Calibration of a star formation and feedback model for cosmological
  simulations with Enzo
  We present results from seventy-one zoom simulations of a Milky Way-sized
(MW) halo, exploring the parameter space for a widely-used star formation and
feedback model in the {\tt Enzo} simulation code. We propose a novel way to
match observations, using functional fits to the observed baryon makeup over a
wide range of halo masses. The model MW galaxy is calibrated using three
parameters: the star formation efficiency $\left(f_*\right)$, the efficiency of
thermal energy from stellar feedback $\left(\epsilon\right)$ and the region
into which feedback is injected $\left(r\ {\rm and}\ s\right)$. We find that
changing the amount of feedback energy affects the baryon content most
significantly. We then identify two sets of feedback parameter values that are
both able to reproduce the baryonic properties for haloes between
$10^{10}\,\mathrm{M_\odot}$ and $10^{12}\,\mathrm{M_\odot}$. We can potentially
improve the agreement by incorporating more parameters or physics. If we choose
to focus on one property at a time, we can obtain a more realistic halo baryon
makeup. We show that the employed feedback prescription is insensitive to dark
matter mass resolution between $10^5\,{\rm M_\odot}$ and $10^7\,{\rm M_\odot}$.
Contrasting both star formation criteria and the corresponding combination of
optimal feedback parameters, we also highlight that feedback is
self-consistent: to match the same baryonic properties, with a relatively
higher gas to stars conversion efficiency, the feedback strength required is
lower, and vice versa. Lastly, we demonstrate that chaotic variance in the code
can cause deviations of approximately 10\% and 25\% in the stellar and baryon
mass in simulations evolved from identical initial conditions.
