  A deep understanding of the Milky Way galaxy, its formation and evolution
requires observations of huge numbers of stars. Stellar photometry, therefore,
provides an economical method to obtain intrinsic stellar parameters. With the
addition of distance information - deriving reliable ages from photometry is a
possibility. We have developed a Bayesian method that generates 2D probability
maps of a star's age and metallicity from photometry and parallax using
isochrones. Our synthetic tests show that including a near-UV passband enables
us to break the degeneracy between a star's age and metallicity for certain
evolutionary stages. It is possible to find well-constrained ages and
metallicities for turn-off and sub-giant stars with colours including a U band
and a parallax with uncertainty less than ~20%. Metallicities alone are
possible for the main sequence and giant branch. We find good agreement with
the literature when we apply our method to the Gaia benchmark stars,
particularly for turn-off and young stars. Further tests on the old open
cluster NGC 188, however, reveal significant limitations in the stellar
isochrones. The ages derived for the cluster stars vary with evolutionary
stage, such that turn-off ages disagree with those on the sub-giant branch, and
metallicities vary significantly throughout. Furthermore, the parameters vary
appreciably depending on which colour combinations are used in the derivation.
We identify the causes of these mismatches and show that improvements are
needed in the modelling of giant branch stars and in the creation and
calibration of synthetic near-UV photometry. Our results warn against applying
isochrone fitting indiscriminately. In particular, the uncertainty on the
stellar models should be quantitatively taken into account. Further efforts to
improve the models will result in significant advancements in our ability to
study the Galaxy.
