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Results for “Background subtraction”

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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Background subtraction in inelastic scattering measurements using machine learning

Identifying, isolating, and subtracting background from the signal of interest is vital for nuclear physics experiments. These backgrounds introduce unwanted uncertainties that must be accounted for properly to extract accurate results from the signals. In nuclear reaction measurements, the typical contaminants are carbon and oxygen, contributing to background signals, and complicating the measurement of the light ejectiles. For instance, in the inelastic scattering measurement of a 20.9-MeV proton beam on 96 Mo, the 96 Mo target was contaminated with carbon and oxygen. Here, we used random forest, a machine learning algorithm commonly used for classification and regression tasks, to separate the inelastic scattering on the carbon and oxygen contaminants from the data of interest resulting from 96 Mo(p, p').

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2017

Subspace-based Background Subtraction Applied to Aeroacoustic Wind Tunnel Testing

A subspace-based form of background subtraction is presented and applied to aeroacoustic wind tunnel data. A variant of this method has seen use in other fields such as climatology and medical imaging. The technique is based on an eigenvalue decomposition of the background noise cross-spectral matrix. Simulated results indicate similar performance to conventional background subtraction when the subtracted spectra are weaker than the true contaminating background levels. Superior performance is observed when the subtracted spectra are stronger than the true contaminating background levels, and when background data do not match between measurements. Experimental results show limited success in recovering signal behavior for data in which conventional background subtraction fails. The results also demonstrate the subspace subtraction technique's ability to maintain a physical coherence relationship in the modified cross-spectral matrix. Deconvolution results from microphone phased array data indicate that array integration methods are largely insensitive to subtraction type, and that background subtraction with appropriate background data is an effective alternative to diagonal removal.

deconvolution↗
NASA NTRS2015

Advanced Background Subtraction Applied to Aeroacoustic Wind Tunnel Testing

An advanced form of background subtraction is presented and applied to aeroacoustic wind tunnel data. A variant of this method has seen use in other fields such as climatology and medical imaging. The technique, based on an eigenvalue decomposition of the background noise cross-spectral matrix, is robust against situations where isolated background auto-spectral levels are measured to be higher than levels of combined source and background signals. It also provides an alternate estimate of the cross-spectrum, which previously might have poor definition for low signal-to-noise ratio measurements. Simulated results indicate similar performance to conventional background subtraction when the subtracted spectra are weaker than the true contaminating background levels. Superior performance is observed when the subtracted spectra are stronger than the true contaminating background levels. Experimental results show limited success in recovering signal behavior for data where conventional background subtraction fails. They also demonstrate the new subtraction technique's ability to maintain a proper coherence relationship in the modified cross-spectral matrix. Beam-forming and de-convolution results indicate the method can successfully separate sources. Results also show a reduced need for the use of diagonal removal in phased array processing, at least for the limited data sets considered.

Bahr, Christopher J.↗
DOE OSTI2025

Deep image reconstruction for background subtraction in heavy-ion collisions

Jet reconstruction in an ultrarelativistic heavy-ion collision suffers from a notoriously large, fluctuating thermal background. Traditional background‐subtraction methods struggle to remove this soft background while preserving the jet's hard substructure. In this Letter, we present DeepSub, a machine-learning-based approach for full-event background‐subtraction. DeepSub utilizes a model based on Swin Transformer layers to denoise jet images and disentangle hard jets from the heavy-ion background. DeepSub significantly outperforms existing subtraction techniques by reproducing key jet observables such as jet 𝑝 T and mass, and substructure observables such as girth and the energy correlation function, at the subpercent to percent level. As such, DeepSub paves the way for precision heavy-ion measurements in hitherto inaccessible kinematic regimes.

Qureshi, Umar Sohail [Stanford University, CA (Uni↗
DOE OSTI2022

Measurement of the 136 Xe two-neutrino double-β-decay half-life via direct background subtraction in NEXT

Here, we report a measurement of the half-life of the 136 Xe two-neutrino double-β decay performed with a novel direct-background-subtraction technique. The analysis relies on the data collected with the NEXT-White detector operated with 136 Xe-enriched and 136 Xe-depleted xenon, as well as on the topology of double-electron tracks. With a fiducial mass of only 3.5 kg of Xe, a half-life of 2.34$_{-0.46}^{+0.80}$(stat)$_{-0.17}^{+0.30}$(sys)×10 21 yr is derived from the background-subtracted energy spectrum. The presented technique demonstrates the feasibility of unique background-model-independent neutrinoless double-β-decay searches.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Innovative dead-time correction and background subtraction for neutron multiplicity measurements using neural networks

