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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Integrating Symbolic and Statistical Methods for Testing Intelligent Systems Applications to Machine Learning and Computer Vision

Embedded intelligent systems ranging from tiny im- plantable biomedical devices to large swarms of autonomous un- manned aerial systems are becoming pervasive in our daily lives. While we depend on the flawless functioning of such intelligent systems, and often take their behavioral correctness and safety for granted, it is notoriously difficult to generate test cases that expose subtle errors in the implementations of machine learning algorithms. Hence, the validation of intelligent systems is usually achieved by studying their behavior on representative data sets, using methods such as cross-validation and bootstrapping.In this paper, we present a new testing methodology for studying the correctness of intelligent systems. Our approach uses symbolic decision procedures coupled with statistical hypothesis testing to. We also use our algorithm to analyze the robustness of a human detection algorithm built using the OpenCV open-source computer vision library. We show that the human detection implementation can fail to detect humans in perturbed video frames even when the perturbations are so small that the corresponding frames look identical to the naked eye.

Jha, Sumit Kumar↗
DOE OSTI2019

How to optimally constrain galaxy assembly bias: supplement projected correlation functions with count-in-cells statistics

Most models for the statistical connection between galaxies and their haloes ignore the possibility that galaxy properties may be correlated with halo properties other than halo mass, a phenomenon known as galaxy assembly bias. And yet, it is known that such correlations can lead to systematic errors in the interpretation of survey data that are analysed using traditional halo occupation models. At present, the degree to which galaxy assembly bias may be present in the real Universe, and the best strategies for constraining it remain uncertain. We study the ability of several observables to constrain galaxy assembly bias from redshift survey data using the decorated halo occupation distribution (dHOD), an empirical model of the galaxy-halo connection that incorporates assembly bias. We cover an expansive set of observables, including the projected two-point correlation function w p ( r p ), the galaxy-galaxy lensing signal ΔΣ( r p ), the void probability function VPF( r ), the distributions of counts-in-cylinders P(NCIC), and counts-in-annuli P(NCIA), and the distribution of the ratio of counts in cylinders of different sizes P ( N 2 /N 5 ). We find that despite the frequent use of the combination w p ( r p ) + ΔΣ( r p ) in interpreting galaxy data, the count statistics, P ( N CIC ) and P ( N CIA ), are generally more efficient in constraining galaxy assembly bias when combined with w p ( r p ). Constraints based upon w p ( r p ) and ΔΣ(rp) share common degeneracy directions in the parameter space, while combinations of r p w p ( r p ) with the count statistics are more complementary. Therefore, we strongly suggest that count statistics should be used to complement the canonical observables in future studies of the galaxy-halo connection.

galaxies: evolution↗
DOE OSTI2017

Determining the hubble constant from hubble parameter measurements

We use 28 measurements of the Hubble parameter, H(z), at intermediate redshifts 0.07⩽z⩽2.3 to determine the present-day Hubble constant H{sub 0} in four cosmological models. We measure H{sub 0}=68.3{sub −2.6}{sup +2.7},68.4{sub −3.3}{sup +2.9},65.0{sub −6.6}{sup +6.5}, and 67.9{sub −2.4}{sup +2.4} km s{sup −1} Mpc{sup −1} (1σ errors) in the ΛCDM (spatially flat and non-flat), ωCDM, and ϕCDM models, respectively. These measured H{sub 0} values are more consistent with the lower values determined from recent data on the cosmic microwave background and baryon acoustic oscillations, as well as with the value found from a median statistical analysis of Huchra’s compilation of H{sub 0} measurements, but include the higher local measurements of H{sub 0} within the 2σ confidence limits.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Cosmology Constraints from the Weak Lensing Peak Counts and the Power Spectrum in CFHTLenS

