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NASA NTRS2013

New Detections of Radio Minihalos in Cool Cores of Galaxy Clusters

Cool cores of some galaxy clusters exhibit faint radio minihalos. Their origin is unclear, and their study has been limited by their small number. We undertook a systematic search for minihalos in a large sample of X-ray luminous clusters with high-quality radio data. In this article, we report four new minihalos (A 478, ZwCl 3146,RXJ 1532.9+3021, and A 2204) and five candidates found in the reanalyzed archival Very Large Array observations.The radio luminosities of our minihalos and candidates are in the range of 102325 W Hz1 at 1.4 GHz, which is consistent with these types of radio sources. Their sizes (40160 kpc in radius) are somewhat smaller than those of previously known minihalos. We combine our new detections with previously known minihalos, obtaining a total sample of 21 objects, and briefly compare the cluster radio properties to the average X-ray temperature and the total masses estimated from Planck.We find that nearly all clusters hosting minihalos are hot and massive. Beyond that, there is no clear correlation between the minihalo radio power and cluster temperature or mass (in contrast with the giant radio halos found in cluster mergers, whose radio luminosity correlates with the cluster mass). Chandra X-ray images indicate gas sloshing in the cool cores of most of our clusters, with minihalos contained within the sloshing regions in many of them. This supports the hypothesis that radio-emitting electrons are reaccelerated by sloshing. Advection of relativistic electrons by the sloshing gas may also play a role in the formation of the less extended minihalos.

X-ray Polarization↗

DOE OSTI2013

DARK MATTER HALO PROFILES OF MASSIVE CLUSTERS: THEORY VERSUS OBSERVATIONS

Dark-matter-dominated cluster-scale halos act as an important cosmological probe and provide a key testing ground for structure formation theory. Focusing on their mass profiles, we have carried out (gravity-only) simulations of the concordance {Lambda}CDM cosmology, covering a mass range of 2 Multiplication-Sign 10{sup 12} to 2 Multiplication-Sign 10{sup 15} h {sup -1} M{sub Sun} and a redshift range of z = 0-2, while satisfying the associated requirements of resolution and statistical control. When fitting to the Navarro-Frenk-White profile, our concentration-mass (c-M) relation differs in normalization and shape in comparison to previous studies that have limited statistics in the upper end of the mass range. We show that the flattening of the c-M relation with redshift is naturally expressed if c is viewed as a function of the peak height parameter, {nu}. Unlike the c-M relation, the slope of the c-{nu} relation is effectively constant over the redshift range z = 0-2, while the amplitude varies by {approx}30% for massive clusters. This relation is, however, not universal: using a simulation suite covering the allowed wCDM parameter space, we show that the c-{nu} relation varies by about {+-}20% as cosmological parameters are varied. At fixed mass, the c(M) distribution is well fit by a Gaussian with {sigma}{sub c}/(c) {approx_equal} 1/3, independent of the radius at which the concentration is defined, the halo dynamical state, and the underlying cosmology. We compare the {Lambda}CDM predictions with observations of halo concentrations from strong lensing, weak lensing, galaxy kinematics, and X-ray data, finding good agreement for massive clusters (M{sub vir} > 4 Multiplication-Sign 10{sup 14} h {sup -1} M{sub Sun }), but with some disagreements at lower masses. Because of uncertainty in observational systematics and modeling of baryonic physics, the significance of these discrepancies remains unclear.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Data Analysis Approaches for the Risk-Informed Safety Margins Characterization Toolkit

