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Overview and public data release of the augmented Auriga Project: cosmological simulations of dwarf and Milky Way-mass galaxies

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Springel,  Volker
Computational Structure Formation, MPI for Astrophysics, Max Planck Society;

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Citation

Grand, R. J. J., Fragkoudi, F., Gomez, F. A., Jenkins, A., Marinacci, F., Pakmor, R., et al. (2024). Overview and public data release of the augmented Auriga Project: cosmological simulations of dwarf and Milky Way-mass galaxies. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 532(2), 1814-1831. doi:10.1093/mnras/stae1598.


Cite as: https://hdl.handle.net/21.11116/0000-000F-E3FD-4
Abstract
We present an extended suite of the Auriga cosmological gravo-magnetohydrodynamical 'zoom-in' simulations of 40 Milky Way-mass haloes and 26 dwarf galaxy-mass haloes run with the moving-mesh code arepo. Auriga adopts the Lambda cold dark matter cosmogony and includes a comprehensive galaxy formation physics model following the coupled cosmic evolution of dark matter, gas, stars, and supermassive black holes which has been shown to produce numerically well-converged galaxy properties for Milky Way-mass systems. We describe the first public data release of this augmented suite of Auriga simulations, which includes raw snapshots, group catalogues, merger trees, initial conditions, and supplementary data, as well as public analysis tools with worked examples of how to use the data. To demonstrate the value and robustness of the simulation predictions, we analyse a series of low-redshift global properties that compare well with many observed scaling relations, such as the Tully-Fisher relation, the star-forming (SF) main sequence, and H i gas fraction/disc thickness. Finally, we show that SF gas discs appear to build rotation and velocity dispersion rapidly for z less than or similar to 3 before they 'settle' into ever-increasing rotation-dispersion ratios (V/sigma). This evolution appears to be in rough agreement with some kinematic measurements from H alpha observations, and demonstrates an application of how to utilize the released data.