Cell-cluster development for the pair distribution function - Application to rigid disks at hight density.
Molecular pair distribution function in perfect crystalline solids, using method based on cell cluster theory
MOLECULAR STRUCTURE↗
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Color-magnitude diagrams for six metal-rich, low-latitude globular clusters
Colors and magnitudes for stars on CCD frames for six metal-rich, low-latitude, previously unstudied globular clusters and one well-studied, metal-rich cluster (47 Tuc) have been derived and color-magnitude diagrams have been constructed. The photometry for stars in 47 Tuc are in good agreement with previous studies, while the V magnitudes of the horizontal-branch stars in the six program clusters do not agree with estimates based on secondary methods. The distances to these clusters are different from prior estimates. Redding values are derived for each program cluster. The horizontal branches of the program clusters all appear to lie entirely redwards of the red edge of the instability strip, as is normal for their metallicities.
Armandroff, Taft E.↗
A measurement of the value of the Hubble constant from the X-ray properties and the Sunyaev-Zel'dovich effect of Abell 665
A comparison of the X-ray properties and the Sunyaev-Zel'dovich (SZ) effect for a cluster of galaxies can be used to measure the distance of the cluster and hence the Hubble constant. This method was applied to the rich cluster Abell 665. The relative normalization of X-ray and SZ-effect data leads to an estimated Hubble constant of H sub 0 = 40 + or - 9 km/s Mpc if only the random errors are included. When the possible systematic errors are added in quadrature, the range of possible values of the Hubble constants expands to (40 to 50) + or - 12 km/s Mpc.
Birkinshaw, M.↗
A New Method to Constrain Supernova Fractions Using X-ray Observations of Clusters of Galaxies
Supernova (SN) explosions enrich the intracluster medium (ICM) both by creating and dispersing metals. We introduce a method to measure the number of SNe and relative contribution of Type Ia supernovae (SNe Ia) and core-collapse supernovae (SNe cc) by directly fitting X-ray spectral observations. The method has been implemented as an XSPEC model called snapec. snapec utilizes a single-temperature thermal plasma code (apec) to model the spectral emission based on metal abundances calculated using the latest SN yields from SN Ia and SN cc explosion models. This approach provides a self-consistent single set of uncertainties on the total number of SN explosions and relative fraction of SN types in the ICM over the cluster lifetime by directly allowing these parameters to be determined by SN yields provided by simulations. We apply our approach to XMM-Newton European Photon Imaging Camera (EPIC), Reflection Grating Spectrometer (RGS), and 200 ks simulated Astro-H observations of a cooling flow cluster, A3112.We find that various sets of SN yields present in the literature produce an acceptable fit to the EPIC and RGS spectra of A3112. We infer that 30.3% plus or minus 5.4% to 37.1% plus or minus 7.1% of the total SN explosions are SNe Ia, and the total number of SN explosions required to create the observed metals is in the range of (1.06 plus or minus 0.34) x 10(exp 9), to (1.28 plus or minus 0.43) x 10(exp 9), fromsnapec fits to RGS spectra. These values may be compared to the enrichment expected based on well-established empirically measured SN rates per star formed. The proportions of SNe Ia and SNe cc inferred to have enriched the ICM in the inner 52 kiloparsecs of A3112 is consistent with these specific rates, if one applies a correction for the metals locked up in stars. At the same time, the inferred level of SN enrichment corresponds to a star-to-gas mass ratio that is several times greater than the 10% estimated globally for clusters in the A3112 mass range.
Observations↗
Improve Data Mining and Knowledge Discovery Through the Use of MatLab
Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(R) (MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.
Shaykhian, Gholam Ali↗
Improve Data Mining and Knowledge Discovery through the use of MatLab
Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(TradeMark)(MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.
