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At least 1,549 records · Page 86

Finite-temperature many-body perturbation theory for electrons: Algebraic recursive definitions, second-quantized derivation, linked-diagram theorem, general-order algorithms, and grand canonical and canonical ensembles

A comprehensive and detailed account is presented for the finite-temperature many-body perturbation theory for electrons that expands in power series all thermodynamic functions on an equal footing. Algebraic recursions in the style of the Rayleigh–Schrödinger perturbation theory are derived for the grand potential, chemical potential, internal energy, and entropy in the grand canonical ensemble and for the Helmholtz energy, internal energy, and entropy in the canonical ensemble, leading to their sum-over-states analytical formulas at any arbitrary order. For the grand canonical ensemble, these sum-over-states formulas are systematically transformed to sum-over-orbitals reduced analytical formulas by the quantum-field-theoretical techniques of normal-ordered second quantization and Feynman diagrams extended to finite temperature. It is found that the perturbation corrections to energies entering the recursions have to be treated as a nondiagonal matrix, whose off-diagonal elements are generally nonzero within a subspace spanned by degenerate Slater determinants. They give rise to a unique set of linked diagrams—renormalization diagrams—whose resolvent lines are displaced upward, which are distinct from the well-known anomalous diagrams of which one or more resolvent lines are erased. A linked-diagram theorem is introduced that proves the size-consistency of the finite-temperature many-body perturbation theory at any order. General-order algorithms implementing the recursions establish the convergence of the perturbation series toward the finite-temperature full-configuration-interaction limit unless the series diverges. As a result, the normal-ordered Hamiltonian at finite temperature sheds light on the relationship between the finite-temperature Hartree–Fock and first-order many-body perturbation theories.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Improving neutrino energy estimation of charged-current interaction events with recurrent neural networks in MicroBooNE

We present a deep learning-based method for estimating the neutrino energy of charged-current neutrino-argon interactions. We employ a recurrent neural network (RNN) architecture for neutrino energy estimation in the MicroBooNE experiment, utilizing liquid argon time projection chamber (LArTPC) detector technology. Traditional energy estimation approaches in LArTPCs, which largely rely on reconstructing and summing visible energies, often experience sizable biases and resolution smearing because of the complex nature of neutrino interactions and the detector response. The estimation of neutrino energy can be improved after considering the kinematics information of reconstructed final-state particles. Utilizing kinematic information of reconstructed particles, the deep learning-based approach shows improved resolution and reduced bias for the muon neutrino Monte Carlo simulation sample compared to the traditional approach. In order to address the common concern about the effectiveness of this method on experimental data, the RNN-based energy estimator is further examined and validated with dedicated data-simulation consistency tests using MicroBooNE data. We also assess its potential impact on a neutrino oscillation study after accounting for all statistical and systematic uncertainties and show that it enhances physics sensitivity. This method has good potential to improve the performance of other physics analyses. Published by the American Physical Society 2024

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Inverse design of a pyrochlore lattice of DNA origami through model-driven experiments

Sophisticated statistical mechanics approaches and human intuition have demonstrated the possibility of self-assembling complex lattices or finite-size constructs. However, attempts so far have mostly only been successful in silico and often fail in experiment because of unpredicted traps associated with kinetic slowing down (gelation, glass transition) and competing ordered structures. Theoretical predictions also face the difficulty of encoding the desired interparticle interaction potential with the experimentally available nano- and micrometer-sized particles. To overcome these issues, we combine SAT assembly (a patchy-particle interaction design algorithm based on constrained optimization) with coarse-grained simulations of DNA nanotechnology to experimentally realize trap-free self-assembly pathways. In this paper, we use this approach to assemble a pyrochlore three-dimensional lattice, coveted for its promise in the construction of optical metamaterials, and characterize it with small-angle x-ray scattering and scanning electron microscopy visualization.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Calibration of the Diffusivity Predictions of Centipede Using Approximate Bayesian Computation and Applications in Nyx (Engineering Scale) and Xolotl-MARMOT (Meso-Scale) Simulations

