  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 morphologies 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.
