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All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

PRECIOUS METALS IN SDSS QUASAR SPECTRA. I. TRACKING THE EVOLUTION OF STRONG, 1.5 < z < 4.5 C IV ABSORBERS WITH THOUSANDS OF SYSTEMS

We have vastly increased the C IV statistics at intermediate redshift by surveying the thousands of quasars in the Sloan Digital Sky Survey (SDSS) Data-Release 7. We visually verified over 16,000 C IV systems with 1.46 < z < 4.55-a sample size that renders Poisson error negligible. Detailed Monte Carlo simulations show that we are approximately 50% complete down to rest equivalent widths W {sub r} Almost-Equal-To 0.6 A. We analyzed the sample as a whole and in 10 small redshift bins with approximately 1500 doublets each. The equivalent width frequency distributions f(W {sub r}) were well modeled by an exponential, with little evolution in shape. In contrast with previous studies that modeled the frequency distribution as a single power law, the fitted exponential gives a finite mass density for the C IV ions. The comoving line density dN{sub CIV}/dX evolved smoothly with redshift, increasing by a factor of 2.37 {+-} 0.09 from z = 4.55-1.96, then plateauing at dN{sub CIV}/dX{approx}0.34 for z = 1.96-1.46. Comparing our SDSS sample with z < 1 (ultraviolet) and z > 5 (infrared) surveys, we see an approximately 10-fold increase in dN{sub CIV}/dX over z Almost-Equal-To 6 {yields} 0, for W {sub r} {>=} 0.6 A. This suggests a monotonic and significant increase in the enrichment of gas outside galaxies over the 12 Gyr lifetime of the universe.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2006

Estimating Random Errors Due to Shot Noise in Backscatter Lidar Observations

In this paper, we discuss the estimation of random errors due to shot noise in backscatter lidar observations that use either photomultiplier tube (PMT) or avalanche photodiode (APD) detectors. The statistical characteristics of photodetection are reviewed, and photon count distributions of solar background signals and laser backscatter signals are examined using airborne lidar observations at 532 nm using a photon-counting mode APD. Both distributions appear to be Poisson, indicating that the arrival at the photodetector of photons for these signals is a Poisson stochastic process. For Poisson-distributed signals, a proportional, one-to-one relationship is known to exist between the mean of a distribution and its variance. Although the multiplied photocurrent no longer follows a strict Poisson distribution in analog-mode APD and PMT detectors, the proportionality still exists between the mean and the variance of the multiplied photocurrent. We make use of this relationship by introducing the noise scale factor (NSF), which quantifies the constant of proportionality that exists between the root-mean-square of the random noise in a measurement and the square root of the mean signal. Using the NSF to estimate random errors in lidar measurements due to shot noise provides a significant advantage over the conventional error estimation techniques, in that with the NSF uncertainties can be reliably calculated from/for a single data sample. Methods for evaluating the NSF are presented. Algorithms to compute the NSF are developed for the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar and tested using data from the Lidar In-space Technology Experiment (LITE). OCIS Codes:

Liu, Zhaoyan↗
DOE OSTI2015

THE X-RAY FLUX DISTRIBUTION OF SAGITTARIUS A* AS SEEN BY CHANDRA

We present a statistical analysis of the X-ray flux distribution of Sgr A* from the Chandra X-Ray Observatory's 3 Ms Sgr A* X-ray Visionary Project in 2012. Our analysis indicates that the observed X-ray flux distribution can be decomposed into a steady quiescent component, represented by a Poisson process with rate Q = (5.24 ± 0.08) × 10{sup –3} counts s{sup –1}, and a variable component, represented by a power law process (dN/dF∝F {sup –ξ}, ξ=1.92{sub −0.02}{sup +0.03}). This slope matches our recently reported distribution of flare luminosities. The variability may also be described by a log-normal process with a median unabsorbed 2-8 keV flux of 1.8{sub −0.6}{sup +0.8}×10{sup −14} erg s{sup –1} cm{sup –2} and a shape parameter σ = 2.4 ± 0.2, but the power law provides a superior description of the data. In this decomposition of the flux distribution, all of the intrinsic X-ray variability of Sgr A* (spanning at least three orders of magnitude in flux) can be attributed to flaring activity, likely in the inner accretion flow. We confirm that at the faint end, the variable component contributes ∼10% of the apparent quiescent flux, as previously indicated by our statistical analysis of X-ray flares in these Chandra observations. Our flux distribution provides a new and important observational constraint on theoretical models of Sgr A*, and we use simple radiation models to explore the extent to which a statistical comparison of the X-ray and infrared can provide insights into the physics of the X-ray emission mechanism.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1971

