Abstract details

The recent advent of major surveys targetting statistically significant samples of high-redshift galaxies has boosted the study of stellar populations at high redshifts. In particular, the star formation rate is a parameter that is difficult to obtain at higher redshift, as local well-calibrated spectral indicators, as e.g. the Halpha emission line, move out of the observed optical wavelength range. While SFRs derived from the rest-frame UV alone are subject to considerable uncertainties due to dust, preliminary studies have shown that, in principle, fits to broad-band spectral energy distributions are a promising avenue to simultaneously constrain a large number of crucial physical parameters such as, for example, stellar mass and specific star formation rate. However, the applicability of such a method at redshift around 1 remains unexplored systematically. Moreover, widely differing data coverage and underlying hypotheses on the star formation histories as well as the use of different sets of publically available stellar population synthesis models add confusion to this subject. Using a combined multiwavelength dataset derived from the cutting edge surveys of Galex, VVDS, CFHTLS and SWIRE, we systematically explore the maximal recoverable complexity of the input SFH as well as the robustness of derived parameters such as stellar mass and star formation rate for different sets of input data and model parameters. We also aim to assess the applicability of different stellar population models to galaxies at high redshifts.