Fission gas evolution and release in UO 2 nuclear fuel are important fuel performance metrics and occur in several distinct stages: 1) nucleation, growth and resolution of intra-granular bubbles, 2) diffusion to grain boundaries and 3) nucleation and growth of bubbles at grain boundaries, which eventually form a connected network (percolation) enabling release of gas from grain boundaries through connections to triple junctions, grain edges or free surfaces. The NE-SciDAC project is developing several computational tools to model this problem, which are connected in a hierarchical multi-scale framework. The information transfer in the multi-scale framework is a critical step that, in addition to best-estimates, should include uncertainty quantification. Despite taking a first-principles multi-scale approach, there is a need to perform parameter calibration to ensure consistency with available experimental data. In the present study, uncertainty quantification (UQ) and parameter calibration is demonstrated for one of the lower length scale codes in the multi-scale framework (Centipede) and then the results, including instances of the propagated uncertainties, are used in other codes within the framework, specifically Nyx and Xolotl-MARMOT. We calibrated the model parameters in Centipede, a computer code used to predict diffusivities of uranium (U) and xenon (Xe) in the context of the simulation of fission gas in uranium oxide (UO 2 ) nuclear fuel. The Centipede code depends on 183 parameters, all of which are subject to uncertainty. The three data sets used in our calibration effort are taken from the literature. This data is available as a set of measurements, including measurement errors. Our goal is to calibrate a statistical model that predicts both the value of the measurement and the uncertainty associated with the measurement. We perform a Bayesian calibration of the model parameters using a dedicated approximate Bayesian computation (ABC) likelihood function. To avoid excessive computational costs, we replace the expensive Centipede simulation code by a higher-order surrogate model, constructed using only the 9 most important parameters. These important parameters are identified by a preliminary global sensitivity analysis (GSA) study. Among the important parameters are T0 (the temperature at which UO 2 is perfectly stoichiometric) and Hf_pO2 (the temperature dependence of the oxygen (O) partial pressure) that should be considered as operating conditions to be estimated along with the other parameters. We consider two different cases: one where we define one set of these operating conditions for all data sets, and one where we define distinct operating condition parameters for each data set. The Xe diffusivities predicted by the latter case show distinct features that could not be observed in the former. Next, we use the diffusivity predictions by Centipede as input to Nyx, a reduced order fuel performance code focused on gas behavior alone, in order to estimate quantities associated with inter-granular bubble formation at conditions specified by the experiments. Finally, the diffusivities obtained from the calibrated Centipede runs were used in coupled Xolotl-MARMOT simulations of intra- and inter-granular gas evolution. The results are compared to simulations using the baseline diffusivities from Turnbull et al.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A correlative study of SSC's, interplanetary shocks, and solar activity

A total of 93 SSC's were examined during the four year period from 1968 to 1971 at and near the peak of the solar activity cycle. Of the 93 SSC's 81 could be associated with solar activity, such as solar flares and radio bursts of Type II and Type IV. The mean propagation speeds of these flare-associated events ranged from 400 to 1000 km/sec with an average speed of 600-700 km/sec. Disturbances associated with 48 of the SSC's have been studied in detail using the corresponding interplanetary (IP) magnetic field, and plasma data when they were available. It was found that 41 of the 48 disturbances corresponded to IP shock waves, and the remaining seven events were tangential discontinuities. Thirty percent of the IP shocks had thick structure (i.e. the magnetic field jump across the shock occurred over a distance much greater than 50 proton Larmor radii). Also given is a statistical study of the gross geometry of a typical or average shock surface based on multiple spacecraft sightings and their relative orientation with respect to the solar flare. It is suggested that a typical shock front propagating out from the sun at l AU has a radius of curvature on the order of l AU. Also given are some general properties of oblique IP flare-shocks.

Chao, J. K.↗

Evaluation of digitally corrected ERTS imagery

Utilizing all digital processing techniques, precision rectified ERTS multispectral imagery have been produced. Precision geometric correction is accomplished by: (1) utilizing a low order piecewise approximation to the image distortions; (2) incorporating spacecraft attitude refinement derived from ground control points utilized in a Kalman filter; (3) utilizing interpolation techniques which preserve value and slope continuity in the image data. Imagery produced is represented in a UTM projection, and has been evaluated for precision by statistical and analytical methods. Extrapolations to modest size computers indicate good throughput with no sacrifice in precision.

