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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 19 records

Improved Gas Plume Identification Using Nearest Neighbor Methods for Background Estimation

Longwave infrared (LWIR) hyperspectral imaging (HSI) can be used for many tasks in remote sensing, including detecting and identifying effluent gases by LWIR sensors on airborne platforms. Identification is used after detection to increase confidence in weakly detected plumes, reduce false positives from detection, and distinguish between similar and confounding material signatures. Background estimation is an important step used to reveal the unique spectral characteristics of the detected gas, allowing the identification model to determine what the gas is specifically. The importance of proper background estimation increases when dealing with weak signals, large libraries of gases of interest, and uncommon or heterogeneous backgrounds. In this article, we propose two methods for background estimation: a novel k-nearest segments (KNS) algorithm and the standard k-nearest neighbors (KNN) algorithm. We test our methods and three existing background estimation methods for comparison against global background estimation to determine which performs best at estimating the true background radiance under a plume and for increasing identification confidence using a neural network classification model. We compare the different methods using 640 simulated weak plumes in an urban environment. For identification, our KNS algorithm improves median neural network identification confidence by 53.2%. For background radiance estimation, the KNN algorithm provides a median of 49 times less RMSE than global background estimation. Furthermore, KNN is the easiest method to tune for different plumes, making it an excellent “out of the box” background estimator.

47 OTHER INSTRUMENTATION↗

Background-field Method and QCD Factorization

One method for deriving a factorization for QCD processes is to use successive integration over fields in the functional integral. In this approach, we separate the fields into two categories: dynamical fields with momenta above a relevant cutoff, and background fields with momenta below the cutoff. The dynamical fields are then integrated out in the background of the low-momentum background fields. This strategy works well at tree level, allowing us to quickly derive QCD factorization formulas at leading order. However, to extend the approach to higher loops, it is necessary to rigorously define the functional integral over dynamical fields in an arbitrary background field. This framework was carefully developed for the calculation of the effective action in a background field at the two-loop level in the classic paper by Abbott «The Background Field Method Beyond One Loop», Nucl. Phys. B 185 , 189 (1981). Building on this work, I specify the renormalized background-field Lagrangian and define the notion of the quantum average of an operator in a background field, consistent with the “separation of scales” scheme mentioned earlier. As examples, I discuss the evolution of the twist-2 gluon light-ray operator and the one-loop gluon propagator in a background field near the light cone.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Radiation portal monitor data file format for comprehensive background radiation monitoring

Radiation portal monitors (RPMs) are widely used at border security checkpoints to detect the presence of radioactive materials in people, vehicles, and cargo. Typically, RPM detection systems consist of two pillars equipped with gamma and neutron detectors. To improve detection efficiency, RPMs employ techniques such as a limited energy window, dynamic alarm thresholds, and lead shielding. However, without continuous monitoring of background radiation, signal interpretation can be compromised, because environmental factors and mechanical failures can cause fluctuations. Here, we introduce a daily file format that logs gamma background and neutron background radiation levels continuously over a 24 h period; this format is different from traditional formats that record data only when the RPM is active or occupied. The approach enables RPM operators and analysts to (1) identify and diagnose malfunctioning components, (2) adjust system settings to account for dynamic environmental factors, and (3) use the recorded data to characterize outer space phenomena. Continuous background reporting is essential for identifying issues such as faulty connections, voltage divider failures, and errors in background updates. Continuous background reporting also enables the detection of external influences, including nearby X-ray scanners, temperature fluctuations, rainfall, cosmic radiation, and lunar phase changes. These data files are designed to be easily evaluated and parsed using common tools, and a quick review by an expert is often sufficient for problem diagnosis. We anticipate that continuous background radiation monitoring and these new strategies will significantly improve the accuracy and reliability of RPM systems, reducing the rate of false alarms and enhancing overall system performance.

