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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

NMSBA-RS21

This report gives introductory guidance on the level of effort required to create a data warehouse for mining data. Numerous tutorials have been provided to demonstrate the process of downloading raw data, processing the raw data, and importing the data into a PostgreSQL database. Additional information and tutorial has been provided on setting up a Hadoop cluster for storing vasts amounts of data. This report has been generated as a deliverable for a New Mexico Small Business Assistance (NMSBA) project.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2017

Machine Learning Force Field Parameters from Ab Initio Data

Machine learning (ML) techniques with the genetic algorithm (GA) have been applied to determine a polarizable force field parameters using only ab initio data from quantum mechanics (QM) calculations of molecular clusters at the MP2/6-31G(d,p), DFMP2(fc)/jul-cc-pVDZ, and DFMP2(fc)/jul-cc-pVTZ levels to predict experimental condensed phase properties (i.e., density and heat of vaporization). The performance of this ML/GA approach is demonstrated on 4943 dimer electrostatic potentials and 1250 cluster interaction energies for methanol. Excellent agreement between the training data set from QM calculations and the optimized force field model was achieved. Our results were further improved by introducing an offset factor during the machine learning process to compensate for the discrepancy between the QM calculated energy and the energy reproduced by optimized force field, while maintaining the local “shape” of the QM energy surface. Throughout the machine learning process, experimental observables were not involved in the objective function, but were only used for model validation. The best model, optimized from the QM data at the DFMP2(fc)/jul-cc-pVTZ level, appears to perform even better than the original AMOEBA force field (amoeba09.prm), which was optimized empirically to match liquid properties. The present effort shows the possibility of using machine learning techniques to develop descriptive polarizable force field using only QM data. The ML/GA strategy to optimize force fields parameters described here could easily be extended to other molecular systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

SHELS: Complete Redshift surveys of two widely separated fields

The Smithsonian Hectospec Lensing Survey (SHELS) is a complete redshift survey covering two well-separated fields (F1 and F2) of the Deep Lens Survey (DLS). Both fields are more than 94% complete to a Galactic extinction corrected R {sub 0} = 20.2. Here, we describe the redshift survey of the F1 field centered at R.A.{sub 2000} = 00{sup h}53{sup m}25.ˢ3 and decl.{sub 2000} = 12°33′55″; like F2, the F1 field covers ∼4 deg{sup 2}. The redshift survey of the F1 field includes 9426 new galaxy redshifts measured with Hectospec on the MMT (published here). As a guide to future uses of the combined survey, we compare the mass metallicity relation and the distributions of D {sub n}4000 as a function of stellar mass and redshift for the two fields. The mass–metallicity relations differ by an insignificant 1.6σ. For galaxies in the stellar mass range 10{sup 10}–10{sup 11} M {sub ⊙}, the increase in the star-forming fraction with redshift is remarkably similar in the two fields. The seemingly surprising 31%–38% difference in the overall galaxy counts in F1 and F2 is probably consistent with the expected cosmic variance given the subtleties of the relative systematics in the two surveys. We also review the DLS cluster detections in the two fields: poorer photometric data for F1 precluded secure detection of the single massive cluster at z = 0.35 that we find in SHELS. Taken together, the two fields include 16,055 redshifts for galaxies with R{sub 0}⩽20.2 and 20,754 redshifts for galaxies with R ≤ 20.6. These dense surveys in two well-separated fields provide a basis for future investigations of galaxy properties and large-scale structure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Surface Brightness Fluctuations in Two SPT Clusters: A Pilot Study

