Host Galaxy Contribution to the Colours of `Red' Quasars

We describe an algorithm that measures self-consistently the relative galaxy contribution in a sample of radio-quasars from their optical spectra alone. This is based on a spectral fitting method which uses the size of the characteristic 4000\AA~ feature of elliptical galaxy SEDs. We apply this method to the Parkes Half-Jansky Flat Spectrum sample of Drinkwater et al. (1997) to determine whether emission from the host galaxy can significantly contribute to the very red optical-to-near-infrared colours observed. We find that at around $2\sigma$ confidence, most of the reddening in unresolved (mostly quasar-like) sources is unlikely to be due to contamination by a red stellar component.Comment: 11 pages, 11 figures. Accepted for Publication in Monthly Notices of the Royal Astronomical Societ

Large Scale Structure at 24 Microns in the SWIRE Survey

We present initial results of galaxy clustering at 24μm by analyzing statistics of the projected galaxy distribution from counts-in-cells. This study focuses on the ELAIS-North1 SWIRE field. The sample covers ≃5.9 deg^2 and contains 24,715 sources detected at 24μm to a 5.6σ limit of 250μJy (in the lowest coverage regions). We have explored clustering as a function of 3.6 - 24μm and 24μm flux density using angular-averaged two-point correlation functions derived from the variance of counts-in-cells on scales 0°.05-0°.7. Using a power-law parameterization, w_2(θ)=A(θ/deg)^(1-γ), we find [A,γ] = [(5.43±0.20)×10^(-4),2.01±0.02] for the full sample (1σ errors throughout). We have inverted Limber's equation and estimated a spatial correlation length of r_0=3.32±0.19 h^(-1)Mpc for the full sample, assuming stable clustering and a redshift model consistent with observed 24μm counts. We also find that blue [f_ν(24)/f_ν(3.6)≤5.5] and red [f_ν(24)/f_ν(3.6)≥6.5] galaxies have the lowest and highest r_0 values respectively, implying that redder galaxies are more clustered (by a factor of ≈3 on scales ≳ 0°.2). Overall, the clustering estimates are smaller than those derived from optical surveys, but in agreement with results from IRAS and ISO in the mid-infrared. This extends the notion to higher redshifts that infrared selected surveys show weaker clustering than optical surveys

Automated Classification of Periodic Variable Stars detected by the Wide-field Infrared Survey Explorer

We describe a methodology to classify periodic variable stars identified using photometric time-series measurements constructed from the Wide-field Infrared Survey Explorer (WISE) full-mission single-exposure Source Databases. This will assist in the future construction of a WISE Variable Source Database that assigns variables to specific science classes as constrained by the WISE observing cadence with statistically meaningful classification probabilities. We have analyzed the WISE light curves of 8273 variable stars identified in previous optical variability surveys (MACHO, GCVS, and ASAS) and show that Fourier decomposition techniques can be extended into the mid-IR to assist with their classification. Combined with other periodic light-curve features, this sample is then used to train a machine-learned classifier based on the random forest (RF) method. Consistent with previous classification studies of variable stars in general, the RF machine-learned classifier is superior to other methods in terms of accuracy, robustness against outliers, and relative immunity to features that carry little or redundant class information. For the three most common classes identified by WISE: Algols, RR Lyrae, and W Ursae Majoris type variables, we obtain classification efficiencies of 80.7%, 82.7%, and 84.5% respectively using cross-validation analyses, with 95% confidence intervals of approximately +/-2%. These accuracies are achieved at purity (or reliability) levels of 88.5%, 96.2%, and 87.8% respectively, similar to that achieved in previous automated classification studies of periodic variable stars.Comment: 48 pages, 17 figures, 1 table, accepted by A

