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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 andfeedback model in the {\tt Enzo} simulation code. We propose a novel way tomatch observations, using functional fits to the observed baryon makeup over awide range of halo masses. The model MW galaxy is calibrated using threeparameters: the star formation efficiency $\left(f_*\right)$, the efficiency ofthermal energy from stellar feedback $\left(\epsilon\right)$ and the regioninto which feedback is injected $\left(r\ {\rm and}\ s\right)$. We find thatchanging the amount of feedback energy affects the baryon content mostsignificantly. We then identify two sets of feedback parameter values that areboth able to reproduce the baryonic properties for haloes between$10^{10}\,\mathrm{M_\odot}$ and $10^{12}\,\mathrm{M_\odot}$. We can potentiallyimprove the agreement by incorporating more parameters or physics. If we chooseto focus on one property at a time, we can obtain a more realistic halo baryonmakeup. We show that the employed feedback prescription is insensitive to darkmatter mass resolution between $10^5\,{\rm M_\odot}$ and $10^7\,{\rm M_\odot}$.Contrasting both star formation criteria and the corresponding combination ofoptimal feedback parameters, we also highlight that feedback isself-consistent: to match the same baryonic properties, with a relativelyhigher gas to stars conversion efficiency, the feedback strength required islower, and vice versa. Lastly, we demonstrate that chaotic variance in the codecan cause deviations of approximately 10\% and 25\% in the stellar and baryonmass in simulations evolved from identical initial conditions.

Calibration of a star formation and feedback model for cosmological simulations with Enzo