fluctuation in a pulsating air-fuel ratio Bunsen burner is measured by means of sodium D-line reversal methods with a new photoelectric circuit to obtain both fluctuating and mean temperature data. The three-D drag probe is made possible by a newly invented differential and total magnetic sensing system that separates signals due to three orthogonal movements so that the vectorial momentum fluctuation can be measured. In the case of the Schlieren technique, the effect of anisotropic density gradients with respect to the angle between the polarization plane and the knife edge of a laser Schlieren system is studied.

Battle, T. M.↗
NASA NTRS1977

Self-scanned anode array with a microchannel plate electron multiplier - The SSANACON

A photoelectron counting detector utilizing a 128-element linear self-scanned anode array to collect the output of a dual microchannel plate electron multiplier is described. The operation of the detector, its spatial resolution and detection efficiency, and radiation behavior are discussed. The low-noise detector was developed for the Mariner Jupiter/Saturn mission UV spectrometer, and offers a large dynamic range and count rate of 0.003 per anode-sec. It can measure simultaneously two spatially separated signals differing by more than six orders of magnitude in count rate.

Broadfoot, A. L.↗
NASA NTRS1979

Efficient dichroic plate for microwaves

Signal separator for dual-frequency antennas has interlaced crossed slots, or dipole elements. Plate reflects or transmits more efficiently than conventionally-designed microwave dichroic plates in which elements are not interlaced. Interlaced plate also increases bandwidth of dual-frequency antenna in which it is used.

Wise, T. E.↗
NASA NTRS1990

The 27-28 October 1986 FIRE IFO cirrus case study - Cloud optical properties determined by High Spectral Resolution Lidar

The High Spectral Resolution Lidar (HSRL) was operated from a roof-top site in Madison, Wisconsin. The transmitter configuration used to acquire the case study data produces about 50 mW of ouput power and achieved eye-safe, direct optical depth, and backscatter cross section measurements with 10 min averaging times. A new continuously pumped, injection seeded, frequency doubled Nd:YAG laser transmitter reduces time-averaging constraints by a factor of about 10, while improving the aerosol-molecular signal separation capabilities and wavelength stability of the instrument. The cirrus cloud backscatter-phase functions have been determined for the October 27-28, 1986 segment of the HSRL FIRE dataset. Features exhibiting backscatter cross sections ranging over four orders of magnitude have been observed within this 33 h period. During this period, cirrus clouds were observed with optical thickness ranging from 0.01 to 1.4. The altitude relationship between cloud top and bottom boundaries and the optical center of the cloud is influenced by the type of formation observed.

Grund, C. J.↗
NASA NTRS1996

Wide Angle, Single Screen, Gridded Square-Loop Frequency Selective Surface for Diplexing Two Closely Separated Frequency Bands

The design and performance of a wide angle, single screen, frequency selective surface (FSS) with gridded square-loop path elements are described for diplexing closely separated signal bands, for example, X- and Ku-band signals in an Orbiting Very Long Baseline Interferometer (OVLBI) earth station reflector antenna system, as well as other applications such as military and commercial communications via satellites. Excellent agreement is obtained between the predicted and measured results of this FSS design using the gridded square-loop patch elements sandwiched between 0.0889 cm thick tetrafluoroethylene fluorocarbon polymer (PTFE) slabs. Resonant frequency drift is reduced by 1 GHz with an incidence angle from 0 deg normal to 40 deg from normal.

Wu, Te-Kao↗
NASA NTRS2002

Microgravity Compatible Reagentless Instrumentation for Detection of Dissolved Organic Acids and Alcohols in Potable Water