Background radiation monitoring↗

Effects of gas purity on backgrounds of collision reaction cell-equipped MC-ICP-MS

The advent of multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) instruments equipped with collision reaction cells (CRCs) facilitates interference removal/mitigation via online gas phase separations. This approach has proven effective for high intensity ion beams measured on Faraday collectors; however, it has been observed that introduction of gas in the CRC can result in significant background signals relative to the more sensitive ion counters. These backgrounds hinder use of these instruments for low level concentration and isotopic ratio measurements when employing a reaction gas. Here, this work directly evaluates the effect of gas purity on backgrounds of CRC-MC-ICP-MS instruments. Introducing high-purity research grade O 2 (99.999%) into the CRC produces complex background spectra with intensities >10 4 cps observed at most masses across the measured mass range (7-300 m / z ). Some features of the observed spectra (i.e., positive mass defects) can be attributed to molecular compounds comprised of significant hydrogen. Additionally, some specific molecular species can be identified (i.e., MoO x H y + ) and appear to be derived from molybdenum rods comprising the CRC. Further purifying the gas reduces the intensity of these backgrounds by several orders of magnitude, to <10 2 cps in many cases, and reduces complexity of the resulting spectra. This reduction in background appears to be in part driven by removal of impurities (i.e., H 2 O) from the gas. This work demonstrates that additional purification of reaction gases prior to introduction into the CRC significantly reduces backgrounds detected, potentially expanding the utility of CRC-MC-ICP-MS for making low level measurements using inline gas phase ion separations.

Schlieder, Tyler D. [Pacific Northwest National La↗

Impact of gas background on XFEL single-particle imaging

Abstract Single-particle imaging (SPI) using X-ray free-electron Lasers (XFELs) offers the potential to determine protein structures at high spatial and temporal resolutions without the need for crystallization or vitrification. However, the technique faces challenges due to weak diffraction signals from single proteins and significant background scattering from gases used for sample delivery. A recent observation of a diffraction pattern from an isolated GroEL protein complex Ekeberg T et al. (Light Sci Appl 13:15, 2024.https://doi.org/10.1038/274s41377-023-01352-7) had similar numbers of signal and background photons. Ongoing efforts aim to reduce the background created by sample delivery, with one approach replacing most of the used gas with helium Yenupuri T et al. (Sci Rep 14:4401, 2024.https://doi.org/10.1038/s41598-024-54605-9). In this study, we investigate the effects of a reduced background on the resolution limits for SPI of isolated proteins under different experiment conditions. As a test case, we used GroEL, and we used experimentally derived parameters for our simulations. We observe that background significantly impacts the achievable resolution, particularly when the signal strength is comparable to the background. This is best exemplified at 6.0 keV, where a background reduction by a factor of 10 leads to a resolution improvement from 1.9 to 1.2 nm, for a dataset of$$10^4$$patterns.

Science & Technology - Other Topics↗

Machine learning method for enforcing variable independence in background estimation with LHC data: ABCDisCoTEC

A novel solution is presented for the problem of estimating the backgrounds of a signal search using observed data while simultaneously maximizing the sensitivity of the search to the signal. The 'ABCD method' provides a reliable framework for background estimation by partitioning events into one signal-enhanced region (A) and three background-enhanced control regions (B, C, and D) via two smoothly varying, statistically independent variables. In practice, even slight correlations between the two variables can significantly undermine the method's performance. Thus, choosing appropriate variables by hand can present a formidable challenge, especially when background and signal differ only subtly. To address this issue, the ABCD with distance correlation (ABCDisCo) method was developed to construct two learned variables via a neural network trained to provide strong signal-background discrimination with small values of the distance correlation (DisCo) measure between the two learned variables. However, relying solely on minimizing the DisCo can result in learned variables that may not have distributions of background events that are smoothly varying and localized at extreme values, as necessary for the validity of the background estimation. The ABCDisCo training enhanced with closure (ABCDisCoTEC) method is introduced to solve this issue by directly minimizing the nonclosure, expressed as a dedicated differentiable loss term. This extended method is applied to a data set of proton-proton collisions at a center-of-mass energy of 13 TeV recorded by the CMS detector at the CERN Large Hadron Collider. Additionally, given the complexity of the minimization problem with constraints on multiple loss terms, the modified differential method of multipliers is applied and shown to greatly improve the stability and robustness of the ABCDisCoTEC method, compared to grid search hyperparameter optimization procedures.

Hayrapetyan, Aram [Yerevan Phys. Inst.]↗

Evaluation of a generalized least squares algorithm for infrasound beamforming with coherent background noise

