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All sources NASA NTRS DOE OSTI

DOE OSTI2023

Young but fading radio sources: searching for remnants among compact steep-spectrum radio sources

The incidence of young but fading radio sources provides important information on the life cycle of radio emission in radio-loud active galactic nuclei. Despite its importance for constraining the models of radio source evolution, there are no systematic studies of remnants in complete samples of young radio sources. We report results of the study of 18 compact steep-spectrum (CSS) radio sources, selected from the statistically complete B3-VLA (Very Large Array) CSS sample, characterized by a steep optically thin spectrum (α ≥ 1.0) and no core detection in earlier studies. Our deep multifrequency VLA, pc-scale Very Long Baseline Array, and enhanced Multi Element Remotely Linked Interferometer Network (e-MERLIN) observations allowed us to locate the core component in 10 objects. In three CSS sources, there is no clear evidence of present-time active regions, suggesting that they are likely in a remnant phase. Among sources with core detection, we find three objects that have no clear active regions (hotspots) at the edges of the radio structure, suggesting that the radio emission may have just restarted. Our results support a power-law distribution of the source ages, although the poor statistics prevents us from setting solid constraints on the percentage of remnants and restarted sources in subpopulations of radio sources.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Convergence acceleration of Monte Carlo many-body perturbation methods by direct sampling

In the Monte Carlo many-body perturbation (MC-MP) method, the conventional correlation-correction formula, which is a long sum of products of low-dimensional integrals, is first recast into a short sum of high-dimensional integrals over electron-pair and imaginary-time coordinates. These high-dimensional integrals are then evaluated by the Monte Carlo method with random coordinates generated by the Metropolis–Hasting algorithm according to a suitable distribution. The latter algorithm, while advantageous in its ability to sample nearly any distribution, introduces autocorrelation in sampled coordinates, which in turn increases the statistical uncertainty of the integrals and thus the computational cost. It also involves wasteful rejected moves and an initial “burn-in” step as well as displays hysteresis. Here, an algorithm is proposed that directly produces a random sequence of electron-pair coordinates for the same distribution used in the MC-MP method, which is free from autocorrelation, rejected moves, a burn-in step, or hysteresis. Furthermore, this direct-sampling algorithm is shown to accelerate second- (MC-MP2) and third-order Monte Carlo many-body perturbation (MC-MP3) calculations by up to 222% and 38%, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

New hints on Maya Blue formation process by PCA-assisted in situ XRPD/PDF and optical spectroscopy

The exact recipe to prepare the ancient Maya Blue (MB), an incredibly resistant and brilliant pigment prepared from indigo (dye) and Paligorskite (clay), is lost to the ages. To unravel the key features of the MB formation process, several inorganic-dye couples were heated to 200°C and cooled to RT, to investigate their reactivity and the diffusion and degree of sequestration of the dye into the inorganic host. In situ XRPD/PDF and fiber optic reflectance spectroscopy (FORS) data, sided by TGA, provided a comprehensive overview on MB formation mechanism. XRPD/PDF gave information on long/short range behaviors of water desorption/adsorption and indigo sequestration, while TGA and in situ FORS gave information on mass and optical changes within temperature. Ex situ dye removal was used to understand the sample stability after the thermal treatments. A statistical approach based on Principal Component Analysis was exploited to efficiently and jointly analyze the ~3000 collected patterns. MB formation starts below 110°C with disordered distribution of indigo within the channels, reaching maximum reaction speed and higher ordering at 150°C. Above 175°C, color changes and a stronger sequestration of indigo into framework channels are observed, while the affinity for water is dramatically reduced. The origin of different colors, hues and stability in historical MB samples can then explained in term of different thermal history of the starting mechanical indigo-palygorskite mixture.

