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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Perspectives for Measuring Neutrino Cross-Sections at Short Baseline Detectors (ICARUS and DUNE-PRISM-like Detector) and Their Implications for Precision Physics

Neutrino physics is rapidly advancing with current and future experiments promising high-statistics data, enabling unprecedented accuracy in measuring Standard Model (SM) parameters and providing crucial insights into neutrino-nucleus interactions. The ICARUS experiment, utilizing LAr TPC technology, is pivotal in this growth. As the far detector of the SBN program at Fermilab, ICARUS is set to investigate the neutrino anomalies observed in LSND and MiniBooNE and prepare for future long-baseline experiments like DUNE. Positioned along the BNB and 5.75°off-axis from the NuMI beamline, ICARUS benefits from numerous neutrino interactions, allowing for precise neutrino-argon nucleus cross-section measurements, which will benchmark future DUNE measurements. This work presents the prospects and progress in measuring the cross-section of the NuMI νµ CC inclusive channel in the ICARUS experiment. High-statistics data will also enable precise determinations of fundamental parameters like the weak mixing angle and the neutrino charge radius (NCR), crucial for testing the SM and exploring potential new physics. This work includes studies of future near detectors, such as DUNE-PRISM, which are sensitive to radiative corrections in neutrino-electron scattering. The DUNE-PRISM configuration allows for the analysis of different neutrino energy spectra, promising accurate NCR measurements with controlled systematic uncertainties.

Moreno-Granados, Guadalupe↗
DOE OSTI2019

Machine learning for analysis of atomic spectral data

Physics based forward models are the basis on which many experimental diagnostics are interpreted. For some diagnostics, models can be computationally expensive which precludes their use in real time analysis. Reduced models have the potential to capture sufficient physics thereby enabling the desired real time analysis. Using statistical inference and machine learning techniques the application of reduced models for inversion of atomic spectral data used to diagnose magnetic fields in a plasma will be examined. Two approaches are considered, (a) a reduction of the forward model where traditional inversion can be performed on the proxy model, and (b) a reduction of the direct inverse where parameters are a function of measured signal. The resulting inversion is sufficiently fast to be utilized in an online context for digital twinning, and ultimately real-time prediction, design, and control of plasma systems, such as tokamaks. Furthermore, these methods will be demonstrated on both simulated and experimentally measured data.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Universality for 1d Random Band Matrices: Sigma-Model Approximation

The paper continues the development of the rigorous supersymmetric transfer matrix approach to the random band matrices started in (J Stat Phys 164:1233–1260, 2016; Commun Math Phys 351:1009–1044, 2017). We consider random Hermitian block band matrices consisting of W×W random Gaussian blocks (parametrized by j,k∈Λ=[1,n]{sup d}∩ℤ{sup d}) with a fixed entry’s variance J{sub jk}=δ{sub j,k}W{sup −1}+βΔ{sub j,k}W{sup −2}, β>0 in each block. Taking the limit W→∞ with fixed n and β, we derive the sigma-model approximation of the second correlation function similar to Efetov’s one. Then, considering the limit β,n→∞, we prove that in the dimension d=1 the behaviour of the sigma-model approximation in the bulk of the spectrum, as β≫n, is determined by the classical Wigner–Dyson statistics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Extensions to models of the galaxy–halo connection

ABSTRACT We explore two widely used empirical models for the galaxy–halo connection, subhalo abundance matching (SHAM) and the halo occupation distribution (HOD), and compare them with the hydrodynamical simulation IllustrisTNG (TNG) for multiple statistics quantifying the galaxy distribution at $n_{\rm gal}\approx 1.3\times 10^{-3}\, ({\rm Mpc}\,h^{-1})^{-3}$. We observe that in their most straightforward implementations, both models fail to reproduce the two-point clustering measured in TNG. We find that SHAM models that use the relaxation velocity, Vrelax, and the peak velocity, Vpeak, perform best, and match the clustering reasonably well, although neither captures adequately the one-halo clustering. Splitting the total sample into sub-populations, we discover that SHAM overpredicts the clustering of high-mass, blue, star-forming, and late-forming galaxies and underpredicts that of low-mass, red, quiescent, and early-forming galaxies. We also study various baryonic effects, finding that subhaloes in the dark-matter-only simulation have consistently higher values of their SHAM-proxy properties than their full-physics counterparts. We then consider a 2D implementation of the HOD model augmented with a secondary parameter (environment, velocity anisotropy, σ2Rhalf-mass, and total potential) tuned so as to match the two-point clustering of the IllustrisTNG galaxies on large scales. We analyse these galaxy populations adopting alternative statistical tools such as galaxy–galaxy lensing, void–galaxy cross-correlations, and cumulants of the density field, finding that the hydrodynamical galaxy distribution disfavours σ2Rhalf-mass and the total potential as secondary parameters, while the environment and velocity anisotropy samples are consistent with full physics across all statistical probes examined. Our results demonstrate the power of examining multiple statistics for determining the secondary parameters that are vital for understanding the galaxy–halo connection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Improving statistical precision in Monte Carlo samples with negative weights via reweighting and uncertainty quantification

