We introduce an ordinal classification algorithm for photometric redshift estimation, which significantly improves the reconstruction of photometric redshift probability density functions (PDFs) for individual galaxies and galaxy samples. As a use ca
se we apply our method to CFHTLS galaxies. The ordinal classification algorithm treats distinct redshift bins as ordered values, which improves the quality of photometric redshift PDFs, compared with non-ordinal classification architectures. We also propose a new single value point estimate of the galaxy redshift, that can be used to estimate the full redshift PDF of a galaxy sample. This method is competitive in terms of accuracy with contemporary algorithms, which stack the full redshift PDFs of all galaxies in the sample, but requires orders of magnitudes less storage space. The methods described in this paper greatly improve the log-likelihood of individual object redshift PDFs, when compared with a popular Neural Network code (ANNz). In our use case, this improvement reaches 50% for high redshift objects ($z geq 0.75$). We show that using these more accurate photometric redshift PDFs will lead to a reduction in the systematic biases by up to a factor of four, when compared with less accurate PDFs obtained from commonly used methods. The cosmological analyses we examine and find improvement upon are the following: gravitational lensing cluster mass estimates, modelling of angular correlation functions, and modelling of cosmic shear correlation functions.
We investigate whether the large scale structure environment of galaxy clusters imprints a selection bias on Sunyaev Zeldovich (SZ) catalogs. Such a selection effect might be caused by line of sight (LoS) structures that add to the SZ signal or conta
in point sources that disturb the signal extraction in the SZ survey. We use the Planck PSZ1 union catalog (Planck Collab- oration et al. 2013a) in the SDSS region as our sample of SZ selected clusters. We calculate the angular two-point correlation function (2pcf) for physically correlated, foreground and background structure in the RedMaPPer SDSS DR8 catalog with respect to each cluster. We compare our results with an optically selected comparison cluster sample and with theoretical predictions. In contrast to the hypothesis of no environment-based selection, we find a mean 2pcf for background structures of -0.049 on scales of $lesssim 40$, significantly non-zero at $sim 4 sigma$, which means that Planck clusters are more likely to be detected in regions of low background density. We hypothesize this effect arises either from background estimation in the SZ survey or from radio sources in the background. We estimate the defect in SZ signal caused by this effect to be negligibly small, of the order of $sim 10^{-4}$ of the signal of a typical Planck detection. Analogously, there are no implications on X-ray mass measurements. However, the environ- mental dependence has important consequences for weak lensing follow up of Planck galaxy clusters: we predict that projection effects account for half of the mass contained within a 15 radius of Planck galaxy clusters. We did not detect a background underdensity of CMASS LRGs, which also leaves a spatially varying redshift dependence of the Planck SZ selection function as a possible cause for our findings.
We introduce a technique to measure gravitational lensing magnification using the variability of type I quasars. Quasars variability amplitudes and luminosities are tightly correlated, on average. Magnification due to gravitational lensing increases
the quasars apparent luminosity, while leaving the variability amplitude unchanged. Therefore, the mean magnification of an ensemble of quasars can be measured through the mean shift in the variability-luminosity relation. As a proof of principle, we use this technique to measure the magnification of quasars spectroscopically identified in the Sloan Digital Sky Survey, due to gravitational lensing by galaxy clusters in the SDSS MaxBCG catalog. The Palomar-QUEST Variability Survey, reduced using the DeepSky pipeline, provides variability data for the sources. We measure the average quasar magnification as a function of scaled distance (r/R200) from the nearest cluster; our measurements are consistent with expectations assuming NFW cluster profiles, particularly after accounting for the known uncertainty in the clusters centers. Variability-based lensing measurements are a valuable complement to shape-based techniques because their systematic errors are very different, and also because the variability measurements are amenable to photometric errors of a few percent and to depths seen in current wide-field surveys. Given the data volume expected from current and upcoming surveys, this new technique has the potential to be competitive with weak lensing shear measurements of large scale structure.
