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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Thermally and vibrationally induced conformational isomerizations, infrared spectra, and photochemistry of gallic acid in low-temperature matrices

Near-infrared (near-IR) narrowband selective vibrational excitation and annealing of gallic acid (3,4,5-trihydroxybenzoic acid) isolated in cryogenic matrices were used to induce interconversions between its most stable conformers. The isomerizations were probed by infrared spectroscopy. An extensive set of quantum chemical calculations, carried out at the DFT(B3LYP)/6-311++G(d,p) level of approximation, was used to undertake a detailed analysis of the ground state potential energy surface of the molecule. This investigation of the molecule conformational space allowed extracting mechanistic insights into the observed annealing- or near-IR-induced isomerization processes. The infrared spectra of the two most stable conformers of gallic acid in N{sub 2}, Xe, and Ar matrices were fully assigned. Finally, the UV-induced photochemistry of the matrix isolated compound was investigated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Measurement and interpretation of Mueller matrices of barley leaves

We report the results of measuring Mueller matrices for three groups of leaf samples of common barley (Hordeum vulgare): Chlorina mutant, Chlorina etiolated mutant and Cesaer varieties. The repeatability of the measurement results of Mueller matrices of such a complex and highly depolarising object as a plant leaf is demonstrated. It is shown that the barley leaves of these three groups can be reliably identified both at forward scattering and backward scattering modes; the best results are obtained in the case of forward scattering. In both cases, the most informative matrix elements are identified. It is also shown that at backward scattering mode linear dichroism comes out, the magnitude of which increases with decreasing observation angle. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Cosmic topology. Part IIa. Eigenmodes, correlation matrices, and detectability of orientable Euclidean manifolds

Abstract If the Universe has non-trivial spatial topology, observables depend on both the parameters of the spatial manifold and the position and orientation of the observer. In infinite Euclidean space, most cosmological observables arise from the amplitudes of Fourier modes of primordial scalar curvature perturbations. Topological boundary conditions replace the full set of Fourier modes with specific linear combinations of selected Fourier modes as the eigenmodes of the scalar Laplacian. We present formulas for eigenmodes in orientable Euclidean manifolds with the topologiesE 1 –E 6 ,E 11 ,E 12 ,E 16 , andE 18 that encompass the full range of manifold parameters and observer positions, generalizing previous treatments. Under the assumption that the amplitudes of primordial scalar curvature eigenmodes are independent random variables, for each topology we obtain the correlation matrices of Fourier-mode amplitudes (of scalar fields linearly related to the scalar curvature) and the correlation matrices of spherical-harmonic coefficients of such fields sampled on a sphere, such as the temperature of the cosmic microwave background (CMB). We evaluate the detectability of these correlations given the cosmic variance of the observed CMB sky. We find that topologies where the distance to our nearest clone is less than about 1.2 times the diameter of the last scattering surface of the CMB give a correlation signal that is larger than cosmic variance noise in the CMB. This implies that if cosmic topology is the explanation of large-angle anomalies in the CMB, then the distance to our nearest clone is not much larger than the diameter of the last scattering surface. We argue that the topological information is likely to be better preserved in three-dimensional data, such as will eventually be available from large-scale structure surveys.

Astronomy & Astrophysics↗
DOE OSTI2025

Semi-analytical covariance matrices for two-point correlation function for DESI 2024 data

We present an optimized way of producing the fast semi-analytical covariance matrices for the Legendre moments of the two-point correlation function, taking into account survey geometry and mimicking the non-Gaussian effects. We validate the approach on simulated (mock) catalogs for different galaxy types, representative of the Dark Energy Spectroscopic Instrument (DESI) Data Release 1, used in 2024 analyses. We find only a few percent differences between the mock sample covariance matrix and our results, which can be expected given the approximate nature of the mocks, although we do identify discrepancies between the shot-noise properties of the DESI fiber assignment algorithm and the faster approximation (emulator) used in the mocks. Importantly, we find a close agreement (≤ 8% relative differences) in the projected errorbars for distance scale parameters for the baryon acoustic oscillation measurements. This confirms our method as an attractive alternative to simulation-based covariance matrices, especially for non-standard models or galaxy sample selections, making it particularly relevant to the broad current and future analyses of DESI data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Covariance matrices for variance-suppressed simulations