Infrasonic signals of interest can occur during periods with persistent, coherent, background noise, which may be natural or anthropogenic. For high signal-to-noise (SNR) ratio transient signals, an ‘overprinting’ of the coherent background may occur, and the signal may still be detected. However, this approach fails for low SNR signals of interest, which may be obscured by coherent noise. An infrasound beamforming method based on generalized least squares (GLS) is investigated for detecting transient signals of interest in the presence of coherent and incoherent background noise. This approach relies on an estimate of the noise covariance, captured in a covariance matrix, to effectively null contributions to the array response from noisy directions of arrival. Synthetic array data is used to investigate the performance of the GLS beamformer compared to the Bartlett beamformer when coherent and incoherent backgrounds are present. Additionally, the effects of array element number and relative strength of the interfering signal on the GLS estimates is investigated. GLS empirical area under the curve estimates suggest that the beamformer can recover coherent power for a signal of interest lower in amplitude than the coherent background, but this effectiveness degrades more quickly with SNR for a four element array compared to a six or eight element infrasound array. Finally, infrasound from the Forensic Surface Experiment, a bolide signal observed at IMS array I37NO, and a volcanic signal recorded at the Alaska Volcano Observatory array ADKI are used to evaluate GLS performance on recorded data. A ten minute window was used to capture the background noise, and the coherent background signal was nulled in all three examples.

58 GEOSCIENCES↗

Characterization of the Cherenkov Photon Background for Low-noise Silicon Detectors in Space

Future space observatories that seek to perform imaging and spectroscopy of faint astronomical sources will require ultra-low-noise detectors that are sensitive over a broad wavelength range. Silicon charge-coupled devices (CCDs), such as EMCCDs, skipper CCDs, multi-amplifier sensing CCDs, and single-electron sensitive read out CCDs have demonstrated the ability to detect and measure single photons from X-ray energies to near the silicon band gap (∼1.1 μm), making them candidate technologies for this application. Here, in this context, we study a relatively unexplored source of low-energy background coming from Cherenkov radiation produced by energetic cosmic rays traversing a silicon detector. We present a model for Cherenkov photon production and absorption that is calibrated to laboratory data, and we use this model to characterize the residual background rate for ultra-low-noise silicon detectors in space. We study how the Cherenkov background rate depends on detector thickness, variations in solar activity, and the contribution of heavy cosmic ray species (Z > 2). We find that for thick silicon detectors, such as those required to achieve high quantum efficiency at long wavelengths, the rate of cosmic-ray-induced Cherenkov photon production is comparable to other detector and astrophysical backgrounds. We apply our Cherenkov background model to simulated spectroscopic observations of extra-solar planets, and we find that thick detectors continue to outperform their thinner counterparts at longer wavelengths despite a larger Cherenkov background rate. Furthermore, we find that minimal masking of cosmic-ray tracks continues to maximize the signal-to-noise ratio of very faint sources despite the existence of extended halos of Cherenkov photons.

Astronomical detectors↗

Beam-induced backgrounds measured in the ATLAS detector during local gas injection into the LHC beam vacuum

Inelastic beam-gas collisions at the Large Hadron Collider (LHC), within a few hundred metres of the ATLAS experiment, are known to give the dominant contribution to beam backgrounds. These are monitored by ATLAS with a dedicated Beam Conditions Monitor (BCM) and with the rate of fake jets in the calorimeters. These two methods are complementary since the BCM probes backgrounds just around the beam pipe while fake jets are observed at radii of up to several metres. In order to quantify the correlation between the residual gas density in the LHC beam vacuum and the experimental backgrounds recorded by ATLAS, several dedicated tests were performed during LHC Run 2. Local pressure bumps, with a gas density several orders of magnitude higher than during normal operation, were introduced at different locations. The changes of beam-related backgrounds, seen in ATLAS, are correlated with the local pressure variation. In addition the rates of beam-gas events are estimated from the pressure measurements and pressure bump profiles obtained from calculations. Using these rates, the efficiency of the ATLAS beam background monitors to detect beam-gas events is derived as a function of distance from the interaction point. These efficiencies and characteristic distributions of fake jets from the beam backgrounds are found to be in good agreement with results of beam-gas simulations performed with theFluka Monte Carlo programme.

43 PARTICLE ACCELERATORS↗

Data-driven background model for the CUORE experiment

Here, we present the model we developed to reconstruct the CUORE radioactive background based on the analysis of an experimental exposure of 1038.4 kg yr. The data reconstruction relies on a simultaneous Bayesian fit applied to energy spectra over a broad energy range. The high granularity of the CUORE detector, together with the large exposure and extended stable operations, allow for an in-depth exploration of both spatial and time dependence of backgrounds. We achieve high sensitivity to both bulk and surface activities of the materials of the setup, detecting levels as low as 10 nBq kg −1 and 0.1 nBq cm −2 , respectively. We compare the contamination levels we extract from the background model with prior radio-assay data, which informs future background risk mitigation strategies. The results of this background model play a crucial role in constructing the background budget for the CUPID experiment as it will exploit the same CUORE infrastructure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurement of the background in the CMS muon detector in ${p}{p}$-collisions at $\sqrt{s} = 13$ TeV