The application of signal detection theory to optics

The restoration of images focused on a photosensitive surface is treated from the standpoint of maximum likelihood estimation, taking into account the Poisson distributions of the observed data, which are the numbers of photoelectrons from various elements of the surface. A detector of an image focused on such a surface utilizes a certain linear combination of those numbers as the optimum detection statistic. Methods for calculating the false alarm and detection probabilities are proposed. It is shown that measuring noncommuting observables in an ideal quantum receiver cannot yield a lower Bayes cost than that attainable by a system measuring only commuting observables.

Helstrom, C. W.↗
NASA NTRSDate not supplied

Watching Without Seeing a Tool to Surveil Astronaut Health Outcomes While Maintaining Astronaut Medical Privacy

BACKGROUND The Privacy Act of 1974 regulates the use a nd disclosure of personally identifiable information by US Federal agencies. The Act applies to biographical, financial, a nd other identity-linked information, a s well a s personal health information (PHI). As such, the use of astronaut PHI is limited to authorized personnel for preapproved uses, with data reporting often limited to aggregated information about groups. These limitations on the use a nd reporting of astronaut PHI complicates surveillance efforts, wherein epidemiologists a t the National Aeronautics and Space Administration (NASA)monitor the incidence of targeted health conditions in the astronaut population, or to discover emerging trends of aging and disease. Stratification on one or more covariates –particularly time-period, sex, a nd mission participation –can lead to extremely small datasets such that the reporting of results is potentially attributable to individuals. An additional challenge is the small size of the astronaut population, both in terms of numbers of individuals a s well a s in terms of density of exposure time. Such small datasets yield volatile rate estimates that are difficult to interpret. To a id the epidemiological surveillance efforts, a surveillance tool is required that can (a) satisfy the need for rapid computation of condition-specific incidence and mortality rates; (b) improve the statistical estimates of these estimated rates; and (c) maintain astronaut privacy. Here we describe a nd demonstrate such a tool. METHODS We devised a system that models incidence a nd mortality rates rather than calculating them directly. This ha s the advantage of using all the available data to derive the estimates, lea ding to rates that a re not attributable to any one individual, a nd a re a s numerically stable a s they can be given the extremely limited data. The system models disease endpoints using a Poisson regression model with exposure density (measured in person-years) a s a n offset term. By doing so the model is estimating event counts per person-year, equivalent to modeling the rates directly. It uses a standard (pre-specified)set of covariates; the system does not engage in “model-building” as model parsimony is not the goa l. Instead, it is explicitly recognized that if a covariate is not statistically significant a nd not a confounder then it will likely have very little effect on the estimate of the incidence a nd mortality rates. Users are able to specify the disease endpoint of interest and the covariates over which they would like to stratify. The system then uses the resulting model to compute the estimated rates for the user-chosen configuration of variables as visualizes those either over an age range within a specified time-period, or over time for astronauts with a specified age range. RESULTS The first iteration of the tool computes incidence a nd mortality rates for cardiovascular conditions and cancers. Code ha s been developed to retrieve the appropriate data from the IMPALA analysis platform, compute the models for incidence a nd mortality, a nd then use those models to generate the corresponding rate curves. A companion graphical user interface allows the user to specify the curves and visualize the results. CONCLUSIONS It is important to note that the rapid surveillance tool described here is neither meant to be a definitive assessment of the incidence or mortality of any particular disease or condition in the astronaut population, nor is it meant to be used for research purposes. Rather, it is meant as an early indicator that in-depth investigation may be warranted. By automating a repetitive process and leveraging carefully curated astronaut health outcomes, the tool makes possible a rapid “first look” into known areas of concern, and, if used judiciously, may surface new areas of concern for long-term astronaut health. This work is supported in part by the Translational Research Institute for Space Health (TRISH) through NASA Cooperative Agreement NNX16AO69A.