ABSTRACT Cosmological N-body simulations provide numerical predictions of the structure of the Universe against which to compare data from ongoing and future surveys, but the growing volume of the Universe mapped by surveys requires correspondingly lower statistical uncertainties in simulations, usually achieved by increasing simulation sizes at the expense of computational power. It was recently proposed to reduce simulation variance without incurring additional computational costs by adopting fixed-amplitude initial conditions. This method has been demonstrated not to introduce bias in various statistics, including the two-point statistics of galaxy samples typically used for extracting cosmological parameters from galaxy redshift survey data, but requires us to revisit current methods for estimating covariance matrices of clustering statistics for simulations. In this work, we find that it is not trivial to construct covariance matrices analytically for fixed-amplitude simulations, but we demonstrate that ezmock (Effective Zel’dovich approximation mock catalogue), the most efficient method for constructing mock catalogues with accurate two- and three-point statistics, provides reasonable covariance matrix estimates for such simulations. We further examine how the variance suppression obtained by amplitude-fixing depends on three-point clustering, small-scale clustering, and galaxy bias, and propose intuitive explanations for the effects we observe based on the ezmock bias model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

rascalc : a jackknife approach to estimating single- and multitracer galaxy covariance matrices

ABSTRACT To make use of clustering statistics from large cosmological surveys, accurate and precise covariance matrices are needed. We present a new code to estimate large-scale galaxy two-point correlation function (2PCF) covariances in arbitrary survey geometries that, due to new sampling techniques, runs ∼104 times faster than previous codes, computing finely binned covariance matrices with negligible noise in less than 100 CPU-hours. As in previous works, non-Gaussianity is approximated via a small rescaling of shot noise in the theoretical model, calibrated by comparing jackknife survey covariances to an associated jackknife model. The flexible code, rascalc, has been publicly released, and automatically takes care of all necessary pre- and post-processing, requiring only a single input data set (without a prior 2PCF model). Deviations between large-scale model covariances from a mock survey and those from a large suite of mocks are found to be indistinguishable from noise. In addition, the choice of input mock is shown to be irrelevant for desired noise levels below ∼105 mocks. Coupled with its generalization to multitracer data sets, this shows the algorithm to be an excellent tool for analysis, reducing the need for large numbers of mock simulations to be computed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Decorrelating the errors of the galaxy correlation function with compact transformation matrices

Abstract Covariance matrix estimation is a persistent challenge for cosmology, often requiring a large number of synthetic mock catalogues. The off-diagonal components of the covariance matrix also make it difficult to show representative error bars on the 2-point correlation function (2PCF) since errors computed from the diagonal values of the covariance matrix greatly underestimate the uncertainties. We develop a routine for decorrelating the projected and anisotropic 2PCF with simple and scale-compact transformations on the 2PCF. These transformation matrices are modelled after the Cholesky decomposition and the symmetric square root of the Fisher matrix. Using mock catalogues, we show that the transformed projected and anisotropic 2PCF recover the same structure as the original 2PCF while producing largely decorrelated error bars. Specifically, we propose simple Cholesky-based transformation matrices that suppress the off-diagonal covariances on the projected 2PCF by ${\sim } 95{{\ \rm per\ cent}}$ and that on the anisotropic 2PCF by ${\sim } 87{{\ \rm per\ cent}}$. These transformations also serve as highly regularized models of the Fisher matrix, compressing the degrees of freedom so that one can fit for the Fisher matrix with a much smaller number of mocks.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Quantum simulation of quantum phase transitions using the convex geometry of reduced density matrices

