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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 OSTI2024

Kubo-Anderson theory of polariton line shape

We apply the Kubo-Anderson stochastic theory of molecular spectral line shapes to the case of polaritons formed in the collective strong-coupling regime. We investigate both the fast and slow limits of the random frequency modulation of the emitter as well as the intermediate regime and show how the interplay between the characteristic timescales of the cavity and the molecular disorder is expressed in the observed polaritons line shapes. The analytical solution obtained for the slow limit is valid for any ratio between the inhomogeneous broadening of the molecules and the Rabi splitting, which is especially relevant for molecular polaritons where these two quantities can be of the same order of magnitude.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1975

Shape of the 5 mm oxygen band in the atmosphere

The problem of absorption of microwaves by molecular oxygen in the atmosphere is treated by means of a first-order approximation to the impact theory of overlapping spectral lines. By including only the coupling between adjacent rotational states in molecular collisions, we have devised a simple approximate method for computing the interference between lines from measurements on the resolved lines. The need for an empirically determined function describing the linewidth/pressure ratio is eliminated. Comparisons with measurements at atmospheric pressures show that the first-order interference accounts for the low absorption at the band wings near 1 atm pressure. It also predicts the correct amount of asymmetry between high and low frequency wings.

Source record↗
NASA NTRS1975

Effects of plasma microfields on radiative transitions from atomic levels above the ionization threshold

The effects of plasma electric microfields on line-like optical features arising from atomic levels above the ionization threshold are investigated within the framework of the quasi-static and single-frequency dynamic-field theories of spectral-line broadening. The 2p(23)P to 1s2p(3)P and 2s2p(3)P to 1s2s(3)S transitions in helium and helium-like ions are treated as examples. The mixing of the doubly excited levels in the perturbing microfields produces Stark broadening of the emission lines and induces autoionization of the 2p(23)P level, which, unlike the 2s2p(3)P level, is metastable against autoionization in the field-free environment. Determination of the complete Stark-broadening profiles in thermal plasmas is complicated by the need to include the effects of both the (quasi-static) ion and the (dynamic) electron fields. Under nonequilibrium conditions, where electric fields from either electron or ion plasma waves can far exceed nearby particle fields, the calculation and interpretation of the line shapes may be simplified and could provide a diagnostic probe of the wave-field properties.

Davis, J.↗
NASA NTRS1993

The initial stellar population

Current theories for the origin of stellar masses and the initial mass function are surveyed, with emphasis on the formation of stars in clusters, and the possibility that several different formation mechanisms are at work in the Galaxy. Models are presented for the evolution of the 2.2-micron premain-sequence luminosity function of a young coeval star cluster, and the implications the results have for the conversion of an observed luminosity function into the underlying mass function are discussed. A description of theories which allow spectral energy distributions of young stellar objects to be used as diagnostics of their evolutionary states is given. The question of the existence of substellar objects (brown dwarfs) in nearby young clusters and regions of star formation is addressed.

Zinnecker, Hans↗
NASA NTRS1991

Basic research in solar physics

This grant, dating back more than 20 years has supported a variety of investigations of the chromospheres and coronae of the Sun and related cool stars by the Principal Investigator, his postdocs and graduate students, and colleagues at other institutions. This work involved studies of radiative transfer and spectral line formation theory, and the application of these techniques to the analysis of spectra obtained from space and ground-based observatories in the optical, ultraviolet, x-ray and radio portions of the spectrum. Space observations have included the analysis of spectra from OSO-7, Skylab, SMM, and the HRTS rocket experiments. Recent work has concentrated on the interaction of magnetic fields, plasma and radiation in the outer atmospheres of the Sun and other magnetically active stars with different fundamental parameters. Our study of phenomena common to the Sun and stars, the 'solar-stellar connection', can elucidate the fundamental physics, because spatially-resolved observations of the Sun provide us with the 'groundtruth,' while interpretation of stellar data permit us to isolate those parameters critical to stellar activity. Recently, we have studied the differences in physical properties between solar regions of high magnetic flux density and the surrounding plasma. High-resolution CN and CO spectroheliograms have been used to model the thermal inhomogeneities driven by unstable CO cooling, and we have analyzed spatially resolved UV spectra from HRTS to model the thermal structure and energy balance of small-scale structures. The study of nonlinear relations between atmospheric radiative losses and the photospheric magnetic flux density has been continued. We have also proposed a new model for the decay of plages by random walk diffusion of magnetic flux. Our analysis of phenomena common to the Sun and stars included the application of available spectroscopic diagnostics, establishing evidence that the atmospheres of the least active stars are heated at a 'basal' rate that is also found in the centers of solar supergranules, and using the Doppler-imaging technique to measure the position, size, and brightness of stellar active regions. We are computing multi-component models for solar and stellar atmospheres, and models for coronal loops and for the transition-region down flows. The study of solar and stellar flares permits us to assess the role of turbulent energy transport, to pinpoint the mechanism behind Type I radio bursts, to determine whether plasma radiation or cyclotron maser is responsible for microwave flares on M dwarfs, and to extend our knowledge of the basic physics pertinent to cyclotron-maser processes operating on the Sun.

