We report on a blind survey for extragalactic radio variability that was carried out by comparing two epochs of data from the FIRST survey with a third epoch from a new 1.4 GHz survey of SDSS Stripe 82. The three epochs are spaced seven years apart a
nd have an overlapping area of 60 deg^2. We uncover 89 variable sources down to the millijansky level, 75 of which are newly-identified, and we find no evidence for transient phenomena. This new sample of variable sources allows us to infer an upper limit to the mean characteristic timescale of AGN radio variability of 14 years. We find that only 1% of extragalactic sources have fractional variability f_var >3, while 44% of Galactic sources vary by this much. The variable sample contains a larger fraction of quasars than a comparable non-variable control sample, though the majority of the variable sources appear to be extended galaxies in the optical. This implies that either quasars are not the dominant contributor to the variability of the sample, or that the deep optical data allow us to detect the host galaxies of some low-z quasars. We use the new, higher resolution data to report on the morphology of the variable sources. Finally, we show that the fraction of sources that are variable remains constant or increases at low flux densities. This may imply that next generation radio surveys with telescopes like the Australian Square Kilometer Array Pathfinder and MeerKAT will see a constant or even increasing fraction of variable sources down into the submillijansky regime.
This document describes a convention for compressing FITS binary tables that is modeled after the FITS tiled-image compression method (White et al. 2009) that has been in use for about a decade. The input table is first optionally subdivided into til
es, each containing an equal number of rows, then every column of data within each tile is compressed and stored as a variable-length array of bytes in the output FITS binary table. All the header keywords from the input table are copied to the header of the output table and remain uncompressed for efficient access. The output compressed table contains the same number and order of columns as in the input uncompressed binary table. There is one row in the output table corresponding to each tile of rows in the input table. In principle, each column of data can be compressed using a different algorithm that is optimized for the type of data within that column, however in the prototype implementation described here, the gzip algorithm is used to compress every column.
This document describes a convention for compressing n-dimensional images and storing the resulting byte stream in a variable-length column in a FITS binary table. The FITS file structure outlined here is independent of the specific data compression
algorithm that is used. The implementation details for 4 widely used compression algorithms are described here, but any other compression technique could also be supported by this convention. The general principle used in this convention is to first divide the n-dimensional image into a rectangular grid of subimages or tiles. Each tile is then compressed as a block of data, and the resulting compressed byte stream is stored in a row of a variable length column in a FITS binary table. By dividing the image into tiles it is generally possible to extract and uncompress subsections of the image without having to uncompress the whole image.
We present results on a survey to find extremely dust-reddened Type-1 Quasars. Combining the FIRST radio survey, the 2MASS Infrared Survey and the Sloan Digital Sky Survey, we have selected a candidate list of 122 potential red quasars. With more tha
n 80% spectroscopically identified objects, well over 50% are classified as dust-reddened Type 1 quasars, whose reddenings (E(B-V)) range from approximately 0.1 to 1.5 magnitudes. They lie well off the color selection windows usually used to detect quasars and many fall within the stellar locus, which would have made it impossible to find these objects with traditional color selection techniques. The reddenings found are much more consistent with obscuration happening in the host galaxy rather than stemming from the dust torus. We find an unusually high fraction of Broad Absorption Line (BAL) quasars at high redshift, all but one of them belonging to the Low Ionization BAL (LoBAL) class and many also showing absorption the metastable FeII line (FeLoBAL). The discovery of further examples of dust-reddened LoBAL quasars provides more support for the hypothesis that BAL quasars (at least LoBAL quasars) represent an early stage in the lifetime of the quasar. The fact that we see such a high fraction of BALs could indicate that the quasar is in a young phase in which quasar feedback from the BAL winds is suppressing star formation in the host galaxy.
Combining radio observations with optical and infrared color selection -- demonstrated in our pilot study to be an efficient selection algorithm for finding red quasars -- we have obtained optical and infrared spectroscopy for 120 objects in a comple
te sample of 156 candidates from a sky area of 2716 square degrees. Consistent with our initial results, we find our selection criteria -- J-K>1.7, R-K>4.0 -- yield a ~50% success rate for discovering quasars substantially redder than those found in optical surveys. Comparison with UVX- and optical color-selected samples shows that >~ 10% of the quasars are missed in a magnitude-limited survey. Simultaneous two-frequency radio observations for part of the sample indicate that a synchrotron continuum component is ruled out as a significant contributor to reddening the quasars spectra. We go on to estimate extinctions for our objects assuming their red colors are caused by dust. Continuum fits and Balmer decrements suggest E(B-V) values ranging from near zero to 2.5 magnitudes. Correcting the K-band magnitudes for these extinctions, we find that for K <= 14.0, red quasars make up between 25% and 60% of the underlying quasar population; owing to the incompleteness of the 2MASS survey at fainter K-band magnitudes, we can only set a lower limit to the radio-detected red quasar population of >20-30%.