Lensing peaks have been proposed as a useful statistic, containing cosmological information from non-Gaussianities that is inaccessible from traditional two-point statistics such as the power spectrum or two-point correlation functions. Here we examine constraints on cosmological parameters from weak lensing peak counts, using the publicly available data from the 154 deg2 CFHTLenS survey. We utilize a new suite of ray-tracing N-body simulations on a grid of 91 cosmological models, covering broad ranges of the three parameters Ω m , σ 8 , and w, and replicating the galaxy sky positions, redshifts, and shape noise in the CFHTLenS observations. We then build an emulator that interpolates the power spectrum and the peak counts to an accuracy of ≤ 5%, and compute the likelihood in the three-dimensional parameter space (Ω m , σ 8 , w) from both observables. We find that constraints from peak counts are comparable to those from the power spectrum, and somewhat tighter when different smoothing scales are combined. Neither observable can constrain w without external data. When the power spectrum and peak counts are combined, the area of the error “banana” in the (Ω m , σ 8 ) plane reduces by a factor of ≈ two, compared to using the power spectrum alone. For a flat Λ cold dark matter model, combining both statistics, we obtain the constraint σ 8 (Ω m /0.27)0.63 = 0.85 +0.03 -0.03 .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Spectral risk measures: the risk quadrangle and optimal approximation

We develop a general risk quadrangle that gives rise to a large class of spectral risk measures. The statistic of this new risk quadrangle is the average value-at-risk at a specific confidence level. As such, this risk quadrangle generates a continuum of error measures that can be used for superquantile regression. For risk-averse optimization, we introduce an optimal approximation of spectral risk measures using quadrature. Lastly, we prove the consistency of this approximation and demonstrate our results through numerical examples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Large-scale scenarios of electric vehicle charging with a data-driven model of control

Transportation electrification is forecast to bring millions of new electric vehicles to roads worldwide this decade. Planning to support those vehicles depends on detailed scenarios of their electricity demand in both uncontrolled and controlled or smart charging scenarios. In this work, we present a novel modeling approach to enable rapid generation of demand estimates that represent the impact of controlled charging for large-scale scenarios with millions of individual drivers. To model the effect of load modulation control on aggregate charging profiles, we propose a novel machine learning approach that replaces traditional optimization approaches. We demonstrate its performance modeling workplace charging control under a range of electricity rate schedules, achieving small errors (2.5%–4.5%) while accelerating computations by more than 4000 times. To generate the uncontrolled charging demand for scenarios with residential, workplace, and public charging we use statistical representations of a large data set of real charging sessions. We demonstrate the methodology by generating diverse sets of scenarios for California's charging demand in 2030 which consider multiple charging segments and controls, each run locally in under 50 s. We further demonstrate support for rate design by modeling the large-scale impact of a new, custom rate schedule for workplace charging.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Identifying Inconsistencies in Fission Product Yield Evaluations with Prompt Neutron Emission

Here, we present a self-consistency analysis of fission product yield evaluations. Anomalous yields are determined using a series of simple conservation checks and comparing charge distributions with common parameterizations. The summed average prompt neutron multiplicity for both products as a function of the heavy product mass is derived directly from the independent fission product yields with a procedure utilizing average charge conservation. This procedure is validated with Monte Carlo simulations of the de-excitation of the fission fragments in a Hauser-Feshbach statistical decay framework. The derived is compared with experimental data, when available, and then used to determine the prompt neutron multiplicity for the various evaluations. The propagated errors on from the average charge conservation method are significantly lower than the simple summation rules, which reveals that some evaluations are inconsistent with prompt neutron data. We propose possible solutions to remedy the observed inconsistencies and identify sources of the observed differences in between the various evaluation libraries.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Detectability of standing accretion shock instabilities activity in supernova neutrino signals

