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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Organ sample generator for expected treatment dose construction and adaptive inverse planning optimization

Purpose: To create an organ sample generator (OSG) for expected treatment dose construction and adaptive inverse planning optimization. The OSG generates random samples of organs of interest from a distribution obeying the patient specific organ variation probability density function (PDF) during the course of adaptive radiotherapy. Methods: Principle component analysis (PCA) and a time-varying least-squares regression (LSR) method were used on patient specific geometric variations of organs of interest manifested on multiple daily volumetric images obtained during the treatment course. The construction of the OSG includes the determination of eigenvectors of the organ variation using PCA, and the determination of the corresponding coefficients using time-varying LSR. The coefficients can be either random variables or random functions of the elapsed treatment days depending on the characteristics of organ variation as a stationary or a nonstationary random process. The LSR method with time-varying weighting parameters was applied to the precollected daily volumetric images to determine the function form of the coefficients. Eleven h and n cancer patients with 30 daily cone beam CT images each were included in the evaluation of the OSG. The evaluation was performed using a total of 18 organs of interest, including 15 organs at risk and 3 targets. Results: Geometric variations of organs of interest during h and n cancer radiotherapy can be represented using the first 3 {approx} 4 eigenvectors. These eigenvectors were variable during treatment, and need to be updated using new daily images obtained during the treatment course. The OSG generates random samples of organs of interest from the estimated organ variation PDF of the individual. The accuracy of the estimated PDF can be improved recursively using extra daily image feedback during the treatment course. The average deviations in the estimation of the mean and standard deviation of the organ variation PDF for h and n cancer radiotherapy were less than 2 and 1 mm, respectively, for most organs after the second week of treatment. After the first three weeks of treatment, the mean discrepancy of the dose estimation accuracy was within 1% for most of organs, the corresponding standard deviation was within 2.5% for parotids, the brain stem and the cochleae, and within 1% for other organs. Conclusions: A patient specific OSG is feasible and can be used to generate random samples of organs of interest for the expected treatment dose construction and adaptive inverse planning. The accuracy of the OSG can be improved continuously and recursively during the adaptive treatment course using daily volumetric image feedback.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Lifetimes of low-lying levels in 158 Gd

The low-lying structure of the well-deformed nucleus 158 Gd has been revisited to elucidate the nature of the low-lying states in 158 Gd. Earlier (p, t) studies identified numerous 0 + states below 4.3 MeV, prompting questions about whether these states correspond to collective vibrations or shape coexistence. New and previously reported (n, n' γ) measurements are combined, including γ-γ coincidences, excitation functions, and angular distributions, to extract lifetimes and transition probabilities for 44 excited states up to 2.7 MeV, including 32 previously unmeasured levels. Our results confirm or revise γ-ray placements and provide detailed transition strengths, revealing both weakly collective and strongly enhanced B(E2) and B(E1) transition probabilities. In particular, a tentative 0 + state at 2437.8 keV exhibits a strong interband B(E2) transition, which may be a candidate for a possible two-phonon (ββ) excitation. Systematic comparisons with neighboring Gd isotopes, Hartree–Fock–Bogoliubov, and interacting-boson model predictions suggest that the first excited 0 + state in 158 Gd is predicted to be a β-vibration, although it is weakly collective.

158Gd↗
DOE OSTI2016

Two-way coupled Lagrangian particles in CTH

A basic two-way coupled discrete Lagrangian particle method has been implemented into CTH as a proof of concept. The approach has applications in modeling dilute multiphase phenomena, such as dust entrainment or explosive dispersion of debris. Only a basic Stokes drag law was implemented, but the framework allows for more advanced physics to be implemented in the future, such as particle-particle interactions or state of the art drag models. This memo outlines the modifications made to the code to implement the method, along with simple verification problems for it. The particle data structure used was designed to be as general as possible to facilitate future particle based methods being pursued in the future. For example the same data structure could be leveraged for Lagrangian notional particles used in Probability Density Function approaches, or the advection of a distribution of states such as a Weibull distribution for mechanics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Modeling and Simulation of Fuel Dispersal During the Loss-of-Coolant Accident