The Organic Acid and Alcohol Monitor (OAAM) program has resulted in the successful development of a computer controlled prototype analyzer capable of accurately determining aqueous organic acids and primary alcohol concentrations over a large dynamic range with high sensitivity. Formic, acetic, and propionic acid were accurately determined at concentrations as low as 5 to 10 micrograms/L in under 20 minutes, or as high as 10 to 20 mg/L in under 30 minutes. Methanol, ethanol, and propanol were determined at concentrations as low as 20 to 100 micrograms/L, or as high as 10 mg/L in under 30 minutes. Importantly for space based application, the OAAM requires no reagents or hazardous chemicals to perform these analyses needing only power, water, and CO2 free purge gas. The OAAM utilized two membrane processes to segregate organic acids from interfering ions. The organic acid concentration was then determined based upon the conductiometric signal. Separation of individual organic acids was accomplished using a chromatographic column. Alcohols are determined in a similar manner after conversion to organic acids by sequential biocatalytic and catalytic oxidation steps. The OAAM was designed to allow the early diagnosis of under performing or failing sub-systems within the Water Recovery System (WRS) baselined for the International Space Station (ISS). To achieve this goal, several new technologies were developed over the course of the OAAM program.

Akse, James R.↗
DOE OSTI2022

Kinematic Variables and Feature Engineering for Particle Phenomenology

Kinematic variables have been playing an important role in collider phenomenology, as they expedite discoveries of new particles by separating signal events from unwanted background events and allow for measurements of particle properties such as masses, couplings, spins, etc. For the past 10 years, an enormous number of kinematic variables have been designed and proposed, primarily for the experiments at the Large Hadron Collider, allowing for a drastic reduction of high-dimensional experimental data to lower-dimensional observables, from which one can readily extract underlying features of phase space and develop better-optimized data-analysis strategies. We review these recent developments in the area of phase space kinematics, summarizing the new kinematic variables with important phenomenological implications and physics applications. We also review recently proposed analysis methods and techniques specifically designed to leverage the new kinematic variables. As machine learning is nowadays percolating through many fields of particle physics including collider phenomenology, we discuss the interconnection and mutual complementarity of kinematic variables and machine learning techniques. We finally discuss how the utilization of kinematic variables originally developed for colliders can be extended to other high-energy physics experiments including neutrino experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2010

Separating Gravitational Wave Signals from Instrument Artifacts

Central to the gravitational wave detection problem is the challenge of separating features in the data produced by astrophysical sources from features produced by the detector. Matched filtering provides an optimal solution for Gaussian noise, but in practice, transient noise excursions or "glitches" complicate the analysis. Detector diagnostics and coincidence tests can be used to veto many glitches which may otherwise be misinterpreted as gravitational wave signals. The glitches that remain can lead to long tails in the matched filter search statistics and drive up the detection threshold. Here we describe a Bayesian approach that incorporates a more realistic model for the instrument noise allowing for fluctuating noise levels that vary independently across frequency bands, and deterministic "glitch fitting" using wavelets as "glitch templates", the number of which is determined by a trans-dimensional Markov chain Monte Carlo algorithm. We demonstrate the method's effectiveness on simulated data containing low amplitude gravitational wave signals from inspiraling binary black hole systems, and simulated non-stationary and non-Gaussian noise comprised of a Gaussian component with the standard LIGO/Virgo spectrum, and injected glitches of various amplitude, prevalence, and variety. Glitch fitting allows us to detect significantly weaker signals than standard techniques.

Littenberg, Tyson B.↗
DOE OSTI2025

Signal-preserving CMB component separation with machine learning

Analysis of microwave sky signals, such as the cosmic microwave background, often requires component separation using multifrequency methods, whereby different signals are isolated according to their different frequency behaviors. Many so-called blind methods, such as the internal linear combination (ILC), make minimal assumptions about the spatial distribution of the signal or contaminants, and only assume knowledge of the frequency dependence of the signal. The ILC produces a minimum-variance linear combination of the measured frequency maps. In the case of Gaussian, statistically isotropic fields, this is the optimal linear combination, as the variance is the only statistic of interest. However, in many cases the signal we wish to isolate, or the foregrounds we wish to remove, are non-Gaussian and/or statistically anisotropic (in particular for the case of Galactic foregrounds). In such cases, it is possible that machine learning (ML) techniques can be used to exploit the non-Gaussian features of the foregrounds and thereby improve component separation. However, many ML techniques require the use of complex, difficult-to-interpret operations on the data. We propose a hybrid method whereby we train an ML model using only combinations of the data that , and combine the resulting ML-predicted foreground estimate with the ILC solution to reduce the error from the ILC. We demonstrate our methods on simulations of extragalactic temperature and Galactic polarization foregrounds and show that our ML model can exploit non-Gaussian features, such as point sources and spatially varying spectral indices, to produce lower-variance maps than ILC—e.g., reducing the variance of the B-mode residual by factors of up to 5—while preserving the signal of interest in an unbiased manner. Moreover, we often find improved performance even when applying our ML technique to foreground models on which it was not trained. Published by the American Physical Society 2025