We introduce a novel methodology for establishing the presence of standing accretion shock instabilities (SASI) in the dynamics of a core collapse supernova from the observed neutrino event rate at water- or ice- based neutrino detectors. The methodology uses a likelihood ratio in the frequency domain as a test- statistics; it is also employed to assess the potential to estimate the frequency and the amplitude of the SASI modulations of the neutrino signal. The parameter estimation errors are consistent with the minimum possible errors as evaluated from the inverse of the Fisher information matrix, and close to the theoretical minimum for the SASI amplitude. Using results from a core-collapse simulation of a 15 solar-mass star by Kuroda et al. [Astrophys. J. 851, 62 (2017).] as a test bed for the method, we find that SASI can be identified with high confidence for a distance to the supernova of up to ~6 kpc for IceCube and up to ~3 kpc for a 0.4 Mt mass water Cherenkov detector. This methodology will aid the investigation of a future galactic supernova.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Efficient scatter distribution estimation and correction in CBCT using concurrent Monte Carlo fitting

Purpose: X-ray scatter is a significant impediment to image quality improvements in cone-beam CT (CBCT). The authors present and demonstrate a novel scatter correction algorithm using a scatter estimation method that simultaneously combines multiple Monte Carlo (MC) CBCT simulations through the use of a concurrently evaluated fitting function, referred to as concurrent MC fitting (CMCF). Methods: The CMCF method uses concurrently run MC CBCT scatter projection simulations that are a subset of the projection angles used in the projection set, P, to be corrected. The scattered photons reaching the detector in each MC simulation are simultaneously aggregated by an algorithm which computes the scatter detector response, S{sub MC}. S{sub MC} is fit to a function, S{sub F}, and if the fit of S{sub F} is within a specified goodness of fit (GOF), the simulations are terminated. The fit, S{sub F}, is then used to interpolate the scatter distribution over all pixel locations for every projection angle in the set P. The CMCF algorithm was tested using a frequency limited sum of sines and cosines as the fitting function on both simulated and measured data. The simulated data consisted of an anthropomorphic head and a pelvis phantom created from CT data, simulated with and without the use of a compensator. The measured data were a pelvis scan of a phantom and patient taken on an Elekta Synergy platform. The simulated data were used to evaluate various GOF metrics as well as determine a suitable fitness value. The simulated data were also used to quantitatively evaluate the image quality improvements provided by the CMCF method. A qualitative analysis was performed on the measured data by comparing the CMCF scatter corrected reconstruction to the original uncorrected and corrected by a constant scatter correction reconstruction, as well as a reconstruction created using a set of projections taken with a small cone angle. Results: Pearson’s correlation, r, proved to be a suitable GOF metric with strong correlation with the actual error of the scatter fit, S{sub F}. Fitting the scatter distribution to a limited sum of sine and cosine functions using a low-pass filtered fast Fourier transform provided a computationally efficient and accurate fit. The CMCF algorithm reduces the number of photon histories required by over four orders of magnitude. The simulated experiments showed that using a compensator reduced the computational time by a factor between 1.5 and 1.75. The scatter estimates for the simulated and measured data were computed between 35–93 s and 114–122 s, respectively, using 16 Intel Xeon cores (3.0 GHz). The CMCF scatter correction improved the contrast-to-noise ratio by 10%–50% and reduced the reconstruction error to under 3% for the simulated phantoms. Conclusions: The novel CMCF algorithm significantly reduces the computation time required to estimate the scatter distribution by reducing the statistical noise in the MC scatter estimate and limiting the number of projection angles that must be simulated. Using the scatter estimate provided by the CMCF algorithm to correct both simulated and real projection data showed improved reconstruction image quality.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Comparison of statistical and deterministic frameworks of uncertainty quantification

Two different approaches to the prediction problem are compared employing a realistic example— combustion of natural gas—with 102 uncertain parameters and 76 quantities of interests. One approach, termed bound-to-bound data collaboration (abbreviated to B2B), deploys semidefinite programming algorithms where the initial bounds on unknowns are combined with initial bounds of experimental data to produce new uncertainty bounds for the unknowns that are consistent with the data and, finally, deterministic uncertainty bounds for prediction in new settings. The other approach is statistical and Bayesian, referred to as BCP (for Bayesian calibration and prediction). It places prior distributions on the unknown parameters and on the parameters of the measurement error distributions and produces posterior distributions for model parameters and posterior distributions for model predictions in new settings. The predictions from the two approaches are consistent; a very large degree of overlap exists between B2B bounds and the support of the BCP predictive distribution. Interpretation and comparison of the results is closely connected with assumptions made about the model and experimental data and how they are used in both settings. As a result, the principal conclusion is that use of both methods protects against possible violations of assumptions in the BCP approach and conservative specifications and predictions using B2B.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Final Technical Report for DE-SC0012297

