The challenge of simultaneously matching the observed diversity of
  chemical abundance patterns in cosmological hydrodynamical simulations
  With the advent of large spectroscopic surveys the amount of high quality
chemo-dynamical data in the Milky Way (MW) increased tremendously. Accurately
and correctly capturing and explaining the detailed features in the
high-quality observational data is notoriously difficult for state-of-the-art
numerical models. In order to keep up with the quantity and quality of
observational datasets, improved prescriptions for galactic chemical evolution
need to be incorporated into the simulations. Here we present a new, flexible,
time resolved chemical enrichment model for cosmological simulations. Our model
allows to easily change a number of stellar physics parameters such as the
shape of the initial mass function (IMF), stellar lifetimes, chemical yields or
SN Ia delay times. We implement our model into the Gasoline2 code and perform a
series of cosmological simulations varying a number of key parameters, foremost
evaluating different stellar yield sets for massive stars from the literature.
We find that total metallicity, total iron abundance and gas phase oxygen
abundance are robust predictions from different yield sets and in agreement
with observational relations. On the other hand, individual element abundances,
especially $\alpha$-elements show significant differences across different
yield sets and none of our models can simultaneously match constraints on the
dwarf and MW mass scale. This offers a unique way of observationally
constraining model parameters. For MW mass galaxies we find for most yield
tables tested in this work a bimodality in the $[\alpha$/Fe] vs. [Fe/H] plane
of rather low intrinsic scatter potentially in tension with the observed
abundance scatter.
