We describe the creation of a set of artificially redshifted galaxies in the range 0.1<z<1.1 using a set of ~100 SDSS low redshift (v<7000 km/s) images as input. The intention is to generate a training set of realistic images of galaxies of diverse m
orphologies and a large range of redshifts for the GEMS and COSMOS galaxy evolution projects. This training set allows other studies to investigate and quantify the effects of cosmological redshift on the determination of galaxy morphologies, distortions and other galaxy properties that are potentially sensitive to resolution, surface brightness and bandpass issues. We use galaxy images from the SDSS in the u, g, r, i, z filter bands as input, and computed new galaxy images from these data, resembling the same galaxies as located at redshifts 0.1<z<1.1 and viewed with the Hubble Space Telescope Advanced Camera for Surveys (HST ACS). In this process we take into account angular size change, cosmological surface brightness dimming, and spectral change. The latter is achieved by interpolating a spectral energy distribution that is fit to the input images on a pixel-to-pixel basis. The output images are created for the specific HST ACS point spread function and the filters used for GEMS (F606W and F850LP) and COSMOS (F814W). All images are binned onto the desired pixel grids (0.03 for GEMS and 0.05 for COSMOS) and corrected to an appropriate point spread function. Noise is added corresponding to the data quality of the two projects and the images are added onto empty sky pieces of real data images. We make these datasets available from our website, as well as the code - FERENGI: Full and Efficient Redshifting of Ensembles of Nearby Galaxy Images - to produce datasets for other redshifts and/or instruments.
We present an overview of the Space Telescope A901/2 Galaxy Evolution Survey (STAGES). STAGES is a multiwavelength project designed to probe physical drivers of galaxy evolution across a wide range of environments and luminosity. A complex multi-clus
ter system at z~0.165 has been the subject of an 80-orbit F606W HST/ACS mosaic covering the full 0.5x0.5 (~5x5 Mpc^2) span of the supercluster. Extensive multiwavelength observations with XMM-Newton, GALEX, Spitzer, 2dF, GMRT, and the 17-band COMBO-17 photometric redshift survey complement the HST imaging. Our survey goals include simultaneously linking galaxy morphology with other observables such as age, star-formation rate, nuclear activity, and stellar mass. In addition, with the multiwavelength dataset and new high resolution mass maps from gravitational lensing, we are able to disentangle the large-scale structure of the system. By examining all aspects of environment we will be able to evaluate the relative importance of the dark matter halos, the local galaxy density, and the hot X-ray gas in driving galaxy transformation. This paper describes the HST imaging, data reduction, and creation of a master catalogue. We perform Sersic fitting on the HST images and conduct associated simulations to quantify completeness. In addition, we present the COMBO-17 photometric redshift catalogue and estimates of stellar masses and star-formation rates for this field. We define galaxy and cluster sample selection criteria which will be the basis for forthcoming science analyses, and present a compilation of notable objects in the field. Finally, we describe the further multiwavelength observations and announce public access to the data and catalogues.
In the context of measuring structure and morphology of intermediate redshift galaxies with recent HST/ACS surveys, we tune, test, and compare two widely used fitting codes (GALFIT and GIM2D) for fitting single-component Sersic models to the light pr
ofiles of both simulated and real galaxy data. We find that fitting accuracy depends sensitively on galaxy profile shape. Exponential disks are well fit with Sersic models and have small measurement errors, whereas fits to de Vaucouleurs profiles show larger uncertainties owing to the large amount of light at large radii. We find that both codes provide reliable fits and little systematic error, when the effective surface brightness is above that of the sky. Moreover, both codes return errors that significantly underestimate the true fitting uncertainties, which are best estimated with simulations. We find that GIM2D suffers significant systematic errors for spheroids with close companions owing to the difficulty of effectively masking out neighboring galaxy light; there appears to be no work around to this important systematic in GIM2Ds current implementation. While this crowding error affects only a small fraction of galaxies in GEMS, it must be accounted for in the analysis of deeper cosmological images or of more crowded fields with GIM2D. In contrast, GALFIT results are robust to the presence of neighbors because it can simultaneously fit the profiles of multiple companions thereby deblending their effect on the fit to the galaxy of interest. We find GALFITs robustness to nearby companions and factor of >~20 faster runtime speed are important advantages over GIM2D for analyzing large HST/ACS datasets. Finally we include our final catalog of fit results for all 41,495 objects detected in GEMS.
