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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Correcting correlation functions for redshift-dependent interloper contamination

ABSTRACT The construction of catalogues of a particular type of galaxy can be complicated by interlopers contaminating the sample. In spectroscopic galaxy surveys this can be due to the misclassification of an emission line; for example in the Hobby–Eberly Telescope Dark Energy Experiment (HETDEX) low-redshift [O ii] emitters may make up a few per cent of the observed Ly α emitter (LAE) sample. The presence of contaminants affects the measured correlation functions and power spectra. Previous attempts to deal with this using the cross-correlation function have assumed sources at a fixed redshift, or not modelled evolution within the adopted redshift bins. However, in spectroscopic surveys like HETDEX, where the contamination fraction is likely to be redshift dependent, the observed clustering of misclassified sources will appear to evolve strongly due to projection effects, even if their true clustering does not. We present a practical method for accounting for the presence of contaminants with redshift-dependent contamination fractions and projected clustering. We show using mock catalogues that our method, unlike existing approaches, yields unbiased clustering measurements from the upcoming HETDEX survey in scenarios with redshift-dependent contamination fractions within the redshift bins used. We show our method returns autocorrelation functions with systematic biases much smaller than the statistical noise for samples with at least as high as 7 per cent contamination. We also present and test a method for fitting for the redshift-dependent interloper fraction using the LAE–[O ii] galaxy cross-correlation function, which gives less biased results than assuming a single interloper fraction for the whole sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

The correlation between metallicity and debris disk mass

We find that the initial dust masses in planetary debris disks are correlated with the metallicities of their central stars. We compiled a large sample of systems, including Spitzer, the Herschel DUNES and DEBRIS surveys, and WISE debris disk candidates. We also merged 33 metallicity catalogs to provide homogeneous [Fe/H] and σ{sub [Fe/H]} values. We analyzed this merged sample, including 222 detected disks (74 warm and 148 cold) around a total of 187 systems (some with multiple components) and 440 disks with only upper limits (125 warm and 315 cold) around a total of 360 systems. The disk dust masses at a common early evolutionary point in time were determined using our numerical disk evolutionary code, evolving a unique model for each of the 662 disks backward to an age of 1 Myr. We find that disk-bearing stars seldom have metallicities less than [Fe/H]=−0.2 and that the distribution of warm component masses lacks examples with large mass around stars of low metallicity ([Fe/H]<−0.085). Previous efforts to find a correlation have been largely unsuccessful; the primary improvements supporting our result are (1) basing the study on dust masses, not just infrared excess detections; (2) including upper limits on dust mass in a quantitative way; (3) accounting for the evolution of debris disk excesses as systems age; (4) accounting fully for the range of uncertainties in metallicity measurements; and (5) having a statistically large enough sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

An Analysis of Biomolecular Force Fields for Simulations of Polyglutamine in Solution

Polyglutamine (polyQ) peptides are a useful model system for biophysical studies of protein folding and aggregation, both for their intriguing aggregation properties and their own relevance to human disease. The genetic expansion of a polyQ tract triggers the formation of amyloid aggregates associated with nine neurodegenerative diseases. Several clearly identifiable and separable factors, notably the length of the polyQ tract, influence the mechanism of aggregation, its associated kinetics, and the ensemble of structures formed. Atomistic simulations are well positioned to answer open questions regarding the thermodynamics and kinetics of polyQ folding and aggregation. The additional, explicit representation of water permits deeper investigation of the role of solvent dynamics, and it permits a direct comparison of simulation results with infrared spectroscopy experiments. The generation of meaningful simulation results hinges on satisfying two essential criteria: achieving sufficient conformational sampling to draw statistically valid conclusions, and accurately reproducing the intermolecular forces that govern system structure and dynamics. In this work, we examine the ability of 12 biomolecular force fields to reproduce the properties of a simple, 30-residue polyQ peptide (Q30) in explicit water. In addition to secondary and tertiary structure, we consider generic structural properties of polymers that provide additional dimensions for analysis of the highly degenerate disordered states of the molecule. We find that the 12 force fields produce a wide range of predictions. We identify AMBER ff99SB, AMBER ff99SB*, and OPLS-AA/L to be most suitable for studies of polyQ folding and aggregation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Serum Proteome Signature of Radiation Response: Upregulation of Inflammation-Related Factors and Downregulation of Apolipoproteins and Coagulation Factors in Cancer Patients Treated With Radiation Therapy—A Pilot Study