Rifman, S. S.↗

Statistical comparison of pooled nitrogen washout data of various altitude decompression response groups

This analysis was done to determine whether various decompression response groups could be characterized by the pooled nitrogen (N2) washout profiles of the group members, pooling individual washout profiles provided a smooth time dependent function of means representative of the decompression response group. No statistically significant differences were detected. The statistical comparisons of the profiles were performed by means of univariate weighted t-test at each 5 minute profile point, and with levels of significance of 5 and 10 percent. The estimated powers of the tests (i.e., probabilities) to detect the observed differences in the pooled profiles were of the order of 8 to 30 percent.

Edwards, B. F.↗

Spectral characteristics and the extent of paleosols of the Palouse formation

Thematic mapping data was analyzed and verified by comparison to previously gathered transect samples and to aerial photographs. A bare-soil field with exposed paleosols characterized by slight enrichment of iron was investigated. Spectral relationships were first investigated statistically by creating a data set with DN values spatially matched as nearly as possible to field sample points. Chemical data for each point included organic carbon, free iron oxide, and amorphous iron content. The chemical data, DN values, and various band ratios were examined with the program package Statistix in order to find the combinations of reflectance data most likely to show a relationship which would dependably separate the exposed paleosols from the other soils. Cluster analysis and Fastclas classification procedures were applied to the most promising of the band ratio combinations.

Frazier, B. E.↗

Numerical Modeling of Spray Combustion with an Unstructured-Grid Method

The present unstructured-grid method follows strictly the basic finite volume forms of the conservation laws of the governing equations for the entire flow domain. High-order spatially accurate formulation has been employed for the numerical solutions of the Navier-Stokes equations. A two-equation k-epsilon turbulence model is also incorporated in the unstructured-grid solver. The convergence of the resulted linear algebraic equation is accelerated with preconditioned Conjugate Gradient method. A statistical spray combustion model has been incorporated into the present unstructured-grid solver. In this model, spray is represented by discrete particles, rather than by continuous distributions. A finite number of computational particles are used to predict a sample of total population of particles. Particle trajectories are integrated using their momentum and motion equations and particles exchange mass, momentum and energy with the gas within the computational cell in which they are located. The interaction calculations are performed simultaneously and eliminate global iteration for the two-phase momentum exchange. A transient spray flame in a high pressure combustion chamber is predicted and then the solution of liquid-fuel combusting flow with a rotating cup atomizer is presented and compared with the experimental data. The major conclusion of this investigation is that the unstructured-grid method can be employed to study very complicated flow fields of turbulent spray combustion. Grid adaptation can be easily achieved in any flow domain such as droplet evaporation and combustion zone. Future applications of the present model can be found in the full three-dimensional study of flow fields of gas turbine and liquid propulsion engine combustion chambers with multi-injectors.

Shang, H. M.↗

A simple model for straggling evaluation

Some straggling models had largely been abandoned in favor of Monte Carlo simulations of straggling which are accurate but time consuming, limiting their application in practice. The difficulty of simple analytic models is the failure to give accurate values past 85% of the particle range. A simple model is derived herein based on a second order approximation upon which rapid analysis tools are developed for improved understanding of material charged particle transmission properties. Published by Elsevier Science B.V.

Models, Statistical↗

Time-Resolved PIV for Space-Time Correlations in Hot Jets

Temporally Resolved Particle Image Velocimetry (TR-PIV) is being used to characterize the decay of turbulence in jet flows a critical element for understanding the acoustic properties of the flow. A TR-PIV system, developed in-house at the NASA Glenn Research Center, is capable of acquiring planar PIV image frame pairs at up to 10 kHz. The data reported here were collected at Mach numbers of 0.5 and 0.9 and at temperature ratios of 0.89 and 1.76. The field of view of the TR-PIV system covered 6 nozzle diameters along the lip line of the 50.8 mm diameter jet. The cold flow data at Mach 0.5 were compared with hotwire anemometry measurements in order to validate the new TR-PIV technique. The axial turbulence profiles measured across the shear layer using TR-PIV were thinner than those measured using hotwire anemometry and remained centered along the nozzle lip line. The collected TR-PIV data illustrate the differences in the single point statistical flow properties of cold and hot jet flows. The planar, time-resolved velocity records were then used to compute two-point space-time correlations of the flow at the Mach 0.9 flow condition. The TR-PIV results show that there are differences in the convective velocity and growth rate of the turbulent structures between cold and hot flows at the same Mach number.