Linsky, Jeffrey L.↗
NASA NTRS1996

Galactic cosmic radiation model and its applications

A model for the differential energy spectra of galactic cosmic radiation as a function of solar activity is described. It is based on the standard diffusion-convection theory of solar modulation. Estimates of the modulation potential based on fitting this theory to observed spectral measurements from 1954 to 1989 are correlated to the Climax neutron counting rates and to the sunspot numbers at earlier times taking into account the polarity of the interplanetary magnetic field at the time of observations. These regression lines then provide a method for predicting the modulation at later times. The results of this model are quantitatively compared to a similar Moscow State University (MSU) model. These model cosmic ray spectra are used to predict the linear energy transfer spectra, differential energy spectra of light (charge less than or = 2) ions, and single event upsets rates in memeory devices. These calculations are compared to observations made aboard the Space Shuttle.

Badhwar, G. D.↗
NASA NTRS2004

Downscattering due to Wind Outflows in Compact X-ray Sources: Theory and Interpretation

A number of recent lines of evidence point towards the presence of hot, outflowing plasma from the central regions of compact Galactic and extragalactic X-ray sources. Additionally, it has long been noted that many of these sources exhibit an "excess" continuum component, above approx. 10 keV, usually attributed to Compton Reflection from a static medium. Motivated by these facts, as well as by recent observational constraints on the Compton reflection models - specifically apparently discrepant variability timescales for line and continuum components in some cases - we consider possible of effects of out-flowing plasma on the high-energy continuum spectra of accretion powered compact objects. We present a general formulation for photon downscattering diffusion which includes recoil and Comptonization effects due to divergence of the flow. We then develop an analytical theory for the spectral formation in such systems that allows us to derive formulae for the emergent spectrum. Finally we perform the analytical model fitting on several Galactic X-ray binaries. Objects which have been modeled with high-covering-fraction Compton reflectors, such as GS1353-64 are included in our analysis. In addition, Cyg X-3, is which is widely believed to be characterized by dense circumstellar winds with temperature of order 10(exp 6) K, provides an interesting test case. Data from INTEGRAL and RXTE covering the approx. 3 - 300 keV range are used in our analysis. We further consider the possibility that the widely noted distortion of the power-law continuum above 10 keV may in some cases be explained by these spectral softening effects.

Titarchuk, Lev↗
DOE OSTI2020

Approximate Inverse Chain Preconditioner: Iteration Count Case Study for Spectral Support Solvers

As the growing availability of computational power slows, there has been an increasing reliance on algorithmic advances. However, faster algorithms alone will not necessarily bridge the gap in allowing computational scientists to study problems at the edge of scientific discovery in the next several decades. Often, it is necessary to simplify or precondition solvers to accelerate the study of large systems of linear equations commonly seen in a number of scientific fields. Preconditioning a problem to increase efficiency is often seen as the best approach; yet, preconditioners which are fast, smart, and efficient do not always exist. Following the progress of [1], we present a new preconditioner for symmetric diagonally dominant (SDD) systems of linear equations. These systems are common in certain PDEs, network science, and supervised learning among others. Based on spectral support graph theory, this new preconditioner builds off of the work of [2], computing and applying a V-cycle chain of approximate inverse matrices. This preconditioner approach is both algebraic in nature as well as hierarchically-constrained depending on the condition number of the system to be solved. Due to its generation of an Approximate Inverse Chain of matrices, we refer to this as the AIC preconditioner. We further accelerate the AIC preconditioner by utilizing precomputations to simplify setup and multiplications in the con-text of an iterative Krylov-subspace solver. While these iterative solvers can greatly reduce solution time, the number of iterations can grow large quickly in the absence of good preconditioners. Initial results for the AIC preconditioner have shown a very large reduction in iteration counts for SDD systems as compared to standard preconditioners such as Incomplete Cholesky (ICC) and Multigrid (MG). We further show significant reduction in iteration counts against the more advanced Combinatorial Multigrid (CMG) preconditioner. We have further developed no-fill sparsification techniques to ensure that the computational cost of applying the AIC preconditioner does not grow prohibitively large as the depth of the V-cycle grows for systems with larger condition numbers. Our numerical results have shown that these sparsifiers maintain the sparsity structure of our system while also displaying significant reductions in iteration counts.1 2

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Approximate Inverse Chain Preconditioner: Iteration Count Case Study for Spectral Support Solvers