Shaykahian, Gholan Ali↗
The distance to the Large Magellanic Cloud - Constraints from Cepheids in Large Magellanic Cloud star clusters
We have used recent observational data for the Cepheids in the rich, young LMC clusters NGC 1866 and NGC 2031 to constrain the cluster distances with the mass-equivalency (ME) method. The basis of this approach is to fix the cluster distances by requiring the Cepheid evolutionary and pulsational masses to be equal. Using evolutionary models incorporating a mild amount of core and envelope overshooting along with recent pulsational models, we derive distance moduli of 18.51 +/- 0.21 and 18.32 +/- 0.20 for NGC 1866 and NGC 2031, respectively. The quoted errors are dominated by the uncertainties in the heavy element abundances of the clusters (assumed to be 0.3 dex for both clusters), with a smaller contribution due to the apparently intrinsic spread in the masses of the Cepheids in each cluster. For the ME method, we find that Delta(m-M)(0)/Delta sub Z(1) = 0.69, where Z(1) = log (Z/0.016). This result implies that the cluster distances can be determined to better than +/- 5 percent if the cluster abundances can be measured to better than about +/- 0.15 dex.
Bertelli, Gianpaolo↗
An efficient formulation and implementation of the analytic energy gradient method to the single and double excitation coupled-cluster wave function - Application to Cl2O2
The analytic energy gradient for the single and double excitation coupled-cluster (CCSD) wave function has been reformulated and implemented in a new set of programs. The reformulated set of gradient equations have a smaller computational cost than any previously published. The iterative solution of the linear equations and the construction of the effective density matrices are fully vectorized, being based on matrix multiplications. The new method has been used to investigate the Cl2O2 molecule, which has recently been postulated as an important intermediate in the destruction of ozone in the stratosphere. In addition to reporting computational timings, the CCSD equilibrium geometries, harmonic vibrational frequencies, infrared intensities, and relative energetics of three isomers of Cl2O2 are presented.
Rendell, Alistair P.↗
The first detection of a collapsed core globular cluster in M31
We report on the observations of a globular cluster (designated G105 = Bo 343) in the nearby spiral galaxy M31, using the Hubble Space Telescope (HST). Image deconvolutions using three different methods indicate that this cluster has a density profile with the morphology characteristic of stellar systems which have undergone core collapse, i.e., a power-law density cusp near the center. This is the first such detection in a galaxy as distant as M31. This discovery may lead to extensive future statistical studies of the globular cluster system of M31, and thus a better understanding of its evolution.
Bendinelli, O.↗
The Sunyaev-Zel'dovich Effect in Abell 370
We present interferometric measurements of the Sunyaev-Zel'dovich (SZ) effect towards the galaxy cluster Abell 370. These measurements, which directly probe the pressure of the cluster's gas, show the gas is strongly aspherical, on agreement with the morphology revealed by x-ray and gravitational lensing observations. We calculate the cluster's gas mass fraction by comparing the gas mass derived from the SZ measurements to the lensing-derived gravitational mass near the critical lensing radius. We also calculate the gas mass fraction from the SZ data by deriving the total mass under the assumption that the gas is in hydrostatic equilibrium (HSE). We test the assumptions in the HSE method by comparing the total cluster mass implied by the two methods. The Hubble constant derived for this cluster, when the known systematic uncertainties are included, has a very wide range of values and therefore does not provide additional constraints on the validity of the assumptions. We examine carefully the possible systematic errors in the gas fraction measurement. The gas fraction is a lower limit to the cluster's baryon fraction and so we compare the gas mass fraction, calibrated by numerical simulations to approximately the virial radius, to measurements of the global mass fraction of baryonic matter, OMEGA(sub B)/OMEGA(sub matter). Our lower limit to the cluster baryon fraction is f(sub B) = (0.043 +/- 0.014)/h (sub 100). From this, we derive an upper limit to the universal matter density, OMEGA(sub matter) <= 0.72/h(sub 100), and a likely value of OMEGA(sub matter) <= (0.44(sup 0.15, sub -0.12)/h(sub 100).
