Hydrodynamical Simulations of Galaxy Clusters with Galcons

Abstract

We present our recently developed {\em galcon} approach to hydrodynamical cosmological simulations of galaxy clusters - a subgrid model added to the {\em Enzo} adaptive mesh refinement code - which is capable of tracking galaxies within the cluster potential and following the feedback of their main baryonic processes. Galcons are physically extended galactic constructs within which baryonic processes are modeled analytically. By identifying galaxy halos and initializing galcons at high redshift ($z\sim 3$, well before most clusters virialize), we are able to follow the evolution of star formation, galactic winds, and ram-pressure stripping of interstellar media, along with their associated mass, metals and energy feedback into intracluster (IC) gas, which are deposited through a well-resolved spherical interface layer. Our approach is fully described and all results from initial simulations with the enhanced {\em Enzo-Galcon} code are presented. With a galactic star formation rate derived from the observed cosmic star formation density, our galcon simulation better reproduces the observed properties of IC gas, including the density, temperature, metallicity, and entropy profiles. By following the impact of a large number of galaxies on IC gas we explicitly demonstrate the advantages of this approach in producing a lower stellar fraction, a larger gas core radius, an isothermal temperature profile in the central cluster region, and a flatter metallicity gradient than in a standard simulation.

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• Parallel HOP: A Scalable Halo Finder for Massive Cosmological Data Sets
• On The Road To More Realistic Galaxy Cluster Simulations: The Effects of Radiative Cooling and Thermal Feedback Prescriptions on the Observational Properties of Simulated Galaxy Clusters
• Evolution of the gas mass fraction in galaxy clusters
• Dispersal of Galactic Magnetic Fields into Intracluster Space
• Alignment between Satellite and Central Galaxies in the EAGLE Simulation: Dependence on the Large-Scale Environments