In the past decades, several numerical simulation codes have been employed to simulate accident dynamics (e.g., RELAP5-3D, RELAP-7, MELCOR, MAAP). In order to evaluate the impact of uncertainties into accident dynamics, several stochastic methodologies have been coupled with these codes. These stochastic methods range from classical Monte-Carlo and Latin Hypercube sampling to stochastic polynomial methods. Similar approaches have been introduced into the risk and safety community where stochastic methods (such as RAVEN, ADAPT, MCDET, ADS) have been coupled with safety analysis codes in order to evaluate the safety impact of timing and sequencing of events. These approaches are usually called Dynamic PRA or simulation-based PRA methods. These uncertainties and safety methods usually generate a large number of simulation runs (database storage may be on the order of gigabytes or higher). The scope of this paper is to present a broad overview of methods and algorithms that can be used to analyze and extract information from large data sets containing time dependent data. In this context, “extracting information” means constructing input-output correlations, finding commonalities, and identifying outliers. Some of the algorithms presented here have been developed or are under development within the RAVEN statistical framework.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

A Distributed OpenCL Framework using Redundant Computation and Data Replication

Applications written solely in OpenCL or CUDA cannot execute on a cluster as a whole. Most previous approaches that extend these programming models to clusters are based on a common idea: designating a centralized host node and coordinating the other nodes with the host for computation. However, the centralized host node is a serious performance bottleneck when the number of nodes is large. In this paper, we propose a scalable and distributed OpenCL framework called SnuCL-D for large-scale clusters. SnuCL-D's remote device virtualization provides an OpenCL application with an illusion that all compute devices in a cluster are confined in a single node. To reduce the amount of control-message and data communication between nodes, SnuCL-D replicates the OpenCL host program execution and data in each node. We also propose a new OpenCL host API function and a queueing optimization technique that significantly reduce the overhead incurred by the previous centralized approaches. To show the effectiveness of SnuCL-D, we evaluate SnuCL-D with a microbenchmark and eleven benchmark applications on a large-scale CPU cluster and a medium-scale GPU cluster.

Kim, Junghyun↗

NASA NTRS2003

A Fast Implementation of the ISOCLUS Algorithm

Unsupervised clustering is a fundamental building block in numerous image processing applications. One of the most popular and widely used clustering schemes for remote sensing applications is the ISOCLUS algorithm, which is based on the ISODATA method. The algorithm is given a set of n data points in d-dimensional space, an integer k indicating the initial number of clusters, and a number of additional parameters. The general goal is to compute the coordinates of a set of cluster centers in d-space, such that those centers minimize the mean squared distance from each data point to its nearest center. This clustering algorithm is similar to another well-known clustering method, called k-means. One significant feature of ISOCLUS over k-means is that the actual number of clusters reported might be fewer or more than the number supplied as part of the input. The algorithm uses different heuristics to determine whether to merge lor split clusters. As ISOCLUS can run very slowly, particularly on large data sets, there has been a growing .interest in the remote sensing community in computing it efficiently. We have developed a faster implementation of the ISOCLUS algorithm. Our improvement is based on a recent acceleration to the k-means algorithm of Kanungo, et al. They showed that, by using a kd-tree data structure for storing the data, it is possible to reduce the running time of k-means. We have adapted this method for the ISOCLUS algorithm, and we show that it is possible to achieve essentially the same results as ISOCLUS on large data sets, but with significantly lower running times. This adaptation involves computing a number of cluster statistics that are needed for ISOCLUS but not for k-means. Both the k-means and ISOCLUS algorithms are based on iterative schemes, in which nearest neighbors are calculated until some convergence criterion is satisfied. Each iteration requires that the nearest center for each data point be computed. Naively, this requires O(kn) time, where k denotes the current number of centers. Traditional techniques for accelerating nearest neighbor searching involve storing the k centers in a data structure. However, because of the iterative nature of the algorithm, this data structure would need to be rebuilt with each new iteration. Our approach is to store the data points in a kd-tree data structure. The assignment of points to nearest neighbors is carried out by a filtering process, which successively eliminates centers that can not possibly be the nearest neighbor for a given region of space. This algorithm is significantly faster, because large groups of data points can be assigned to their nearest center in a single operation. Preliminary results on a number of real Landsat datasets show that our revised ISOCLUS-like scheme runs about twice as fast.