This document is the compilation of the milestone portion to a larger end of project NEUP report. The executive summary of the modeling portion is provided below: In the event of cladding rupture during a postulated LOCA in a pressurized water reactor, fuel particles, along with fission gases, can be expelled into the reactor core from the fractured fuel rod, a phenomenon referred to as fuel dispersal. The initial stage of fuel dispersal is strongly influenced by the high-pressure ejection of fuel fragments, the size and geometry of the ruptured cladding, and the depressurization history of the fuel rod during the postulated LOCA transient. Depending on the location of the burst orifice relative to the quench front, the dispersal event represents an intricate three-phase flow and heat transfer phenomenon, where high-temperature fuel particles carried by the fission gases interact with the coolant within the narrow subchannels of the fuel assemblies, inducing localized phase change. Given the unique multiphysics nature of this phenomena, the current study develops a dedicated computational framework to predict the mass distribution and cooling of dispersing fuel particles, facilitating post-accident assessment and management of the fuel assemblies. Considering the scale of nuclear reactor applications, a continuum three-fluid model is proposed for simulating the transport of solids within the reactor core. With high-temperature fuel fragments within the liquid media, nucleation sites inducing phase changes are dispersed within the flow domain. Coupled with the fact that the transient dispersal event occurs on different time scales than other three-phase flow applications, this study derives a time-averaged three-fluid flow model without losing generality. The assumptions regarding the continuum treatment of the solid phase and the modeling of fuel dispersal behavior are incorporated to simplify the governing equations and derive applicable closure relations. The computational validation of the model was conducted using adiabatic experimental results obtained from ongoing research at Oregon State University, focusing on characterizing fuel dispersal behavior during simulated LOCA conditions. Settlement characteristics of the solids, quantified by the probability distribution of equivalent particles, closely matched the probability density functions reported in experimental studies. The transport of fuel particles within a scaled 5 × 5 lattice of a pressurized-water reactor rod bundle geometry was modeled through a two-fluid Eulerian framework. The required boundary conditions were evaluated from the fuel performance code BISON in a postulated large-break LOCA scenario. The modeling framework considered solid fuel particles as granular matter, interacting with the gaseous dry steam phase and fission gases through the governing interfacial momentum exchange between the participating fluids. The simulation results provided the volume fraction of the solids obtained at the bottom surface of the enclosing tank geometry. Postulated LOCA leading to fuel dispersal phenomena involves the strong coupling between fuel thermomechanics, cladding deformation, thermal-hydraulics, and fuel particle transport. Incorporation of such a strong coupling in numerical simulation is performed by coupling the multiphysics solvers. In the case of fuel dispersal, a strong coupled simulation can be performed by coupling the BISON code for fuel performance, the TRACE code for system-level thermal hydraulics, and fuel particle transport in Multiphysics Object-Oriented Simulation Environment (MOOSE). For such intricate infrastructure, the MOOSE Framework eases the data transfer between codes. The recent version of MOOSE has incorporated the Navier-Stokes module for the fluid flow. An exploratory exercise was done to gain familiarity with finite volume capabilities in the MOOSE framework to incorporate the Spalart-Allmaras (SA) turbulence model. New finite-volume and auxiliary kernels were introduced to assemble the SA transport equation, compute turbulent viscosity, and evaluate wall distance and diagnostic turbulence terms, fully integrated with existing Navier-Stokes modules. A turbulent lid-driven cavity at a Reynolds number of approximately 10,000 is used for verification. MOOSE shows the robust solver convergence and produces the turbulent features. But it underpredicts the velocity profile and turbulent quantities, emphasizing the need to develop improved SA near-wall treatments (e.g., low-Re corrections or wall functions) as a key direction for future work.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2010