Studies of surface brightness fluctuations in the intracluster medium present an indirect probe of turbulent properties such as the turbulent velocities, injection scales, and the slope of the power spectrum of fluctuations toward smaller scales. With the advancement of Sunyaev–Zel’dovich (SZ) studies and surveys relative to X-ray observations, we seek to investigate surface brightness fluctuations in a sample of South Pole Telescope (SPT)-SZ clusters which also have archival XMM-Newton data. Here we present a pilot study of two typical clusters in that sample: SPT-CLJ0232-4421 and SPT-CLJ0638-5358. We infer injection scales larger than 500 kpc in both clusters and Mach numbers ≈ 0.5 in SPT-CLJ0232-4421 and Mach numbers ≈ 0.6–1.6 in SPT-CLJ0638-5358, which has a known shock. We find hydrostatic bias values for M$_{500}$ less than 0.2 for SPT-CLJ0232-4421 and less than 0.1 for SPT-CLJ0638-5358. These results show the importance to assess quantitative values via a detailed multiwavelength approach and suggest that the drivers of turbulence may occur at quite large scales.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2001

A Deep X-Ray Survey of Low Mass PMS Stars in NGC 2264

We have proposed to make a deep X-ray survey of a rotation- and proper-motion selected sample of young (3-15 Myr old), low-mass, pre-main sequence (PMS) stars in the populous star-forming region NGC 2264. These X-ray Multimirror Mission (XMM) data will be combined with an extensive set of rotation data for members of this cluster to allow us, for the first time, to probe the early evolution of magnetic dynamo activity for both fully convective stars and those stars found lower on their Hayashi tracks, which are developing radiative cores. We will use these data to study the interrelationship between rotation, interior structure, and coronal activity as a function of mass and age in the PMS and to define empirical constraints for theoretical models of angular momentum/dynamo evolution.

Patten, Brian M.↗
NASA NTRS2004

Non-Thermal Hard X-Ray Emission in Galaxy Clusters Observed with the BeppoSAX PDS

We study the X-ray emission in a sample of galaxy clusters using the BeppoSAX PDS instrument in the 20-80 keV energy band. We estimate the nonthermal hard X-ray (HXR) cluster emission by modeling the thermal contribution from the cluster gas and the nonthermal contamination from the unobscured active galactic nuclei (AGNs) in the clusters. We also evaluate the systematic uncertainties due to the background fluctuations. Assuming negligible contamination from the obscured AGNs, the resulting nonthermal component is detected at a 2 sigma level in approx. 50% of the nonsignificantly AGN-contaminated clusters: A2142, A2199, A2256, A3376, Coma, Ophiuchus, and Virgo. The data are consistent with a scenario whereby relaxed clusters have no hard X-ray component of nonthermal origin, whereas merger clusters do, with a 20-80 keV luminosity of approx. 10(exp 43)-10(exp 44) h(sup -2 sub 50) ergs/s. The co-added spectrum of the above clusters indicates a power-law spectrum for the HXR emission with a photon index of 2.8(sup +0.3 sub -0.4) in the 12-115 keV band, and we find indication that it has extended distribution. These indications argue against significant contamination from obscured AGNs, which have harder spectra and a centrally concentrated distribution. These results are supportive of the assumption of the merger shock acceleration of electrons in clusters, which has been proposed as a possible origin of the nonthermal hard X-ray emission models. Assuming that the cosmic microwave background photons experience inverse Compton scattering from the merger-accelerated relativistic electrons and thus produce the observed HXR, the measured hard X-ray slope corresponds to a differential momentum spectra of the relativistic electrons with a slope of mu = 3.8-5.0. In presence of cluster magnetic fields this relativistic electron population produces synchrotron emission with a spectral index of 1.4-2.1, consistent with radio halo observations of merger clusters. Thus both hard X-ray and radio observations of merger clusters are consistent with the inverse Compton model.