Memarsadeghi, Nargess↗

DOE OSTI2013

ON THE ORIGIN OF MASS SEGREGATION IN NGC 3603

We present deep Hubble Space Telescope/Wide Field and Planetary Camera 2 photometry of the young HD 97950 star cluster in the giant H II region NGC 3603. The data were obtained in 1997 and 2007 permitting us to derive membership based on proper motions of the stars. Our data are consistent with an age of 1 Myr for the HD 97950 cluster. A possible age spread, if present in the cluster, appears to be small. The global slope of the incompleteness-corrected mass function for member stars within 60'' is {Gamma} = -0.88 {+-} 0.15, which is flatter than the value of a Salpeter slope of -1.35. The radially varying mass function shows pronounced mass segregation ranging from slopes of -0.26 {+-} 0.32 in the inner 5'' to -0.94 {+-} 0.36 in the outermost annulus (40''-60''). Stars more massive than 50 M {sub Sun} are found only in the cluster center. The {Lambda} minimum spanning tree technique confirms significant mass segregation down to 30 M {sub Sun }. The dependence of {Lambda} on mass, i.e., that high-mass stars are more segregated than low-mass stars, and the (weak) dependence of the velocity dispersion on stellar mass might imply that the mass segregation is dynamical in origin. While primordial segregation cannot be excluded, the properties of the mass segregation indicate that dynamical mass segregation may have been the dominant process for segregation of high-mass stars.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1989

On developing the local research environment of the 1990s - The Space Station era

A requirements analysis for the Space Station's polar platform data system has been performed. Based upon this analysis, a cluster, layered cluster, and layered-modular implementation of one specific module within the Eos Data and Information System (EosDIS), an active data base for satellite remote sensing research has been developed. It is found that a distributed system based on a layered-modular architecture and employing current generation work station technologies has the requisite attributes ascribed by the remote sensing research community. Although, based on benchmark testing, probabilistic analysis, failure analysis and user-survey technique analysis, it is found that this architecture presents some operational shortcomings that will not be alleviated with new hardware or software developments. Consequently, the potential of a fully-modular layered architectural design for meeting the needs of Eos researchers has also been evaluated, concluding that it would be well suited to the evolving requirements of this multidisciplinary research community.

Chase, Robert↗

NASA NTRS2006

The Evolution of the Cluster X-ray Scaling Relations in the Wide Angle ROSAT Pointed Survey Sample at 0.6 < z < 1.0

The X-ray properties of a sample of 11 high-redshift (0.6 < z < 1 .O) clusters observed with Chardm and/or XMM-Newton are used to investigate the evolution of the cluster scaling relations. The observed evolution in the normalization of the L-T, M-T, M(sub 2)-T and M-L relations is consistent with simple self-similar predictions, in which the properties of clusters reflect the properties of the Universe at their redshift of observation. Under the assumption that the model of self-similar evolution is correct and that the local systems formed via a single spherical collapse, the high-redshift L-T relation is consistent with the high-z clusters having virialized at a significantly higher redshift than the local systems. The data are also consistent with the more realistic scenario of clusters forming via the continuous accretion of material. The slope of the L-T relation at high redshift (B = 3.32 +/- 0.37) is consistent with the local relation, and significantly steeper than the self-similar prediction of B = 2. This suggests that the same non-gravitational processes are responsible for steepening the local and high-z relations, possibly occurring universally at z is approximately greater than 1 or in the early stages of the cluster formation, prior to their observation. The properties of the intracluster medium at high redshift are found to be similar to those in the local Universe. The mean surface-brightness profile slope for the sample is Beta = 0.66 +/- 0.05, the mean gas mass fractions within R(sub 2500(z)) and R(200(z)) are 0.069 +/- 0.012 and 0.11 +/- 0.02, respectively, and the mean metallicity of the sample is 0.28 +/- 0.11 Z(sub solar).

Maughan, B. J.↗

NASA NTRS1988

Einstein Observatory solid state detector observations of cooling flows in clusters of galaxies

Einstein Observatory (EO) solid state spectrometer results for the cooling flows in nine clusters of galaxies are discussed. An analysis of the data using three separate models provides strong evidence for the existence of cool components in the centers of these clusters. The obtained distribution of emission versus temperature for M87 is found to agree well with that determined from data obtained by the EO focal Plane Crystal Spectrometer.

