10,286 research outputs found

    Special Libraries, March 1955

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    Volume 46, Issue 3https://scholarworks.sjsu.edu/sla_sl_1955/1002/thumbnail.jp

    ESO Imaging Survey: Optical follow-up of 12 selected XMM-Newton fields

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    (Abridged) This paper presents the data recently released for the XMM-Newton/WFI survey carried out as part of the ESO Imaging Survey (EIS) project. The aim of this survey is to provide optical imaging follow-up data in BVRI for identification of serendipitously detected X-ray sources in selected XMM-Newton fields. In this paper, fully calibrated individual and stacked images of 12 fields as well as science-grade catalogs for the 8 fields located at high-galactic latitude are presented. The data covers an area of \sim 3 square degrees for each of the four passbands. The median limiting magnitudes (AB system, 2" aperture, 5\sigma detection limit) are 25.20, 24.92, 24.66, and 24.39 mag for B-, V-, R-, and I-band, respectively. These survey products, together with their logs, are available to the community for science exploitation in conjunction with their X-ray counterparts. Preliminary results from the X-ray/optical cross-correlation analysis show that about 61% of the detected X-ray point sources in deep XMM-Newton exposures have at least one optical counterpart within 2" radius down to R \simeq 25 mag, 50% of which are so faint as to require VLT observations thereby meeting one of the top requirements of the survey, namely to produce large samples for spectroscopic follow-up with the VLT, whereas only 15% of the objects have counterparts down to the DSS limiting magnitude.Comment: 24 pages, 10 figures, accepted for publication in Astronomy and Astrophysics. Accompanying data releases available at http://archive.eso.org/archive/public_datasets.html (WFI images), http://www.eso.org/science/eis/surveys/release_65000025_XMM.html (optical catalogs), http://www.aip.de/groups/xray/XMM_EIS/ (X-ray data). Full resolution version available at http://www.astro.uni-bonn.de/~dietrich/publications/3785.ps.g

    The SOAR Gravitational Arc Survey - I: Survey overview and photometric catalogs

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    We present the first results of the SOAR (Southern Astrophysical Research) Gravitational Arc Survey (SOGRAS). The survey imaged 47 clusters in two redshift intervals centered at z=0.27z=0.27 and z=0.55z=0.55, targeting the richest clusters in each interval. Images were obtained in the gg', rr' and ii' bands using the SOAR Optical Imager (SOI), with a median seeing of 0.83, 0.76 and 0.71 arcsec, respectively, in these filters. Most of the survey clusters are located within the Sloan Digital Sky Survey (SDSS) Stripe 82 region and all of them are in the SDSS footprint. Photometric calibration was therefore performed using SDSS stars located in our SOI fields. We reached for galaxies in all fields the detection limits of g23.5g \sim 23.5, r23r \sim 23 and i22.5i \sim 22.5 for a signal-to-noise ratio (S/N) = 3. As a by-product of the image processing, we generated a source catalogue with 19760 entries, the vast majority of which are galaxies, where we list their positions, magnitudes and shape parameters. We compared our galaxy shape measurements to those of local galaxies and concluded that they were not strongly affected by seeing. From the catalogue data, we are able to identify a red sequence of galaxies in most clusters in the lower zz range. We found 16 gravitational arc candidates around 8 clusters in our sample. They tend to be bluer than the central galaxies in the lensing cluster. A preliminary analysis indicates that 10\sim 10% of the clusters have arcs around them, with a possible indication of a larger efficiency associated to the high-zz systems when compared to the low-zz ones. Deeper follow-up images with Gemini strengthen the case for the strong lensing nature of the candidates found in this survey.Comment: 17 pages, 11 figures (most of them multi-panel) MNRAS (2013

    The High Cadence Transit Survey (HiTS): Compilation and Characterization of Light-curve Catalogs