As the growing availability of computational power slows, there has been an increasing reliance on algorithmic advances. However, faster algorithms alone will not necessarily bridge the gap in allowing computational scientists to study problems at the edge of scientific discovery in the next several decades. Often, it is necessary to simplify or precondition solvers to accelerate the study of large systems of linear equations commonly seen in a number of scientific fields. Preconditioning a problem to increase efficiency is often seen as the best approach; yet, preconditioners which are fast, smart, and efficient do not always exist. Following the progress of [1], we present a new preconditioner for symmetric diagonally dominant (SDD) systems of linear equations. These systems are common in certain PDEs, network science, and supervised learning among others. Based on spectral support graph theory, this new preconditioner builds off of the work of [2], computing and applying a V-cycle chain of approximate inverse matrices. This preconditioner approach is both algebraic in nature as well as hierarchically-constrained depending on the condition number of the system to be solved. Due to its generation of an Approximate Inverse Chain of matrices, we refer to this as the AIC preconditioner. We further accelerate the AIC preconditioner by utilizing precomputations to simplify setup and multiplications in the con-text of an iterative Krylov-subspace solver. While these iterative solvers can greatly reduce solution time, the number of iterations can grow large quickly in the absence of good preconditioners. Initial results for the AIC preconditioner have shown a very large reduction in iteration counts for SDD systems as compared to standard preconditioners such as Incomplete Cholesky (ICC) and Multigrid (MG). We further show significant reduction in iteration counts against the more advanced Combinatorial Multigrid (CMG) preconditioner. We have further developed no-fill sparsification techniques to ensure that the computational cost of applying the AIC preconditioner does not grow prohibitively large as the depth of the V-cycle grows for systems with larger condition numbers. Our numerical results have shown that these sparsifiers maintain the sparsity structure of our system while also displaying significant reductions in iteration counts.1 2

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Unraveling intrinsic correlation effects with angle-resolved photoemission spectroscopy

Interaction effects can change materials properties in intriguing ways, and they have, in general, a huge impact on electronic spectra. In particular, satellites in photoemission spectra are pure many-body effects, and their study is of increasing interest in both experiment and theory. However, the intrinsic spectral function is only a part of a measured spectrum, and it is notoriously difficult to extract this information, even for simple metals. Our joint experimental and theoretical study of the prototypical simple metal aluminum demonstrates how intrinsic satellite spectra can be extracted from measured data using angular resolution in photoemission. A nondispersing satellite is detected and explained by electron–electron interactions and the thermal motion of the atoms. Additional nondispersing intensity comes from the inelastic scattering of the outgoing photoelectron. The ideal intrinsic spectral function, instead, has satellites that disperse both in energy and in shape. Theory and the information extracted from experiment describe these features with very good agreement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Machine-learned quantum molecular dynamics calculations of warm dense equation of state and ionic transport coefficients of deuterated water

White dwarf models require accurate equations of state and ionic transport coefficients in the warm dense matter regime, where kinetic theory models and tabulated equations of state are often inaccurate. In this work, spectral-partitioned density functional theory and machine-learned interatomic potentials are combined to perform large-scale, first-principles quantum molecular dynamics simulations of deuterated water (D 2 O) near the principal Hugoniot. This approach retains Kohn-Sham accuracy while achieving orders-of-magnitude speedup, yielding converged equation of state and transport properties over a broad pressure and temperature range. The results reveal the thermodynamic conditions under which ionic transport models for interdiffusivity and shear viscosity converge and identify those in closest agreement with density functional theory benchmarks at temperatures in the warm dense matter regime. The present framework extends first-principles transport calculations to higher temperatures than previously achieved, and provides an efficient, scalable, and general approach for studying transport properties in complex multicomponent mixtures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Deciphering the Solvation Structure of Aqueous ZnCl 2 Solutions from X-ray Absorption Spectra Using the Interpretable Graph Neural Network

Machine learning (ML) provides powerful pathways for predicting spectroscopic observables from atomic structures, but its broader impact depends on making model predictions interpretable in terms of physical and chemical principles. Here, we introduce a physics-guided graph neural network (GNN) model that predicts Zn K-edge X-ray spectroscopy (XAS) spectra of aqueous ZnCl 2 solutions. Training data are generated from ab initio XAS calculations on molecular dynamics snapshots obtained using a machine learning interatomic potential. The GNN reproduces experimental spectra across concentrations from dilute (<0.1 m) to highly concentrated (30 m, “water-in-salt”) regimes and scales efficiently to large, disordered liquid systems beyond the reach of conventional ab initio approaches. Gradient-based attribution analysis reveals that the model learns physically meaningful structure-spectrum relationships. Ligand-specific attributions reflect orbital hybridization patterns and the origin of the excitations derived from the density functional theory. Bond-length attributions recover spectral shifts consistent with multiple-scattering theory. Finally, this work bridges data-driven prediction with electronic-structure theory, establishing a general paradigm for interpretable ML that links atomic structure, electronic structure, and spectroscopic observables.