Purpose: Ionizing radiation affects the proteome of irradiated cells and tissue, yet data concerning changes induced during radiation therapy (RT) in human blood are fragmentary and inconclusive. We aimed to identify features of serum proteome and associated processes involved in response to partial body irradiation during cancer treatment. Methods and Materials: Twenty patients with head and neck squamous cell cancer (HNSCC) and 20 patients with prostate cancer received definitive intensity modulated RT. Blood samples were collected before RT, just after RT, and 1 month after the end of RT. Complete serum proteome was analyzed in individual samples, using a shotgun liquid chromatography-tandem mass spectrometry approach which allowed identification of approximately 450 proteins. Approximately 100 unique proteins were quantified in all samples after exclusion of immunoglobulins, and statistical significance of differences among consecutive samples was assessed. Processes associated with quantified proteins and their functional interactions were predicted using gene ontology tools. Results: RT-induced changes were marked in the HNSCC patient group: 22 upregulated and 33 downregulated proteins were detected in post-RT sera. Most of the changes reversed during follow-up, yet levels of some proteins remained affected 1 month after the end of RT. RT-upregulated proteins were associated with acute phase, inflammatory response, and complement activation. RT-downregulated proteins were associated with transport and metabolism of lipids (plasma apolipoproteins) and blood coagulation. RT-induced changes were much weaker in prostate cancer patients, which corresponded to differences in acute radiation toxicity observed in both groups. Nevertheless, general patterns of RT-induced sera proteome changes were similar in both of the groups of cancer patients. Conclusions: In this pilot study, we proposed to identify a molecular signature of radiation response, based on specific features of serum proteome. The signature included upregulation of factors involved in acute or inflammatory response but also downregulation of plasma apolipoproteins and factors involved in blood coagulation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Dosimetric comparison of rectal-sparing capabilities of rectal balloon vs injectable spacer gel in stereotactic body radiation therapy for prostate cancer: lessons learned from prospective trials

This study aimed to compare the rectal-sparing capabilities of rectal balloons vs absorbable injectable spacer gel in stereotactic body radiation therapy (SBRT) for prostate cancer. Patient samples included in this analysis were obtained from 2 multi-institutional prospective trials of SBRT for prostate cancer using a rectal balloon (n = 36 patients) and injectable spacer gel (n = 36). Treatment prescription dose was 45 Gy in 5 fractions in 42 patients; for equal comparison, the remaining 30 patients were rescaled to 45 Gy from 47.5 Gy prescription (n = 6) and 50 Gy prescription (n = 24). The median prostate volumes and body mass index in the 2 patient samples were not statistically significantly different (p = 0.67 and 0.45, respectively), supporting anatomic similarity between cohorts. The injectable spacer gel achieved dosimetric superiority over the rectal balloon with respect to the maximum dose to the rectum (42.3 vs 46.2 Gy, p vs 35.1 Gy, p Gy ), V40{sub Gy}, and V30{sub Gy} (0.3 vs 1.7 cc, 1 vs 5.4 cc, and 4.1 vs 9.6 cc, respectively; p Gy of the rectum or the dose to 50% of the rectal circumference (p = 0.29 and 0.06, respectively). The V18.3{sub Gy} of the bladder was significantly larger with the rectal balloon (19.9 vs 14.5 cc, p = 0.003). In this analysis of patients enrolled on 2 consecutive multi-institutional prospective trials of SBRT for prostate cancer, the injectable spacer gel outperformed the rectal balloon in the majority of the examined and relevant dosimetric rectal-sparing parameters. The rectal balloon did not outperform the injectable spacer gel in any measured rectal dose parameter.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Evidence of Skewness and Sub-Gaussian Character in Temperature-Dependent Distributions of One Million Electronic Excitation Energies in PbS Quantum Dots