Transitions of many-particle quantum systems between distinct phases at absolute-zero temperature, known as quantum phase transitions, require an exacting treatment of particle correlations. Here in this work, we present a general quantum-computing approach to quantum phase transitions that exploits the geometric structure of reduced density matrices. While typical approaches to quantum phase transitions examine discontinuities in the order parameters, the origin of phase transitions—their order parameters and symmetry breaking—can be understood geometrically in terms of the set of two-particle reduced density matrices (2-RDMs). The convex set of 2-RDMs provides a comprehensive map of the quantum system including its distinct phases as well as the transitions connecting these phases. Because 2-RDMs can potentially be computed on quantum computers at nonexponential cost, even when the quantum system is strongly correlated, they are ideally suited for a quantum-computing approach to quantum phase transitions. We compute the convex set of 2-RDMs for a Lipkin-Meshkov-Glick spin model on IBM superconducting-qubit quantum processors. Even though computations are limited to few-particle models due to device noise, comparisons with a classically solvable 1000-particle model reveal that the finite-particle quantum solutions capture the key features of the phase transitions including the strong correlation and the symmetry breaking.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2011

Spectroscopy of barium atoms in liquid and solid helium matrices

We present an exhaustive overview of optical absorption and laser-induced fluorescence lines of Ba atoms in liquid and solid helium matrices in visible and near-infrared spectral ranges. Due to the increased density of isolated atoms, we have found a large number of spectral lines that were not observed in condensed helium matrices before. We have also measured the lifetimes of metastable states. The lowest {sup 3}D{sub 1} metastable state has lifetime of 2.6 s and can be used as an intermediate state in two-step excitations of high-lying states. Various matrix-induced radiationless population transfer channels have been identified.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2011

Neutrino mass matrices with M{sub ee}=0

Motivated by the possibility that the amplitude for neutrinoless double beta decay may be much smaller than the planned sensitivity of future experiments, we study Ansaetze for the neutrino mass matrix with M{sub ee}=0. For the case in which CP is conserved, we consider two classes of real-valued mass matrices: ''Class I'' defined by |M{sub e{mu}|}=|M{sub e{tau}|}, and ''Class II'' defined by |M{sub {mu}{mu}|}=|M{sub {tau}{tau}|}. The important phenomenological distinction between the two is that Class I permits only small values of V{sub e3} up to {approx}0.03, while Class II admits large values of V{sub e3} up to its empirical upper limit of 0.22. Then we introduce CP-violating complex phases into the mass matrix. We show that it is possible to have tribimaximal mixing with M{sub ee}=0 and |M{sub {mu}{tau}|}=|M{sub {mu}{mu}|}=|M{sub {tau}{tau}|} if the Majorana phase angles are {+-}{pi}/4. Alternatively, for smaller values of |M{sub {mu}{tau}|}=|M{sub {mu}{mu}|}=|M{sub {tau}{tau}|} it is possible to obtain |V{sub e3}|{approx}0.2 and generate relatively large CP-violating amplitudes. To eliminate phase redundancy, we emphasize rephasing any mass matrix with M{sub ee}=0 into a standard form with two complex phases. The discussion alternates between analytical and numerical but remains purely phenomenological, without any attempt to derive mass matrices from a fundamental theory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Generalized Analytical Estimation of Sensitivity Matrices in Unbalanced Distribution Networks

Fast and accurate estimation of sensitivity matrices is significant for the enhancement of distribution system modeling and automation. Analytical estimations have mainly focused on voltage magnitude sensitivity to active/reactive power injections for unbalanced networks with Wye-connected loads and neglecting DERs' smart inverter functionality. Hence, this paper enhances the scope of analytical estimation of sensitivity matrices for unbalanced networks with 1- Φ, 2- Φ, and 3- Φ Delta/Wye-connected loads, DERs with smart inverter functionality, and substation/line step-voltage regulators (SVR). A composite bus model comprising of DER, Delta- and Wye-connected load is proposed to represent a generic distribution bus, which can be simplified to load, PV, or voltage-controlled bus as required. Furthermore, the proposed matrix-based analytical method consolidates voltage magnitude and angle sensitivity to active/reactive power injection and tap-position of all SVRs into a single algorithm. Extensive case studies on IEEE and EPRI networks show the accuracy and wide scope of the proposed algorithm compared to the existing benchmark method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Quickest Detection for Changes in Maximal kNN Coherence of Random Matrices