High statistical precision is critical for Monte Carlo (MC) samples in high energy physics and is degraded by negatively weighted events. This paper investigates a procedure to learn the relationship between the negative and positive weight distributions of any sample, allowing the reduction of statistical uncertainty by reweighting kinematically equivalent events with the same sign. A robust uncertainty quantification method is required for the practical application of such method. Two methods for the estimation of the reweighting uncertainty are developed: one at the event and another one at the final observable level. The latter method is strongly favored. The gains in statistical precision are then quantified. The method is demonstrated on Sherpa vector boson plus jets samples when using all generated events and when restricted to the signal region of a mock analysis. It is demonstrated to significantly reduce stochastic behavior in sparse MC samples while decreasing the overall uncertainty with a sufficiently well-known reweighting function.

Monte Carlo methods↗
DOE OSTI2012

AGR-1 Thermocouple Data Analysis

This report documents an effort to analyze measured and simulated data obtained in the Advanced Gas Reactor (AGR) fuel irradiation test program conducted in the INL's Advanced Test Reactor (ATR) to support the Next Generation Nuclear Plant (NGNP) R&D program. The work follows up on a previous study (Pham and Einerson, 2010), in which statistical analysis methods were applied for AGR-1 thermocouple data qualification. The present work exercises the idea that, while recognizing uncertainties inherent in physics and thermal simulations of the AGR-1 test, results of the numerical simulations can be used in combination with the statistical analysis methods to further improve qualification of measured data. Additionally, the combined analysis of measured and simulation data can generate insights about simulation model uncertainty that can be useful for model improvement. This report also describes an experimental control procedure to maintain fuel target temperature in the future AGR tests using regression relationships that include simulation results. The report is organized into four chapters. Chapter 1 introduces the AGR Fuel Development and Qualification program, AGR-1 test configuration and test procedure, overview of AGR-1 measured data, and overview of physics and thermal simulation, including modeling assumptions and uncertainties. A brief summary of statistical analysis methods developed in (Pham and Einerson 2010) for AGR-1 measured data qualification within NGNP Data Management and Analysis System (NDMAS) is also included for completeness. Chapters 2-3 describe and discuss cases, in which the combined use of experimental and simulation data is realized. A set of issues associated with measurement and modeling uncertainties resulted from the combined analysis are identified. This includes demonstration that such a combined analysis led to important insights for reducing uncertainty in presentation of AGR-1 measured data (Chapter 2) and interpretation of simulation results (Chapter 3). The statistics-based simulation-aided experimental control procedure described for the future AGR tests is developed and demonstrated in Chapter 4. The procedure for controlling the target fuel temperature (capsule peak or average) is based on regression functions of thermocouple readings and other relevant parameters and accounting for possible changes in both physical and thermal conditions and in instrument performance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Towards New Physics Through Precision Measurements in B$^0_S$ and $\tau$ Decays

Despite the correct and consistent description of the elementary particle interactions, there is evidence that the Standard Model (SM) is an incomplete theory. Solving the issues faced by the SM requires the introduction of new interactions and, if such interactions exist, they can be observed as deviations in the SM predictions or forbidden processes. Particularly of interest for this work are the B$^0_s$ mesons and $\tau$ leptons produced in the DØ and Belle II experiments, respectively, where the luminosity provides the statistics for high precision SM measurements and searches for new physics. In this work, the lifetime measurement of the B$^0_s$ meson in the decay channel $B^0_s \to J/\Psi f_0(980)$ is reported, which is a CP-odd final state. Using 10.4 fb$^{-1}$ of data collected with the DØ detector in Run II of the Tevatron, the lifetime of the CP-odd component of the B$^0_s$ meson is measured to be $\tau(B^0_s)$ = 1.70$\pm$0.14 (stat)$\pm$0.05 (syst) ps. This measurement is closely related to the $B^0_s - \bar{B^0_s}$ mixing and searches for new CP violation mechanisms. Additionally, the $\tau$ lepton physics program of Belle II is reviewed and two sensitivity studies are shown: (i) $\tau^- \to \eta \pi^-\pi^0 \nu_{\tau}$, which in the isospin symmetry limit SU(2) is a cross-check of consistency with the cross section $\sigma(e^+e^- \to \eta \pi^+ \pi^-$) at low energies; (ii) $\tau^- \to \eta \pi^- \nu_{\tau}$, which has never been observed and, given the suppression by G-parity, it allows the searches of scalar and tensor interactions. Estimations from 1 to 20 ab$^{-1}$ are shown, corresponding to the integrated luminosity expected during the first years of operation of Belle II.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