Mushotzky, R. F.↗

DOE OSTI2014

New detections of radio minihalos in cool cores of galaxy clusters

Cool cores of some galaxy clusters exhibit faint radio 'minihalos'. Their origin is unclear, and their study has been limited by their small number. We undertook a systematic search for minihalos in a large sample of X-ray luminous clusters with high-quality radio data. In this article, we report four new minihalos (A 478, ZwCl 3146, RXJ 1532.9+3021, and A 2204) and five candidates found in the reanalyzed archival Very Large Array observations. The radio luminosities of our minihalos and candidates are in the range of 10{sup 23-25} W Hz{sup –1} at 1.4 GHz, which is consistent with these types of radio sources. Their sizes (40-160 kpc in radius) are somewhat smaller than those of previously known minihalos. We combine our new detections with previously known minihalos, obtaining a total sample of 21 objects, and briefly compare the cluster radio properties to the average X-ray temperature and the total masses estimated from Planck. We find that nearly all clusters hosting minihalos are hot and massive. Beyond that, there is no clear correlation between the minihalo radio power and cluster temperature or mass (in contrast with the giant radio halos found in cluster mergers, whose radio luminosity correlates with the cluster mass). Chandra X-ray images indicate gas sloshing in the cool cores of most of our clusters, with minihalos contained within the sloshing regions in many of them. This supports the hypothesis that radio-emitting electrons are reaccelerated by sloshing. Advection of relativistic electrons by the sloshing gas may also play a role in the formation of the less extended minihalos.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Region templates: Data representation and management for high-throughput image analysis

Compartment fires exhibit unique features associated with smoke accumulation and restricted air ventilation. The objective of the present study is to evaluate the ability of CFD-based fire models to simulate these features and in particular the effects of flame extinction that results from under-ventilated fire conditions. The study is performed using FireFOAM; FireFOAM is an advanced fire modeling software developed by FM Global and is based on a general-purpose open-source software called OpenFOAM. A new flame extinction model based on the concept of a critical value of the flame Damköhler number is incorporated into FireFOAM. The performance of the extinction model is evaluated via comparisons with a previously developed experimental database corresponding to a reduced-scale, heptane-fueled, compartment fire configuration. The numerical simulations also include a description of fuel evaporation driven by the computed gas-to-liquid heat feedback. Comparisons between experimental data and numerical results provide a suitable test bed to evaluate the ability of CFD-based fire models to describe the transition from over- to under-ventilated fire conditions, as well as the transition from extinction-free conditions to conditions in which the flame experiences partial or total quenching.

Energy & Fuels↗

DOE OSTI2013

IDENTIFICATION OF MEMBERS IN THE CENTRAL AND OUTER REGIONS OF GALAXY CLUSTERS

The caustic technique measures the mass of galaxy clusters in both their virial and infall regions and, as a byproduct, yields the list of cluster galaxy members. Here we use 100 galaxy clusters with mass M{sub 200} {>=} 10{sup 14} h {sup -1} M{sub Sun} extracted from a cosmological N-body simulation of a {Lambda}CDM universe to test the ability of the caustic technique to identify the cluster galaxy members. We identify the true three-dimensional members as the gravitationally bound galaxies. The caustic technique uses the caustic location in the redshift diagram to separate the cluster members from the interlopers. We apply the technique to mock catalogs containing 1000 galaxies in the field of view of 12 h {sup -1} Mpc on a side at the cluster location. On average, this sample size roughly corresponds to 180 real galaxy members within 3r{sub 200}, similar to recent redshift surveys of cluster regions. The caustic technique yields a completeness, the fraction of identified true members, f{sub c} = 0.95 {+-} 0.03, within 3r{sub 200}. The contamination, the fraction of interlopers in the observed catalog of members, increases from f{sub i}=0.020{sup +0.046}{sub -0.015} at r{sub 200} to f{sub i}=0.08{sup +0.11}{sub -0.05} at 3r{sub 200}. No other technique for the identification of the members of a galaxy cluster provides such large completeness and small contamination at these large radii. The caustic technique assumes spherical symmetry and the asphericity of the cluster is responsible for most of the spread of the completeness and the contamination. By applying the technique to an approximately spherical system obtained by stacking the individual clusters, the spreads decrease by at least a factor of two. We finally estimate the cluster mass within 3r{sub 200} after removing the interlopers: for individual clusters, the mass estimated with the virial theorem is unbiased and within 30% of the actual mass; this spread decreases to less than 10% for the spherically symmetric stacked cluster.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Elemental Mixing State of Aerosol Particles Collected in Central Amazonia during GoAmazon2014/15