36 MATERIALS SCIENCE↗

DOE OSTI2012

Uncertainties in model-independent extractions of amplitudes from complete experiments

A new generation of over-complete experiments is underway, with the goal of performing a high precision extraction of pseudoscalar meson photo-production amplitudes. Such experimentally determined amplitudes can be used both as a test to validate models and as a starting point for an analytic continuation in the complex plane to search for poles. Of crucial importance for both is the level of uncertainty in the extracted multipoles. We have probed these uncertainties by analyses of pseudo-data for KLambda photoproduction, first for the set of 8 observables that have been published for the K{sup +} Lambda channel and then for pseudo-data on a complete set of 16 observables with the uncertainties expected from analyses of ongoing CLAS experiments. In fitting multipoles, we have used a combined Monte Carlo sampling of the amplitude space, with gradient minimization, and have found a shallow X{sup 2} valley pitted with a large number of local minima. This results in bands of solutions that are experimentally indistinguishable. All ongoing experiments will measure observables with limited statistics. We have found a dependence on the particular random choice of values of Gaussian distributed pseudo-data, due to the presence of multiple local minima. This results in actual uncertainties for reconstructed multipoles that are often considerable larger than those returned by gradient minimization routines such as Minuit which find a single local minimum. As intuitively expected, this additional level of uncertainty decreases as larger numbers of observables are included.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2018

Ultrafast Self-Induced X-Ray Transparency and Loss of Magnetic Diffraction

Using ultrafast ≃2.5 fs and ≃25 fs self-amplified spontaneous emission pulses of increasing intensity and a novel experimental scheme, we report the concurrent increase of stimulated emission in the forward direction and loss of out-of-beam diffraction contrast for a Co/Pd multilayer sample. The experimental results are quantitatively accounted for by a statistical description of the pulses in conjunction with the optical Bloch equations. Here, the dependence of the stimulated sample response on the incident intensity, coherence time, and energy jitter of the employed pulses reveals the importance of increased control of x-ray free electron laser radiation.

74 ATOMIC AND MOLECULAR PHYSICS↗

NASA NTRS1993

Estimating risk for earth-satellite attenuation prediction

Annual cumulative distributions of attenuation measurements and of rain-rate measurements were obtained from several locations in Europe and the United States. They were analyzed to estimate the year-to-year variability to be associated with a prediction of the expected cumulative distribution. Two models were constructed to estimate variability, an ad hoc model that summarized a number of observations when compared to model predictions and a probabilistic model that applied the ideas of order statistics to the prediction problem when the number of independent attenuation or rain-rate events in a sample year could be estimated. Based on these models, the statistical uncertainty in a model prediction may be estimated. The estimation procedure also provides an answer to the question of the number of years of observation needed to provide an estimate of the empirical distribution with a specified statistical uncertainty.

Crane, Robert K.↗

NASA NTRS1974

A Monte Carlo investigation of thrust imbalance of solid rocket motor pairs

A technique is described for theoretical, statistical evaluation of the thrust imbalance of pairs of solid-propellant rocket motors (SRMs) firing in parallel. Sets of the significant variables, determined as a part of the research, are selected using a random sampling technique and the imbalance calculated for a large number of motor pairs. The performance model is upgraded to include the effects of statistical variations in the ovality and alignment of the motor case and mandrel. Effects of cross-correlations of variables are minimized by selecting for the most part completely independent input variables, over forty in number. The imbalance is evaluated in terms of six time - varying parameters as well as eleven single valued ones which themselves are subject to statistical analysis. A sample study of the thrust imbalance of 50 pairs of 146 in. dia. SRMs of the type to be used on the space shuttle is presented. The FORTRAN IV computer program of the analysis and complete instructions for its use are included. Performance computation time for one pair of SRMs is approximately 35 seconds on the IBM 370/155 using the FORTRAN H compiler.