Oblique incidence for broad monoenergetic proton beams

Purpose: The depth dose of a monoenergetic broad parallel proton beam has been modeled in a number of ways, but evidently not yet for oblique incidence. The purpose of this investigation is to find an accurate analytic formula for this case, which can then be used to model the depth dose of a broad beam with an initial Gaussian angular distribution. Methods: The Bortfeld model of depth dose in a broad normally incident proton beam has been extended to the case of oblique incidence. This extension uses an empirically determined Gaussian parameter {sigma}{sub x} which (roughly) characterizes the off-axis dose of a proton pencil beam. As with Bortfeld's work, the modeling is done in terms of parabolic cylinder functions. To obtain the depth dose for an initial angular distribution, the result is integrated over the angle of incidence, weighted by a Gaussian probability function. The predictions of the theory have been compared to MCNPX Monte Carlo calculations for four phantom materials (water, bone, aluminum, and copper) and for initial proton energies of 50, 100, 150, 200, and 250 MeV. Results: Comparisons of the depth dose predicted by this theory with Monte Carlo calculations have established that with very good accuracy, {sigma}{sub x} can be taken to be independent both of the depth and of the angle of incidence. As a function of initial proton range or of initial proton energy, {sigma}{sub x} has been found to obey a power law to very high accuracy. Good fits to Monte Carlo calculations have also been found for an initial Gaussian angular distribution. Conclusions: This investigation is the first step in the accurate modeling of a proton pencil beam with initial Gaussian angular distribution. It provides the longitudinal factor, with its Bragg peak buildup and sharp distal falloff. A transverse factor must still be incorporated into this theory and this will give the lateral penumbra of a collimated proton beam. Also, it will be necessary to model the dose of product particles from nuclear interactions of the proton beam. With the accurate modeling of a pencil beam, it will be possible to accurately take into account the effect of localized tissue inhomogeneities.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Data synergy between leaf area index and clumping index Earth Observation products using photon recollision probability theory

Clumping index (CI) is a measure of foliage aggregation relative to a random distribution of leaves in space. The CI can help with estimating fractions of sunlit and shaded leaves for a given leaf area index (LAI) value. Both the CI and LAI can be obtained from global Earth Observation data from sensors such as the Moderate Resolution Imaging Spectrometer (MODIS). Here, the synergy between a MODIS-based CI and a MODIS LAI product is examined using the theory of spectral invariants, also referred to as photon recollision probability (‘p-theory’), along with raw LAI-2000/2200 Plant Canopy Analyzer data from 75 sites distributed across a range of plant functional types. The p-theory describes the probability (p-value) that a photon, having intercepted an element in the canopy, will recollide with another canopy element rather than escape the canopy. We show that empirically-based CI maps can be integrated with the MODIS LAI product. Our results indicate that it is feasible to derive approximate p-values for any location solely from Earth Observation data. This approximation is relevant for future applications of the photon recollision probability concept for global and local monitoring of vegetation using Earth Observation data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Probabilistic fatigue life prediction model for alloys with defects: applied to A206

Presented here is a model for the prediction of fatigue life based on the statistical distribution of pores, intermetallic particles and grains. This has been applied to a cast Al alloy A206, before and after friction stir processing (FSP). The model computes the probability to initiate a small crack based on the probability of finding combinations of defects and grains on the surface. The crack initiation and propagation life of small cracks due to these defect and grain combinations are computed and summed to obtain the total fatigue life. The defect and grain combinations are ranked according to total fatigue life and the failure probability computed. Bending fatigue experiments were carried out on A206 before and after FSP. FSP eliminated the porosity, broke down the particles and refined the microstructure. The model predicted the fatigue life of A206 before and after FSP well. The cumulative probability distribution vs. fatigue life was fitted to a three parameter Weibull distribution function. The scatter reduced after FSP and the threshold of fatigue life increased. The potential improvement in the fatigue life of A206 for a microstructure consisting of a finer distribution of particle sizes after FSP was predicted using the model.

36 MATERIALS SCIENCE↗
DOE OSTI2016

The CU 2-D-MAX-DOAS instrument – Part 2: Raman scattering probability measurements and retrieval of aerosol optical properties