Obtaining statistical distributions by sampling a large number of conformations is vital for an accurate description of temperature-dependent properties of chemical systems. However, constructing distributions with 105??106 samples is computationally challenging because of the prohibitively high computational cost of performing rst-principles quantum-mechanical calculations. In this work, we present a new technique called the Eective Stochastic Potential Conguration Interaction Singles (ESP-CIS) method to obtain excitation energies. The ESP-CIS method uses random matrix theory for the construction of an eective stochastic representation of the Fock operator and combines it with linear-response theory. Here, we perform excitation calculations on PbS quantum dots (0.75-1.75 nm) at temperatures of 200-400 K. Results from a total of 15 million excitation energy calculations (1 million samples for each of the three dots at ve dierent temperatures) revealed the distributions to be sub-Gaussian in nature with negative skewness. The distributions progressively became red-shifted with increasing temperature. The study shows that random distortions in structure from the minimum-energy geometry of these quantum dots are more likely to lower the excitation energies.

Scher, Jeremy A.↗
DOE OSTI2016

Dependence of the critical temperature in overdoped copper oxides on superfluid density

The physics of underdoped copper-oxide superconductors, including the pseudogap, spin and charge ordering, and their relation to superconductivity 1-3 , is intensely debated. The overdoped side is perceived as simpler, with strongly-correlated fermion physics evolving smoothly into the conventional Bardeen-Cooper-Schrieffer (BCS) behavior. Pioneering studies on a few overdoped samples 4-11 indicated that the superfluid density was much smaller than expected, but this was attributed to pair-breaking, disorder, and phase separation. Here, we test this conjecture by studying how the magnetic penetration depth λ and the phase stiffness ρs depend on temperature and doping, scanning densely the entire overdoped side of the La 2-x Sr x CuO 4 (LSCO) phase diagram. We have measured the absolute values of λ and ρs to the accuracy of ±1% in thousands of cuprate samples; the large statistics reveals clear trends and intrinsic properties. The films are quite homogeneous; variations in the critical temperature (T c ) within a film are very small (< 1 K). At every doping, ρs(T) decreases linearly with temperature. The T c (ρ s0) dependence is linear but with an offset, (T c - T 0 ) ∝ ρs0 where T0 ≈ 7 K, except very close to the origin where Tc ∝ √ρ s0. This scaling law defies the standard BCS description, posing a challenge to theory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Delayed Slater determinant update algorithms for high efficiency quantum Monte Carlo

Within ab initio Quantum Monte Carlo simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunction. Each Monte Carlo step requires finding the determinant of a dense matrix. This is most commonly iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. The overall computational cost is therefore formally cubic in the number of electrons or matrix size. To improve the numerical efficiency of this procedure, we propose a novel multiple rank delayed update scheme. This strategy enables probability evaluation with application of accepted moves to the matrices delayed until after a predetermined number of moves, K . The accepted events are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency via matrix-matrix operations instead of matrix-vector operations. Here this procedure does not change the underlying Monte Carlo sampling or its statistical efficiency. For calculations on large systems and algorithms such as diffusion Monte Carlo where the acceptance ratio is high, order of magnitude improvements in the update time can be obtained on both multi- core CPUs and GPUs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Micro on a macroscale: relating microbial-scale soil processes to global ecosystem function

ABSTRACT Soil microorganisms play a key role in driving major biogeochemical cycles and in global responses to climate change. However, understanding and predicting the behavior and function of these microorganisms remains a grand challenge for soil ecology due in part to the microscale complexity of soils. It is becoming increasingly clear that understanding the microbial perspective is vital to accurately predicting global processes. Here, we discuss the microbial perspective including the microbial habitat as it relates to measurement and modeling of ecosystem processes. We argue that clearly defining and quantifying the size, distribution and sphere of influence of microhabitats is crucial to managing microbial activity at the ecosystem scale. This can be achieved using controlled and hierarchical sampling designs. Model microbial systems can provide key data needed to integrate microhabitats into ecosystem models, while adapting soil sampling schemes and statistical methods can allow us to collect microbially-focused data. Quantifying soil processes, like biogeochemical cycles, from a microbial perspective will allow us to more accurately predict soil functions and address long-standing unknowns in soil ecology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Quantitative Particle Analysis of Neptunium-237 Oxides: Optimization of MAMA Analysis for Modified Direct Denitration Products