R J Reynolds↗
DOE OSTI2012

Fuel Cycle Research & Development: Technical Monthly – June 2012

Topics are: (1) MPACT Campaign - (a) Management and Integration • Coordination meetings between NE and NA-22, NA-24, and NA-82 were conducted the week of June 11th. Preparations are being made for the next MPACT working group meeting, scheduled for Aug 28-30 at Idaho Falls. In addition to covering accomplishments and discussing future plans, a site tour of INL facilities (MFC, EBR, ATR, INTEC) is being organized. (2) Accounting and Control Technologies - (a) Microcalorimetry • Now operating 256-pixel array at LANL. We are in the process of tuning detector parameters to improve and optimize performance. Preliminary measurements show approximate number of live pixels is similar to that observed previously at NIST. Continuing to study contribution to systematic error from uncertainties in tabulated gamma-ray energies. (b) Electrochemical Sensor • Testing of sensors fashioned from different precursor materials continued. SEM analysis of all used sensors has been or will be performed. (c) Lead Slowing Down Spectrometer • Ongoing perturbation calculations are providing information on the fundamental systematic error limits of LSDS. In order to achieve separating the contribution of Pu and 235U to the signal, there will need to be tight controls on systematic errors. Continuing to look into a He4 detector. Research into local construction of a He4 detector continued. We have started to apply the algorithm to test the LSDS using experimental data from previous RPI measurements. PNNL also developed a plan to address the lack of statistics in the MCNP modeling of the NGSI 64 assemblies. The ISU graduate student built and tested a fission chamber to gain experience with them. (d) Fast Neutron Imaging to Quantify Nuclear Materials • The imaging detector design was modified for each pixel to have an 8 x 8 pixel array. Quotations and purchasing process for components, including the new PSD scintillator are in progress. (e) Fast Neutron Multiplicity Analysis • The team submitted two papers to the upcoming INMM meeting that are related to the fast neutron multiplicity R&D effort. Progress was made on the project's main goal of designing a concept for a prototype fast-neutron multiplicity counter. We started laying out the outline for the final report. We have been working with our ORNL collaborators to develop a new digitizer system to support our experimental campaign planned for next year. (3) MPACT Analysis Tools - (a) Multi-isotope Process Monitor • Fuel characterization framework development continued during June. A report describing the methodologies is being completed. Kenneth Dayman, from University of Texas, spent a week at PNNL wrapping up his master's research and working on a journal submission covering that work. The target journal is the IEEE transactions on Nuclear Science; submission is planned for the end of July. A proposal to instrument H-Canyon is being prepared in conjunction with SRNL and the NNSA's NGSI program. The impact of gamma-ray spectrum counting statistics on the precision of relative radioisotope component intensities as reconstructed via Principal Component Regression (PCR) continued in June with Monte Carlo simulations of a two-component (i.e., two radioisotope) system. This work generalizes earlier studies in FY12 in which Poisson counting variations of only a single spectrum component were simulated. (b) Modeling and Simulation for Analysis of Safeguards Performance (Electrochemical) • Preliminary insights into safeguards challenges and the initial design for an electrochemical plant have been written up into an INMM paper and will be presented at the INMM Summer Meeting. Work is currently adding a new visualization capability for integrating materials accountancy with physical protection. (c) Material Control including Process Monitoring (Pattern Recognition, Sensors) • Fabrication of quartz chips continued at an external foundry. Awaiting delivery of the heat exchange manifold and chip holder. (d) MPACT System Integration and Technical Support • The initial report on cost-basis metrics for nuclear material security risk and proliferation risk was completed as scheduled. (4) Safeguards and Security by Design - (a) Used fuels storage security analysis, guidance and best practices • RFP was finalized and sent out. Awaiting response from World Institute for Nuclear Security. Coordinated with Scott Demuth on joint report • LANL milestone on best practices. Attended Nuclear Energy Institute National Nuclear Security Conference. Developed plan for soliciting input on prioritized issues for used fuel storage security. Worked on setting up a meeting with the Nuclear Regulatory Commission. Worked on FY2013 work package planning.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1979