Nevalainen, J.↗
DOE OSTI2013

ABOUT THE LINEARITY OF THE COLOR-MAGNITUDE RELATION OF EARLY-TYPE GALAXIES IN THE VIRGO CLUSTER

We revisit the color-magnitude relation of Virgo Cluster early-type galaxies in order to explore its alleged nonlinearity. To this aim, we reanalyze the relation already published from data obtained within the ACS Virgo Cluster Survey of the Hubble Space Telescope and perform our own photometry and analysis of the images of 100 early-type galaxies observed as part of this survey. In addition, we compare our results with those reported in the literature from data of the Sloan Digital Sky Survey. We have found that when the brightest galaxies and untypical systems are excluded from the sample, a linear relation arises in agreement with what is observed in other groups and clusters. The central regions of the brightest galaxies also follow this relation. In addition, we notice that Virgo contains at least four compact elliptical galaxies besides the well-known object VCC 1297 (NGC 4486B). Their locations in the ({mu}{sub eff})-luminosity diagram define a trend different from that followed by normal early-type dwarf galaxies, setting an upper limit in effective surface brightness and a lower limit in the effective radius for their luminosities. Based on the distribution of different galaxy sub-samples in the color-magnitude and ({mu}{sub eff})-luminosity diagrams, we draw some conclusions on their formation and the history of their evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Survey of Surveys: I. The largest compilation of radial velocities for the Galaxy

In the present-day panorama of large spectroscopic surveys, the amount, diversity, and complexity of the available data continuously increase. The overarching goal of studying the formation and evolution of our Galaxy is hampered by the heterogeneity of instruments, selection functions, analysis methods, and measured quantities. Here, we present a comprehensive catalogue, the Survey of Surveys (SoS), built by homogeneously merging the radial velocity (RV) determinations of the largest ground-based spectroscopic surveys to date, such as APOGEE, GALAH, Gaia-ESO, RAVE, and LAMOST, using Gaia as a reference. This pilot study serves to prove the concept and to test the methodology that we plan to apply in the future to the stellar parameters and abundance ratios as well. We have devised a multi-staged procedure that includes: (i) the cross match between Gaia and the spectroscopic surveys using the official Gaia cross-match algorithm, (ii) the normalisation of uncertainties using repeated measurements or the three-cornered hat method, (iii) the cross calibration of the RVs as a function of the main parameters on which depend (magnitude, effective temperature, surface gravity, metallicity, and signal-to-noise ratio) to remove trends and zero point offsets, and (iv) the comparison with external high-resolution samples, such as the Gaia RV standards and the Geneva-Copenhagen survey, to validate the homogenisation procedure and to calibrate the RV zero-point of the SoS catalogue. We provide the largest homogenised RV catalogue to date, containing almost 11 million stars, of which about half come exclusively from Gaia and half in combination with the ground-based surveys. We estimate the accuracy of the RV zero-point to be about 0.16–0.31 km s –1 and the RV precision to be in the range 0.05–1.50 km s –1 depending on the type of star and on its survey provenance. We validate the SoS RVs with open clusters from a high resolution homogeneous samples and provide the systemic velocity of 55 individual open clusters. Additionally, we provide median RVs for 532 clusters recently discovered by Gaia data. The SoS is publicly available and ready to be applied to various research projects, such as the study of star clusters, Galactic archaeology, stellar streams, or the characterisation of planet-hosting stars, to name a few. We also plan to include survey updates and more data sources in future versions of the SoS.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Accurate argon cluster-ion sputter yields: Measured yields and effect of the sputter threshold in practical depth-profiling by x-ray photoelectron spectroscopy and secondary ion mass spectrometry

Argon Gas Cluster-Ion Beam sources are likely to become widely used on x-ray photoelectron spectroscopy and secondary ion mass spectrometry instruments in the next few years. At typical energies used for sputter depth profiling the average argon atom in the cluster has a kinetic energy comparable with the sputter threshold, meaning that for the first time in practical surface analysis a quantitative model of sputter yields near threshold is needed. We develop a simple equation based on a very simple model. Though greatly simplified it is likely to have realistic limiting behaviour and can be made useful for estimating sputter yields by fitting its three parameters to experimental data. We measure argon cluster-ion sputter yield using a quartz crystal microbalance close to the sputter threshold, for silicon dioxide, poly(methyl methacrylate), and polystyrene and (along with data for gold from the existing literature) perform least-squares fits of our new sputter yield equation to this data. The equation performs well, with smaller residuals than for earlier empirical models, but more importantly it is very easy to use in the design and quantification of sputter depth-profiling experiments.