Abstract. The multiannual global mean of aerosol optical depth at 550 nm (AOD550) over land is ∼ 0.19, and that over oceans is ∼ 0.13. About 45 % of the Earth surface shows AOD550 smaller than 0.1. There is a need for measurement techniques that are optimized to measure aerosol optical properties under low AOD conditions. We present an inherently calibrated retrieval (i.e., no need for radiance calibration) to simultaneously measure AOD and the aerosol phase function parameter, g, based on measurements of azimuth distributions of the Raman scattering probability (RSP), the near-absolute rotational Raman scattering (RRS) intensity. We employ radiative transfer model simulations to show that for solar azimuth RSP measurements at solar elevation and solar zenith angle (SZA) smaller than 80°, RSP is insensitive to the vertical distribution of aerosols and maximally sensitive to changes in AOD and g under near-molecular scattering conditions. The University of Colorado two-dimensional Multi-AXis Differential Optical Absorption Spectroscopy (CU 2-D-MAX-DOAS) instrument was deployed as part of the Two Column Aerosol Project (TCAP) at Cape Cod, MA, during the summer of 2012 to measure direct sun spectra and RSP from scattered light spectra at solar relative azimuth angles (SRAAs) between 5 and 170°. During two case study days with (1) high aerosol load (17 July, 0.3 < AOD430 < 0.6) and (2) near-molecular scattering conditions (22 July, AOD430 < 0.13) we compare RSP-based retrievals of AOD430 and g with data from a co-located CIMEL sun photometer, Multi-Filter Rotating Shadowband Radiometer (MFRSR), and an airborne High Spectral Resolution Lidar (HSRL-2). The average difference (relative to DOAS) for AOD430 is +0.012 ± 0.023 (CIMEL), −0.012 ± 0.024 (MFRSR), −0.011 ± 0.014 (HSRL-2), and +0.023 ± 0.013 (CIMELAOD − MFRSRAOD) and yields the following expressions for correlations between different instruments: DOASAOD = −(0.019 ± 0.006) + (1.03 ± 0.02) × CIMELAOD (R2 = 0.98), DOASAOD = −(0.006 ± 0.005) + (1.08 ± 0.02) × MFRSRAOD (R2 = 0.98), and CIMELAOD = (0.013 ± 0.004) + (1.05 ± 0.01) × MFRSRAOD (R2 = 0.99). The average g measured by DOAS on both days was 0.66 ± 0.03, with a difference of 0.014 ± 0.05 compared to CIMEL. Active steps to minimize the error in the RSP help to reduce the uncertainty in retrievals of AOD and g. As AOD decreases and SZA increases, the RSP signal-to-noise ratio increases. At AOD430 ∼ 0.4 and 0.10 the absolute AOD errors are ∼ 0.014 and 0.003 at 70° SZA and 0.02 and 0.004 at 35° SZA. Inherently calibrated, precise AOD and g measurements are useful to better characterize the aerosol direct effect in urban polluted and remote pristine environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Quantum information approach to high energy interactions

High energy hadron interactions are commonly described by using a probabilistic parton model that ignores quantum entanglement present in the light-cone wave functions. Here, we argue that since a high energy interaction samples an instant snapshot of the hadron wave function, the phases of different Fock state wave functions cannot be measured—therefore the light-cone density matrix has to be traced over these unobservable phases. Performing this trace with the corresponding U(1) Haar integration measure leads to ‘Haar scrambling’ of the density matrix, and to the emergence of entanglement entropy. This entanglement entropy is determined by the Fock state probability distribution, and is thus directly related to the parton structure functions. As proposed earlier, at large rapidity η the hadron state becomes maximally entangled, and the entanglement entropy is S E ~η according to QCD evolution equations. When the phases of Fock state components are controlled, for example in spin asymmetry measurements, the Haar average cannot be performed, and the probabilistic parton description breaks down.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

THE GALAXY-HALO/SUBHALO CONNECTION: MASS RELATIONS AND IMPLICATIONS FOR SOME SATELLITE OCCUPATIONAL DISTRIBUTIONS

We infer the local stellar-to-halo/subhalo mass relations (MRs) for central and satellite galaxies separately. Our statistical method is an extension of the abundance matching, halo occupation distribution, and conditional stellar mass function formalisms. We constrain the model using several combinations of observational data, consisting of the total galaxy stellar mass function (GSMF), its decomposition into centrals and satellites, and the projected two-point correlation functions (2PCFs) measured in different stellar mass (M{sub *}) bins. In addition, we use the {Lambda}CDM halo and subhalo mass functions. The differences among the resulting MRs are within the model-fit uncertainties (which are very small, smaller than the intrinsic scatter between galaxy and halo mass), no matter what combination of data are used. This shows that matching abundances or occupational numbers is equivalent, and that the GSMFs and 2PCFs are tightly connected. We also constrain the values of the intrinsic scatter around the central-halo (CH) and satellite-subhalo (SS) MRs assuming them to be constant: {sigma}{sub c} = 0.168 {+-} 0.051 dex and {sigma}{sub s} = 0.172 {+-} 0.057 dex, respectively. The CH and SS MRs are actually different, in particular when we take the subhalo mass at the present-day epoch instead of at their accretion time. When using the MRs for studying the satellite population (e.g., in the Milky Way, MW), the SS MR should be chosen instead of the average one. Our model allows one to calculate several population statistics. We find that the central galaxy M{sub *} is not on average within the mass distribution of the most massive satellite, even for cluster-sized halos, i.e., centrals are not a mere realization of the high end of the satellite mass function; however for >3 Multiplication-Sign 10{sup 13} M{sub Sun} halos, {approx}15% of centrals could be. We also find that the probabilities of MW-sized halos of having N Magellanic Cloud (MC) sized satellites agree well with observational measures; for a halo mass of 2 Multiplication-Sign 10{sup 12} M{sub Sun }, the probability to have two MCs is 5.4%, but if we exclude those systems with satellites larger than the MCs, then the probability decreases to <2.2%.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