Parameter estimation in X-ray astronomy using maximum likelihood

Methods of estimation of parameter values and confidence regions by maximum likelihood and Fisher efficient scores starting from Poisson probabilities are developed for the nonlinear spectral functions commonly encountered in X-ray astronomy. It is argued that these methods offer significant advantages over the commonly used alternatives called minimum chi-squared because they rely on less pervasive statistical approximations and so may be expected to remain valid for data of poorer quality. Extensive numerical simulations of the maximum likelihood method are reported which verify that the best-fit parameter value and confidence region calculations are correct over a wide range of input spectra.

Wachter, K.↗
NASA NTRS2005

Small-Scale Drop-Size Variability: Empirical Models for Drop-Size-Dependent Clustering in Clouds

By analyzing aircraft measurements of individual drop sizes in clouds, it has been shown in a companion paper that the probability of finding a drop of radius r at a linear scale l decreases as l(sup D(r)), where 0 less than or equals D(r) less than or equals 1. This paper shows striking examples of the spatial distribution of large cloud drops using models that simulate the observed power laws. In contrast to currently used models that assume homogeneity and a Poisson distribution of cloud drops, these models illustrate strong drop clustering, especially with larger drops. The degree of clustering is determined by the observed exponents D(r). The strong clustering of large drops arises naturally from the observed power-law statistics. This clustering has vital consequences for rain physics, including how fast rain can form. For radiative transfer theory, clustering of large drops enhances their impact on the cloud optical path. The clustering phenomenon also helps explain why remotely sensed cloud drop size is generally larger than that measured in situ.

Marshak, Alexander↗
NASA NTRS1977

Flight inspection data and crack initiation times

Lockheed C-130 service-flight inspection data is reduced by means of fracture mechanics and statistical analysis into a form from which the probability of time to crack initiation and the distribution of initial flaw sizes for various locations on the aircraft can be determined. Crack sizes are normalized by extrapolating a growing crack backwards from its first recorded size to .03 inches (crack initiation size) yielding the time to crack initiation. In a similar fashion, the crack is grown backwards to a time equal to zero to yield an initial flaw size. In order to perform the discussed computations, crack growth constants were computed for each individual location and were analyzed statistically. Statistical distributions were fitted to times to crack initiation and to initial flaw sizes in order to describe their expected behavior. Weibull and Johnson distributions have been found to fit the data reasonably well but for a better fit convolution integrals of Poisson load distributions and Weibull strength distributions are needed.

Johnson, W. S.↗
NASA NTRS1991

Statistical-mechanical selection of the shapes of disk galaxies

A new method is proposed for selecting steady state shapes of disk galaxies as 'most probable states' of a large number of stars, given only the total energy and total angular momentum. A partial differential equation is derived for the mean gravitational potential; it is closely related to the 'sinh-Poisson' equation for the mean-field description of a line vortex system or electrostatic guiding-center plasma. A 'water bag' approximation to the distribution function for bound stars renders the equation analytically tractable, but accurate solution of it may require numerical integration, in view of its general nonlinearity.

Montgomery, David↗
NASA NTRS2004

Spatial Distribution of Large Cloud Drops

The analysis of aircraft measurements of individual drop sizes in clouds suggests that for sufficiently small volumes the mean number of cloud drops with a given radius is proportional to volume powered by a drop-size dependent exponent. For abundant small drops present, the exponent is 1 as assumed in conventional approach. However, for rarer large drops, the exponents fall below unity. We show striking examples of the spatial distribution of large cloud drops using models that simulate the observed power laws. In contrast to currently used models that assume homogeneity and therefore a Poisson distribution of cloud drops, these models show strong drop clustering, the more so the larger the drops. The degree of clustering is determined by the observed exponents. The strong clustering of large drops arises naturally from the observed power-law statistics. This clustering has vital consequences for rain physics explaining how rain can form so fast and also helps explain why remotely sensed cloud drop size is generally biased.