Two complementary techniques, Scanning Transmission X-ray Microscopy/Near Edge Fine Structure spectroscopy (STXM/NEXAFS) and Scanning Electron Microscopy/Energy Dispersive X-ray spectroscopy (SEM/EDX), have been quantitatively combined to characterize individual atmospheric particles. This pair of techniques was applied to particle samples at three sampling sites (ATTO, ZF2, and T3) in the Amazon basin as part of the Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) field campaign during the dry season of 2014. The combined data was subjected to k-means clustering using mass fractions of the following elements: C, N, O, Na, Mg, P, S, Cl, K, Ca, Mn, Fe, Ni, and Zn. Cluster analysis identified 12 particle types, across different sampling sites and particle sizes. Samples from the remote Amazon Tall Tower Observatory (ATTO, also T0a) exhibited less cluster variety and fewer anthropogenic clusters than samples collected at the sites nearer to the Manaus metropolitan region, ZF2 (also T0t) or T3. Samples from the ZF2 site contained aged/anthropogenic clusters not readily explained by transport from ATTO or Manaus, possibly suggesting the effects of long range atmospheric transport or other local aerosol sources present during sampling. In addition, this data set allowed for recently established diversity parameters to be calculated. All sample periods had high mixing state indices (χ) that were >0.8. Two individual particle diversity (D i ) populations were observed, with particles <0.5 μm having a D i of ~2.4 and >0.5 μm particles having a D i of ~3.6, which likely correspond to fresh and aged aerosols respectively. The diversity parameters determined by the quantitative method presented here will serve to aid in the accurate representation of aerosol mixing state, source apportionment, and aging in both less polluted and more industrialized environments in the Amazon Basin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Searching for the 3.5 keV line in the stacked Suzaku observations of galaxy clusters

We perform a detailed study of the stacked Suzaku observations of 47 galaxy clusters, spanning a redshift range of 0.01–0.45, to search for the unidentified 3.5 keV line. This sample provides an independent test for the previously detected line. We detect a 2σ-significant spectral feature at 3.5 keV in the spectrum of the full sample. When the sample is divided into two subsamples (cool-core and non-cool core clusters), the cool-core subsample shows no statistically significant positive residuals at the line energy. A very weak (∼2σ confidence) spectral feature at 3.5 keV is permitted by the data from the non-cool-core clusters sample. The upper limit on a neutrino decay mixing angle of sin{sup 2}(2θ)=6.1×10{sup −11} from the full Suzaku sample is consistent with the previous detections in the stacked XMM-Newton sample of galaxy clusters (which had a higher statistical sensitivity to faint lines), M31, and Galactic center, at a 90% confidence level. However, the constraint from the present sample, which does not include the Perseus cluster, is in tension with previously reported line flux observed in the core of the Perseus cluster with XMM-Newton and Suzaku.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1973

Analysis of usefulness of ERTS-1 MSS data in detecting and measuring coastal marshes

The author has identified the following significant results. The usefulness of ERTS-1 data in detecting and measuring coastal marshes has been analyzed. The data chosen for study was taken over the Houston Area Test Site on August 29, 1972. A study site was selected which contained marshes of varying size. Using a computerized clustering algorithm which groups areas of spectral homogeneity, it was possible to distinguish twenty-five classes or features. To determine the total acreage of the marshes, the pure picture elements were counted. Using a technique developed by the team, the boundary picture elements were also counted. Ground truth was provided from rectified, enlarged, and scaled high altitude aircraft photography acquired during the same time frame. Comparison of the ground truth coverage depicted by the aircraft photography to the clustering acreage displayed from the ERTS-1 data showed a percentage of accuracy ranging from 89% to 99% for determining areal extent of coastal marshes.

