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At least 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

STATISTICS OF MICROLENSING CAUSTIC CROSSINGS IN Q 2237+0305: PECULIAR VELOCITY OF THE LENS GALAXY AND ACCRETION DISK SIZE

We use the statistics of caustic crossings induced by microlensing in the lens system Q 2237+0305 to study the lens galaxy peculiar velocity. We calculate the caustic crossing rates for a comprehensive family of stellar mass functions and find a dependence of the average number of caustic crossings with the effective transverse velocity and the average mass, 〈n〉∝v{sub eff}/√(〈m〉), equivalent to the theoretical prediction for the case of microlenses with identical masses. We explore the possibilities of the method to measure v {sub eff} using the ∼12 yr of Optical Gravitational Lensing Experiment monitoring of the four images of Q 2237+0305. To determine a lower limit for v {sub eff}, we count, conservatively, a single caustic crossing for each one of the four high magnification events identified in the literature (plus one additional proposed by us) obtaining v{sub eff}≳240√(〈m〉/0.17 M{sub ⊙}) km s{sup −1} at 68% of confidence. From this value and the average FWHM of the four high magnification events, we obtain a lower limit of r{sub s}≳1.4√(〈m〉/0.17 M{sub ⊙}) light-days for the radius of the source (r{sub s} = FWHM/2.35). Tentative identification of three additional caustic crossing events leads to estimates of v{sub eff}≃(493±246)√(〈m〉/0.17 M{sub ⊙}) km s{sup −1} for the effective transverse velocity and of r{sub s}≃(2.7±1.3)√(〈m〉/0.17 M{sub ⊙}) light-days for the source size. The estimated transverse peculiar velocity of the galaxy is v{sub t}≃(429±246)√(〈m〉/0.17 M{sub ⊙}) km s{sup −1}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

The statistics of BAT-to-XRT flux ratio in GRBs: Evidence for a characteristic value and its implications

We present the statistics of the ratio, R, between the prompt and afterglow “plateau” fluxes of gamma-ray bursts (GRBs). We define this as the ratio of the mean prompt energy flux in Swift BAT and the Swift XRT one, immediately following the steep transition between these two states and the beginning of the afterglow stage referred to as the “plateau”. Like the distribution of many other GRB observables, the histogram of R is log-normal with maximum at a value R{sub m}≃2000, FWHM of about two decades, and with the entire distribution spanning about five decades in the value of R. We note that the peak of the distribution is close to the proton-to-electron mass ratio (R{sub m}≃m{sub p}/m{sub e}=1836), as proposed to be the case in an earlier publication, on the basis of a specific model of the GRB dissipation process. It therefore appears that, in addition to the values of the energy of peak luminosity E{sub pk}∼m{sub e}c{sup 2}, GRBs present us with one more quantity with an apparent characteristic value. The fact that the values of both these quantities (E{sub pk} and R) are consistent with the same specific model invoked to account for the efficient conversion of their relativistic proton energies to electrons argues favorably for its underlying assumptions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Lens statistics with gravitationally lensed yet morphologically regular images

GRAMORs are GRAvitationally highly magnified yet MORphologically regular images. An example of this phenomenon was discovered in the cluster MACS J1149.5+2223 in 2009. We investigate the lens statistics of GRAMORs in detail. Assuming a NFW profile for a sample of clusters, we calculate the expected number and redshift distribution of GRAMORs using parameters from COSMOS data for the number density of the background galaxy. A model with a cluster placed at z = 0.544 based on WMAP5 cosmology predicts the redshift of a GRAMOR at z≃1.49 which is close to the observed z = 1.4906. These results show that the expected number of GRAMORs is about two per cluster in the most likely case, and thus a large number of GRAMORs would be observed in a systematic survey. The probability distribution function of source redshift for GRAMORs depends strongly on dark energy and may be useful for constraining the nature of dark energy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