Marshak, Alexander↗
DOE OSTI2015

DETECTING UNSPECIFIED STRUCTURE IN LOW-COUNT IMAGES

Unexpected structure in images of astronomical sources often presents itself upon visual inspection of the image, but such apparent structure may either correspond to true features in the source or be due to noise in the data. This paper presents a method for testing whether inferred structure in an image with Poisson noise represents a significant departure from a baseline (null) model of the image. To infer image structure, we conduct a Bayesian analysis of a full model that uses a multiscale component to allow flexible departures from the posited null model. As a test statistic, we use a tail probability of the posterior distribution under the full model. This choice of test statistic allows us to estimate a computationally efficient upper bound on a p-value that enables us to draw strong conclusions even when there are limited computational resources that can be devoted to simulations under the null model. We demonstrate the statistical performance of our method on simulated images. Applying our method to an X-ray image of the quasar 0730+257, we find significant evidence against the null model of a single point source and uniform background, lending support to the claim of an X-ray jet.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2004

Spatial Distribution of Large Cloud Drops

By analyzing aircraft measurements of individual drop sizes in clouds, we have shown in a companion paper (Knyazikhin et al., 2004) that the probability of finding a drop of radius r at a linear scale l decreases as l(sup D(r)) where 0 less than or equal to D(r) less than or equal to 1. This paper shows striking examples of the spatial distribution of large cloud drops using models that simulate the observed power laws. In contrast to currently used models that assume homogeneity and therefore a Poisson distribution of cloud drops, these models show strong drop clustering, the more so the larger the drops. The degree of clustering is determined by the observed exponents D(r). The strong clustering of large drops arises naturally from the observed power-law statistics. This clustering has vital consequences for rain physics explaining how rain can form so fast. It also helps explain why remotely sensed cloud drop size is generally biased and why clouds absorb more sunlight than conventional radiative transfer models predict.

Marshak, A.↗
DOE OSTI2023

AGC-2 Specimen Post Irradiation Data Package Report

This report documents results of the post-irradiation examination material property testing of the creep, control, and piggyback specimens from the irradiation creep capsule Advanced Graphite Creep (AGC)-2 are reported. This is the second of a series of six irradiation test trains planned as part of the AGC experiment to fully characterize the neutron irradiation effects and radiation creep behavior of current nuclear graphite grades. The AGC-2 capsule was irradiated in the Idaho National Laboratory Advanced Test Reactor at a nominal temperature of 600°C and to a peak dose of 5 dpa (displacements per atom). One half of the creep specimens were subjected to mechanical stresses (an applied stress of either 13.8, 17.2, or 20.7 MPa) to induce irradiation creep. All post-irradiation testing and measurement results are reported with the exception of the irradiation mechanical strength testing, which is the last destructive testing stage of the irradiation testing program. Material property tests were conducted on specimens from 15 nuclear graphite grades using a similar loading configuration as the first AGC capsule (AGC-1) to provide easy comparison between the two capsules. However, AGC-2 contained an increased number of specimens (i.e., 487 total specimens irradiated) and replaced specimens of the minor grade 2020 with the newer grade 2114. The data reported include specimen dimensions for both stressed and unstressed specimens to establish the irradiation creep rates, mass and volume data necessary to derive density, elastic constants (Young’s modulus, shear modulus, and Poisson’s ratio) from ultrasonic time of flight velocity measurements, Young’s modulus from the fundamental frequency of vibration, electrical resistivity, and thermal diffusivity and thermal expansion data from 100–500°C. No data outliers were determined after all measurements were completed. A brief statistical analysis was performed on the irradiated data and a limited comparison between pre- and post-irradiation properties is presented. A more complete evaluation of trends in the material property changes, as well as irradiation-induced creep due to irradiation, temperature, and applied load on specimens will be discussed in later AGC-2 post-irradiation examination analysis reports.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Multiple Facets of the Poisson Distribution Applicable to Health Physics Measurements

