Abstract
We have simulated the formation of a galaxy cluster in a Λ cold dark matter universe using 13 different codes modelling only gravity and non-radiative hydrodynamics (RAMSES, ART, AREPO, HYDRA and nine incarnations of GADGET). This range of codes includes particle-based, moving and fixed mesh codes as well as both Eulerian and Lagrangian fluid schemes. The various GADGET implementations span classic and modern smoothed particle hydrodynamics (SPH) schemes. The goal of this comparison is to assess the reliability of cosmological hydrodynamical simulations of clusters in the simplest astrophysically relevant case, that in which the gas is assumed to be non-radiative. We compare images of the cluster at z = 0, global properties such as mass and radial profiles of various dynamical and thermodynamical quantities. The underlying gravitational framework can be aligned very accurately for all the codes allowing a detailed investigation of the differences that develop due to the various gas physics implementations employed. As expected, the mesh-based codes RAMSES, ART and AREPO form extended entropy cores in the gas with rising central gas temperatures. Those codes employing classic SPH schemes show falling entropy profiles all the way into the very centre with correspondingly rising density profiles and central temperature inversions. We show that methods with modern SPH schemes that allow entropy mixing span the range between these two extremes and the latest SPH variants produce gas entropy profiles that are essentially indistinguishable from those obtained with grid-based methods.
Original language | English (US) |
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Pages (from-to) | 4063-4080 |
Number of pages | 18 |
Journal | Monthly Notices of the Royal Astronomical Society |
Volume | 457 |
Issue number | 4 |
DOIs | |
State | Published - Feb 10 2016 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Astronomy and Astrophysics
- Space and Planetary Science
Keywords
- Cosmology: theory
- Dark matter
- Galaxies: haloes
- Methods: numerical