36 MATERIALS SCIENCE↗
NASA NTRS2001

Low-Altitude AVIRIS Data for Mapping Land Cover in Yellowstone National Park: Use of Isodata Clustering Techniques

Northeast Yellowstone National Park (YNP) has a diversity of forest, range, and wetland cover types. Several remote sensing studies have recently been done in this area, including the NASA Earth Observations Commercial Applications Program (EOCAP) hyperspectral project conducted by Yellowstone Ecosystems Studies (YES) on the use of hyperspectral imaging for assessing riparian and in-stream habitats. In 1999, YES and NASA's Commercial Remote Sensing Program Office began collaborative study of this area, assessing the potential of synergistic use of hyperspectral, synthetic aperture radar (SAR), and multiband thermal data for mapping forest, range, and wetland land cover. Since the beginning, a quality 'reference' land cover map has been desired as a tool for developing and validating other land cover maps produced during the project. This paper recounts an effort to produce such a reference land cover map using low-altitude Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data and unsupervised classification techniques. The main objective of this study is to assess ISODATA classification for mapping land cover in Northeast YNP using select bands of low-altitude AVIRIS data. A secondary, more long-term objective is to assess the potential for improving ISODATA-based classification of land cover through use of principal components analysis and minimum noise fraction (MNF) techniques. This paper will primarily report on work regarding the primary research objective. This study focuses on an AVIRIS cube acquired on July 23, 1999, by the confluence of Soda Butte Creek with the Lamar River. Range and wetland habitats dominate the image with forested habitats being a comparatively minor component of the scene. The scene generally tracks from southwest to northeast. Most of the scene is valley bottom with some lower side slopes occurring on the western portion. Elevations within the AVIRIS scene range from approximately 1998 to 2165 m above sea level, based on US Geological Survey (USGS) 30-m digital elevation model (DEM) data. Despain and the National Park Service (NPS) provide additional description of the study area.

Spruce, Joseph P.↗
DOE OSTI2019

Toward Fast and Reliable Potential Energy Surfaces for Metallic Pt Clusters by Hierarchical Delta Neural Networks

Data-driven machine learning force fields (MLF) are more and more popular in atomistic simulations, and exploit machine learning methods to predict energies and forces for unknown structures based on the knowledge learned from an existing reference database. The latter usually comes from density functional theory calculations. One main drawback of MLFs is that physical laws are not incorporated in the machine learning models and instead, MLFs are designed to be very flexible to simulate complex quantum chemistry potential energy surface (PES). In general, MLFs have poor transferability, and hence a very large trainset is required to span all the target feature space to get a reliable MLF. This procedure becomes more troublesome when the PES is complicated, with a large number of degrees of freedom, in which building a large database is inevitable and very expensive, especially when accurate but costly exchange-correlation functionals have to be used. In this manuscript, we exploit a high dimensional neural network potential (HDNNP) on Pt clusters of size 6 to 20 as one example. Furthermore, our standard level of energy calculation is DFT GGA (PBE) using a plane wave basis set. We introduce an approximate but fast level with the PBE functional and a minimal atomic orbital basis set, then a more accurate but expensive level, using a hybrid functional or non-local vdw functional and a plane wave basis set, is reliably predicted by learning the difference with HDNNP. Findings show that such a differential approach (named ΔHDNNP) can deliver very accurate predictions (error < 10 meV/atom) in reference to converged basis set energies as well as more accurate but expensive xc functional. The overall speedup can be as large as 900 for 20 atom Pt cluster. More importantly, ΔHDNNP shows much better transferability due to the intrinsic smoothness of delta potential energy surface, and accordingly one can use much smaller trainset data to obtain better accuracy than the conventional HDNNP. A multi-layer ΔHDNNP is thus proposed to obtain very accurate predictions versus expensive non-local vdW functional calculations in which the required trainset is further reduced. The approach can be easily generalized to any other machine learning methods and opens a path to study the structure and dynamics of Pt clusters and nanoparticles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Stochastic economic dispatch of wind power under uncertainty using clustering-based extreme scenarios

