1,390 research outputs found
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
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 -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
Demonstrating that Medical Devices Satisfy User Related Safety Requirements
One way of contributing to a demonstration that a medical device is acceptably safe is to show that the device satisfies a set of requirements known to mitigate hazards. This paper describes experience using formal techniques to model an IV infusion device and to prove that the modelled device captures a set of requirements. The requirements chosen for the study are based on a draft proposal developed by the US Food and Drug Administration (FDA). A major contributor to device related errors are (user) interaction errors. For this reason the chosen models and requirements focus on user interface related issues.FEDER - Federación Española de Enfermedades Raras(000062)This work has been funded by the EPSRC research grant EP/G059063/1: CHI+MED (Computer–Human Interaction for Medical Devices). J. C. Campos was funded by project NORTE-07-0124-FEDER-00006
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
- …