Grego, Laura↗
Clustered DNA damages induced in isolated DNA and in human cells by low doses of ionizing radiation
Clustered DNA damages-two or more closely spaced damages (strand breaks, abasic sites, or oxidized bases) on opposing strands-are suspects as critical lesions producing lethal and mutagenic effects of ionizing radiation. However, as a result of the lack of methods for measuring damage clusters induced by ionizing radiation in genomic DNA, neither the frequencies of their production by physiological doses of radiation, nor their repairability, nor their biological effects are known. On the basis of methods that we developed for quantitating damages in large DNAs, we have devised and validated a way of measuring ionizing radiation-induced clustered lesions in genomic DNA, including DNA from human cells. DNA is treated with an endonuclease that induces a single-strand cleavage at an oxidized base or abasic site. If there are two closely spaced damages on opposing strands, such cleavage will reduce the size of the DNA on a nondenaturing gel. We show that ionizing radiation does induce clustered DNA damages containing abasic sites, oxidized purines, or oxidized pyrimidines. Further, the frequency of each of these cluster classes is comparable to that of frank double-strand breaks; among all complex damages induced by ionizing radiation, double-strand breaks are only about 20%, with other clustered damage constituting some 80%. We also show that even low doses (0.1-1 Gy) of high linear energy transfer ionizing radiation induce clustered damages in human cells.
NASA Discipline Radiation Health↗
The missing bulge globular clusters in M31 - New optical candidates
A new method to attack the question of the 'missing' globular clusters in the bulge of M31 is used. Image-processing techniques were used on 13 videocamera fields to obtain an accurate photometric census of stellar objects in M31's bulge down to a limiting B magnitude of 21. This luminosity distribution is compared with the Bahcall-Soneira model of galactic foreground stars. A statistically significant excess of bright images in the luminosity range of globular clusters at M31's distance is found. If the optical candidates considered prove to be globular clusters, they would double the number of known globular clusters in the surveyed region. The colors of a subsample of the candidates are the same as those of the known globular clusters. It is concluded that the previously observed flattening away from a de Vaucouleurs law in the radial distribution of M31 may be an observational selection effect. As an offshoot of this analysis, no evidence is found for very luminous stars in the inner bulge of M31. The lack of such stars indicates that there has not been active star formation (with a normal IMF) in the recent past. Coupled with the existence of many planetary nebulae in the bulge, this may strengthen the case for a galactic wind in M31's bulge.
Wirth, A.↗
Cluster Seeking Techniques in Pattern Recognition
A cluster seeking technique is defined as a method of dividing data into subsets, called clusters. These clusters contain data points that are similar to each other and different from the elements of other clusters. Various cluster seeking techniques were broken down into seven categories: (1) probabilistic, (2) signal detection, (3) clustering, (4) clumping, (5) eigenvalue, (6) minimal mode seeking, and (7) miscellaneous. Each category is described and one or more algorithms of that type are presented.
Barr, B. J.↗
Determination of Cluster Distances from Chandra Imaging Spectroscopy and Sunyaev-Zeldovich Effect Measurements: Analysis Methods and Initial Results - I
X-ray and Sunyaev-Zeldovich Effect data ca,n be combined to determine the distance to galaxy clusters. High-resolution X-ray data are now available from the Chandra Observatory, which provides both spatial and spectral information, and interferometric radio measurements of the Sunyam-Zeldovich Effect are available from the BIMA and 0VR.O arrays. We introduce a Monte Carlo Markov chain procedure for the joint analysis of X-ray and Sunyaev-Zeldovich Effect data. The advantages of this method are the high computational efficiency and the ability to measure the full probability distribution of all parameters of interest, such as the spatial and spectral properties of the cluster gas and the cluster distance. We apply this technique to the Chandra X-ray data and the OVRO radio data for the galaxy cluster Abell 611. Comparisons with traditional likelihood-ratio methods reveal the robustness of the method. This method will be used in a follow-up paper to determine the distance of a large sample of galaxy clusters for which high-resolution Chandra X-ray and BIMA/OVRO radio data are available.
