24 research outputs found

    The Chandra Source Catalog

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    The Chandra Source Catalog (CSC) is a general purpose virtual X-ray astrophysics facility that provides access to a carefully selected set of generally useful quantities for individual X-ray sources, and is designed to satisfy the needs of a broad-based group of scientists, including those who may be less familiar with astronomical data analysis in the X-ray regime. The first release of the CSC includes information about 94,676 distinct X-ray sources detected in a subset of public ACIS imaging observations from roughly the first eight years of the Chandra mission. This release of the catalog includes point and compact sources with observed spatial extents <~ 30''. The catalog (1) provides access to the best estimates of the X-ray source properties for detected sources, with good scientific fidelity, and directly supports scientific analysis using the individual source data; (2) facilitates analysis of a wide range of statistical properties for classes of X-ray sources; and (3) provides efficient access to calibrated observational data and ancillary data products for individual X-ray sources, so that users can perform detailed further analysis using existing tools. The catalog includes real X-ray sources detected with flux estimates that are at least 3 times their estimated 1 sigma uncertainties in at least one energy band, while maintaining the number of spurious sources at a level of <~ 1 false source per field for a 100 ks observation. For each detected source, the CSC provides commonly tabulated quantities, including source position, extent, multi-band fluxes, hardness ratios, and variability statistics, derived from the observations in which the source is detected. In addition to these traditional catalog elements, for each X-ray source the CSC includes an extensive set of file-based data products that can be manipulated interactively.Comment: To appear in The Astrophysical Journal Supplement Series, 53 pages, 27 figure

    Statistical Characterization of the Chandra Source Catalog

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    The first release of the Chandra Source Catalog (CSC) contains ~95,000 X-ray sources in a total area of ~0.75% of the entire sky, using data from ~3,900 separate ACIS observations of a multitude of different types of X-ray sources. In order to maximize the scientific benefit of such a large, heterogeneous data-set, careful characterization of the statistical properties of the catalog, i.e., completeness, sensitivity, false source rate, and accuracy of source properties, is required. Characterization efforts of other, large Chandra catalogs, such as the ChaMP Point Source Catalog (Kim et al. 2007) or the 2 Mega-second Deep Field Surveys (Alexander et al. 2003), while informative, cannot serve this purpose, since the CSC analysis procedures are significantly different and the range of allowable data is much less restrictive. We describe here the characterization process for the CSC. This process includes both a comparison of real CSC results with those of other, deeper Chandra catalogs of the same targets and extensive simulations of blank-sky and point source populations.Comment: To be published in the Astrophysical Journal Supplement Series (Fig. 52 replaced with a version which astro-ph can convert to PDF without issues.

    UBVRI Light Curves of 44 Type Ia Supernovae

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    We present UBVRI photometry of 44 type-Ia supernovae (SN Ia) observed from 1997 to 2001 as part of a continuing monitoring campaign at the Fred Lawrence Whipple Observatory of the Harvard-Smithsonian Center for Astrophysics. The data set comprises 2190 observations and is the largest homogeneously observed and reduced sample of SN Ia to date, nearly doubling the number of well-observed, nearby SN Ia with published multicolor CCD light curves. The large sample of U-band photometry is a unique addition, with important connections to SN Ia observed at high redshift. The decline rate of SN Ia U-band light curves correlates well with the decline rate in other bands, as does the U-B color at maximum light. However, the U-band peak magnitudes show an increased dispersion relative to other bands even after accounting for extinction and decline rate, amounting to an additional ~40% intrinsic scatter compared to B-band.Comment: 84 authors, 71 pages, 51 tables, 10 figures. Accepted for publication in the Astronomical Journal. Version with high-res figures and electronic data at http://astron.berkeley.edu/~saurabh/cfa2snIa

    Long-term thermal sensitivity of Earth’s tropical forests

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    The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (−9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth’s climate

    Parkinson’s disease neurons exhibit alterations in mitochondrial quality control proteins

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    Abstract Mitochondrial dysfunction has been suggested to contribute to Parkinson’s disease pathogenesis, though an understanding of the extent or exact mechanism of this contribution remains elusive. This has been complicated by challenging nature of pathway-based analysis and an inability simultaneously study multiple related proteins within human brain tissue. We used imaging mass cytometry (IMC) to overcome these challenges, measuring multiple protein targets, whilst retaining the spatial relationship between targets in post-mortem midbrain sections. We used IMC to simultaneously interrogate subunits of the mitochondrial oxidative phosphorylation complexes, and several key signalling pathways important for mitochondrial homoeostasis, in a large cohort of PD patient and control cases. We revealed a generalised and synergistic reduction in mitochondrial quality control proteins in dopaminergic neurons from Parkinson’s patients. Further, protein-protein abundance relationships appeared significantly different between PD and disease control tissue. Our data showed a significant reduction in the abundance of PINK1, Parkin and phosphorylated ubiquitinSer65, integral to the mitophagy machinery; two mitochondrial chaperones, HSP60 and PHB1; and regulators of mitochondrial protein synthesis and the unfolded protein response, SIRT3 and TFAM. Further, SIRT3 and PINK1 did not show an adaptive response to an ATP synthase defect in the Parkinson’s neurons. We also observed intraneuronal aggregates of phosphorylated ubiquitinSer65, alongside increased abundance of mitochondrial proteases, LONP1 and HTRA2, within the Parkinson’s neurons with Lewy body pathology, compared to those without. Taken together, these findings suggest an inability to turnover mitochondria and maintain mitochondrial proteostasis in Parkinson’s neurons. This may exacerbate the impact of oxidative phosphorylation defects and ageing related oxidative stress, leading to neuronal degeneration. Our data also suggest that that Lewy pathology may affect mitochondrial quality control regulation through the disturbance of mitophagy and intramitochondrial proteostasis
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