PRIMUS: The relationship between star formation and AGN accretion

We study the evidence for a connection between active galactic nuclei (AGNs) fueling and star formation by investigating the relationship between the X-ray luminosities of AGNs and the star formation rates (SFRs) of their host galaxies. We identify a sample of 309 AGNs with 10{sup 41}<L{sub X}<10{sup 44} erg s{sup −1} at 0.2<z<1.2 in the PRIMUS redshift survey. We find AGNs in galaxies with a wide range of SFR at a given L{sub X}. We do not find a significant correlation between SFR and the observed instantaneous L{sub X} for star-forming AGN host galaxies. However, there is a weak but significant correlation between the mean L{sub X} and SFR of detected AGNs in star-forming galaxies, which likely reflects that L{sub X} varies on shorter timescales than SFR. We find no correlation between stellar mass and L{sub X} within the AGN population. Within both populations of star-forming and quiescent galaxies, we find a similar power-law distribution in the probability of hosting an AGN as a function of specific accretion rate. Furthermore, at a given stellar mass, we find a star-forming galaxy ∼2–3 more likely than a quiescent galaxy to host an AGN of a given specific accretion rate. The probability of a galaxy hosting an AGN is constant across the main sequence of star formation. These results indicate that there is an underlying connection between star formation and the presence of AGNs, but AGNs are often hosted by quiescent galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Baseline evaluation of the impact of updates to the MIT Earth System Model on its model parameter estimates

Abstract. For over 20 years, the Massachusetts Institute of Technology Earth System Model (MESM) has been used extensively for climate change research. The model is under continuous development with components being added and updated. To provide transparency in the model development, we perform a baseline evaluation by comparing model behavior and properties in the newest version to the previous model version. In particular, changes resulting from updates to the land surface model component and the input forcings used in historical simulations of climate change are investigated. We run an 1800-member ensemble of MESM historical climate simulations where the model parameters that set climate sensitivity, the rate of ocean heat uptake, and the net anthropogenic aerosol forcing are systematically varied. By comparing model output to observed patterns of surface temperature changes and the linear trend in the increase in ocean heat content, we derive probability distributions for the three model parameters. Furthermore, we run a 372-member ensemble of transient climate simulations where all model forcings are fixed and carbon dioxide concentrations are increased at the rate of 1 % year −1 . From these runs, we derive response surfaces for transient climate response and thermosteric sea level rise as a function of climate sensitivity and ocean heat uptake. We show that the probability distributions shift towards higher climate sensitivities and weaker aerosol forcing when using the new model and that the climate response surfaces are relatively unchanged between model versions. Because the response surfaces are independent of the changes to the model forcings and similar between model versions with different land surface models, we suggest that the change in land surface model has limited impact on the temperature evolution in the model. Thus, we attribute the shifts in parameter estimates to the updated model forcings.

58 GEOSCIENCES↗
DOE OSTI2010

Time-dependent generalized polynomial chaos

Generalized polynomial chaos (gPC) has non-uniform convergence and tends to break down for long-time integration. The reason is that the probability density distribution (PDF) of the solution evolves as a function of time. The set of orthogonal polynomials associated with the initial distribution will therefore not be optimal at later times, thus causing the reduced efficiency of the method for long-time integration. Adaptation of the set of orthogonal polynomials with respect to the changing PDF removes the error with respect to long-time integration. In this method new stochastic variables and orthogonal polynomials are constructed as time progresses. In the new stochastic variable the solution can be represented exactly by linear functions. This allows the method to use only low order polynomial approximations with high accuracy. The method is illustrated with a simple decay model for which an analytic solution is available and subsequently applied to the three mode Kraichnan-Orszag problem with favorable results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

How many eigenvalues of a Gaussian random matrix are positive?