Wernet, Mark P.↗

Comparison of Iterative and Non-Iterative Strain-Gage Balance Load Calculation Methods

The accuracy of iterative and non-iterative strain-gage balance load calculation methods was compared using data from the calibration of a force balance. Two iterative and one non-iterative method were investigated. In addition, transformations were applied to balance loads in order to process the calibration data in both direct read and force balance format. NASA's regression model optimization tool BALFIT was used to generate optimized regression models of the calibration data for each of the three load calculation methods. This approach made sure that the selected regression models met strict statistical quality requirements. The comparison of the standard deviation of the load residuals showed that the first iterative method may be applied to data in both the direct read and force balance format. The second iterative method, on the other hand, implicitly assumes that the primary gage sensitivities of all balance gages exist. Therefore, the second iterative method only works if the given balance data is processed in force balance format. The calibration data set was also processed using the non-iterative method. Standard deviations of the load residuals for the three load calculation methods were compared. Overall, the standard deviations show very good agreement. The load prediction accuracies of the three methods appear to be compatible as long as regression models used to analyze the calibration data meet strict statistical quality requirements. Recent improvements of the regression model optimization tool BALFIT are also discussed in the paper.

Ulbrich, N.↗

Time Resolved PIV for Space-Time Correlations in Hot Jets

Temporally Resolved Particle Image Velocimetry (TR-PIV) is the newest and most exciting tool recently developed to support our continuing efforts to characterize and improve our understanding of the decay of turbulence in jet flows -- a critical element for understanding the acoustic properties of the flow. A new TR-PIV system has been developed at the NASA Glenn Research Center which is capable of acquiring planar PIV image frame pairs at up to 25 kHz. The data reported here were collected at Mach numbers of 0.5 and 0.9 and at temperature ratios of 0.89 and 1.76. The field of view of the TR-PIV system covered 6 nozzle diameters along the lip line of the 50.8 mm diameter jet. The cold flow data at Mach 0.5 were compared with hotwire anemometry measurements in order to validate the new TR-PIV technique. The axial turbulence profiles measured across the shear layer using TR-PIV were thinner than those measured using hotwire anemometry and remained centered along the nozzle lip line. The collected TR-PIV data illustrate the differences in the single point statistical flow properties of cold and hot jet flows. The planar, time-resolved velocity records were then used to compute two-point space-time correlations of the flow at the Mach 0.9 flow condition. The TR-PIV results show that there are differences in the convective velocity and growth rate of the turbulent structures between cold and hot flows at the same Mach number

Wernet, Mark P.↗

A Practical Methodology for Quantifying Random and Systematic Components of Unexplained Variance in a Wind Tunnel

This paper documents a check standard wind tunnel test conducted in the Langley 0.3-Meter Transonic Cryogenic Tunnel (0.3M TCT) that was designed and analyzed using the Modern Design of Experiments (MDOE). The test designed to partition the unexplained variance of typical wind tunnel data samples into two constituent components, one attributable to ordinary random error, and one attributable to systematic error induced by covariate effects. Covariate effects in wind tunnel testing are discussed, with examples. The impact of systematic (non-random) unexplained variance on the statistical independence of sequential measurements is reviewed. The corresponding correlation among experimental errors is discussed, as is the impact of such correlation on experimental results generally. The specific experiment documented herein was organized as a formal test for the presence of unexplained variance in representative samples of wind tunnel data, in order to quantify the frequency with which such systematic error was detected, and its magnitude relative to ordinary random error. Levels of systematic and random error reported here are representative of those quantified in other facilities, as cited in the references.