The production of plutonium-238 through irradiation of neptunium-237 ( 237 Np) target materials for the use in radioisotope thermoelectric generators is paramount for continued deep space exploration. This work employs scanning electron microscopy to analyze 237 Np materials coupled with a well-developed image analysis framework (Morphological Analysis for Material Attribution, or MAMA) to determine the degree of micron-scale homogeneity in the materials. This work demonstrated how the quantification of particle characteristics can validate production materials and affirm the qualitative similarities observed in micrographs. The 237 Np oxide particle analysis determined that the materials from five production runs were quantitatively homogenous (significant at α = 0.05) in particle area, circularity, equivalent circular diameter, and ellipse aspect ratio, with two of the sampling dates having statistically significant different means for one of the four characteristics. Furthermore, these metrics not only confirm general homogeneity of the material but also expand the application of MAMA workflows to 237 Np materials, demonstrating the utility of MAMA analysis for a wider breadth of nuclear materials than previously reported. In the open literature, this study is the first time that these microanalytical techniques were applied to 237 Np materials to this degree.

MAMA↗
DOE OSTI2024

Testing hadronic-model predictions of depth of maximum of air-shower profiles and ground-particle signals using hybrid data of the Pierre Auger Observatory

We test the predictions of hadronic interaction models regarding the depth of maximum of air-shower profiles, X max , and ground-particle signals in water-Cherenkov detectors at 1000 m from the shower core, S ( 1000 ) , using the data from the fluorescence and surface detectors of the Pierre Auger Observatory. The test consists of fitting the measured two-dimensional ( S ( 1000 ) , X max ) distributions using templates for simulated air showers produced with hadronic interaction models pos-, et--04, 2.3d and leaving the scales of predicted X max and the signals from hadronic component at ground as free-fit parameters. The method relies on the assumption that the mass composition remains the same at all zenith angles, while the longitudinal shower development and attenuation of ground signal depend on the mass composition in a correlated way. The analysis was applied to 2239 events detected by both the fluorescence and surface detectors of the Pierre Auger Observatory with energies between 10 18.5 eV to 10 19.0 eV and zenith angles below 60°. We found, that within the assumptions of the method, the best description of the data is achieved if the predictions of the hadronic interaction models are shifted to deeper X max values and larger hadronic signals at all zenith angles. Given the magnitude of the shifts and the data sample size, the statistical significance of the improvement of data description using the modifications considered in the paper is larger than 5 σ even for any linear combination of experimental systematic uncertainties. Published by the American Physical Society 2024

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Phase-space methods for neutrino oscillations: Extension to multibeams

The phase-space approach (PSA), which was originally introduced in Lacroix [] to describe neutrino flavor oscillations for interacting neutrinos emitted from stellar objects is extended to describe arbitrary numbers of neutrino beams. The PSA is based on mapping the quantum fluctuations into a statistical treatment by sampling initial conditions followed by independent mean-field evolution. A new method is proposed to perform this sampling that allows treating an arbitrary number of neutrinos in each neutrino beams. We validate the technique successfully and confirm its predictive power on several examples where a reference exact calculation is possible. We show that it can describe many-body effects, such as entanglement and dissipation induced by the interaction between neutrinos. Due to the complexity of the problem, exact solutions can only be calculated for rather limited cases, with a limited number of beams and/or neutrinos in each beam. The PSA approach considerably reduces the numerical cost and provides an efficient technique to accurately simulate arbitrary numbers of beams. Examples of PSA results are given here, including up to 200 beams with time-independent or time-dependent Hamiltonians. We anticipate that this approach will be useful to bridge exact microscopic techniques with more traditional transport theories used in neutrino oscillations. It will also provide important reference calculations for future quantum computer applications where other techniques are not applicable to classical computers. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Robust Design Under Uncertainty in Quantum Error Mitigation