McCarthy, Fiona (ORCID:0000000253893565)↗
NASA NTRS1981

Adaptive polarization separation

A broadband adaptively controlled polarization separation network is discussed. Two transmitted signals vertically and horizontally polarized are received as elliptically polarized signals. If there is any vertical polarization on the other signal the separation network provides two signals. The separation is done automatically by the use of two sets of crosscouplers which couple a single line to the other line to complete the polarization decoupling operation.

Pelchat, G. M.↗
DOE OSTI2025

PySolate : A Python‐Based Thresholding Tool to Denoise or Designal Seismic Waveforms Based on the Continuous Wavelet Transform

PySolate is a Python‐based toolset that implements the continuous wavelet transform and nonlinear thresholding operations to denoise or designal seismic data, following Langston and Mousavi (2019). This filtering approach can remove microseismic noise to isolate intermediate‐period seismic signals that are key to enabling full‐waveform modeling and analysis of smaller‐magnitude regional events. This approach is best for the application to signals with frequency or time separation of signal and noise, in contrast to Fourier analysis, which is effective when signal and noise are separated in frequency. We demonstrate the Python toolset using the six announced Democratic People’s Republic of Korea declared nuclear tests, showing the effectiveness of isolating the seismic signal compared to standard bandpass filtering. In conclusion, we also demonstrate the ease of using the toolset with any Python processing tools.

Asia↗
DOE OSTI2020

Separating the intrinsic alignment signal and the lensing signal using self-calibration in photo- z surveys with KiDS450 and KV450 Data

ABSTRACT To reach the full potential for the next generation of weak lensing surveys, it is necessary to mitigate the contamination of intrinsic alignments (IAs) of galaxies in the observed cosmic shear signal. The self-calibration (SC) of IAs provides an independent method to measure the IA signal from the survey data and the photometric redshift information. It operates differently from the marginalization method based on the IA modelling. In this work, we present the first application of SC to the KiDS450 data and the KV450 data, to split directly the intrinsic shape–galaxy density (Ig) correlation signal and the gravitational shear–galaxy density (Gg) correlation signal, using the information from photometric redshift (photo-z). We achieved a clear separation of the two signals and performed several validation tests. Our measured signals are found to be in general agreement with the KiDS450 cosmic shear best-fitting cosmology, for both lensing and IA measurements. For KV450, we use partial (high-z) data, and our lensing measurements are also in good agreement with KV450 cosmic shear best fit, while our IA signal suggests a larger IA amplitude for the high-z sample. We discussed the impact of photo-z quality on IA detection and several other potential systematic biases. Finally, we discuss the potential application of the information extracted for both the lensing signal and the IA signal in future surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1975

Dual frequency scatterometer measurement of ocean wave height

A technique for remotely measuring wave height averaged over an area of the sea surface was developed and verified with a series of aircraft flight experiments. The measurement concept involves the cross correlation of the amplitude fluctuations of two monochromatic reflected signals with variable frequency separation. The signal reflected by the randomly distributed specular points on the surface is observed in the backscatter direction at nadir incidence angle. The measured correlation coefficient is equal to the square of the magnitude of the characteristic function of the specular point height from which RMS wave height can be determined. The flight scatterometer operates at 13.9 GHz and 13.9 - delta f GHz with a maximum delta f of 40 MHz. Measurements were conducted for low and moderate sea states at altitudes of 2, 5, and 10 thousand feet. The experimental results agree with the predicted decorrelation with frequency separation and with off-nadir incidence angle.

Johnson, J. W.↗