Day 947

Tuesday.


1508.03860

On methods of estimating cosmological bulk flows
Nusser

Explore similarities and differences between several estimators of the cosmo bulk flow, B, from the observed radial peculiar velocities of galaxies.  A distinction is made between two theoretical definitions of B as a dipole moment of the velocity field weighted by a radial window function.  One definition involves the 3D peculiar velocity, while the other is based on its radial component alone.  Different methods attempt at inferring B for either of these definitions which coincide only for a constant velocity field.  Focus on the Wiener Filtering (WF, Hoffmann+2015) and the Constrained Minimum Variance (CMB, Feldman+2010) methodologies.  Both methodologies require a prior expressed in terms of the radial velocity correlation function.  Hoffmann+ compute  in Top-Hat windows from a WF realization of the 3D peculiar velocity field.  Feldman+ infer B directly from the observed velocities for the second definition of B.  The WF methodology could easily be adapted to the second definition, in which case it will be equivalent to the CMV with the exception of the imposed constraint.  For a prior with vanishing correlations or very noisy data, CMV reproduces the standard Maximum Likelihood (ML, Kaiser 1988) estimation for B of the entire sample independent of the radial weighting function.  Therefore, this estimator is likely more susceptible to observational biases that could be present in measurement of distant galaxies.  Finally, two additional estimators are proposed.


1508.04121
Quasar classification using color and variability
Peters, Richards, Myers, Strauss, Schmidt, Ivezic, Ross, MacLeod, Riegel

Conduct a pilot investigation to determine the optimal combination of color and variability information to identify quasars in current and future multi-epoch optical surveys.  Use a Bayesian quasar selection algorithm (Richards+ 2004) to identify 35,820 type 1 quasar candidates in a 239 sq deg field of SDSS Stripe 82, using a combination of optical photometry and variability.  Color analysis is performed on 5-band single- and multi-epoch SDSS optical photometry to a depth of r~22.4.  From these data, variability parameters are calculated by fitting the structure function of each object in each band with a power law model using 10 to >100 observations over timescales from ~1 day to ~8 years.  Selection was based on a training sample of 13,221 spectroscopically-confirmed type-1 quasars, largely from SDSS.  Using variability alone, colors alone, and combining variability and colors, achieve 91, 93, 97% efficiency respectively, with particular improvement in the selection of quasars at 2.7<z<3.5 where quasars and stars have similar optical colors.  The 22,867 quasar candidates that are not spectroscopically confirmed reach a depth of i~22.0; 21876 (95.7%) are dimmer than coadded i-band magnitude of 19.9, the cut off for spectroscopic follow-up for SDSS on Stripe82.  Brighter than 19.9, find 5.7% more quasar candidates without confirming spectra in sky regions otherwise considered complete.  The resulting quasar sample has sufficient purity (and statistically correctable incompleteness) to produce a luminosity function comparable to those determined by spectroscopic investigations.  Discuss improvements that can be made to the process in preparation for performing similar photometric selection nan science on data from post-SDSS sky surveys.