Abstract The number of neutrons emitted from a nuclear reaction plays a crucial role in various fields, including nuclear theory, nuclear nonproliferation, nuclear energy and nuclear criticality safety. Accurate determination of neutron multiplicities requires the application of several corrections, with dead-time correction and background subtraction being particularly significant. These corrections become more challenging for neutron detectors with time-dependent neutron capture. In this work, we perform a comprehensive study of three existing methods used for dead-time correction and background subtraction in neutron detectors with time-dependent neutron capture. The methods were tested for dead-times in the range from 0 to 1 μs using a Monte Carlo model simulating the dead-time and background effects in the standard neutron multiplicity probability distribution of $$^{252}$$ 252 Cf. The previous methods showed larger than desired uncertainty or systematic trade off. Those uncertainties prompted the development of a novel approach using neural networks trained with data from Monte Carlo simulations. The Neural Network method enabled the correction of neutron multiplicity probabilities more accurately than the other methods with fractional errors smaller than 3% for multiplicities around the peak of $$^{252}$$ 252 Cf. A similar approach using neural networks could be applied to problems where the system being studied can be accurately simulated without having an accurate analytical description available. The neural network method presented in this paper can be easily expanded if multiplicities greater than 10 are expected.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1988

Diffraction, chopping, and background subtraction for LDR

The Large Deployable Reflector (LDR) will be an extremely sensitive infrared telescope if the noise due to the photons in the large thermal background is the only limiting factor. For observations with a 3 arcsec aperture in a broadband at 100 micrometers, a 20-meter LDR will emit 10(exp 12) per second, while the photon noise limited sensitivity in a deep survey observation will be 3,000 photons per second. Thus the background subtraction has to work at the 1 part per billion level. Very small amounts of scattered or diffracted energy can be significant if they are modulated by the chopper. The results are presented for 1-D and 2-D diffraction calculations for the lightweight, low-cost LDR concept that uses an active chopping quaternary to correct the wavefront errors introduced by the primary. Fourier transforms were used to evaluate the diffraction of 1 mm waves through this system. Unbalanced signals due to dust and thermal gradients were also studied.

Wright, Edward L.↗
DOE OSTI2026

HostSub_GP: Precise Galaxy Background Subtraction in Transient Long-slit Spectroscopy with Gaussian Processes

We present a novel host galaxy subtraction technique in long-slit spectroscopy for extragalactic transients. Unlike classic methods which generally estimate the background using simple interpolation of local galaxy flux in the 2D spectrum, our approach leverages multi-band archival images of the host galaxies to model the background emission from the galaxy in the 2D spectrum. Such imaging encodes the wavelength-dependent galaxy profile along the slit, and is readily accessible through wide-field imaging surveys. We construct a smooth prior for the 2D galaxy profile with a Gaussian process (GP) based on these reference images, and use another GP to model the correlated deviations from the prior in the observed spectrum. This enables accurate inference of the galaxy flux blended with the transient. On synthetic long-slit data of a spiral galaxy extracted from a Multi Unit Spectroscopic Explorer hyper-spectral cube, the GP method remains robust as long as the host galaxy is spatially resolved and consistently outperforms classic methods. We apply the method to archival Keck spectra of two real transients, SN 2019eix and AT 2019qiz, to further demonstrate how the method uniquely recovers weak spectral features amid strong galaxy contamination, enabling refined constraints on the properties of both transients. We have released the software implementation, HostSub_GP, a scalable toolkit that leverages JAX, with an MIT license.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1983

The GSFC Advanced Compton Telescope (ACT)

A new telescope is being developed at GSFC for the study of point sources of gamma rays in the energy range 1-30 MeV. Using the detection principle of a Compton scatter in a 2.5 cm thick NaI(Tl) detector followed by absorption in a 15 cm thick NaI(Tl) detector, the telescope uses a rocking collimator for field-of-view reduction and background subtraction. Background reduction techniques include lead-plastic scintillator shielding, pulse shape discrimination and Anger camera operation to both NaI detectors, as well as a time-of-flight measurement between them. The instrument configuration and status is described.

Hartman, R.↗
NASA NTRS2001

A High Resolution Study of the X-Ray Emission From 3C400.2

The ROSAT HRI observation of 3C400.2 was conducted and the data have been received by the PI. The data have been processed using the Extended Source Analysis SW (ESAS) developed by Steve Snowden for the analysis of extended objects with ROSAT. The ESAS SW models and subtracts the particle background of the ROSAT HRI which is the dominant contributor to the non-cosmic background in the HRI. The background-subtracted image was smoothed with an adaptive-smoothing algorithm in order to enhance faint structure but also to maintain the superb angular resolution of the HRI where a sufficient number of counts were available. We have also used the ESAS SW to analyze the existing archival PSPC data. We have generated background-subtracted and merged images from the multiple PSPC observations. In the future, we will conduct a detailed comparison between the HRI and PSPC images. In addition, we plan to use the existing archival ASCA data to better determine the spectrum as a function of position in the remnant. The PI has not been able to finish the analysis and write the paper due to his demands on his time supporting operations of the Chandra X-ray Observatory. The PI will have more time in the coming year and hopes to finish the analysis.

Plucinsky, Paul↗