Optimal multihump filter for photometric redshifts

We propose a novel type filter for multicolor imaging to improve on the photometric redshift estimation of galaxies. An extra filter - specific to a certain photometric system - may be utilized with high efficiency. We present a case study of the Hubble Space Telescope's Advanced Camera for Surveys and show that one extra exposure could cut down the mean square error on photometric redshifts by 34% over the z<1.3 redshift range.Comment: 9 pages, 3 figures, LaTeX AASTeX, accepted to A

Finding counterparts for All-sky X-ray surveys with Nway: a Bayesian algorithm for cross-matching multiple catalogues

We release the AllWISE counterparts and Gaia matches to 106,573 and 17,665 X-ray sources detected in the ROSAT 2RXS and XMMSL2 surveys with |b|>15. These are the brightest X-ray sources in the sky, but their position uncertainties and the sparse multi-wavelength coverage until now rendered the identification of their counterparts a demanding task with uncertain results. New all-sky multi-wavelength surveys of sufficient depth, like AllWISE and Gaia, and a new Bayesian statistics based algorithm, NWAY, allow us, for the first time, to provide reliable counterpart associations. NWAY extends previous distance and sky density based association methods and, using one or more priors (e.g., colors, magnitudes), weights the probability that sources from two or more catalogues are simultaneously associated on the basis of their observable characteristics. Here, counterparts have been determined using a WISE color-magnitude prior. A reference sample of 4524 XMM/Chandra and Swift X-ray sources demonstrates a reliability of ~ 94.7% (2RXS) and 97.4% (XMMSL2). Combining our results with Chandra-COSMOS data, we propose a new separation between stars and AGN in the X-ray/WISE flux-magnitude plane, valid over six orders of magnitude. We also release the NWAY code and its user manual. NWAY was extensively tested with XMM-COSMOS data. Using two different sets of priors, we find an agreement of 96% and 99% with published Likelihood Ratio methods. Our results were achieved faster and without any follow-up visual inspection. With the advent of deep and wide area surveys in X-rays (e.g. SRG/eROSITA, Athena/WFI) and radio (ASKAP/EMU, LOFAR, APERTIF, etc.) NWAY will provide a powerful and reliable counterpart identification tool.Comment: MNRAS, Paper accepted for publication. Updated catalogs are available at www.mpe.mpg.de/XraySurveys/2RXS_XMMSL2 . NWAY available at https://github.com/JohannesBuchner/nwa

Galaxy bimodality versus stellar mass and environment

We analyse a z<0.1 galaxy sample from the Sloan Digital Sky Survey focusing on the variation of the galaxy colour bimodality with stellar mass and projected neighbour density Sigma, and on measurements of the galaxy stellar mass functions. The characteristic mass increases with environmental density from about 10^10.6 Msun to 10^10.9 Msun (Kroupa IMF, H_0=70) for Sigma in the range 0.1--10 per Mpc^2. The galaxy population naturally divides into a red and blue sequence with the locus of the sequences in colour-mass and colour-concentration index not varying strongly with environment. The fraction of galaxies on the red sequence is determined in bins of 0.2 in log Sigma and log mass (12 x 13 bins). The red fraction f_r generally increases continuously in both Sigma and mass such that there is a unified relation: f_r = F(Sigma,mass). Two simple functions are proposed which provide good fits to the data. These data are compared with analogous quantities in semi-analytical models based on the Millennium N-body simulation: the Bower et al. (2006) and Croton et al. (2006) models that incorporate AGN feedback. Both models predict a strong dependence of the red fraction on stellar mass and environment that is qualitatively similar to the observations. However, a quantitative comparison shows that the Bower et al. model is a significantly better match; this appears to be due to the different treatment of feedback in central galaxies.Comment: 19 pages, 17 figures; accepted by MNRAS, minor change

Spatial Clustering of Galaxies in Large Datasets

Datasets with tens of millions of galaxies present new challenges for the analysis of spatial clustering. We have built a framework that integrates a database of object catalogs, tools for creating masks of bad regions, and a fast (NlogN) correlation code. This system has enabled unprecedented efficiency in carrying out the analysis of galaxy clustering in the SDSS catalog. A similar approach is used to compute the three-dimensional spatial clustering of galaxies on very large scales. We describe our strategy to estimate the effect of photometric errors using a database. We discuss our efforts as an early example of data-intensive science. While it would have been possible to get these results without the framework we describe, it will be infeasible to perform these computations on the future huge datasets without using this framework.Comment: original documents at http://research.microsoft.com/scripts/pubs/view.asp?TR_ID=MSR-TR-2002-8

GalICS V : Low and high order clustering in mock SDSS's

[Abridged] We use mock catalogues based on the GALICS model (Hatton et al. 03) to explore the nature of galaxy clustering observed in the SDSS. We measure low and high order angular clustering statistic from these mock catalogues, after selecting galaxies the same way as for observations, and compare them directly to estimates from SDSS data. Note that we also present measurements of S3-S5 on the SDSS DR1. We find that our model is in general good agreement with observations in the scale/luminosity range where we can trust the predictions. This range is found to be limited (i) by the size of the dark matter simulation used -- which introduces finite volume effects at large scales -- and by the mass resolution of this simulation -- which introduces incompleteness at apparent magnitudes fainter than $r\sim 20$. We then focus on the small scale clustering properties of galaxies and investigate the behaviour of three different prescriptions for positioning galaxies within haloes of dark matter. We show that galaxies are poor tracers both of DM particles or DM sub-structures, within groups and clusters. Instead, SDSS data tells us that the distribution of galaxies lies somewhat in between these two populations. This confirms the general theoretical expectation from numerical simulations and semi-analytic modelling.Comment: MNRAS, in pres