Bonamente, Massimiliano↗
Globular cluster photometry with the Hubble Space Telescope. I - Description of the method and analysis of the core of 47 Tuc
Accurate photometry for individual post-main-sequence stars in the core of the Galactic globular cluster 47 Tuc is presented and analyzed using an empirical point spread function model and Monte Carlo simulations. A V vs. V-I color-magnitude diagrams is constructed which shows several distinct stellar types, including RGB and HB stars. Twenty-four blue straggler stars are detected in 47 Tuc, more concentrated toward the center of the cluster than the giants. This supports the hypothesis is that the stragglers are either coalesced stars or members of binary systems that are more massive than single stars. The radial profile of the projected stellar density is flat in the central region of 47 Tuc with a core radius of 23 +/- 2 arcsec. No signature of a collapsed core is evident. The observed radial cumulative distribution of stars rules out the presence of a massive compact object in the center.
Guhathakurta, Puragra↗
The determination of the helium abundance in main-sequence B stars
It is pointed out that the abundances of deuterium, helium, and lithium provide fundamental constraints on cosmological models. The central question is related to the compatibility of the observed abundances with big bang models of primordial nucleosynthesis, taking into account a modification by subsequent nuclear processing in stars or a modification of standard models. The present paper has the objective to assess critically the feasibility of deriving accurate helium abundances from measurements of the photospheric lines in main-sequence B-type stars. A method is established for assigning atmospheric parameters to main-sequence stars with spectral types in the range (approximately) B1-B5. It is found that an analysis of stars in distant anticenter H II regions and clusters offer an alternative method which seems capable of determining relative abundances with more than the requisite accuracy.
Wolff, S. C.↗
Experimental and Theoretical Study of Thermodynamics of the Reaction of Titania and Water at High Temperatures
The transpiration method was used to determine the volatility of titanium dioxide (TiO2) in water vapor-containing environments at temperatures between 1473 and 1673 K. Water contents ranged from 0 to 76 mole % in oxygen or argon carrier gases for 20 to 250 hr exposure times. Results indicate that oxygen is not a key contributor to volatilization and the primary reaction for volatilization in this temperature range is: TiO2(s) + H2O(g) = TiO(OH)2(g). Data were analyzed with both the second and third law methods to extract an enthalpy and entropy of formation. The geometry and vibrational frequencies of TiO(OH)2(g) were computed using B3LYP density functional theory, and the enthalpy of formation was computed using the coupled-cluster singles and doubles method with a perturbative correction for connected triple substitutions [CCSD(T)]. Thermal functions are calculated using both a structure with bent and linear hydroxyl groups. Calculated second and third heats show closer agreement with the linear hydroxyl group, suggesting more experimental and computational spectroscopic and structural work is needed on this system.
equilibrium↗
Cluster Masses Derived from X-ray and Sunyaev-Zeldovich Effect Measurements
We infer the gas mass and total gravitational mass of 11 clusters using two different methods; analysis of X-ray data from the Chandra X-ray Observatory and analysis of centimeter-wave Sunyaev-Zel'dovich Effect (SZE) data from the BIMA and OVRO interferometers. This flux-limited sample of clusters from the BCS cluster catalogue was chosen so as to be well above the surface brightness limit of the ROSAT All Sky Survey; this is therefore an orientation unbiased sample. The gas mass fraction, f_g, is calculated for each cluster using both X-ray and SZE data, and the results are compared at a fiducial radius of r_500. Comparison of the X-ray and SZE results for this orientation unbiased sample allows us to constrain cluster systematics, such as clumping of the intracluster medium. We derive an upper limit on Omega_M assuming that the mass composition of clusters within r_500 reflects the universal mass composition Omega_M h_100 is greater than Omega _B / f-g. We also demonstrate how the mean f_g derived from the sample can be used to estimate the masses of clusters discovered by upcoming deep SZE surveys.
Laroque, S.↗