Deriving star formation histories from photometry using energy balance
  spectral energy distribution modelling
  Panchromatic spectral energy distribution (SED) fitting is a critical tool
for determining the physical properties of distant galaxies, such as their
stellar mass and star formation rate. One widely used method is the publicly
available MAGPHYS code. We build on our previous analysis (Hayward & Smith
2015) by presenting some modifications which enable MAGPHYS to automatically
estimate galaxy star formation histories (SFHs), including uncertainties, based
on ultra-violet to far-infrared photometry. We use state-of-the art synthetic
photometry derived by performing three-dimensional dust radiative transfer on
hydrodynamic simulations of isolated disc and merging galaxies to test how well
the modified MAGPHYS is able to recover SFHs under idealised conditions, where
the true SFH is known. We find that while the SFH of the model with the best
fit to the synthetic photometry is a poor representation of the true SFH
(showing large variations with the line-of-sight to the galaxy and spurious
bursts of star formation), median-likelihood SFHs generated by marginalising
over the default MAGPHYS libraries produce robust estimates of the
smoothly-varying isolated disk simulation SFHs. This preference for the
median-likelihood SFH is quantitatively underlined by our estimates of
$\chi^2_{{\rm SFH}}$ (analogous to the $\chi^2$ goodness-of-fit estimator) and
$\Delta M/M$ (the integrated absolute mass discrepancy between the model and
true SFH) that strongly prefer the median-likelihood SFHs over those that best
fit the UV-to-far-IR photometry. In contrast, we are unable to derive a good
estimate of the SFH for the merger simulations (either best-fit or
median-likelihood) despite being able to obtain a reasonable fit to the
simulated photometry, likely because the analytic SFHs with bursts superposed
in the standard MAGPHYS library are insufficiently general/realistic.
