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arXiv 2003.12576astro-ph.GA
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Reproducing the Universe: a comparison between the EAGLE simulations and the nearby DustPedia galaxy sample

Ana Trčka, Maarten Baes, Peter Camps, Sharon E. Meidt, James Trayford, Simone Bianchi, Viviana Casasola, Letizia P. Cassarà, Ilse De Looze, Pieter De Vis, Woute… 展开作者

Ana Trčka, Maarten Baes, Peter Camps, Sharon E. Meidt, James Trayford, Simone Bianchi, Viviana Casasola, Letizia P. Cassarà, Ilse De Looze, Pieter De Vis, Wouter Dobbels, Jacopo Fritz, Maud Galametz, Frédéric Galliano, Antonios Katsianis, Suzanne C. Madden, Aleksandr V. Mosenkov, Angelos Nersesian, Sébastien Viaene, Emmanuel M. Xilouris

英文摘要:

We compare the spectral energy distributions (SEDs) and inferred physical properties for simulated and observed galaxies at low redshift. We exploit UV-submillimetre mock fluxes of ~7000 z=0 galaxies from the EAGLE suite of cosmological simulations, derived using the radiative transfer code SKIRT. We compare these to ~800 observed galaxies in the UV-submillimetre range, from the DustPedia sample of nearby galaxies. To derive global properties, we apply the SED fitting code CIGALE consistently to both data sets, using the same set of ~80 million models. The results of this comparison reveal overall agreement between the simulations and observations, both in the SEDs and in the derived physical properties, with a number of discrepancies. The optical and far-infrared regimes, and the scaling relations based upon the global emission, diffuse dust and stellar mass, show high levels of agreement. However, the mid-infrared fluxes of the EAGLE galaxies are overestimated while the far-UV domain is not attenuated enough, compared to the observations. We attribute these discrepancies to a combination of galaxy population differences between the samples, and limitations in the subgrid treatment of star-forming regions in the EAGLE-SKIRT post-processing recipe. Our findings show the importance of detailed radiative transfer calculations and consistent comparison, and provide suggestions for improved numerical models.

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