The CMS detector, including its muon system, has been operating at the CERN LHC in increasingly challenging conditions for about 15 years. The muon detector was designed to provide excellent triggering and track reconstruction for muons produced in proton–proton collisons at an instantaneous luminosity ($\mathcal{L}$) of 1 x 10 34 cm –2 s –1 . During the Run 2 data-taking period (2015–2018), the LHC achieved an instantaneous luminosity of twice its design value, resulting in larger background rates and making the efficient detection of muons more difficult. While some backgrounds result from natural radioactivity, cosmic rays, and interactions of the circulating protons with residual gas in the beam pipe, the dominant source of background hits in the muon system arises from proton–proton interactions themselves. Charged hadrons leaving the calorimeters produce energy deposits in the muon chambers. In addition, high-energy particles interacting in the hadron calorimeter and forward shielding elements generate thermal neutrons, which leak out of the calorimeter and shielding structures, filling the CMS cavern. We describe the method used to measure the background rates in the various muon subsystems. These rates, in conjunction with simulations, can be used to estimate the expected backgrounds in the High-Luminosity LHC. This machine will run for at least 10 years starting in 2029 reaching an instantaneous luminosity of $\mathcal{L}$ = 5 x 10 34 cm –2 s –1 and increasing ultimately to $\mathcal{L}$ = 7.5 x 10 34 cm –2 s –1 . These background estimates have been a key ingredient for the planning and design of the muon detector upgrade.

Tytgat, M. (ORCID:0000000239902074)↗

A data-driven method to estimate the antiproton background in the Mu2e experiment

The Mu2e experiment at Fermilab will search for the Charged Lepton Flavour Violating (CLFV) process of coherent, neutrinoless µ− → e − conversion in the field of an aluminum nucleus. The expected signal is a monochromatic electron with the energy of 104.97 MeV, slightly below the muon rest mass. Observation of a CLFV process would provide unambiguous evidence for Beyond the Standard Model (BSM) physics. Mu2e is sensitive to a wide range of BSM models and has the capability to distinguish between them, guiding us towards the most accurate models. The key features of the Mu2e experiment are: (1) a high intensity pulsed negative muon beam with about 1010 stopped µ −/s, and (2) a sophisticated superconducting solenoid system with a gradient magnetic field to form and guide the intense muon beam to the target. The Mu2e physics data taking is expected to begin in 2027. For Run I, the expected 5σ discovery sensitivity is Rµe = 1.2 × 10−15, with a total expected background of 0.11 ± 0.03 events. In the absence of a signal, the expected upper limit is Rµe < 6.2 × 10−16 at 90% CL. The success of this experiment hinges on the accurate estimation of the background from various SM processes that could provide signal-like electrons. One of the background processes is antiprotons annihilating in the stopping target to produce signal like electrons through π0 → γγ decays followed by γ conversions, and π− → µ−ν¯ decays followed by µ− decay. It is a relatively small background with large uncertainty (100%) due to the lack of antiproton production cross section information for the Mu2e proton beam energy of 8 GeV. We have developed a novel methodology to estimate the antiproton background in-situ. This forms the main theme of the thesis. We observed that at Mu2e energies, antiproton annihilation in the stopping target is the only source of events with multiple, simultaneous particle trajectories. From Geant4 simulations, only about 0.2% of the simulated antiproton annihilation events have a signal-like electron. Meanwhile, ∼ 5% of events have multiple reconstructible particle tracks per event. Therefore, we have devised a methodology to reconstruct the multi-track events and estimate the antiproton background by exploiting the large ratio of the production rates of the two final states.

Chithirasreemadam, Namitha [Pisa U.] (ORCID:000000↗

The neutrino force in neutrino backgrounds: Spin dependence and parity-violating effects

The neutrino force results from the exchange of a pair of neutrinos. A neutrino background can significantly influence this force. In this work, we present a comprehensive calculation of the neutrino force in various neutrino backgrounds with spin dependence taken into account. In particular, we calculate the spin-independent and spin-dependent parity-conserving neutrino forces, in addition to the spin-dependent parity-violating neutrino forces with and without the presence of a neutrino background for both isotropic and anisotropic backgrounds. Compared with the vacuum case, the neutrino background can effectively violate Lorentz invariance and lead to additional parity-violating terms that are not suppressed by the velocity of external particles. We estimate the magnitude of the effect of atomic parity-violation experiments, and it turns out to be well below the current experimental sensitivity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Radon-induced backgrounds in the NEXT-100 experiment