This is the final report on the work performed in award DE-SC0012297, Cosmic Frontier work in support of the LSST Dark Energy Science Collaboration's work to develop algorithms, simulations, and statistical tests to ensure optimal extraction of the dark energy properties from galaxy clusters observed with LSST. This work focused on effects that could produce a systematic error on the measurement of cluster masses (that will be used to probe the effects of dark energy on the growth of structure). These effects stem from the deviations from pure ellipticity of the gravitational lensing signal and from the blending of light of neighboring galaxies. Both these effects are expected to be more significant for LSST than for the stage III experiments such as the Dark Energy Survey. We calculate the magnitude of the mass error (or bias) for the first time and demonstrate that it can be treated as a multiplicative correction and calibrated out, allowing mass measurements of clusters from gravitational lensing to meet the requirements of LSST's dark energy investigation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

CV4Quantum: Reducing the Sampling Overhead in Probabilistic Error Cancellation Using Control Variates

Quasiprobabilistic decompositions (QPDs) play a key role in maximizing the utility of near-term quantum hardware. For example, Probabilistic Error Cancellation (PEC) (an error mitigation technique) and circuit cutting (which enables large quantum computations to be performed on quantum hardware with a limited number of qubits) both involve QPDs. Computations based on QPDs typically incur large sampling overheads that grow exponentially with the number of error-terms mitigated or number of circuit-cuts employed, limiting their practical feasibility. In this work, we adapt the control variates variance reduction technique from the statistics literature in order to reduce the sampling overhead in QPD-based computations. We demonstrate our method using simulation experiments that mimic a realistic PEC scenario. In our experiments, we observed a more than 50% reduction in the number of samples needed to achieve a given precision, in more than 50% of the PEC-based estimations performed in the study when using our approach. We discuss how future research on constructing good control variates can lead to even stronger sampling overhead reduction.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

The non-statistical dynamics of the {sup 18}O + {sup 32}O{sub 2} isotope exchange reaction at two energies

The dynamics of the {sup 18}O({sup 3}P) + {sup 32}O{sub 2} isotope exchange reaction were studied using crossed atomic and molecular beams at collision energies (E{sub coll}) of 5.7 and 7.3 kcal/mol, and experimental results were compared with quantum statistical (QS) and quasi-classical trajectory (QCT) calculations on the O{sub 3}(X{sup 1}A’) potential energy surface (PES) of Babikov et al. [D. Babikov, B. K. Kendrick, R. B. Walker, R. T. Pack, P. Fleurat-Lesard, and R. Schinke, J. Chem. Phys. 118, 6298 (2003)]. In both QS and QCT calculations, agreement with experiment was markedly improved by performing calculations with the experimental distribution of collision energies instead of fixed at the average collision energy. At both collision energies, the scattering displayed a forward bias, with a smaller bias at the lower E{sub coll}. Comparisons with the QS calculations suggest that {sup 34}O{sub 2} is produced with a non-statistical rovibrational distribution that is hotter than predicted, and the discrepancy is larger at the lower E{sub coll}. If this underprediction of rovibrational excitation by the QS method is not due to PES errors and/or to non-adiabatic effects not included in the calculations, then this collision energy dependence is opposite to what might be expected based on collision complex lifetime arguments and opposite to that measured for the forward bias. While the QCT calculations captured the experimental product vibrational energy distribution better than the QS method, the QCT results underpredicted rotationally excited products, overpredicted forward-bias and predicted a trend in the strength of forward-bias with collision energy opposite to that measured, indicating that it does not completely capture the dynamic behavior measured in the experiment. Thus, these results further underscore the need for improvement in theoretical treatments of dynamics on the O{sub 3}(X{sup 1}A’) PES and perhaps of the PES itself in order to better understand and predict non-statistical effects in this reaction and in the formation of ozone (in which the intermediate O{sub 3}{sup *} complex is collisionally stabilized by a third body). The scattering data presented here at two different collision energies provide important benchmarks to guide these improvements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A multi-year short-range hindcast experiment with CESM1 for evaluating climate model moist processes from diurnal to interannual timescales