HERSCHEL-ATLAS GALAXY COUNTS AND HIGH-REDSHIFT LUMINOSITY FUNCTIONS: THE FORMATION OF MASSIVE EARLY-TYPE GALAXIES

Exploiting the Herschel Astrophysical Terahertz Large Area Survey Science Demonstration Phase survey data, we have determined the luminosity functions (LFs) at rest-frame wavelengths of 100 and 250 {mu}m and at several redshifts z {approx}> 1, for bright submillimeter galaxies with star formation rates (SFRs) {approx}> 100 M{sub Sun} yr{sup -1}. We find that the evolution of the comoving LF is strong up to z Almost-Equal-To 2.5, and slows down at higher redshifts. From the LFs and the information on halo masses inferred from clustering analysis, we derived an average relation between SFR and halo mass (and its scatter). We also infer that the timescale of the main episode of dust-enshrouded star formation in massive halos (M{sub H} {approx}> 3 Multiplication-Sign 10{sup 12} M{sub Sun }) amounts to {approx}7 Multiplication-Sign 10{sup 8} yr. Given the SFRs, which are in the range of 10{sup 2}-10{sup 3} M{sub Sun} yr{sup -1}, this timescale implies final stellar masses of the order of 10{sup 11}-10{sup 12} M{sub Sun }. The corresponding stellar mass function matches the observed mass function of passively evolving galaxies at z {approx}> 1. The comparison of the statistics for submillimeter and UV-selected galaxies suggests that the dust-free, UV bright phase is {approx}> 10{sup 2} times shorter than the submillimeter bright phase, implying that the dust must form soon after the onset of star formation. Using a single reference spectral energy distribution (SED; the one of the z Almost-Equal-To 2.3 galaxy SMM J2135-0102), our simple physical model is able to reproduce not only the LFs at different redshifts >1 but also the counts at wavelengths ranging from 250 {mu}m to Almost-Equal-To 1 mm. Owing to the steepness of the counts and their relatively broad frequency range, this result suggests that the dispersion of submillimeter SEDs of z > 1 galaxies around the reference one is rather small.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Higher order corrected thermodynamics and statistics of Kerr–Newman–Gödel black hole

In this paper, we consider the rotating charged Gödel black hole and study the effect of the higher order corrections of the entropy on the thermodynamics and statistics quantities of the Kerr–Newman–Gödel black hole. The leading order correction is logarithmic while higher-order terms are proportional to the inverse of the area of the black hole. We obtain modified thermodynamics and statistics and find that correction terms are important in the stability of the black hole.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Upper entropy axioms and lower entropy axioms

The paper suggests the concepts of an upper entropy and a lower entropy. We propose a new axiomatic definition, namely, upper entropy axioms, inspired by axioms of metric spaces, and also formulate lower entropy axioms. We also develop weak upper entropy axioms and weak lower entropy axioms. Their conditions are weaker than those of Shannon–Khinchin axioms and Tsallis axioms, while these conditions are stronger than those of the axiomatics based on the first three Shannon–Khinchin axioms. The subadditivity and strong subadditivity of entropy are obtained in the new axiomatics. Tsallis statistics is a special case of satisfying our axioms. Moreover, different forms of information measures, such as Shannon entropy, Daroczy entropy, Tsallis entropy and other entropies, can be unified under the same axiomatics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Testing new physics in oscillations at a neutrino factory

A neutrino factory is a potential successor to the upcoming generation of neutrino oscillation experiments and a possible precursor to next-generation muon colliders. Such a machine would provide a well characterized beam of , , , and neutrinos with comparable statistics. Here we show the sensitivity of a neutrino factory to new oscillation physics scenarios such as vector neutrino non-standard interactions and CPT violation. We study two different potential setups for a neutrino factory with different assumptions on charge identification in the far detector. We find that a neutrino factory can improve over most of the current constraints on these scenarios and over forecasted constraints by DUNE, even when doubling DUNE's statistics. Additionally, we find that a neutrino factory can break degeneracies between the standard oscillation parameters and neutrino non-standard interaction parameters present at DUNE.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