TOWARD COMPLETE STATISTICS OF MASSIVE BINARY STARS: PENULTIMATE RESULTS FROM THE CYGNUS OB2 RADIAL VELOCITY SURVEY

We analyze orbital solutions for 48 massive multiple-star systems in the Cygnus OB2 association, 23 of which are newly presented here, to find that the observed distribution of orbital periods is approximately uniform in log P for P < 45 days, but it is not scale-free. Inflections in the cumulative distribution near 6 days, 14 days, and 45 days suggest key physical scales of ≅0.2, ≅0.4, and ≅1 A.U. where yet-to-be-identified phenomena create distinct features. No single power law provides a statistically compelling prescription, but if features are ignored, a power law with exponent β ≅ –0.22 provides a crude approximation over P = 1.4-2000 days, as does a piece-wise linear function with a break near 45 days. The cumulative period distribution flattens at P > 45 days, even after correction for completeness, indicating either a lower binary fraction or a shift toward low-mass companions. A high degree of similarity (91% likelihood) between the Cyg OB2 period distribution and that of other surveys suggests that the binary properties at P ≲ 25 days are determined by local physics of disk/clump fragmentation and are relatively insensitive to environmental and evolutionary factors. Fully 30% of the unbiased parent sample is a binary with period P < 45 days. Completeness corrections imply a binary fraction near 55% for P < 5000 days. The observed distribution of mass ratios 0.2 < q < 1 is consistent with uniform, while the observed distribution of eccentricities 0.1 < e < 0.6 is consistent with uniform plus an excess of e ≅ 0 systems. We identify six stars, all supergiants, that exhibit aperiodic velocity variations of ∼30 km s{sup –1} attributed to atmospheric fluctuations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Statistical methods for thermonuclear reaction rates and nucleosynthesis simulations

Rigorous statistical methods for estimating thermonuclear reaction rates and nucleosynthesis are becoming increasingly established in nuclear astrophysics. The main challenge being faced is that experimental reaction rates are highly complex quantities derived from a multitude of different measured nuclear parameters (e.g., astrophysical S-factors, resonance energies and strengths, particle and γ-ray partial widths). We discuss the application of the Monte Carlo method to two distinct, but related, questions. First, given a set of measured nuclear parameters, how can one best estimate the resulting ther- monuclear reaction rates and associated uncertainties? Second, given a set of appropriate reaction rates, how can one best estimate the abundances from nucleosynthesis (i.e., reaction network) calculations? The techniques described here provide probability density functions that can be used to derive statisti- cally meaningful reaction rates and final abundances for any desired coverage probability. Examples are given for applications to s-process neutron sources, core-collapse supernovae, classical novae, and Big Bang nucleosynthesis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Statistical measures of Planck scale signal correlations in interferometers

Here, a model-independent statistical framework is presented to interpret data from systems where the mean time derivative of positional cross correlation between world lines, a measure of spreading in a quantum geometrical wave function, is measured with a precision smaller than the Planck time. The framework provides a general way to constrain possible departures from perfect independence of classical world lines, associated with Planck scale bounds on positional information. A parametrized candidate set of possible correlation functions is shown to be consistent with the known causal structure of the classical geometry measured by an apparatus, and the holographic scaling of information suggested by gravity. Frequency-domain power spectra are derived that can be compared with interferometer data. As a result, simple projections of sensitivity for specific experimental set-ups suggests that measurements will directly yield constraints on a universal time derivative of the correlation function, and thereby confirm or rule out a class of Planck scale departures from classical geometry.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Nonequilibrium statistical mechanics and optimal prediction of partially-observed complex systems

Abstract Only a subset of degrees of freedom are typically accessible or measurable in real-world systems. As a consequence, the proper setting for empirical modeling is that of partially-observed systems. Notably, data-driven models consistently outperform physics-based models for systems with few observable degrees of freedom; e.g. hydrological systems. Here, we provide an operator-theoretic explanation for this empirical success. To predict a partially-observed system’s future behavior with physics-based models, the missing degrees of freedom must be explicitly accounted for using data assimilation and model parametrization. Data-driven models, in contrast, employ delay-coordinate embeddings and their evolution under the Koopman operator to implicitly model the effects of the missing degrees of freedom. We describe in detail the statistical physics of partial observations underlying data-driven models using novel maximum entropy and maximum caliber measures. The resulting nonequilibrium Wiener projections applied to the Mori–Zwanzig formalism reveal how data-driven models may converge to the true dynamics of the observable degrees of freedom. Additionally, this framework shows how data-driven models infer the effects of unobserved degrees of freedom implicitly, in much the same way that physics models infer the effects explicitly. This provides a unified implicit-explicit modeling framework for predicting partially-observed systems, with hybrid physics-informed machine learning methods combining both implicit and explicit aspects.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Tomography and weak lensing statistics

We provide generic predictions for the lower order cumulants of weak lensing maps, and their correlators for tomographic bins as well as in three dimensions (3D). Using small-angle approximation, we derive the corresponding one- and two-point probability distribution function for the tomographic maps from different bins and for 3D convergence maps. The modelling of weak lensing statistics is obtained by adopting a detailed prescription for the underlying density contrast that involves hierarchal ansatz and lognormal distribution. We study the dependence of our results on cosmological parameters and source distributions corresponding to the realistic surveys such as LSST and DES. We briefly outline how photometric redshift information can be incorporated in our results. We also show how topological properties of convergence maps can be quantified using our results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Distinguishing dark matter from unresolved point sources in the Inner Galaxy with photon statistics

