McAlpine, S. and Helly, J. C. and Schaller, M. and Trayford, J. W. and Qu, Y. and Furlong, M. and Bower, R. G. and Crain, R. A. and Schaye, J. and Theuns, T. and Dalla Vecchia, C. and Frenk, C. S. and McCarthy, I. G. and Jenkins, A. and Rosas-Guevara, Y. and White, S. D. M. and Baes, M. and Camps, P. and Lemson, G. (2016) 'The EAGLE simulations of galaxy formation : public release of halo and galaxy catalogues.', Astronomy and computing., 15 . pp. 72-89.
We present the public data release of halo and galaxy catalogues extracted from the eagle suite of cosmological hydrodynamical simulations of galaxy formation. These simulations were performed with an enhanced version of the gadget code that includes a modified hydrodynamics solver, time-step limiter and subgrid treatments of baryonic physics, such as stellar mass loss, element-by-element radiative cooling, star formation and feedback from star formation and black hole accretion. The simulation suite includes runs performed in volumes ranging from 25 to 100 comoving megaparsecs per side, with numerical resolution chosen to marginally resolve the Jeans mass of the gas at the star formation threshold. The free parameters of the subgrid models for feedback are calibrated to the redshift z=0 galaxy stellar mass function, galaxy sizes and black hole mass–stellar mass relation. The simulations have been shown to match a wide range of observations for present-day and higher-redshift galaxies. The raw particle data have been used to link galaxies across redshifts by creating merger trees. The indexing of the tree produces a simple way to connect a galaxy at one redshift to its progenitors at higher redshift and to identify its descendants at lower redshift. In this paper we present a relational database which we are making available for general use. A large number of properties of haloes and galaxies and their merger trees are stored in the database, including stellar masses, star formation rates, metallicities, photometric measurements and mock gri images. Complex queries can be created to explore the evolution of more than 105 galaxies, examples of which are provided in the Appendix. The relatively good and broad agreement of the simulations with a wide range of observational datasets makes the database an ideal resource for the analysis of model galaxies through time, and for connecting and interpreting observational datasets.
|Full text:||(AM) Accepted Manuscript|
Available under License - Creative Commons Attribution Non-commercial No Derivatives.
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|Publisher Web site:||https://doi.org/10.1016/j.ascom.2016.02.004|
|Publisher statement:||© 2016 This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/|
|Date accepted:||25 February 2016|
|Date deposited:||29 November 2016|
|Date of first online publication:||17 March 2016|
|Date first made open access:||17 March 2017|
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