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nIFTy galaxy cluster simulations I: dark matter & non-radiative models

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abstract

We have simulated the formation of a galaxy cluster in a $\Lambda$CDM universe using twelve different codes modeling only gravity and non-radiative hydrodynamics (\art, \arepo, \hydra\ and 9 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 traditional and advanced 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 ART and AREPO form extended entropy cores in the gas with rising central gas temperatures. Those codes employing traditional 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.

fields

astro-ph.IM 1

years

2026 1

verdicts

UNVERDICTED 1

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OpenGadget3 GPU solver tests

astro-ph.IM · 2026-06-15 · unverdicted · novelty 2.0

GPU version of OpenGadget3 matches CPU results across multiple test suites with chip-to-chip speedups of 2-5x.

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  • OpenGadget3 GPU solver tests astro-ph.IM · 2026-06-15 · unverdicted · none · ref 44 · internal anchor

    GPU version of OpenGadget3 matches CPU results across multiple test suites with chip-to-chip speedups of 2-5x.