Abstract. We present a multi-year short-range hindcast experiment and its experimental design for better evaluation of both the mean state and variability of atmospheric moist processes in climate models from diurnal to interannual timescales and facilitate model development. We used the Community Earth System Model version 1 as the base model and performed a suite of 3 d hindcasts initialized every day starting at 00:00 Z from 1997 to 2012. Three processes – the diurnal cycle of clouds during different cloud regimes over the central US, precipitation and diabatic heating associated with the Madden–Julian Oscillation (MJO), and the response of precipitation, surface radiative and heat fluxes, as well as zonal wind stress to sea surface temperature anomalies associated with the El Niño–Southern Oscillation – are evaluated as examples to demonstrate how one can better utilize simulations from this experiment to gain insights into model errors and their connection to physical parameterizations or large-scale state. This is achieved by comparing the hindcasts with corresponding long-term observations for periods based on different phenomena. These analyses can only be done through this multi-year hindcast approach to establish robust statistics of the processes under well-controlled large-scale environment because these phenomena are either a result of interannual climate variability or only happen a few times in a given year (e.g., MJO, or cloud regime types). Furthermore, comparison of hindcasts to the typical simulations in climate mode with the same model allows one to infer what portion of a model's climate error directly comes from fast errors in the parameterizations of moist processes. As demonstrated here, model biases in the mean state and variability associated with parameterized moist processes usually develop within a few days and manifest within weeks to affect the simulations of large-scale circulation and ultimately the climate mean state and variability. Therefore, model developers can achieve additional useful understanding of the underlying problems in model physics by conducting a multi-year hindcast experiment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Nitrogen abundances and multiple stellar populations in the globular clusters of the Fornax dSph

We use measurements of nitrogen abundances in red giants to search for multiple stellar populations in the four most metal-poor globular clusters (GCs) in the Fornax dwarf spheroidal galaxy (Fornax 1, 2, 3, and 5). New imaging in the F343N filter, obtained with the Wide Field Camera 3 on the Hubble Space Telescope, is combined with archival F555W and F814W observations to determine the strength of the NH band near 3370 Å. After accounting for observational errors, the spread in the F343N-F555W colors of red giants in the Fornax GCs is similar to that in M15 and corresponds to an abundance range of Δ[N/Fe] ∼ 2 dex, as observed also in several Galactic GCs. The spread in F555W-F814W is, instead, fully accounted for by observational errors. The stars with the reddest F343N-F555W colors (indicative of N-enhanced composition) have more centrally concentrated radial distributions in all four clusters, although the difference is not highly statistically significant within any individual cluster. From double-Gaussian fits to the color distributions, we find roughly equal numbers of 'N-normal' and 'N-enhanced' stars (formally ∼40% N-normal stars in Fornax 1, 3, and 5 and ∼60% in Fornax 2). We conclude that GC formation, in particular, regarding the processes responsible for the origin of multiple stellar populations, appears to have operated similarly in the Milky Way and in the Fornax dSph. Combined with the high ratio of metal-poor GCs to field stars in the Fornax dSph, this places an important constraint on scenarios for the origin of multiple stellar populations in GCs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Modeling noise in global Mølmer-Sørensen interactions applied to quantum approximate optimization