Operation of power systems with high penetrations of renewable energy sources requires tools for robust decision making under uncertainty. Stochastic economic dispatch and stochastic unit commitment are effective techniques for planning and operation under uncertainty, whose effectiveness depends on the cardinality and quality of the scenario set. Here, this article proposes a machine learning method using -means clustering for capturing relevant physical information from a large population of analog scenarios. Extreme scenario samples drawn from the clusters are used in a two-stage stochastic economic dispatch computation. The effectiveness of the proposed approach is assessed on a synthetic 200-bus system with a geographic footprint over Illinois, USA for four months from each season of WIND Toolkit data. The combination of -means clustering with importance sampling is shown to reduce the total operational cost by over 43% compared to sampling from populations based on heuristic clustering-based methods. Additionally, the variability in the mean cost is about 56% lower than the variability using Monte Carlo sampling. Moreover, the operational cost with the presented approach is shown to be close to the cost calculated based on a hindsight exact wind profile, signifying a highly accurate quantification of wind uncertainty by the presented -means clustering based sampling method.

17 WIND ENERGY↗
NASA NTRS2001

The Sunyaev-Zeldovich Effect Spectrum of Abell 2163

We present a measurement of the Sunyaev-Zeldovich effect (SZE) at 30 GHz for the galaxy cluster Abell 2163. Combining this data point with previous measurements at 140, 220, and 270 GHz from the SuZIE and Daibolo experiments, we construct them most complete SZE spectrum to date. The spectrum is fitted to determine the compton y parameter and the peculiar velocity for this cluster; our results are y_0=3.6 x 10(circumflex)4 and v_p=360 km s(circumflex)-1. These results include corrections for contamination by Galactic dust emission; we find the contamination level to be much less than previously reported. The dust emission, while strong, is distributed over much larger angular scales than the cluster signal and contributes little to the measured signal when the proper SZE observing strategy is taken into account.

LaRoque, S.↗
DOE OSTI2016

Mapping Arctic plant functional type distributions in the Barrow Environmental Observatory using WorldView-2 and LiDAR datasets

Multi-scale modeling of Arctic tundra vegetation requires characterization of the heterogeneous tundra landscape, which includes representation of distinct plant functional types (PFTs). We combined high-resolution multi-spectral remote sensing imagery from the WorldView-2 satellite with light detecting and ranging (LiDAR)-derived digital elevation models (DEM) to characterize the tundra landscape in and around the Barrow Environmental Observatory (BEO), a 3021-hectare research reserve located at the northern edge of the Alaskan Arctic Coastal Plain. Vegetation surveys were conducted during the growing season (June August) of 2012 from 48 1 m 1 m plots in the study region for estimating the percent cover of PFTs (i.e., sedges, grasses, forbs, shrubs, lichens and mosses). Statistical relationships were developed between spectral and topographic remote sensing characteristics and PFT fractions at the vegetation plots from field surveys. These derived relationships were employed to statistically upscale PFT fractions for our study region of 586 hectares at 0.25-m resolution around the sampling areas within the BEO, which was bounded by the LiDAR footprint. We employed an unsupervised clustering for stratification of this polygonal tundra landscape and used the clusters for segregating the field data for our upscaling algorithm over our study region, which was an inverse distance weighted (IDW) interpolation. We describe two versions of PFT distribution maps upscaled by IDW from WorldView-2 imagery and LiDAR: (1) a version computed from a single image in the middle of the growing season; and (2) a version computed from multiple images through the growing season. This approach allowed us to quantify the value of phenology for improving PFT distribution estimates. We also evaluated the representativeness of the field surveys by measuring the Euclidean distance between every pixel. This guided the ground-truthing campaign in late July of 2014 for addressing uncertainty based on representativeness analysis by selecting 24 1 m 1 m plots that were well and poorly represented. Ground-truthing indicated that including phenology had a better accuracy (R 2 =0.75, RMSE=9.94) than the single image upscaling (R 2 =0.63 , RMSE=12.05) predicted from IDW. We also updated our upscaling approach to include the 24 ground-truthing plots, and a second ground-truthing campaign in late August of 2014 indicated a better accuracy for the phenology model (R 2 =0.61 , RMSE=13.78 ) than only using the original 48 plots for the phenology model (R 2 =0.23 , RMSE=17.49). After all, we believe that the cluster-based IDW upscaling approach and the representativeness analysis offer new insights for upscaling high-resolution data in fragmented landscapes. This analysis and approach provides PFT maps needed to inform land surface models in Arctic ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