The NEXT-100 detector at the LSC aims at the first competitive search for the 0νββ decay using a high-pressure $^{136}$Xe electroluminescent time projection chamber. The first low-background run of NEXT-100 at 3.95 bar has been devoted to the measurement of the radon-induced backgrounds impacting this search. The contributions from both the internal and external airborne radon have been evaluated. The internal $^{222}$Rn activity is found to be (0.95±0.04(stat)±0.09(sys)) Bq/m$^{3}$, while no traces of $^{220}$Rn have been observed. Most of the $^{222}$Rn progeny plate-out on the surface of the cathode of the detector, leading to a rate of Rn-induced $^{214}$Bi of (0.97±0.05(stat)±0.10(sys)) Hz for visible energies above 400 keV. The corresponding background index in the 0νββ region of interest is evaluated as (7.3±1.5(stat)±0.8(sys))×10$^{−4}$ counts/(keV·kg·yr) after selection of the fully contained events. This background index is reduced to ∼4×10$^{−5}$ counts/(keV·kg·yr) by applying a topological selection requiring only one double-electron-like track in the events. This value is one order of magnitude below the total radiogenic background expectation in NEXT-100. By analyzing the correlation of the airborne radon activity and the measured rate of events in NEXT-100, it is concluded that the detector operates in a virtually radon-free environment thanks to the radon abatement system of the LSC.[graphic not available: see fulltext]

Cortes-Parra, C. [Valencia U., IFIC] (ORCID:000000↗

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↗

Two-Step Procedure to Detect Cosmological Gravitational Wave Backgrounds with Next-Generation Terrestrial Gravitational-Wave Detectors

Cosmological gravitational-wave backgrounds are an exciting science target for next-generation ground-based detectors, as they encode invaluable information about the primordial Universe. However, any such background is expected to be obscured by the astrophysical foreground from compact-binary coalescences. We propose a novel framework to detect a cosmological gravitational-wave background in the presence of binary black holes and binary neutron star signals with next-generation ground-based detectors, including Cosmic Explorer and the Einstein Telescope. Our procedure involves first removing all the individually resolved binary black hole signals by notching them out in the time-frequency domain. Then, we perform joint Bayesian inference on the individually resolved binary neutron star signals, the unresolved binary neutron star foreground, and the cosmological background. For a flat cosmological background, we find that we can claim detection at 5⁢𝜎 level when Ω ref ≥ 2.7 × 10 −12 /$\sqrt{𝑇_{obs}/yr}$, where 𝑇 obs is the observation time (in years), which is within a factor of ≲ 2 from the sensitivity reached in the absence of these astrophysical foregrounds.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Searching for cosmological stochastic backgrounds by notching out resolvable compact binary foregrounds with next-generation gravitational-wave detectors

Stochastic gravitational-wave backgrounds can be of either cosmological or astrophysical origin. The detection of an astrophysical stochastic gravitational-wave background with ground-based interferometers is expected in the near future. Perhaps even more excitingly, the detection of stochastic backgrounds of cosmological origin by future ground-based interferometers could reveal invaluable information about the early Universe. From this perspective, the astrophysical background is a foreground that can prevent the extraction of this information from the data. In this paper, we revisit a time-frequency domain notching procedure previously proposed to remove the astrophysical foreground in the context of next-generation ground-based detectors, but we consider the more realistic scenario where we remove individually detectable signals by taking into account the uncertainty in the estimation of their parameters. We find that time-frequency domain masks can still efficiently remove the astrophysical foreground and suppress it to about 5% of its original level. Further removal of the foreground formed by unresolvable events (in particular, unresolvable binary neutron stars), which is about 10 times larger than the residual foreground from realistic notching, would require detector sensitivity improvements. Therefore, the main limitation in the search for a cosmological background is the unresolvable foreground itself, and not the residual of the notching procedure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

RAIS Generic Soil Background Values

The RAIS offers two approaches to background screening: generic and site-specific. The Generic Background Values tool (https://rais.ornl.gov/tools/bg_search.php) contains generic soil background values for selected metals. These values can be applied to any area across the U.S. Users can compare these values against local background data or supplement an existing background value dataset. Results can be downloaded in .xlsx format.

Dolislager, Fred [Oak Ridge National Laboratory (O↗