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    Indexación: Scopus.J.M. acknowledges support from CONICYT-Chile through CONICYT-PCHA/Doctorado-Nacional/2014-21140892. J.M., F.F., G.C.V., and G.M. acknowledge support from the Ministry of Economy, Development, and Tourism’s Millennium Science Initiative through grant IC120009, awarded to the Millennium Institute of Astrophysics (MAS). F.F. acknowledges support from Conicyt through the Fondecyt Initiation into Research project No. 11130228. J.M., F.F., J.S.M., G.C.V., and S.G. acknowledge support from Basal Project PFB-03, Centro de Modelamiento Matemáico (CMM), Universidad de Chile. P.L. acknowledges support by Fondecyt through project #1161184. G.C.V. gratefully acknowledges financial support from CON-ICYT-Chile through FONDECYT postdoctoral grant number 3160747 and CONICYT-Chile and NSF through the Programme of International Cooperation project DPI201400090. P.H. acknowledges support from FONDECYT through grant 1170305. L.G. was supported in part by the US National Science Foundation under grant AST-1311862. G.M. acknowledges support from Conicyt through CONICYT-PCHA/Magís-terNacional/2016-22162353. Support for T.d.J. has been provided by US NSF grant AST-1211916, the TABASGO Foundation, and Gary and Cynthia Bengier. R.R.M. acknowledges partial support from BASAL Project PFB-06, as well as FONDECYT project N◦1170364. Powered@NLHPC: this research was supported by the High Performance Computing infrastructure of the National Laboratory for High Performance Computing (NLHPC), PIA ECM-02, CONICYT. This project used data obtained with the Dark Energy Camera (DECam), which was constructed by the Dark Energy Survey (DES) collaborating institutions: Argonne National Lab, the University of California Santa Cruz, the University of Cambridge, Centro de Investigaciones Energeticas, Medioambientales y Tecnologi-cas-Madrid, the University of Chicago, University College London, the DES-Brazil consortium, the University of Edinburgh, ETH-Zurich, the University of Illinois at Urbana-Champaign, Institut de Ciencies de l’Espai, Institut de Fisica d’Altes Energies, Lawrence Berkeley National Lab, Ludwig-Maximilians Universitat, the University of Michigan, the National Optical Astronomy Observatory, the University of Nottingham, Ohio State University, the University of Pennsylvania, the University of Portsmouth, SLAC National Lab, Stanford University, the University of Sussex, and Texas A&M University. Funding for DES, including DECam, has been provided by the U.S. Department of Energy, National Science Foundation, Ministry of Education and Science (Spain), Science and Technology Facilities Council (UK), Higher Education Funding Council (England), National Center for Supercomputing Applications, Kavli Institute for Cosmological Physics, Financia-dora de Estudos e Projetos, Fundação Carlos Chagas Filho de Amparo a Pesquisa, Conselho Nacional de Desenvolvimento Científico e Tecnológico and the Ministério da Ciência e Tecnologia (Brazil), the German Research Foundation-sponsored cluster of excellence “Origin and Structure of the universe,” and the DES collaborating institutions. Facility: CTIO:1.5 m (DECam).The High Cadence Transient Survey (HiTS) aims to discover and study transient objects with characteristic timescales between hours and days, such as pulsating, eclipsing, and exploding stars. This survey represents a unique laboratory to explore large etendue observations from cadences of about 0.1 days and test new computational tools for the analysis of large data. This work follows a fully data science approach, from the raw data to the analysis and classification of variable sources. We compile a catalog of ∼15 million object detections and a catalog of ∼2.5 million light curves classified by variability. The typical depth of the survey is 24.2, 24.3, 24.1, and 23.8 in the u, g, r, and i bands, respectively. We classified all point-like nonmoving sources by first extracting features from their light curves and then applying a random forest classifier. For the classification, we used a training set constructed using a combination of cross-matched catalogs, visual inspection, transfer/active learning, and data augmentation. The classification model consists of several random forest classifiers organized in a hierarchical scheme. The classifier accuracy estimated on a test set is approximately 97%. In the unlabeled data, 3485 sources were classified as variables, of which 1321 were classified as periodic. Among the periodic classes, we discovered with high confidence one δ Scuti, 39 eclipsing binaries, 48 rotational variables, and 90 RR Lyrae, and for the nonperiodic classes, we discovered one cataclysmic variable, 630 QSOs, and one supernova candidate. The first data release can be accessed in the project archive of HiTS (http://astro.cmm.uchile.cl/HiTS/). © 2018. The American Astronomical Society. All rights reserved.https://iopscience.iop.org/article/10.3847/1538-3881/aadfd
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