Data from the Fermi Large Area Telescope suggests that there is an extended excess of GeV gamma-ray photons in the Inner Galaxy. Identifying potential astrophysical sources that contribute to this excess is an important step in verifying whether the signal originates from annihilating dark matter. In this paper, we focus on the potential contribution of unresolved point sources, such as millisecond pulsars (MSPs). We propose that the statistics of the photons—in particular, the flux probability density function (PDF) of the photon counts below the point-source detection threshold—can potentially distinguish between the dark-matter and point-source interpretations. We calculate the flux PDF via the method of generating functions for these two models of the excess. Working in the framework of Bayesian model comparison, we then demonstrate that the flux PDF can potentially provide evidence for an unresolved MSP-like point-source population.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Vacuum statistics and stability in axionic landscapes

We investigate vacuum statistics and stability in random axionic landscapes. For this purpose we developed an algorithm for a quick evaluation of the tunneling action, which in most cases is accurate within 10%. We find that stability of a vacuum is strongly correlated with its energy density, with lifetime rapidly growing as the energy density is decreased. On the other hand, the probability P(B) for a vacuum to have a tunneling action B greater than a given value declines as a slow power law in B. This is in sharp contrast with the studies of random quartic potentials, which found a fast exponential decline of P(B). Our results suggest that the total number of relatively stable vacua (say, with B>100) grows exponentially with the number of fields N and can get extremely large for N∼> 100. The problem with this kind of model is that the stable vacua are concentrated near the absolute minimum of the potential, so the observed value of the cosmological constant cannot be explained without fine-tuning. To address this difficulty, we consider a modification of the model, where the axions acquire a quadratic mass term, due to their mixing with 4-form fields. This results in a larger landscape with a much broader distribution of vacuum energies. The number of relatively stable vacua in such models can still be extremely large.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Statistics of the charge spectrum of photo-multipliers and methods for absolute calibration

We derive the full expression for the shape of the charge spectrum that results from the illumination of a photo-multiplier tube. The derivation is for low intensity illumination with constant gain, a common condition for most nuclear and particle physics applications. Under these conditions, it is shown that an analytic expression can be formulated that describes details of the spectrum including the pedestal and dark noise with excellent fidelity to allow statistical fits to data. The derivation and full formula using either Gaussian or Poisson models for gain, and its limiting forms under various simplifying assumptions are presented with strategies on their use. The analytic description can be used to formulate data acquisition strategies to perform precise absolute calibration of photo-multipliers, the digitizers, and the data acquisition system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Self-calibrating the look-elsewhere effect: fast evaluation of the statistical significance using peak heights

In experiments where one searches a large parameter space for an anomaly, one often finds many spurious noise-induced peaks in the likelihood. This is known as the look-elsewhere effect, and must be corrected for when performing statistical analysis. Here, this paper introduces a method to calibrate the false alarm probability (FAP), or p-value, for a given dataset by considering the heights of the highest peaks in the likelihood. Specifically, we derive an equation relating the global p-value to the rank and height of local maxima. In the simplest form of self-calibration, the look-elsewhere-corrected $\chi^2$ of a physical peak is approximated by the $\chi^2$ of the peak minus the $\chi^2$ of the highest noise-induced peak, with accuracy improved by considering lower peaks. In contrast to alternative methods, this approach has negligible computational cost as peaks in the likelihood are a byproduct of every peak-search analysis. We apply to examples from astronomy, including planet detection, periodograms, and cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Statistical theory of deformation distributions in nuclear spectra

The dependence of the nuclear level density on intrinsic deformation is an important input to dynamical nuclear processes such as fission. The auxiliary-field Monte Carlo (AFMC) method is a powerful method for computing state densities. However, the statistical distribution of intrinsic shapes is not readily accessible due to the formulation of the AFMC method in a spherical configuration-interaction shell-model approach. Instead, the theory of deformation has largely relied on a mean-field approximation which breaks rotational symmetry. We show here how the distributions of the intrinsic quadrupole deformation parameters can be calculated within the AFMC method and present results for a chain of even-mass samarium nuclei ( 148 Sm, 150 Sm, 152 Sm, 154 Sm) which includes spherical, transitional, and strongly deformed isotopes. The method relies on a Landau-like expansion of the Helmholtz free energy in invariant polynomials of the quadrupole tensor. Here we find that an expansion to fourth order provides an excellent description of the AFMC results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Solidarity of signal of measures for the liquid-gas phase transition in the statistical multifragmentation model

