Galaxy formation and evolution

Abstract:

VANDELS is a uniquely deep spectroscopic survey of high-redshift galaxies with the VIMOS spectrograph on ESO'sVery Large Telescope (VLT). The survey has obtained ultradeep optical (0.48 < ? < 1.0 μm) spectroscopy of ≃2100 galaxies within the redshift interval 1.0≤z≤ 7.0, over a total area of ≃0.2 deg2centred on the CANDELS Ultra Deep Survey and Chandra Deep Field South fields. Based on accurate photometric redshift pre-selection, 85 per cent of the galaxies targeted by VANDELS were selected to be at z ≥ 3. Exploiting the red sensitivity of the refurbished VIMOS spectrograph, the fundamental aim of the survey is to provide the high-signal-to-noise ratio spectra necessary to measure key physical properties such as stellar population ages, masses, metallicities, and outflow velocities from detailed absorption-line studies. Using integration times calculated to produce an approximately constant signal-tonoise ratio (20>tint>80 h), theVANDELS survey targeted: (a) bright star-forming galaxies at 2.4≤z≤5.5, (b) massive quiescent galaxies at 1.0≤z≤2.5, (c) fainter star-forming galaxies at 3.0≤z≤7.0, and (d) X-ray/Spitzer-selected active galactic nuclei and Herschel-detected galaxies. By targeting two extragalactic survey fields with superb multiwavelength imaging data, VANDELS will produce a unique legacy data set for exploring the physics underpinning high-redshift galaxy evolution. In this paper, we provide an overview of the VANDELS survey designed to support the science exploitation of the first ESO public data release, focusing on the scientific motivation, survey design, and target selection.

Abstract:

Using mock spectra based on Vazdekis/MILES library fitted within the wavelength region 3600-7350\AA, we analyze the bias and scatter on the resulting physical parameters induced by the choice of fitting algorithms and observational uncertainties, but avoid effects of those model uncertainties. We consider two full-spectrum fitting codes: pPXF and STARLIGHT, in fitting for stellar population age, metallicity, mass-to-light ratio, and dust extinction. With pPXF we find that both the bias in the population parameters and the scatter in the recovered logarithmic values follows the expected trend. The bias increases for younger ages and systematically makes recovered ages older, M∗/Lr larger and metallicities lower than the true values. For reference, at S/N=30, and for the worst case (t=108yr), the bias is 0.06 dex in M∗/Lr, 0.03 dex in both age and [M/H]. There is no significant dependence on either E(B-V) or the shape of the error spectrum. Moreover, the results are consistent for both our 1-SSP and 2-SSP tests. With the STARLIGHT algorithm, we find trends similar to pPXF, when the input E(B-V)<0.2 mag. However, with larger input E(B-V), the biases of the output parameter do not converge to zero even at the highest S/N and are strongly affected by the shape of the error spectra. This effect is particularly dramatic for youngest age, for which all population parameters can be strongly different from the input values, with significantly underestimated dust extinction and [M/H], and larger ages and M∗/Lr. Results degrade when moving from our 1-SSP to the 2-SSP tests. The STARLIGHT convergence to the true values can be improved by increasing Markov Chains and annealing loops to the "slow mode". For the same input spectrum, pPXF is about two order of magnitudes faster than STARLIGHT's "default mode" and about three order of magnitude faster than STARLIGHT's "slow mode".