Many-qubit Mølmer-Sørensen (MS) interactions applied to trapped ions offer unique capabilities for quantum information processing, with applications including quantum simulation and the quantum approximate optimization algorithm (QAOA). Here, we develop a physical model to describe many-qubit MS interactions under four sources of experimental noise: vibrational mode frequency fluctuations, laser power fluctuations, thermal initial vibrational states, and state preparation and measurement errors. The model parametrizes these errors from simple experimental measurements, without free parameters. Herein, we validate the model in comparison with experiments that implement sequences of MS interactions on two 171 Yb + ions. The model shows reasonable agreement after several MS interactions as quantified by the reduced chi-squared statistic $χ^{2}_{red}$≈2. As an application we examine MaxCut QAOA experiments on three and six ions. The experimental performance is quantified by approximation ratios that are 91% and 83% of the optimal theoretical values. Our model predicts $0.93^{+0.03}_{-0.02}$ and $0.95^{+0.04}_{-0.03}$, respectively, with disagreement in the latter value attributable to secondary noise sources beyond those considered in our analysis. With realistic experimental improvements to reduce measurement error and radial trap frequency variations, the model achieves approximation ratios that are 99% of the optimal. Incorporating these improvements into future experiments is expected to reveal new aspects of noise for future modeling and experimental improvements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

TH-EF-207A-01: Respiratory Motion Correction in 4D-Multi Pinhole Small Animal SPECT

Purpose: Respiration causes lesion smearing, image blurring and quality degradation, affecting lesion contrast and the ability to define correct lesion size. The spatial resolution of current multi pinhole SPECT (MPHS) scanners is sub-millimeter. Therefore, the effect of motion is more noticeable in comparison to conventional SPECT scanner. Gated imaging aims to reduce motion artifacts. A major issue in gating is the lack of statistics and individual reconstructed frames are noisy. The increased noise in each frame, deteriorates the quantitative accuracy of the MPHS Images. The objective of this work, is to enhance the image quality in 4D-MPHS imaging, by 4D image reconstruction. Methods: The new algorithm requires deformation vector fields (DVFs) that are calculated by non-rigid Demons registration. The algorithm is based on the motion-incorporated version of ordered subset expectation maximization (OSEM) algorithm. This iterative algorithm is capable to make full use of all projections to reconstruct each individual frame. To evaluate the performance of the proposed algorithm a simulation study was conducted. A fast ray tracing method was used to generate MPHS projections of a 4D digital mouse phantom with a small tumor in liver in eight different respiratory phases. To evaluate the 4D-OSEM algorithm potential, tumor to liver activity ratio was compared with other image reconstruction methods including 3D-MPHS and post reconstruction registered with Demons-derived DVFs. Results: Image quality of 4D-MPHS is greatly improved by the 4D-OSEM algorithm. When all projections are used to reconstruct a 3D-MPHS, motion blurring artifacts are present, leading to overestimation of the tumor size and 24% tumor contrast underestimation. This error reduced to 16% and 10% for post reconstruction registration methods and 4D-OSEM respectively. Conclusion: 4D-OSEM method can be used for motion correction in 4D-MPHS. The statistics and quantification are improved since all projection data are combined together to update the image.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Energy considerations in the Community Atmosphere Model (CAM)

An error in the energy formulation in the Community Atmosphere Model (CAM) is identified and corrected. Ten year AMIP simulations are compared using the correct and incorrect energy formulations. Statistics of selected primary variables all indicate physically insignificant differences between the simulations, comparable to differences with simulations initialized with rounding sized perturbations. The two simulations are so similar mainly because of an inconsistency in the application of the incorrect energy formulation in the original CAM. CAM used the erroneous energy form to determine the states passed between the parameterizations, but used a form related to the correct formulation for the state passed from the parameterizations to the dynamical core. If the incorrect form is also used to determine the state passed to the dynamical core the simulations are significantly different. In addition, CAM uses the incorrect form for the global energy fixer, but that seems to be less important. The difference of the magnitude of the fixers using the correct and incorrect energy definitions is very small.

54 ENVIRONMENTAL SCIENCES↗