This paper discusses several ways to view the standard Poisson distribution as applied to health physics scaler counts. The intent is not so much to present calculational details but rather to present some underlying concepts. Examples are provided that illustrate the various concepts for several types of specific measurements. The concepts presented involve purely Poisson-based contributions to variance; extra-Poisson variance is presently ignored, and any counting system would be presumed to function properly and without counting loss.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Assessing compatibility of direct detection data: halo-independent global likelihood analyses

We present two different halo-independent methods to assess the compatibility of several direct dark matter detection data sets for a given dark matter model using a global likelihood consisting of at least one extended likelihood and an arbitrary number of Gaussian or Poisson likelihoods. In the first method we find the global best fit halo function (we prove that it is a unique piecewise constant function with a number of down steps smaller than or equal to a maximum number that we compute) and construct a two-sided pointwise confidence band at any desired confidence level, which can then be compared with those derived from the extended likelihood alone to assess the joint compatibility of the data. In the second method we define a “constrained parameter goodness-of-fit” test statistic, whose p-value we then use to define a “plausibility region” (e.g. where p≥10%). For any halo function not entirely contained within the plausibility region, the level of compatibility of the data is very low (e.g. p<10%). We illustrate these methods by applying them to CDMS-II-Si and SuperCDMS data, assuming dark matter particles with elastic spin-independent isospin-conserving interactions or exothermic spin-independent isospin-violating interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

On the statistical thermodynamics of a free-standing nanocrystal: Silicon

The dependence of the thermodynamic parameters of a free-standing nanocrystal of simple matter on its size, density, temperature, and surface shape has been studied. The following parameters have been analyzed: Debye temperature Θ, Gruneisen parameter γ, melting temperature T{sub m}, surface energy σ, surface pressure P{sub sf}, elastic modulus B{sub T}, Poisson ratio μ, thermal expansion coefficient α{sub p}, and specific heats c{sub v} and c{sub p}. Calculations performed for silicon have shown that the functions Θ, T{sub m}, σ, and B{sub T} decrease, whereas the functions γ, |P{sub sf}|, μ, α{sub p}, c{sub v}, and c{sub p} increase with an isomorphic decrease in the number of atoms N. The stronger the nanocrystal shape deviates from the most energetically stable shape, the more pronounced the change in the aforementioned functions with an isothermal decrease in N is.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2013

Assessing the Uncertainty in QUANTEC's Dose–Response Relation of Lung and Spinal Cord With a Bootstrap Analysis

Purpose: To apply a statistical bootstrap analysis to assess the uncertainty in the dose–response relation for the endpoints pneumonitis and myelopathy reported in the QUANTEC review. Methods and Materials: The bootstrap method assesses the uncertainty of the estimated population-based dose-response relation due to sample variability, which reflects the uncertainty due to limited numbers of patients in the studies. A large number of bootstrap replicates of the original incidence data were produced by random sampling with replacement. The analysis requires only the dose, the number of patients, and the number of occurrences of the studied endpoint, for each study. Two dose–response models, a Poisson-based model and the Lyman model, were fitted to each bootstrap replicate using maximum likelihood. Results: The bootstrap analysis generates a family of curves representing the range of plausible dose–response relations, and the 95% bootstrap confidence intervals give an estimated upper and lower toxicity risk. The curve families for the 2 dose–response models overlap for doses included in the studies at hand but diverge beyond that, with the Lyman model suggesting a steeper slope. The resulting distributions of the model parameters indicate correlation and non-Gaussian distribution. For both data sets, the likelihood of the observed data was higher for the Lyman model in >90% of the bootstrap replicates. Conclusions: The bootstrap method provides a statistical analysis of the uncertainty in the estimated dose–response relation for myelopathy and pneumonitis. It suggests likely values of model parameter values, their confidence intervals, and how they interrelate for each model. Finally, it can be used to evaluate to what extent data supports one model over another. For both data sets considered here, the Lyman model was preferred over the Poisson-based model.

62 RADIOLOGY AND NUCLEAR MEDICINE↗