A kinetic-based regularization method for data science applications

We propose a physics-based regularization technique for function learning, inspired by statistical mechanics. By drawing an analogy between optimizing the parameters of an interpolator and minimizing the energy of a system, we introduce corrections that impose constraints on the lower-order moments of the data distribution. This minimizes the discrepancy between the discrete and continuum representations of the data, in turn allowing to access more favorable energy landscapes, thus improving the accuracy of the interpolator. Our approach improves performance in both interpolation and regression tasks, even in high-dimensional spaces. Unlike traditional methods, it does not require empirical parameter tuning, making it particularly effective for handling noisy data. We also show that thanks to its local nature, the method offers computational and memory efficiency advantages over Radial Basis Function interpolators, especially for large datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Study of UV Cu + Ne – CuBr laser lifetime by statistical methods

On the basis of a large amount of experimental data, statistical investigation of the average lifetime of a UV Cu + Ne – CuBr laser depending on ten input physical laser parameters is carried out. It is found that only three of the parameters have a substantial influence on the laser lifetime. Physical analysis and interpretation of the results are provided. (lasers)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Hadron production cross-sections at relativistic energies with large phase-space coverage - Paper 39

Accurate measurements of soft particle production in hadronic interactions at relativistic energies have long been an experimental challenge, in particular when the measurement is over a large final state phase-space, and when multiple combinations of beam and targets are investigated. Lacking quantitative predictions from the fundamental theory of quantum chromo-dynamics (QCD) in the non-perturbative sector, the study of soft hadronic physics needs to rely on precise, self-consistent, high-statistics data sets with full phase-space coverage and low systematic errors. Phenomenological models of particle production in hadronic collisions need such data to constrain their parameters, and possibly to discriminate among the underlying features of these models. In this article the 'soft' physics refers to production of particles with transverse momenta, pT, below 2 GeV/c, which comprises over 99% of the total production cross-section. It is also known as 'bulk' particle production, or the 'underlying event' in reference to the background of hard processes, particles produced with much larger transverse momentum which are usually described in the framework of perturbative QCD. Improving these models is of interest of the Radiation Protection and Shielding Division (RPSD) community, as well as the availability of accurate data with large phase space coverage. The NA49 collaboration has published new, high precision, and comprehensive sets of inclusive meson and baryon cross sections in p+p and p+C interactions over most of the available phase space with comparisons to past experimental results. The corresponding physics analysis presents a model-independent approach to soft hadronic physics and constitutes a novel approach to exploration of this non-perturbative sector of QCD. The precision study of p+A interactions may allow for differentiation between assumptions underlying different microscopic models of bulk particle production in relativistic hadronic collisions, and thus aid model development. The final data on inclusive particle production including the invariant double differential cross sections, the transversely integrated yields, and the developed interpolations, along with the published papers and other documents relevant to this work are conveniently available. (author)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Fast strength model characterization using Bayesian statistics

A variety of flow stress models exist with new models constantly being developed. These models aim to approximate the strength of materials in a variety of regimes from quasistatic loading through shock scenarios. All models contain an array of parameters which need to be tuned to the material under study. Some models perform well under limited conditions, requiring adjustment of the parameters when venturing outside of those predefined ranges. Other models perform well over a wide range of conditions with a set of parameters, but may be outperformed by other models optimized on a tighter range of conditions. Recent research by Los Alamos demonstrated the ability to optimize the Johnson Cook (JC) model using a set of 3 plate-impact experiments on Aluminum. They utilized Bayesian statistics and emulation to determine optimal parameters for the model with a quantification of parameter uncertainty. We present an extension of this capability to incorporate velocimetry from plate-impact tests, stress-strain data from split Hopkinson pressure bar and quasistatic compression tests, plus profiles from Taylor cylinders in a unified fashion. Statistically robust comparisons of the performance and uncertainty of different realizations of the JC flow stress model were carried out based on calibration to several possible combinations of these three different experiment types.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Evaluation of statistical variation of microstructural properties and temperature effects on creep fracture of Grade 91

This report describes three improvements made to a physically-based model for creep and creep rupture in Grade 91 steel developed as part of the Advanced Reactor Technologies program: 1. Progress on transitioning the model framework to the MOOSE finite element package to improve parallel scalability, increase the physical size of the simulations, and incorporate multiphysics effects into the model. 2. The development of a physically-based method of scaling the model parameters to accurately capture creep in Grade 91 for temperatures in the range of 450° to 500° C. 3. Extending the model to account for microstructural statistical variations, specifically capturing the effect of grain boundary energy on the physical parameters underling the model for grain boundary void nucleation and cavitation. Put together, these improvements result in an accurate, predictive model for the physical response of Grade 91 steel over the expected use temperature range for the material in future liquid metal cooled fast reactors. The model can be used to more accurately predict engineering properties of the material for very long service lives, which could lead to safer, more economical future advanced reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