This paper addresses the problem of quickest detection of a change in the maximal coherence between columns of a n p random matrix based on a sequence of matrix observations having a single unknown change point. The random matrix is assumed to have identically distributed rows and the maximal coherence is defined as the largest of the ( 2 p) correlation coefficients associated with any row. Likewise the κ nearest neighbor (kNN) coherence is defined as the κ-th largest of these correlation coefficients. The forms of the preand postchange distributions of the observed matrices are assumed to belong to the family of elliptically contoured densities with sparse dispersion matrices but are otherwise unknown. A nonparametric stopping rule is proposed that is based on the maximal kNN sample coherence between columns of each observed random matrix. This is a summary statistic that is related to a test of existence of a hub vertex in a sample correlation graph having degree at least κ. Performance bounds on the delay and false alarm performance of the proposed stopping rule are obtained in the purely high-dimensional regime where p → ∞ and n is fixed. When the prechange dispersion matrix is diagonal it is shown that, among all functions of the proposed summary statistic, the proposed stopping rule is asymptotically optimal under a minimax quickest change detection model as the stopping threshold approaches infinity. Furthermore, the theory developed also applies to sequential hypothesis testing and fixed sample size tests.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2011

Sensitivity analysis of a geometric calibration method using projection matrices for digital tomosynthesis systems

Purpose: To study the sensitivity of a geometric calibration method using projection matrices for digital tomosynthesis systems. Methods: A generic geometric calibration method for tomographic imaging systems has been presented in our previous work. The method involves a scan of a calibration phantom with multiple markers. Their locations in projection images are detected and are associated with their 3D coordinates to compute 3x4 projection matrices, which can be used in subsequent image reconstruction. The accuracy of geometric calibration may be affected by errors in the input data of marker positions. The effects of errors may depend on the number of markers and the volume surrounded by them in 3D space. This work analyzed the sensitivity of the calibration method to the above factors. A 6 cm CIRS breast research phantom and a prototype breast tomosynthesis system were used for our tests. A high contrast ring and two small speck groups were reconstructed in various testing cases for comparison. To achieve quantitative assessment, a 15x15 point detection mask was adopted for detecting signals and for computing changes between testing cases and the regular geometric calibration. Results: When 3D coordinates and 2D projections of markers were accurate, all tested numbers of markers, 6-44, provided similar high quality reconstructions of the ring and the two speck groups. Errors in marker positions resulted in image degradations and signal changes, which increased with fewer markers and smaller volume surrounded by markers in the 3D object space. Signal changes of small specks were more significant than those of the ring. Errors in marker projections produced drastic image degradations. Coplanar marker placement caused a failure in projection matrix computation. Conclusions: For practical geometric calibration phantom design, ample markers are desired. They need to have a large volumetric coverage in the 3D space and be far from being coplanar. Precise determination of marker projections on detector planes is crucial for accurate geometric calibration and for small object detection using the reconstructed images.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

A customized MOF-polymer composite for rapid gold extraction from water matrices

With the fast-growing accumulation of electronic waste and rising demand for rare metals, it is compelling to develop technologies that can promotionally recover targeted metals, like gold, from waste, a process referred to as urban mining. Thus, there is increasing interest in the design of materials to achieve rapid, selective gold capture while maintaining high adsorption capacity, especially in complex aqueous-based matrices. Here, a highly porous metal-organic framework (MOF)–polymer composite, BUT-33–poly(para-phenylenediamine) (PpPD), is assessed for gold extraction from several matrices including river water, seawater, and leaching solutions from CPUs. BUT-33–PpPD exhibits a record-breaking extraction rate, with high Au3+ removal efficiency (>99%) within seconds (less than 45 s), a competitive capacity (1600 mg/g), high selectivity, long-term stability, and recycling ability. Furthermore, the high porosity and redox adsorption mechanism were shown to be underlying reasons for the material’s excellent performance. Given the accumulation of recovered metallic gold nanoparticles inside, the material was also efficiently applied as a catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Phase composition and radiation stability of matrices for isolation of REE-actinide waste