25 ENERGY STORAGE↗
DOE OSTI2020

Many-Body Level Statistics of Single-Particle Quantum Chaos

We consider a noninteracting many-fermion system populating levels of a unitary random matrix ensemble (equivalent to the q = 2 complex Sachdev-Ye-Kitaev model)—a generic model of single-particle quantum chaos. We study the corresponding many-particle level statistics by calculating the spectral form factor analytically using algebraic methods of random matrix theory, and match it with an exact numerical simulation. Despite the integrability of the theory, the many-body spectral rigidity is found to have a surprisingly rich landscape. In particular, we find a residual repulsion of distant many-body levels stemming from single-particle chaos, together with islands of level attraction. These results are encoded in an exponential ramp in the spectral form factor, which we show to be a universal feature of nonergodic many-fermion systems embedded in a chaotic medium.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1992

A unified perturbation expansion for surface scattering

Starting with the extinction theorem, a perturbation expansion which, to first and second orders, converges over a wider domain than the small perturbation expansion and the momentum transfer expansion is presented. It is shown that, in the appropriate limits, both of these theories, as well as the two-scale expansion, are recovered. There is no adjustable parameter, such as a spectral split, in the theory. This theory is applied to random rough surfaces and derive analytic expressions for the coherent field and the bistatic cross section. Finally, a numerical test of the theory against method of moments results for Gaussian random rough surfaces with a power law spectrum is given. These results show that the expansion is ramarkably accurate over a large range of surface heights and slopes for both horizontal and vertical polarization.

Rodriguez, Ernesto↗
DOE OSTI2022

Stochastic exciton-scattering theory of optical line shapes: Renormalized many-body contributions

Spectral line shapes provide a window into the local environment coupled to a quantum transition in the condensed phase. In this paper, we build upon a stochastic model to account for non-stationary background processes produced by broad-band pulsed laser stimulation, as distinguished from those for stationary phonon bath. In particular, we consider the contribution of pair-fluctuations arising from the full bosonic many-body Hamiltonian within a mean-field approximation, treating the coupling to the system as a stochastic noise term. Herein, using the Itô transformation, we consider two limiting cases for our model, which lead to a connection between the observed spectral fluctuations and the spectral density of the environment. In the first case, we consider a Brownian environment and show that this produces spectral dynamics that relax to form dressed excitonic states and recover an Anderson–Kubo-like form for the spectral correlations. In the second case, we assume that the spectrum is Anderson–Kubo like and invert to determine the corresponding background. Using the Jensen inequality, we obtain an upper limit for the spectral density for the background. The results presented here provide the technical tools for applying the stochastic model to a broad range of problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1979

Two-stream theory of reflectance of snow

Spectral reflectance of snow under diffuse illumination is studied using the two-stream approximation of the radiative transfer equation. The scattering and absorption parameters of the radiative transfer equation - the single scattering albedo, the optical depth, and the integrated phase function are obtained from the grain size and density of snow. Analytical expressions for the intensity within the snowpack, the reflectance, and the asymptotic flux extinction coefficient, are given. Good agreement is shown between the theory and available experimental data on visible and near-infrared reflectance, and the asymptotic flux extinction coefficient. The theory may also be used to explain the observed effect of aging on the snow reflectance.

Choudhury, B. J.↗
NASA NTRS1982

A climate index derived from satellite measured spectral infrared radiation

The vertical infrared radiative emitting structure (VIRES) climate index, based on radiative transfer theory and derived from the spectral radiances typically used to retrieve temperature profiles, is introduced. It is assumed that clouds and climate are closely related and a change in one will result in a change in the other. The index is a function of the cloud, temperature, and moisture distributions. It is more accurately retrieved from satellite data than is cloudiness per se. The VIRES index is based upon the shape and relative magnitude of the broadband weighting function of the infrared radiative transfer equation. The broadband weighting curves are retrieved from simulated satellite infrared sounder data (spectral radiances). The retrieval procedure is described and the error error sensitivities of the method investigated. Index measuring options and possible applications of the VIRES index are proposed.

Abel, M. D.↗
NASA NTRS1984

Techniques for the estimation of leaf area index using spectral data

Based on the radiative transport theory of a homogeneous canopy, a new approach for obtaining transformations of spectral data used to estimate leaf area index (LAI), is developed. The transformations which are obtained without any ground knowledge of LAI show low sensitivity to soil variability, and are linearly related to LAI with relationships which are predictable from leaf reflectance, transmittance properties, and canopy reflectance models. Evaluation of the SAIL (scattering by arbitrarily inclined leaves) model is considered. Using only nadir view data, results obtained on winter and spring wheat and corn crops are presented.

Badhwar, G. D.↗