Data Release of UV to Submillimeter Broadband Fluxes for Simulated Galaxies from the EAGLE Project

Monthly Notices of the Royal Astronomical Society

Camps

et al. 2020

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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.

Section: Introductionmentioning

confidence: 81%

Reproducing the Universe: a comparison between the EAGLE simulations and the nearby DustPedia galaxy sample

Trčka

Monthly Notices of the Royal Astronomical Society

Camps

et al. 2020

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“…We have presented infrared luminosity functions and dust mass functions for the EAGLE cosmological simulation. These luminosity functions and dust mass functions are based on synthetic infrared luminosities, generated by means of the EAGLE-SKIRT post-processing recipe presented by Camps et al (2016Camps et al ( , 2018. The goal of this paper was to compare these EAGLE-SKIRT luminosity and dust mass functions to observational ones, as a test of the EA-GLE simulations and the EAGLE-SKIRT recipe.…”

Section: Discussionmentioning

confidence: 99%

“…The parameters in the post-processing scheme were calibrated to reproduce the observed submm colours and dust scaling relations of nearby Herschel Reference Survey (HRS) galaxies (Boselli et al 2012;Cortese et al 2012Cortese et al , 2014. Camps et al (2018) used this framework to generate synthetic observations for six different EAGLE simulations, including the Ref-100 and Recal-25 simulations. The resulting EAGLE-SKIRT database contains synthetic UV to submm flux densities and intrinsic luminosities for all galaxies in the simulations with at least 250 dust containing particles, and with stellar masses above 10 8.5 M .…”

Section: The Datamentioning

confidence: 99%

Infrared luminosity functions and dust mass functions in the EAGLE simulation

Monthly Notices of the Royal Astronomical Society

Trčka

Camps

et al. 2020

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We present infrared luminosity functions and dust mass functions for the EAGLE cosmological simulation, based on synthetic multi-wavelength observations generated with the SKIRT radiative transfer code. In the local Universe, we reproduce the observed infrared luminosity and dust mass functions very well. Some minor discrepancies are encountered, mainly in the high luminosity regime, where the EAGLE-SKIRT luminosity functions mildly but systematically underestimate the observed ones. The agreement between the EAGLE-SKIRT infrared luminosity functions and the observed ones gradually worsens with increasing lookback time. Fitting modified Schechter functions to the EAGLE-SKIRT luminosity and dust mass functions at different redshifts up to z = 1, we find that the evolution is compatible with pure luminosity/mass evolution. The evolution is relatively mild: within this redshift range, we find an evolution of L ,250 ∝ (1 + z) 1.68 , L ,TIR ∝ (1 + z) 2.51 and M ,dust ∝ (1 + z) 0.83 for the characteristic luminosity/mass. For the luminosity/mass density we find ε 250 ∝ (1 + z) 1.62 , ε TIR ∝ (1 + z) 2.35 and ρ dust ∝ (1 + z) 0.80 , respectively. The mild evolution of the dust mass density is in relatively good agreement with observations, but the slow evolution of the infrared luminosity underestimates the observed luminosity evolution significantly. We argue that these differences can be attributed to increasing limitations in the radiative transfer treatment due to increasingly poorer resolution, combined with a slower than observed evolution of the SFR density in the EAGLE simulation and the lack of AGN emission in our EAGLE-SKIRT post-processing recipe.

“…The minimum and maximum subdivision level are chosen to be 6 and 36, respectively, and we set the stopping criterion for individual cells to the point where they contain less than 5×10 −7 of the total dust mass (Saftly et al 2013). This threshold is similar to values used in the previous SKIRT simulations of spiral galaxies (De Looze et al 2014;Saftly et al 2015;Camps et al 2016Camps et al , 2018Viaene et al 2017;Trayford et al 2017).…”

Section: Set Up Of the Skirt Simulationsmentioning

confidence: 99%

“…Furthermore, we have assumed that the intrinsic luminosity of bulge and old stellar disc can directly be obtained from the IRAC 3.6 µm emission, which implicitly assumes that the emission is unaffected by dust attenuation or emission, and that the young stellar populations have a negligible contribution to the IRAC 3.6 µm band. These conditions may not always be satisfied for all galaxies (e.g., Camps et al 2018).…”

Section: Limitations and Caveats In Our Modelling Approachmentioning

confidence: 99%

High-resolution, 3D radiative transfer modelling

Verstocken

Nersesian

et al. 2020

A&A

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Context. Interstellar dust absorbs stellar light very efficiently and thus shapes the energetic output of galaxies. Studying the impact of different stellar populations on the dust heating remains hard because it requires decoupling the relative geometry of stars and dust, and involves complex processes as scattering and non-local dust heating. Aims. We aim to constrain the relative distribution of dust and stellar populations in the spiral galaxy M 81 and create a realistic model of the radiation field that describes the observations. Investigating the dust-starlight interaction on local scales, we want to quantify the contribution of young and old stellar populations to the dust heating. We aim to standardise the setup and model selection of such inverse radiative transfer simulations so this can be used for comparable modelling of other nearby galaxies. Methods. We present a semi-automated radiative transfer modelling pipeline that implements the necessary steps such as the geometric model construction and the normalisation of the components through an optimisation routine. We use the Monte Carlo radiative transfer code SKIRT to calculate a self-consistent, panchromatic model of the interstellar radiation field. By looking at different stellar populations independently, we can quantify to what extent different stellar age populations contribute to the dust heating. Our method takes into account the effects of non-local heating. Results. We obtain a realistic 3D radiative transfer model of the face-on galaxy M 81. We find that only 50.2% of the dust heating can be attributed to young stellar populations ( 100 Myr). We confirm a tight correlation between the specific star formation rate and the heating fraction by young stellar populations, both in sky projection and in 3D, also found for radiative transfer models of M 31 and M 51. Conclusions. We conclude that the old stellar populations can be a major contributor to the heating of dust. In M 81, old stellar populations are the dominant heating agent in the central regions and they contribute to half of the absorbed radiation. Regions of higher star formation do not correspond to the highest dust temperatures. On the contrary, it is the dominant bulge which is most efficient in heating the dust. The approach we present here can immediately be applied to other galaxies. It does contain a number of caveats which are discussed in detail.