CFHTLenS: the environmental dependence of galaxy halo masses from weak lensing

We use weak gravitational lensing to analyse the dark matter haloes around satellite galaxies in galaxy groups in the Canada–France–Hawaii Telescope Lensing Survey (CFHTLenS) data set. This data set is derived from the Canada–France–Hawaii Telescope Legacy Survey Wide survey, and encompasses 154 deg^2 of high-quality shape data. Using the photometric redshifts, we divide the sample of lens galaxies with stellar masses in the range 10^(9)–10^(10.5) M_⊙ into those likely to lie in high-density environments (HDE) and those likely to lie in low-density environments (LDE). Through comparison with galaxy catalogues extracted from the Millennium Simulation, we show that the sample of HDE galaxies should primarily (∼61 per cent) consist of satellite galaxies in groups, while the sample of LDE galaxies should consist of mostly (∼87 per cent) non-satellite (field and central) galaxies. Comparing the lensing signals around samples of HDE and LDE galaxies matched in stellar mass, the lensing signal around HDE galaxies clearly shows a positive contribution from their host groups on their lensing signals at radii of ∼500–1000 kpc, the typical separation between satellites and group centres. More importantly, the subhaloes of HDE galaxies are less massive than those around LDE galaxies by a factor of 0.65 ± 0.12, significant at the 2.9σ level. A natural explanation is that the haloes of satellite galaxies are stripped through tidal effects in the group environment. Our results are consistent with a typical tidal truncation radius of ∼40 kpc

Star/galaxy separation at faint magnitudes : application to a simulated Dark Energy Survey

We address the problem of separating stars from galaxies in future large photometric surveys. We focus our analysis on simulations of the Dark Energy Survey (DES). In the first part of the paper, we derive the science requirements on star/galaxy separation, for measurement of the cosmological parameters with the gravitational weak lensing and large-scale structure probes. These requirements are dictated by the need to control both the statistical and systematic errors on the cosmological parameters, and by point spread function calibration. We formulate the requirements in terms of the completeness and purity provided by a given star/galaxy classifier. In order to achieve these requirements at faint magnitudes, we propose a new method for star/galaxy separation in the second part of the paper.We first use principal component analysis to outline the correlations between the objects parameters and extract from it the most relevant information.We then use the reduced set of parameters as input to an Artificial Neural Network. This multiparameter approach improves upon purely morphometric classifiers (such as the classifier implemented in SEXTRACTOR), especially at faint magnitudes: it increases the purity by up to 20 per cent for stars and by up to 12 per cent for galaxies, at i-magnitude fainter than 23

Star/galaxy separation at faint magnitudes : application to a simulated Dark Energy Survey

We address the problem of separating stars from galaxies in future large photometric surveys. We focus our analysis on simulations of the Dark Energy Survey (DES). In the first part of the paper, we derive the science requirements on star/galaxy separation, for measurement of the cosmological parameters with the gravitational weak lensing and large-scale structure probes. These requirements are dictated by the need to control both the statistical and systematic errors on the cosmological parameters, and by point spread function calibration. We formulate the requirements in terms of the completeness and purity provided by a given star/galaxy classifier. In order to achieve these requirements at faint magnitudes, we propose a new method for star/galaxy separation in the second part of the paper.We first use principal component analysis to outline the correlations between the objects parameters and extract from it the most relevant information.We then use the reduced set of parameters as input to an Artificial Neural Network. This multiparameter approach improves upon purely morphometric classifiers (such as the classifier implemented in SEXTRACTOR), especially at faint magnitudes: it increases the purity by up to 20 per cent for stars and by up to 12 per cent for galaxies, at i-magnitude fainter than 23

Mass and galaxy distributions of four massive galaxy clusters from Dark Energy Survey Science Verification data

We measure the weak lensing masses and galaxy distributions of four massive galaxy clusters observed during the Science Verification phase of the Dark Energy Survey (DES). This pathfinder study is meant to (1) validate the Dark Energy Camera (DECam) imager for the task of measuring weak lensing shapes, and (2) utilize DECam’s large field of view to map out the clusters and their environments over 90 arcmin. We conduct a series of rigorous tests on astrometry, photometry, image quality, point spread function (PSF) modelling, and shear measurement accuracy to single out flaws in the data and also to identify the optimal data processing steps and parameters. We find Science Verification data from DECam to be suitable for the lensing analysis described in this paper. The PSF is generally well behaved, but the modelling is rendered difficult by a flux-dependent PSF width and ellipticity. We employ photometric redshifts to distinguish between foreground and background galaxies, and a red-sequence cluster finder to provide cluster richness estimates and cluster–galaxy distributions. By fitting Navarro–Frenk–White profiles to the clusters in this study, we determine weak lensing masses that are in agreement with previous work. For Abell 3261, we provide the first estimates of redshift, weak lensing mass, and richness. In addition, the cluster–galaxy distributions indicate the presence of filamentary structures attached to 1E 0657−56 and RXC J2248.7−4431, stretching out as far as 1◦(approximately 20 Mpc), showcasing the potential of DECam and DES for detailed studies of degree-scale features on the sky

Mass and galaxy distributions of four massive galaxy clusters from Dark Energy Survey Science Verification data

We measure the weak lensing masses and galaxy distributions of four massive galaxy clusters observed during the Science Verification phase of the Dark Energy Survey (DES). This pathfinder study is meant to (1) validate the Dark Energy Camera (DECam) imager for the task of measuring weak lensing shapes, and (2) utilize DECam’s large field of view to map out the clusters and their environments over 90 arcmin. We conduct a series of rigorous tests on astrometry, photometry, image quality, point spread function (PSF) modelling, and shear measurement accuracy to single out flaws in the data and also to identify the optimal data processing steps and parameters. We find Science Verification data from DECam to be suitable for the lensing analysis described in this paper. The PSF is generally well behaved, but the modelling is rendered difficult by a flux-dependent PSF width and ellipticity. We employ photometric redshifts to distinguish between foreground and background galaxies, and a red-sequence cluster finder to provide cluster richness estimates and cluster–galaxy distributions. By fitting Navarro–Frenk–White profiles to the clusters in this study, we determine weak lensing masses that are in agreement with previous work. For Abell 3261, we provide the first estimates of redshift, weak lensing mass, and richness. In addition, the cluster–galaxy distributions indicate the presence of filamentary structures attached to 1E 0657−56 and RXC J2248.7−4431, stretching out as far as 1◦(approximately 20 Mpc), showcasing the potential of DECam and DES for detailed studies of degree-scale features on the sky