Sforzini, R. H.↗

NASA NTRS1991

Analysis of delay reducing and fuel saving sequencing and spacing algorithms for arrival traffic

The air traffic control subsystem that performs sequencing and spacing is discussed. The function of the sequencing and spacing algorithms is to automatically plan the most efficient landing order and to assign optimally spaced landing times to all arrivals. Several algorithms are described and their statistical performance is examined. Sequencing brings order to an arrival sequence for aircraft. First-come-first-served sequencing (FCFS) establishes a fair order, based on estimated times of arrival, and determines proper separations. Because of the randomness of the arriving traffic, gaps will remain in the sequence of aircraft. Delays are reduced by time-advancing the leading aircraft of each group while still preserving the FCFS order. Tightly spaced groups of aircraft remain with a mix of heavy and large aircraft. Spacing requirements differ for different types of aircraft trailing each other. Traffic is reordered slightly to take advantage of this spacing criterion, thus shortening the groups and reducing average delays. For heavy traffic, delays for different traffic samples vary widely, even when the same set of statistical parameters is used to produce each sample. This report supersedes NASA TM-102795 on the same subject. It includes a new method of time-advance as well as an efficient method of sequencing and spacing for two dependent runways.

Neuman, Frank↗

DOE OSTI2024

Barium stars as tracers of s -process nucleosynthesis in AGB stars

Barium (Ba) stars help to verify asymptotic giant branch (AGB) star nucleosynthesis models since they experienced pollution from an AGB binary companion and thus their spectra carry the signatures of the slow neutron capture process (s process). For a large number (180) of Ba stars, we searched for AGB stellar models that match the observed abundance patterns. We aim to uncover any systematic deviations of the sample abundances from the predictions of the nucleosynthesis models. We employed three machine learning algorithms as classifiers: a Random Forest method, developed for this work, and the two classifiers used in our previous study. Compared to that work, we also expanded our observational sample with 11 Ba stars available in the supersolar metallicity range. We studied the statistical behaviour of the different s-process elements in the observational sample to investigate if the AGB models systematically under- or overpredict the abundances observed in the Ba stars and show the results in the form of violin plots of the residuals between spectroscopic abundances and model predictions. We inspected the correlations between the observed [Fe/H], the s-process elemental abundances, and the residuals. We employed the [Zr/Fe] and [Nb/Fe] abundances as a thermometer to constrain the operational temperature that rules the production of these elements in the sample stars, assuming a steady-state s process. We also investigated the mass distribution of the identified polluter AGB stars and the behaviour of the δ parameter, which describes the fraction of accreted AGB material relative to the Ba star envelope. We find a significant trend in the residuals that implies an underproduction of the elements just after the first s-process peak (Nb, Mo, and Ru) in the models relative to the observations. This may originate from a neutron-capture process (e.g. the intermediate neutron-capture process, i process) not yet included in the AGB models of metallicity from solar to roughly 1/5 solar, corresponding to the range of the Ba stars. Correlations are found between the residuals of these peculiar elements, suggesting a common origin for the deviations from the models. In addition, there is a weak metallicity dependence of the residuals of these elements. The s-process temperatures derived with the [Zr/Fe] – [Nb/Fe] thermometer have an unrealistic value for the majority of our stars. The most likely explanation is that at least a fraction of these elements are not produced in a steady-state s process, and instead may be due to processes not included in the AGB models. The mass distribution of the identified models confirms that our sample of Ba stars was polluted by low-mass AGB stars (< 4 M ⊙ ). Most of the matching AGB models require low accreted mass, but a few systems with high accreted mass are needed to explain the observations.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2012

DUST EXTINCTION BIAS IN THE COLUMN DENSITY DISTRIBUTION OF GAMMA-RAY BURSTS: HIGH COLUMN DENSITY, LOW-REDSHIFT GRBs ARE MORE HEAVILY OBSCURED

