The Impact of Modeling Assumptions in Galactic Chemical Evolution Models
  We use the OMEGA galactic chemical evolution code to investigate how the
assumptions used for the treatment of galactic inflows and outflows impact
numerical predictions. The goal is to determine how our capacity to reproduce
the chemical evolution trends of a galaxy is affected by the choice of
implementation used to include those physical processes. In pursuit of this
goal, we experiment with three different prescriptions for galactic inflows and
outflows and use OMEGA within a Markov Chain Monte Carlo code to recover the
set of input parameters that best reproduces the chemical evolution of nine
elements in the dwarf spheroidal galaxy Sculptor. This provides a consistent
framework for comparing the best-fit solutions generated by our different
models. Despite their different degrees of intended physical realism, we found
that all three prescriptions can reproduce in an almost identical way the
stellar abundance trends observed in Sculptor. While the three models have the
same capacity to fit the data, the best values recovered for the parameters
controlling the number of Type Ia supernovae and the strength of galactic
outflows, are substantially different and in fact mutually exclusive from one
model to another. For the purpose of understanding how a galaxy evolves, we
conclude that only reproducing the evolution of a limited number of elements is
insufficient and can lead to misleading conclusions. More elements or
additional constraints such as the galaxy's star formation efficiency and the
gas fraction are needed in order to break the degeneracy between the different
modeling assumptions. Our results show that the successes and failures of
chemical evolution models are predominantly driven by the input stellar yields,
rather than by the complexity of the galaxy model itself. Simple models such as
OMEGA are therefore sufficient to test and validate stellar yields.
