On the importance of using appropriate spectral models to derive
  physical properties of galaxies at 0.7<z<2.8
  Interpreting observations of distant galaxies in terms of constraints on
physical parameters - such as stellar mass, star-formation rate (SFR) and dust
optical depth - 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 (Pacifici et al. 2012). We present a Bayesian analysis of the spectra
and multi-wavelength 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/Mo)<12. We find
that, using the classical spectral library, stellar masses are systematically
overestimated (~0.1 dex) and SFRs are systematically underestimated (~0.6 dex)
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 optical depth of the dust, reducing the
uncertainties on these parameters. Finally, we show how the biases of classical
approaches can affect the correlation between stellar mass 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 stellar mass and SFR.