We study the probability distribution of the index N{sub +}, i.e., the number of positive eigenvalues of an NxN Gaussian random matrix. We show analytically that, for large N and large N{sub +} with the fraction 0{<=}c=N{sub +}/N{<=}1 of positive eigenvalues fixed, the index distribution P(N{sub +}=cN,N){approx}exp[-{beta}N{sup 2}{Phi}(c)] where {beta} is the Dyson index characterizing the Gaussian ensemble. The associated large deviation rate function {Phi}(c) is computed explicitly for all 0{<=}c{<=}1. It is independent of {beta} and displays a quadratic form modulated by a logarithmic singularity around c=1/2. As a consequence, the distribution of the index has a Gaussian form near the peak, but with a variance {Delta}(N) of index fluctuations growing as {Delta}(N){approx}lnN/{beta}{pi}{sup 2} for large N. For {beta}=2, this result is independently confirmed against an exact finite-N formula, yielding {Delta}(N)=lnN/2{pi}{sup 2}+C+O(N{sup -1}) for large N, where the constant C for even N has the nontrivial value C=({gamma}+1+3ln2)/2{pi}{sup 2}{approx_equal}0.185 248... and {gamma}=0.5772... is the Euler constant. We also determine for large N the probability that the interval [{zeta}{sub 1},{zeta}{sub 2}] is free of eigenvalues. Some of these results have been announced in a recent letter [Phys. Rev. Lett. 103, 220603 (2009)].

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Multiobjective fuzzy stochastic linear programming problems with inexact probability distribution

This study deals with multiobjective fuzzy stochastic linear programming problems with uncertainty probability distribution which are defined as fuzzy assertions by ambiguous experts. The problem formulation has been presented and the two solutions strategies are; the fuzzy transformation via ranking function and the stochastic transformation when α{sup –}. cut technique and linguistic hedges are used in the uncertainty probability distribution. The development of Sen’s method is employed to find a compromise solution, supported by illustrative numerical example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Flexible and scalable methods for quantifying stochastic variability in the era of massive time-domain astronomical data sets

We present the use of continuous-time autoregressive moving average (CARMA) models as a method for estimating the variability features of a light curve, and in particular its power spectral density (PSD). CARMA models fully account for irregular sampling and measurement errors, making them valuable for quantifying variability, forecasting and interpolating light curves, and variability-based classification. We show that the PSD of a CARMA model can be expressed as a sum of Lorentzian functions, which makes them extremely flexible and able to model a broad range of PSDs. We present the likelihood function for light curves sampled from CARMA processes, placing them on a statistically rigorous foundation, and we present a Bayesian method to infer the probability distribution of the PSD given the measured light curve. Because calculation of the likelihood function scales linearly with the number of data points, CARMA modeling scales to current and future massive time-domain data sets. We conclude by applying our CARMA modeling approach to light curves for an X-ray binary, two active galactic nuclei, a long-period variable star, and an RR Lyrae star in order to illustrate their use, applicability, and interpretation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Energy density functional analysis of shape coexistence in {sup 44}S

The structure of low-energy collective states in the neutron-rich nucleus {sup 44}S is analyzed using a microscopic collective Hamiltonian model based on energy density functionals (EDFs). The calculated triaxial energy map, low-energy spectrum and corresponding probability distributions indicate a coexistence of prolate and oblate shapes in this nucleus.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2011

Copula cosmology: Constructing a likelihood function

To estimate cosmological parameters from a given data set, we need to construct a likelihood function, which sometimes has a complicated functional form. We introduce the copula, a mathematical tool to construct an arbitrary multivariate distribution function from one-dimensional marginal distribution functions with any given dependence structure. It is shown that a likelihood function constructed by the so-called Gaussian copula can reproduce very well the n-dimensional probability distribution of the cosmic shear power spectrum obtained from a large number of ray-tracing simulations. This suggests that the Copula likelihood will be a powerful tool for future weak lensing analyses, instead of the conventional multivariate Gaussian likelihood.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