Deloach, Richard↗

Time Resolved Particle Image Velocimetry in Nozzle Flow

Temporally resolved particle image velocimetry (TR-PIV) is the newest and most exciting tool recently developed to support our continuing efforts to characterize and improve our understanding of the decay of turbulence in jet flows—a critical element for understanding the acoustic properties of the flow. A new TR-PIV system has been developed at the NASA Glenn Research Center which is capable of acquiring planar PIV image frame pairs at up to 25 kHz. The data reported here were collected at Mach numbers of 0.5 and 0.9 and at temperature ratios of 0.89 and 1.76. The field of view of the TR-PIV system covered six nozzle diameters along the lip line of the 50.8 mm diameter jet. The cold flow data at Mach 0.5 were compared with hotwire anemometry measurements in order to validate the new TR-PIV technique. The axial turbulence profiles measured across the shear layer using TR-PIV were thinner than those measured using hotwire anemometry and remained centred along the nozzle lip line. The collected TR-PIV data illustrate the differences in the single point statistical flow properties of cold and hot jet flows. The planar, time-resolved velocity records were then used to compute two-point space–time correlations of the flow at the Mach 0.9 flow condition. The TR-PIV results show that there are differences in the convective velocity and growth rate of the turbulent structures between cold and hot flows at the same Mach number.

Temporally Resolved Particle Image Velocimetry↗

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials

Atomic disorder can strongly influence material properties such as charge transport, optical response, and catalytic activity. However, efficiently modeling these disorder effects remains challenging for first-principles methods due to the cost of sampling large configurational spaces and computing complex physical quantities. Recent advances of machine learning techniques, particularly graph neural networks (GNNs), has enabled the efficient and accurate predictions of complex material properties, offering promising tools for studying disordered systems. In this work, we present a general machine-learning-assisted computational framework that integrates equivariant GNNs with Monte Carlo simulations to compute the thermodynamic and ensemble-averaged functional properties of disordered materials. Using the surface-termination-disordered MXene monolayer Ti 3 C 2 T 2–x as a representative system, we find that electrical conductivity exhibits an emergent peak near the order–disorder phase transition temperature due to the interplay between electron scattering and doping. In contrast, optical conductivity remains largely insensitive to local atomic disorder and reflects the global surface chemical composition. These results highlight the role of atomic disorder in affecting material properties and demonstrate the potential of our approach for statistically modeling disorder effects in a wide range of materials such as high-entropy alloys and spin liquids.

MXene↗

An analytically tractable marked power spectrum

The increasing precision of cosmology data in the modern era is calling for methods to allow the extraction of non-Gaussian information using tools beyond two-point statistics. The marked power spectrum has the potential to extract beyond two-point information in a computationally efficient way while using much of the infrastructure already available for the power spectrum. In this work we explore the marked power spectrum from an analytical perspective. In particular, we explore a low-order polynomial for the mark that allows us to better control the theoretical uncertainties and we show that with minimal new degrees of freedom the analytical results match measurements from N-body simulations for both the matter field and biased tracers in redshift space. Finally, we show that even within the limited forms of mark that we consider, there are degeneracies that can be broken by inclusion of the marked auto-spectrum or the cross-spectrum with the unmarked field. I n conclusion, we discuss future theoretical developments that would enable us to apply this approach to survey data.

79 ASTRONOMY AND ASTROPHYSICS↗

Broadband quadrature-squeezed vacuum and nonclassical photon number correlations from a nanophotonic device

We report demonstrations of both quadrature-squeezed vacuum and photon number difference squeezing generated in an integrated nanophotonic device. Squeezed light is generated via strongly driven spontaneous four-wave mixing below threshold in silicon nitride microring resonators. The generated light is characterized with both homodyne detection and direct measurements of photon statistics using photon number–resolving transition-edge sensors. We measure 1.0(1) decibels of broadband quadrature squeezing (~4 decibels inferred on-chip) and 1.5(3) decibels of photon number difference squeezing (~7 decibels inferred on-chip). Nearly single temporal mode operation is achieved, with measured raw unheralded second-order correlations g (2) as high as 1.95(1). Multiphoton events of over 10 photons are directly detected with rates exceeding any previous quantum optical demonstration using integrated nanophotonics. These results will have an enabling impact on scaling continuous variable quantum technology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