Error mitigation techniques are crucial to achieving near-term quantum advantage. Classical postprocessing of quantum computation outcomes is a popular approach for error mitigation, which includes methods, such as zero noise extrapolation, virtual distillation, and learning-based error mitigation. However, these techniques have limitations due to the propagation of uncertainty resulting from the finite shot number of a quantum measurement. In this work, we introduce general and unbiased methods for quantifying the uncertainty and error of error-mitigated observables based on the strategic sampling of error mitigation outcomes. We then extend our approach to demonstrate the optimization of performance and robustness of error mitigation under uncertainty. To illustrate our methods, we apply them to zero noise extrapolation and Clifford date regression in the ground state of the XY model simulated using depolarizing and International Business Machines Corporation (IBM) Toronto noise models, respectively. In particular, we optimize the choice of noise levels and the allocation of shots for zero noise extrapolation and the distribution of the training circuits for Clifford data regression. While our methods are readily applicable to any postprocessing-based error mitigation approach, in practice they must not be prohibitively expensive—even though they perform optimizations of the error mitigation hyperparameters requiring sampling of a statistical distribution of error mitigation outcomes. By leveraging surrogate-based optimization, we show that our methods can efficiently perform optimal design for a zero noise extrapolation implementation. We then further demonstrate the transferability of learned zero noise extrapolation hyperparameters to other similar circuits.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Understanding relative metal prices and availability: Combining physical and economic perspectives

Abstract Scientists typically use physical indicators, such as average crustal abundance, and energy requirements in production, as measures of the availability of mineral resources. Economists, on the other hand, typically rely on measures such as prices, and extraction costs. This study investigates the role of crustal abundance, energy requirements, and other physical indicators in determining relative metal prices. The relationship between prices, and physical indicators is estimated statistically for a sample of 22 chemical elements over the period 1970–2013 using an economic market model. The results suggest that energy requirements in production explain 43% of observed variation in metal prices, crustal abundance 21%, and other physical indicators (toxicity, native metal status, and melting point) combine to explain 12% of the observed differences in metal prices.

Watson, Brett J.↗
DOE OSTI2021

Prediction of Probabilistic Shock Initiation Thresholds of Energetic Materials Through Evolution of Thermal-Mechanical Dissipation and Reactive Heating

The ignition threshold of an energetic material (EM) quantifies the macroscopic conditions for the onset of self-sustaining chemical reactions. The threshold is an important theoretical and practical measure of material attributes that relate to safety and reliability. Historically, the thresholds are measured experimentally. In this work, we present a new Lagrangian computational framework for establishing the probabilistic ignition thresholds of heterogeneous EM out of the evolutions of coupled mechanical-thermal-chemical processes using mesoscale simulations. Furthermore, the simulations explicitly account for microstructural heterogeneities, constituent properties, and interfacial processes and capture processes responsible for the development of material damage and the formation of hotspots in which chemical reactions initiate. The specific mechanisms tracked include viscoelasticity, viscoplasticity, fracture, post-fracture contact, frictional heating, heat conduction, reactive chemical heating, gaseous product generation, and convective heat transfer. To determine the ignition threshold, the minimum macroscopic loading required to achieve self-sustaining chemical reactions with a rate of reactive heat generation exceeding the rate of heat loss due to conduction and other dissipative mechanisms is determined. Probabilistic quantification of the processes and the thresholds are obtained via the use of statistically equivalent microstructure sample sets (SEMSS). The predictions are in agreement with available experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2024

COSUBS

COSUBS (COrrelated Sampling Using Batch Statistics) reads MCNP6 output files and propagates the statistical uncertainties of various combinations of tallies using batch statistics, accounting for correlations.

Favorite, Jeffrey↗
DOE OSTI2024

CORRLA-RS

The CORRLA-RS package provides a suite of statistical methods for sampling multidimensional distributions and to conduct sensitivity and correlation analysis of large scale data in the Rust programming language. The software provides a unique solution to multidimensional constrained sampling problems utilizing a combination of parallelized Markov Chain Monte Carlo methods and traditional rejection sampling. The sensitivity and correlation analysis methods are backed by a high performance randomized singular value decomposition implementation which enables datasets larger than the random access memory (RAM) size to be analyzed. Additionally, CORRLA-RS implements the active subspace identification method using a KD-Tree and the randomized singular value decomposition acting in concert.

Gurecky, William [Oak Ridge National Laboratory (O↗