The afterglows of gamma-ray bursts (GRBs) have more soft-X-ray absorption than expected from the foreground gas column in the Galaxy. While the redshift of the absorption can in general not be constrained from current X-ray observations, it has been assumed that the absorption is due to metals in the host galaxy of the GRB. The large sample of X-ray afterglows and redshifts now available allows the construction of statistically meaningful distributions of the metal column densities. We construct such a sample and show, as found in previous studies, that the typical absorbing column density (N{sub H{sub X}}) increases substantially with redshift, with few high column density objects found at low-to-moderate redshifts. We show, however, that when highly extinguished bursts are included in the sample, using redshifts from their host galaxies, high column density sources are also found at low-to-moderate redshift. We infer from individual objects in the sample and from observations of blazars that the increase in column density with redshift is unlikely to be related to metals in the intergalactic medium or intervening absorbers. Instead we show that the origin of the apparent increase with redshift is primarily due to dust extinction bias: GRBs with high X-ray absorption column densities found at z {approx}< 4 typically have very high dust extinction column densities, while those found at the highest redshifts do not. It is unclear how such a strongly evolving N{sub H{sub X}}/A{sub V} ratio would arise, and based on current data, remains a puzzle.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Photometric classification and redshift estimation of LSST Supernovae

Supernova (SN) classification and redshift estimation using photometric data only have become very important for the Large Synoptic Survey Telescope (LSST), given the large number of SNe that LSST will observe and the impossibility of spectroscopically following up all the SNe. We investigate the performance of an SN classifier that uses SN colours to classify LSST SNe with the Random Forest classification algorithm. Our classifier results in an area-under-the-curve of 0.98 which represents excellent classification. We are able to obtain a photometric SN sample containing 99 percent SNe Ia by choosing a probability threshold. We estimate the photometric redshifts (photo-z) of SNe in our sample by fitting the SN light curves using the SALT2 model with nested sampling. We obtain a mean bias ($\langle$z phot - z spec $\rangle$) of 0.012 with σ($\frac{zphot-zspec}{1+zspec}$)=0.0294 σ(zphot-zspec1+zspec)=0.0294 without using a host-galaxy photo-z prior, and a mean bias ($\langle$z phot - z spec $\rangle$) of 0.0017 with σ($\frac{zphot-zspec}{1+zspec}$)=0.0116 using a host-galaxy photo-z prior. Assuming a flat ΛCDM model with Ω m = 0.3, we obtain Ω m of 0.305 ± 0.008 (statistical errors only), using the simulated LSST sample of photometric SNe Ia (with intrinsic scatter σ int = 0.11) derived using our methodology without using host-galaxy photo-z prior. Our method will help boost the power of SNe from the LSST as cosmological probes.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

CoverM: read alignment statistics for metagenomics

SUMMARY: Genome-centric analysis of metagenomic samples is a powerful method for understanding the function of microbial communities. Calculating read coverage is a central part of analysis, enabling differential coverage binning for recovery of genomes and estimation of microbial community composition. Coverage is determined by processing read alignments to reference sequences of either contigs or genomes. Per-reference coverage is typically calculated in an ad-hoc manner, with each software package providing its own implementation and specific definition of coverage. Here we present a unified software package CoverM which calculates several coverage statistics for contigs and genomes in an ergonomic and flexible manner. It uses "Mosdepth arrays" for computational efficiency and avoids unnecessary I/O overhead by calculating coverage statistics from streamed read alignment results. AVAILABILITY AND IMPLEMENTATION: CoverM is free software available at https://github.com/wwood/coverm. CoverM is implemented in Rust, with Python (https://github.com/apcamargo/pycoverm) and Julia (https://github.com/JuliaBinaryWrappers/CoverM_jll.jl) interfaces.

Aroney, Samuel T N↗

DOE OSTI2022

Triton Field Trials - Changes in Habitats, a Literature Review of Monitoring Technologies