Safe treatment with highly radioactive wastes from processing of irradiated fuel is a key problem at the final stage of the nuclear energy cycle. The waste prod ucts are currently immobilized in glassy matrices for loading in underground storage [1]. Glasses are insuf ficiently stable for isolation of long living radionu clides, including actinides. It is suggested to fraction ate such wastes and include long living nuclides in the most stable crystalline matrices in order to increase safety [2]. The available technologies allow us to sepa rate actinides (U, Np, Pu), the REE–actinide compo nent, and products of decay.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Dispersion of Lifetimes of Excited States of Single Molecules in Organic Matrices at Ultralow Temperatures

Fluorescence excitation spectra of single terrylene molecules in transparent naphthalene and polyethylene matrices at ultralow (30–100 mK) temperatures have been studied under the conditions where the widths of zero-phonon spectral lines are determined only by the lifetime T{sub 1} of the excited electronic state. The experimentally observed dispersion of T{sub 1} values for identical molecules is attributed to local field effects, which are responsible for the dependence of T{sub 1} on the effective value of refractive index n of the matrix, which is characteristic of the localization region of each molecule. It has been shown that the dependence T{sub 1}(n) for ensembles of point emitters in organic matrices is satisfactorily explained within the model of a “virtual cavity” around the emitter inside a continuous medium, as well as within the developed quantum kinetic approach including various contributions of the local environment to the lifetime T{sub 1}. The recalculation of average T{sub 1} values to the corresponding n values with the use of the expressions obtained for T{sub 1}(n) has shown that the difference of the calculated refractive indices of naphthalene and polyethylene from the well-known tabulated n values is less than 1%.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Explicit Quantum Circuits for Block Encodings of Certain Sparse Matrices

Many standard linear algebra problems can be solved on a quantum computer by using recently developed quantum linear algebra algorithms that make use of block encodings and quantum eigenvalue/singular value transformations. A block encoding embeds a properly scaled matrix of interest A in a larger unitary transformation U that can be decomposed into a product of simpler unitaries and implemented efficiently on a quantum computer. Although quantum algorithms can potentially achieve exponential speedup in solving linear algebra problems compared to the best classical algorithm, such a gain in efficiency ultimately hinges on our ability to construct an efficient quantum circuit for the block encoding of A, which is difficult in general, and not trivial even for well structured sparse matrices. Here, in this paper, we give a few examples on how efficient quantum circuits can be explicitly constructed for some well structured sparse matrices and discuss a few strategies used in these constructions. We also provide implementations of these quantum circuits in MATLAB.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Fast and Scalable FFT-Based GPU-Accelerated Algorithms for Block-Triangular Toeplitz Matrices with Application to Linear Inverse Problems Governed by Autonomous Dynamical Systems

In this work, we present an efficient and scalable algorithm for performing matrix-vector multiplications (matvecs) for block Toeplitz matrices. Such matrices, which are shift-invariant with respect to their blocks, arise in the context of solving inverse problems governed by autonomous systems, and time-invariant systems in particular. In this article, we consider inverse problems that infer unknown parameters from observational data of a linear time-invariant dynamical system given in the form of partial differential equations (PDEs). Matrix-free Newton-conjugate-gradient methods are often the gold standard for solving these inverse problems, but they require numerous actions of the Hessian on a vector. Matrix-free adjoint-based Hessian matvecs require solution of a pair of linearized forward/adjoint PDE solves per Hessian action, which may be prohibitive for large-scale inverse problems. Time invariance of the forward PDE problem leads to a block Toeplitz structure of the discretized parameter-to-observable (p2o) map defining the mapping from inputs (parameters) to outputs (observables) of the PDEs. This block Toeplitz structure enables us to exploit two key properties: (1) compact storage of the p2o map and its adjoint, and (2) efficient fast Fourier transform–based Hessian matvecs. The proposed algorithm is mapped onto large multi-GPU clusters and achieves more than 80% of peak bandwidth on NVIDIA A100 GPUs. Excellent weak scaling is shown for up to 48 A100 GPUs. For the targeted problems, the implementation executes Hessian matvecs within fractions of a second, which is orders of magnitude faster than can be achieved by conventional matrix-free Hessian matvecs via forward/adjoint PDE solves.

97 MATHEMATICS AND COMPUTING↗