We describe the Galaxy Evolution Explorer (GALEX) satellite that was launched in April 2003 specifically to accomplish far ultraviolet (FUV) and near ultraviolet (NUV) imaging and spectroscopic sky-surveys. GALEX is currently providing new and significant information on how galaxies form and evolve over a period that encompasses 80% of the history of the Universe. This is being accomplished by the precise measurement of the UV brightness of galaxies which is a direct measurement of their rate of star formation. We briefly describe the design of the GALEX mission followed by an overview of the instrumentation that comprises the science payload. We then focus on a description of the development of the UV sealed tube micro-channel plate detectors and provide data that describe their on-orbit performance. Finally, we provide a short overview of some of the science highlights obtained with GALEX.
Christopher Martin, Thomas Barlow, William Barnhart, Luciana Bianchi, Brian Blakkolb, Dominique Bruno, Joseph Bushman, Yong-Ik Byun, Michael Chiville, Timothy Conrow, Brian Cooke, Jose Donas, James Fanson, Karl Forster, Peter Friedman, Robert Grange, David Griffiths, Timothy Heckman, James Lee, Patrick Jelinsky, Sug-Whan Kim, Siu-Chun Lee, Young-Wook Lee, Dankai Liu, Barry Madore, Roger Malina, Alan Mazer, Ryan McLean, Bruno Milliard, William Mitchell, Marco Morais, Patrick Morrissey, Susan Neff, Frederic Raison, David Randall, Michael Rich, David Schiminovich, Wes Schmitigal, Amit Sen, Oswald Siegmund, Todd Small, Joseph Stock, Frank Surber, Alexander Szalay, Arthur Vaughan, Timothy Weigand, Barry Welsh, Patrick Wu, Ted Wyder, C. Kevin Xu, Jennifer Zsoldas
The Galaxy Evolution Explorer (GALEX), a NASA Small Explorer Mission planned for launch in Fall 2002, will perform the first Space Ultraviolet sky survey. Five imaging surveys in each of two bands (1350-1750Å and 1750-2800Å) will range from an all-sky survey (limit mAB~20-21) to an ultra-deep survey of 4 square degrees (limit mAB~26). Three spectroscopic grism surveys (R=100-300) will be performed with various depths (mAB~20-25) and sky coverage (100 to 2 square degrees) over the 1350-2800Å band. The instrument includes a 50 cm modified Ritchey-Chrétien telescope, a dichroic beam splitter and astigmatism corrector, two large sealed tube microchannel plate detectors to simultaneously cover the two bands and the 1.2 degree field of view. A rotating wheel provides either imaging or grism spectroscopy with transmitting optics. We will use the measured UV properties of local galaxies, along with corollary observations, to calibrate the UV-global star formation rate relationship in galaxies. We will apply this calibration to distant galaxies discovered in the deep imaging and spectroscopic surveys to map the history of star formation in the universe over the red shift range zero to two. The GALEX mission will include an Associate Investigator program for additional observations and supporting data analysis. This will support a wide variety of investigations made possible by the first UV sky survey.
KEYWORDS: Galactic astronomy, Stars, Space telescopes, Signal detection, Monte Carlo methods, Hubble Space Telescope, Observatories, Atmospheric optics, Telescopes, Signal processing
For the discovery of period variable stars using the Hubble Space Telescope an efficient and novel search strategy was developed. We present here a brief overview of the algorithm and its advantages as compared to strict Nyquist sampling.
The NASA/IPAC Extragalactic Database (NED,http://ned.ipac.caltech.edu/) currently contains over 4.5 million photometric measurements covering the electromagnetic spectrum from gamma rays through radio wavelengths for objects that are being cross-correlated among major sky surveys (e.g., SDSS, 2MASS, IRAS, NVSS, FIRST) and thousands of smaller, but unique and important, catalogs and journal articles. The ability to retrieve photometric data (including uncertainties, aperture information, and references) and display spectral energy distributions (SEDs) for individual objects has been available in NED for six years. In this paper we summarize recent enhancements that enable construction of large panchromatic data sets to facilitate multi-dimensional photometric analysis. The database can now be queried for samples of objects that meet flux constraints at any wavelength(e.g., objects with any available 20cm flux, or objects with fν10μm] > 5.0Jy). The ability to utilize criteria involving flux ratios (e.g., objects with fν[20cm]/fν[60μm] > 0.5) is under development. Such queries can be jointly combined with additional constraints on sky area, redshifts, object types, or sample membership, and the data are output with consistent physical units required for comparative analysis. Some results derived from fused photometric data in NED are presented to highlight the large number and diversity of available SEDs.
We review the capabilities of the NASA/IPAC Extragalactic Database (NED, http://ned.ipac.caltech.edu) for information retrieval and knowledge discovery in the context of a globally distributed virtual observatory. Since it's inception in 1990, NED has provided astronomers world-wide with the results of a systematic cross-correlation of catalogs covering all wavelengths, along with thousands of extragalactic observations culled from published journal articles. NED is continuously being expanded and revised to include new catalogs and published observations, each undergoing a process of cross-identification to capture the current state of knowledge about extragalactic sources in a panchromatic fashion. In addition to assimilating data from the literature, the team in incrementally folding in millions of observations from new large-scale sky surveys such as 2MASS, NVSS, APM, and SDSS. At the time of writing the system contains over 3.3 million unique objects with 4.2 million cross-identifications. We summarize the recent evolution of NED from its initial emphasis on object name-, position-, and literature-based queries into a research environment that also assists statistical data exploration and discovery using large samples of objects. Newer capabilities enable intelligent Web mining of entries in geographically distributed astronomical archives that are indexed by object names and positions in NED, sample building using constraints on redshifts, object types and other parameters, as well as image and spectral archives for targeted or serendipitous discoveries. A pilot study demonstrates how NED is being used in conjunction with linked survey archives to characterize the properties of galaxy classes to form a training set for machine learning algorithms; an initial goal is production of statistical likelihoods that newly discovered sources belong to known classes, represent statistical outliers, or candidates for fundamentally new types of objects. Challenges and opportunities for tighter integration of NED capabilities into data mining tools for astronomy archives are also discussed.
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