Marine energy devices are installed in highly dynamic environments and have the potential to affect benthic and pelagic habitats around them. Regulatory bodies often require baseline characterization and/or post-installation monitoring to determine whether changes in these habitats are being observed. However, a great diversity of technologies is available for surveying and sampling marine habitats. Selecting the most suitable instrument to identify and measure changes in habitats at marine energy sites can become a daunting task. We conducted a thorough review of journal articles, survey reports, and grey literature to extract information about the technologies used, the data collection and processing methods, and the performance and effectiveness of these instruments. We examined documents related to marine energy development, offshore wind farms, oil and gas offshore sites, and other marine industries around the world over the last 20 years, as well as national and international guidelines for surveying habitats around offshore activities. A total of 120 different technologies were identified across six main habitat categories: seafloor, sediment, infauna, epifauna, pelagic, and biofouling. The technologies were organized into 12 broad technology classes: acoustic, corer, dredge, grab, hook and line, net and trawl, plate, remote sensing, scrape samples, trap, visual, and others. Visual was the most common and the most diverse technology class, with applications across all six habitat categories. Sampling designs varied considerably among the reviewed studies but transect was the predominant design for surveying seafloor, epifauna, and pelagic habitats. The most common data analyses were univariate and multivariate statistical analyses aimed at calculating and comparing biodiversity indices, characterizing faunal assemblages or sediment classes, or modeling the distribution of animals related to abiotic parameters. Technologies and sampling methods adaptable and designed to work efficiently in energetic environments have greater success at marine energy sites. In addition, sampling designs and statistical analyses should be carefully thought through to identify differences in faunal assemblages and spatiotemporal changes in habitats.

16 TIDAL AND WAVE POWER↗

DOE OSTI2021

Merging Fungal and Bacterial Community Profiles via an Internal Control

Integrated measurements of fungi and bacteria are critical to understand how interactions between these taxa drive key processes in ecosystems ranging from soils to animal guts. High-throughput amplicon sequencing is commonly used to census microbiomes, but the genetic markers targeted for fungi and bacteria (typically ribosomal regions) are domain-specific so profiling must be performed separately, obscuring relationships between these groups. To solve this problem, we developed a spike-in method with an internal control (IC) construct containing primer sites commonly used for bacterial and fungal taxonomic profiling. The internal control offers several advantages: estimation of absolute abundances, estimation of fungal to bacterial ratios (F:B), integration of bacterial and fungal profiles for holistic community analysis, and lower costs compared to other quantitation methods. To validate the IC as a scaling method, we compared IC-derived measures of F:B to measures from quantitative PCR (qPCR) using a commercial mock community (the ZymoBiomic Microbial Community DNA Standard II, containing two fungi and eight bacteria) and complex environmental samples. For both the mock community and the environmental samples, the IC produced F:B values that were statistically consistent with qPCR. Merging the environmental fungal and bacterial profiles based on the IC-derived F:B values revealed new relationships among samples in terms of community similarity. As a result, this IC method is the first spike-in method to employ a single construct for cross-domain amplicon sequencing, offering more reliable measurements.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Radionuclide stochastic distribution in the irradiated graphite - 15206

In France, about 17,000 tons of irradiated graphite waste will be produced from the decommissioning of the six gas-cooled nuclear reactors operated by Electricite De France (EDF). Radionuclide measurements in irradiated graphite exhibit very high discrepancies especially when corresponding to precursors at trace level which is often the case for nuclear grade graphite. As evidenced by numerous studies nuclear graphite is a very pure material, however, it cannot be considered from an analytical viewpoint as a typical homogeneous material. Geo-statistics do not give any notable results when the 3D neutron flux and power history are known. Without taking into account the very origin of the stochastic behavior of radionuclide, their properties may be assumed with the statistical properties which are used in the case of contaminated soils but which have no interest for irradiated graphite. At every scale, the huge discrepancy cannot be avoided but can be easily explained by Theory Of Sampling (TOS) of finely divided materials. The complexity of nuclear graphite is due to its high purity. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

acdc – Automated Contamination Detection and Confidence estimation for single-cell genome data