NEOWISE observations of comet C/2013 A1 (Siding Spring) as it approaches Mars

The Near-Earth Object Wide-field Infrared Survey Explorer (NEOWISE) mission observed comet C/2013 A1 (Siding Spring) three times at 3.4 {\mu}m and 4.6 {\mu}m as the comet approached Mars in 2014. The comet is an extremely interesting target since its close approach to Mars in late 2014 will be observed by various spacecraft in-situ. The observations were taken in 2014 Jan., Jul. and Sep. when the comet was at heliocentric distances of 3.82 AU, 1.88 AU, and 1.48 AU. The level of activity increased significantly between the Jan. and Jul. visits but then decreased by the time of the observations in Sep., approximately 4 weeks prior to its close approach to Mars. In this work we calculate Af\r{ho} values, and CO/CO2 production rates.Comment: 9 pages, 3 figures, accepted by Astrophysical Journal Letter

Cosmological Obscuration by Galactic Dust: Effects of Dust Evolution

We explore the effects of dust in cosmologically distributed intervening galaxies on the high redshift universe using a generalised model where dust content evolves with cosmic time. The absorbing galaxies are modelled as exponential disks which form coevally, maintain a constant space density and evolve in dust content at a rate that is uniform throughout. We find that the inclusion of moderate to moderately weak amounts of evolution consistent with other studies can reduce the mean observed $B$-band optical depth to redshifts z \simgt 1 by at least 60% relative to non-evolving models. Our predictions imply that intervening galactic dust is unlikely to bias the optical counts of quasars at high redshifts and their evolution in space density derived therefrom.Comment: 10 pages, 6 figures, Accepted for publication in Monthly Notices of the Royal Astronomical Societ

AWAIC: A WISE Astronomical Image Co-adder

We describe a new image co-addition tool, AWAIC, to support the creation of a digital Image Atlas from the multiple frame exposures acquired with the Wide-field Infrared Survey Explorer (WISE). AWAIC includes preparatory steps such as frame background matching and outlier detection using robust frame-stack statistics. Frame co-addition is based on using the detector's Point Response Function (PRF) as an interpolation kernel. This kernel reduces the impact of prior-masked pixels; enables the creation of an optimal matched filtered product for point source detection; and most important, it allows for resolution enhancement (HiRes) to yield a model of the sky that is consistent with the observations to within measurement error. The HiRes functionality allows for non-isoplanatic PRFs, prior noise-variance weighting, uncertainty estimation, and includes a ringing-suppression algorithm. AWAIC also supports the popular overlap-area weighted interpolation method, and is generic enough for use on any astronomical image data that supports the FITS and WCS standards.Comment: 16 pages, 6 figures. Invited paper to appear in Proceedings of ADASS XVIII Conferenc

On the relation between the seismic activity and the Hurst exponent of the geomagnetic field at the time of the 2000 Izu swarm

Many papers document the observation of earthquake-related precursory signatures in geomagnetic field data. However, the significance of these findings is ambiguous because the authors did not adequately take into account that these signals could have been generated by other sources, and the seismogenic origin of these signals have not been validated by comparison with independent datasets. Thus, they are not reliable examples of magnetic disturbances induced by the seismic activity. Hayakawa et al.(2004) claim that at the time of the 2000 Izu swarm the Hurst exponent of the Ultra- Low-Frequency (ULF: 0.001–10 Hz) band of the geomagnetic field varied in accord with the energy released by the seismicity. The present paper demonstrates that the behaviour of the Hurst exponent was insufficiently investigated and also misinterpreted by the authors. We clearly show that during the Izu swarm the changes of the Hurst exponent were strongly related to the level of global geomagnetic activity and not to the increase of the local seismic activity

Variability Flagging in the Wide-field Infrared Survey Explorer Preliminary Data Release

The Wide-field Infrared Survey Explorer Preliminary Data Release Source Catalog contains over 257 million objects. We describe the method used to flag variable source candidates in the Catalog. Using a method based on the chi-square of single-exposure flux measurements, we generated a variability flag for each object, and have identified almost 460,000 candidate sources that exhibit significant flux variability with greater than ~7σ confidence. We discuss the flagging method in detail and describe its benefits and limitations. We also present results from the flagging method, including example light curves of several types of variable sources including Algol-type eclipsing binaries, RR Lyr, W UMa, and a blazar candidate