On the kinematic separation of field and cluster stars across the bulge globular NGC 6528

We present deep and precise multi-band photometry of the Galactic bulge globular cluster NGC 6528. The current data set includes optical and near-infrared images collected with ACS/WFC, WFC3/UVIS, and WFC3/IR on board the Hubble Space Telescope. The images cover a time interval of almost 10 yr, and we have been able to carry out a proper-motion separation between cluster and field stars. We performed a detailed comparison in the m {sub F814W}, m {sub F606W} – m {sub F814W} color-magnitude diagram with two empirical calibrators observed in the same bands. We found that NGC 6528 is coeval with and more metal-rich than 47 Tuc. Moreover, it appears older and more metal-poor than the super-metal-rich open cluster NGC 6791. The current evidence is supported by several diagnostics (red horizontal branch, red giant branch bump, shape of the sub-giant branch, slope of the main sequence) that are minimally affected by uncertainties in reddening and distance. We fit the optical observations with theoretical isochrones based on a scaled-solar chemical mixture and found an age of 11 ± 1 Gyr and an iron abundance slightly above solar ([Fe/H] = +0.20). The iron abundance and the old cluster age further support the recent spectroscopic findings suggesting a rapid chemical enrichment of the Galactic bulge.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

A Redshift Survey of the Nearby Galaxy Cluster Abell 2199: Comparison of the Spatial and Kinematic Distributions of Galaxies with the Intracluster Medium

We present the results from an extensive spectroscopic survey of the central region of the nearby galaxy cluster Abell 2199 (A2199) at z = 0.03. By combining 775 new redshifts from the MMT/Hectospec observations with the data in the literature, we construct a large sample of 1624 galaxies with measured redshifts at R<30{sup ′}, which results in high spectroscopic completeness at r{sub petro,0}<20.5 (77%). We use these data to study the kinematics and clustering of galaxies, focusing on the comparison with those of the intracluster medium (ICM) from Suzaku X-ray observations. We identify 406 member galaxies of A2199 at R<30{sup ′} using the caustic technique. The velocity dispersion profile of cluster members appears smoothly connected to the stellar velocity dispersion profile of the cD galaxy. The luminosity function is well fitted with a Schechter function at M{sub r}<−15. The radial velocities of cluster galaxies generally agree well with those of the ICM, but there are some regions where the velocity difference between the two is about a few hundred kilometers per second. The cluster galaxies show a hint of global rotation at R<5{sup ′} with v{sub rot}=300--600 km s{sup −1}, but the ICM in the same region does not show such rotation. We apply a friends-of-friends algorithm to the cluster galaxy sample at R<60{sup ′} and identify 32 group candidates, and examine the spatial correlation between the galaxy groups and X-ray emission. This extensive survey in the central region of A2199 provides an important basis for future studies of interplay among the galaxies, the ICM, and the dark matter in the cluster.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

Comparison of the Highly Reflective Cloud and Outgoing Longwave Radiation datasets for use in estimating tropical deep convection

Two currently existing long-term satellite-derived data sets (the Highly Reflective Cloud (HRC) and the Outgoing Longwave Radiation (OLR) data sets) were compared for the accuracy in estimating tropical deep convection, in terms of their climatological and frequency-dependent characteristics, their consistency in identifying deep tropical convection, and their relationship to local sea surface temperature (SST). The results reveal some important differences between the HRC and OLR data sets in terms of their temporal and spatial scales of variability, their relationships to other geophysical fields, and the logistics of their use. It was found that, for many applications, the HRC data set represents the characteristics of the cloud cluster-scale tropical convection more accurately than the OLR data set.

Waliser, Duane E.↗