2015MNRAS.447..786P

Interpreting observations of distant galaxies in terms of constraints on physical parameters - such as stellar mass (M*), star formation rate (SFR) and dust optical depth (1_V) - requires spectral synthesis modelling. We analyse the reliability of these physical parameters as determined under commonly adopted `classical' assumptions: star formation histories assumed to be exponentially declining functions of time, a simple dust law and no emission-line contribution. Improved modelling techniques and data quality now allow us to use a more sophisticated approach, including realistic star formation histories, combined with modern prescriptions for dust attenuation and nebular emission. We present a Bayesian analysis of the spectra and multiwavelength photometry of 1048 galaxies from the 3D-HST survey in the redshift range 0.7 < z < 2.8 and in the stellar mass range 9 ≲ log(M*/M<sub>☉</sub>) ≲ 12. We find that, using the classical spectral library, stellar masses are systematically overestimated ( ∼ 0.1 dex) and SFRs are systematically underestimated ( ∼ 0.6dex) relative to our more sophisticated approach. We also find that the simultaneous fit of photometric fluxes and emission-line equivalent widths helps break a degeneracy between SFR and 1_V, reducing the uncertainties on these parameters. Finally, we show how the biases of classical approaches can affect the correlation between M* and SFR for star-forming galaxies (the `star-formation main sequence'). We conclude that the normalization, slope and scatter of this relation strongly depend on the adopted approach and demonstrate that the classical, oversimplified approach cannot recover the true distribution of M* and SFR.