Erb, R. B.↗

DOE OSTI2026

The SPT-deep Cluster Catalog: Sunyaev–Zel’dovich Selected Clusters from Combined SPT-3G and SPTpol Measurements over 100 Square Degrees

We present a catalog of 500 galaxy cluster candidates in the SPT-Deep field: a 100 deg$^{2}$ field that combines data from the SPT-3G and SPTpol surveys to reach noise levels of 3.0, 2.2, and 9.0 μK-arcmin at 95, 150, and 220 GHz, respectively. Candidates are selected via the thermal Sunyaev–Zel’dovich (SZ) effect with a minimum significance of ξ = 4.0, resulting in a catalog of purity ∼89%. Optical data from the Dark Energy Survey and infrared data from the Spitzer Space Telescope are used to confirm 442 cluster candidates. The clusters span 0.12 < z ≲ 1.8 and 1.0 × 10$^{14}$M$_{⊙}$/h$_{70}$ < M$_{500c}$ < 8.7 × 10$^{14}$M$_{⊙}$/h$_{70}$. The sample’s median redshift is 0.74, and the median mass is 1.7 × 10$^{14}$M$_{⊙}$/h$_{70}$; these are the lowest median mass and highest median redshift of any SZ-selected sample to date. We assess the effect of infrared emission from cluster member galaxies on cluster selection by performing a joint fit to the infrared dust and tSZ signals by combining measurements from SPT and overlapping submillimeter data from Herschel/SPIRE. We find that at high redshift (z > 1), the tSZ signal is reduced by $17.9_{−3.2}^{+3.8}$%$(3.8_{−0.7}^{+0.9}$%$)$ at 150 GHz (95 GHz) due to dust contamination. We repeat our cluster finding method on dust-nulled SPT maps and find the resulting catalog is consistent with the nominal SPT-Deep catalog, suggesting dust contamination does not significantly impact the SPT-Deep selection function; we attribute this lack of bias to the inclusion of the SPT 220 GHz band.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1988

Cloud classification from satellite data using a fuzzy sets algorithm: A polar example

Where spatial boundaries between phenomena are diffuse, classification methods which construct mutually exclusive clusters seem inappropriate. The Fuzzy c-means (FCM) algorithm assigns each observation to all clusters, with membership values as a function of distance to the cluster center. The FCM algorithm is applied to AVHRR data for the purpose of classifying polar clouds and surfaces. Careful analysis of the fuzzy sets can provide information on which spectral channels are best suited to the classification of particular features, and can help determine likely areas of misclassification. General agreement in the resulting classes and cloud fraction was found between the FCM algorithm, a manual classification, and an unsupervised maximum likelihood classifier.

Key, J. R.↗

NASA NTRS1989

Cloud classification from satellite data using a fuzzy sets algorithm - A polar example

Where spatial boundaries between phenomena are diffuse, classification methods which construct mutually exclusive clusters seem inappropriate. The Fuzzy c-means (FCM) algorithm assigns each observation to all clusters, with membership values as a function of distance to the cluster center. The FCM algorithm is applied to AVHRR data for the purpose of classifying polar clouds and surfaces. Careful analysis of the fuzzy sets can provide information on which spectral channels are best suited to the classification of particular features, and can help determine like areas of misclassification. General agreement in the resulting classes and cloud fraction was found between the FCM algorithm, a manual classification, and an unsupervised maximum likelihood classifier.

Key, J. R.↗