A systematic study of system size, N / Z asymmetry, and fragmenting volume effects as well as the Coulomb effect on experimental measures for the nuclear liquid-gas phase transition and the mechanism of phase transition are carried out in the framework of the statistical multifragmentation model (SMM). The measures examined here are the caloric curve, the specific heat capacity ( C v ), the multiplicity derivative (dM / dT), the moment parameters (M2 and γ2), the fluctuation of maximum fragment charge number (NVZ), the Fisher exponent (τ), and the Zipf's law parameter (ξ). A signal for the first-order phase transition for all the measures is observed. A stronger signal is observed in the system with smaller sizes or with more neutron rich or in smaller fragmenting volumes for the caloric curve, Cv, and dM/dT. The phase-transition temperatures are independent of the system size, N / Z asymmetry, fragmenting volume, and Coulomb force, which indicates these measures give a solid signal for the liquid-gas phase transition in SMM. On the other hand, the phase transition temperature and its behavior of the others slightly depend on the size, the N / Z asymmetry and the volume of the system. A negative heat capacity is observed for systems with A s ≥ 100 without the Coulomb force but disappears with the Coulomb. An instructive picture is given in the charge distributions for the observed first-order phase transition.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
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↗
DOE OSTI2024

Thermodynamically informed priors for uncertainty propagation in first-principles statistical mechanics

Here, this work demonstrates how first-principles statistical mechanics approaches within a Bayesian framework can quantify and propagate uncertainties to downstream thermodynamic calculations. To address the issue of Bayesian prior selection, knowledge of 0 K ground states in the material system of interest is incorporated into the prior. The effectiveness of this framework is shown by creating a phase diagram for the fcc zirconium nitride system, including confidence intervals on order-disorder transition temperatures.

Bayesian methods↗
DOE OSTI2025

Temporal Forecasting of Distributed Temperature Sensing in a Thermal Hydraulic System With Machine Learning and Statistical Models

We benchmark performance of long-short term memory (LSTM) network machine learning model and autoregressive integrated moving average (ARIMA) statistical model in temporal forecasting of distributed temperature sensing (DTS). Data in this study consists of fluid temperature transient measured with two co-located Rayleigh scattering fiber optic sensors (FOS) in a forced convection mixing zone of a thermal tee. We treat each gauge of a FOS as an independent temperature sensor. We first study prediction of DTS time series using Vanilla LSTM and ARIMA models trained on prior history of the same FOS that is used for testing. The results yield maximum absolute percentage error (MaxAPE) and root mean squared percentage error (RMSPE) of 1.58% and 0.06% for ARIMA, and 3.14% and 0.44% for LSTM, respectively. Next, we investigate zero-shot forecasting (ZSF) with LSTM and ARIMA trained on history of the co-located FOS only, which is advantageous when limited training data is available. The ZSF MaxAPE and RMSPE values for ARIMA are comparable to those of the Vanilla use case, while the error values for LSTM increase. We show that in ZSF, performance of LSTM network can be improved by training on most correlated gauges between the two FOS, which are identified by calculating the Pearson correlation coefficient. The improved ZSF MaxAPE and RMSPE for LSTM are 4.4% and 0.33%, respectively. Performance of ZSF LSTM can be further enhanced through transfer learning (TL), where LSTM is re-trained on a subset of the FOS that is the target of forecasting. We show that LSTM pre-trained on correlated dataset and re-trained on 30% of testing target dataset achieves MaxAPE and RMSPE values of 2.32% and 0.28%, respectively.

ARIMA↗
DOE OSTI2017

Representative Day Selection Using Statistical Bootstrapping for Accelerating Annual Distribution Simulations

Capturing technical and economic impacts of solar photovoltaics (PV) and other distributed energy resources (DERs) on electric distribution systems can require high-time resolution (e.g. 1 minute), long-duration (e.g. 1 year) simulations. However, such simulations can be computationally prohibitive, particularly when including complex control schemes in quasi-steady-state time series (QSTS) simulation. Various approaches have been used in the literature to down select representative time segments (e.g. days), but typically these are best suited for lower time resolutions or consider only a single data stream (e.g. PV production) for selection. We present a statistical approach that combines stratified sampling and bootstrapping to select representative days while also providing a simple method to reassemble annual results. We describe the approach in the context of a recent study with a utility partner. This approach enables much faster QSTS analysis by simulating only a subset of days, while maintaining accurate annual estimates.

14 SOLAR ENERGY↗