Abstract Background A major obstacle in single-cell sequencing is sample contamination with foreign DNA. To guarantee clean genome assemblies and to prevent the introduction of contamination into public databases, considerable quality control efforts are put into post-sequencing analysis. Contamination screening generally relies on reference-based methods such as database alignment or marker gene search, which limits the set of detectable contaminants to organisms with closely related reference species. As genomic coverage in the tree of life is highly fragmented, there is an urgent need for a reference-free methodology for contaminant identification in sequence data. Results We present acdc, a tool specifically developed to aid the quality control process of genomic sequence data. By combining supervised and unsupervised methods, it reliably detects both known and de novo contaminants. First, 16S rRNA gene prediction and the inclusion of ultrafast exact alignment techniques allow sequence classification using existing knowledge from databases. Second, reference-free inspection is enabled by the use of state-of-the-art machine learning techniques that include fast, non-linear dimensionality reduction of oligonucleotide signatures and subsequent clustering algorithms that automatically estimate the number of clusters. The latter also enables the removal of any contaminant, yielding a clean sample. Furthermore, given the data complexity and the ill-posedness of clustering, acdc employs bootstrapping techniques to provide statistically profound confidence values. Tested on a large number of samples from diverse sequencing projects, our software is able to quickly and accurately identify contamination. Results are displayed in an interactive user interface. Acdc can be run from the web as well as a dedicated command line application, which allows easy integration into large sequencing project analysis workflows. Conclusions Acdc can reliably detect contamination in single-cell genome data. In addition to database-driven detection, it complements existing tools by its unsupervised techniques, which allow for the detection of de novo contaminants. Our contribution has the potential to drastically reduce the amount of resources put into these processes, particularly in the context of limited availability of reference species. As single-cell genome data continues to grow rapidly, acdc adds to the toolkit of crucial quality assurance tools.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Combining cosmic shear data with correlated photo-z uncertainties: constraints from DESY1 and HSC-DR1

An accurate calibration of the source redshift distribution p(z) is a key aspect in the analysis of cosmic shear data. This, one way or another, requires the use of spectroscopic or high-quality photometric samples. However, the difficulty to obtain colour-complete spectroscopic samples matching the depth of weak lensing catalogs means that the analyses of different cosmic shear datasets often use the same samples for redshift calibration. This introduces a source of statistical and systematic uncertainty that is highly correlated across different weak lensing datasets, and which must be accurately characterised and propagated in order to obtain robust cosmological constraints from their combination. In this paper we introduce a method to quantify and propagate the uncertainties on the source redshift distribution in two different surveys sharing the same calibrating sample. The method is based on an approximate analytical marginalisation of the p(z) statistical uncertainties and the correlated marginalisation of residual systematics. We apply this method to the combined analysis of cosmic shear data from the DESY1 data release and the HSC-DR1 data, using the COSMOS 30-band catalog as a common redshift calibration sample. We find that, although there is significant correlation in the uncertainties on the redshift distributions of both samples, this does not change the final constraints on cosmological parameters significantly. The same is true also for the impact of residual systematic uncertainties from the errors in the COSMOS 30-band photometric redshifts. Additionally, we show that these effects will still be negligible in Stage-IV datasets. Finally, the combination of DESY1 and HSC-DR1 allows us to constrain the "clumpiness" parameter to S 8 = ${0.768}_{-0.017}^{+0.021}$. This corresponds to a ~√(2) improvement in uncertainties with respect to either DES or HSC alone.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Dose Assessment of Los Alamos National Laboratory-Derived Residual Radionuclides in Soils within C Tracts (C-2, C-3, and C-4) for Land Transfer Decisions

Three separate Sampling and Analysis Plans (SAPs) were prepared for tracts C-2, C-3, and C-4. The objective of sampling was to confirm, within the stated statistical confidence limits, that the mean levels of potential radioactive residual contamination in soils in the C Tracts are documented, in appropriate units, and are below the 15 mrem/y (150 μSv/y) Screening Action Levels (SALs). Results show that radionuclide concentration upper-bound 95% confidence levels were close to background levels, with the exception of Pu-239 and Cs-137 being slightly elevated above background, and all measurements were below the ALs and meet the real property release criteria for future construction or recreational use. A follow-up ALARA analysis showed that the costs of cleanup of the soil in areas of elevated concentration and confirmatory sampling would far exceed any benefit from dose reduction.

54 ENVIRONMENTAL SCIENCES↗