53 research outputs found

    GaBoDS: The Garching-Bonn Deep Survey -- I. Anatomy of galaxy clusters in the background of NGC 300

    Full text link
    The Garching-Bonn Deep Survey (GaBoDS) is a virtual 12 square degree cosmic shear and cluster lensing survey, conducted with the [email protected] MPG/ESO telescope at La Silla. It consists of shallow, medium and deep random fields taken in R-band in subarcsecond seeing conditions at high galactic latitude. A substantial amount of the data was taken from the ESO archive, by means of a dedicated ASTROVIRTEL program. In the present work we describe the main characteristics and scientific goals of GaBoDS. Our strategy for mining the ESO data archive is introduced, and we comment on the Wide Field Imager data reduction as well. In the second half of the paper we report on clusters of galaxies found in the background of NGC 300, a random archival field. We use weak gravitational lensing and the red cluster sequence method for the selection of these objects. Two of the clusters found were previously known and already confirmed by spectroscopy. Based on the available data we show that there is significant evidence for substructure in one of the clusters, and an increasing fraction of blue galaxies towards larger cluster radii. Two other mass peaks detected by our weak lensing technique coincide with red clumps of galaxies. We estimate their redshifts and masses.Comment: 20 pages, 16 figures, gzipped. An online postscript version with higher quality figures (3.3 MBytes) can be downloaded from http://www.mpa-garching.mpg.de/~mischa/ngc300/ngc300.ps.gz . Submitted to A&

    The Pan-STARRS Moving Object Processing System

    Full text link
    We describe the Pan-STARRS Moving Object Processing System (MOPS), a modern software package that produces automatic asteroid discoveries and identifications from catalogs of transient detections from next-generation astronomical survey telescopes. MOPS achieves > 99.5% efficiency in producing orbits from a synthetic but realistic population of asteroids whose measurements were simulated for a Pan-STARRS4-class telescope. Additionally, using a non-physical grid population, we demonstrate that MOPS can detect populations of currently unknown objects such as interstellar asteroids. MOPS has been adapted successfully to the prototype Pan-STARRS1 telescope despite differences in expected false detection rates, fill-factor loss and relatively sparse observing cadence compared to a hypothetical Pan-STARRS4 telescope and survey. MOPS remains >99.5% efficient at detecting objects on a single night but drops to 80% efficiency at producing orbits for objects detected on multiple nights. This loss is primarily due to configurable MOPS processing limits that are not yet tuned for the Pan-STARRS1 mission. The core MOPS software package is the product of more than 15 person-years of software development and incorporates countless additional years of effort in third-party software to perform lower-level functions such as spatial searching or orbit determination. We describe the high-level design of MOPS and essential subcomponents, the suitability of MOPS for other survey programs, and suggest a road map for future MOPS development.Comment: 57 Pages, 26 Figures, 13 Table

    Small scale systems of galaxies I. Photometric and spectroscopic properties of members

    Full text link
    This paper is the first of a series addressed to the investigation of galaxy formation/evolution in small scale systems of galaxies (SSSGs) which are located in low density cosmic environments. Our algorithm for SSSG selection includes galaxy systems of 2 or more galaxies lying within 1000 km/s and a 200 h_{100}^{-1} kpc radius volume. We present the analysis of the photometric and spectroscopic properties of 19 member galaxies belonging to a sample of 11 SSSGs. In the ÎŒe−re\mu_e - r_e plane, early-type members may be considered "ordinary", not "bright" galaxies in the definition given by Capaccioli et al.(1992) with a significant fraction of galaxies having a disk or disky isophotes. We do not detect fine structure and signatures of recent interaction events in the early-type galaxy population, a picture also confirmed by the spectroscopy. At odd, there are several spiral members with open arm configurations as expected in interacting systems. At the same time, emission lines in the spectra of spiral members fall in the HII regions regime defined with diagnostic diagrams (Veilleux & Osterbrock 1987). None of the objects displays unambiguous indication of nuclear activity, although fourspiral nuclei could be ascribed to the class of Seyferts. The star formation rate seems enhanced over the average expected in spiral galaxies only for poorer SSSGs in particular pairs (<50 solar masses per year) but without being in the range of starburst systems.Comment: 24 pages, including 6 figures and 6 tables. Accepted for publication in A

    LSST: from Science Drivers to Reference Design and Anticipated Data Products

    Get PDF
    (Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg2^2 field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5σ\sigma point-source depth in a single visit in rr will be ∌24.5\sim 24.5 (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg2^2 with ÎŽ<+34.5∘\delta<+34.5^\circ, and will be imaged multiple times in six bands, ugrizyugrizy, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg2^2 region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to r∌27.5r\sim27.5. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

    Astropy: A Community Python Package for Astronomy

    Get PDF
    We present the first public version (v0.2) of the open-source and community-developed Python package, Astropy. This package provides core astronomy-related functionality to the community, including support for domain-specific file formats such as Flexible Image Transport System (FITS) files, Virtual Observatory (VO) tables, and common ASCII table formats, unit and physical quantity conversions, physical constants specific to astronomy, celestial coordinate and time transformations, world coordinate system (WCS) support, generalized containers for representing gridded as well as tabular data, and a framework for cosmological transformations and conversions. Significant functionality is under active development, such as a model fitting framework, VO client and server tools, and aperture and point spread function (PSF) photometry tools. The core development team is actively making additions and enhancements to the current code base, and we encourage anyone interested to participate in the development of future Astropy versions
    • 

    corecore