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The cosmic spectral energy distribution (CSED) is the total emissivity as a function of wavelength of galaxies in a given cosmic volume. We compare the observed CSED from the UV to the submm to that computed from the EAGLE cosmological hydrodynamical simulation, post-processed with stellar population synthesis models and including dust radiative transfer using the SKIRT code. The agreement with the data is better than 0.15 dex over the entire wavelength range at redshift $z=0$, except at UV wavelengths where the EAGLE model overestimates the observed CSED by up to a factor 2. Global properties of the CSED as inferred from CIGALE fits, such as the stellar mass density, mean star formation density, and mean dust-to-stellar-mass ratio, agree to within better than 20 per cent. At higher redshift, EAGLE increasingly underestimates the CSED at optical-NIR wavelengths with the FIR/submm emissivity underestimated by more than a factor of 5 by redshift $z=1$. We believe that these differences are due to a combination of incompleteness of the EAGLE-SKIRT database, the small simulation volume and the consequent lack of luminous galaxies, and our lack of knowledge on the evolution of the characteristics of the interstellar dust in galaxies. The impressive agreement between the simulated and observed CSED at lower $z$ confirms that the combination of EAGLE and SKIRT dust processing yields a fairly realistic representation of the local Universe., 14 pages, 5 figures, accepted for publication in MNRAS

Methods. We have modelled a sample of ~800 nearby galaxies, spanning a wide range of metallicity, gas fraction, specific star formation rate and Hubble stage. We have derived the dust properties of each object from its spectral energy distribution. Through an additional level of analysis, we have inferred the timescales of dust condensation in core-collapse supernova ejecta, grain growth in cold clouds and dust destruction by shock waves. Throughout this paper, we have adopted a hierarchical Bayesian approach, resulting in a single large probability distribution of all the parameters of all the galaxies, to ensure the most rigorous interpretation of our data. Results. We confirm the drastic evolution with metallicity of the dust-to-metal mass ratio (by two orders of magnitude), found by previous studies. We show that dust production by core-collapse supernovae is efficient only at very low-metallicity, a single supernova producing on average less than ~0.03 Msun/SN of dust. Our data indicate that grain growth is the dominant formation mechanism at metallicity above ~1/5 solar, with a grain growth timescale shorter than ~50 Myr at solar metallicity. Shock destruction is relatively efficient, a single supernova clearing dust on average in at least ~1200 Msun/SN of gas. These results are robust when assuming different stellar initial mass functions. In addition, we show that early-type galaxies are outliers in several scaling relations. This feature could result from grain thermal sputtering in hot X-ray emitting gas, an hypothesis supported by a negative correlation between the dust-to-stellar mass ratio and the X-ray photon rate per grain. Finally, we confirm the well-known evolution of the aromatic-feature-emitting grain mass fraction as a function of metallicity and interstellar radiation field intensity. Our data indicate the relation with metallicity is significantly stronger., Comment: 64 pages, 36 figures, accepted for publication in Astronomy & Astrophysics

International audience; ABSTRACT The objective of this paper is to understand the variance of the far-infrared (FIR) spectral energy distribution (SED) of the DustPedia galaxies, and its link with the stellar and dust properties. An interesting aspect of the dust emission is the inferred FIR colours which could inform us about the dust content of galaxies, and how it varies with the physical conditions within galaxies. However, the inherent complexity of dust grains as well as the variety of physical properties depending on dust, hinder our ability to utilize their maximum potential. We use principal component analysis (PCA) to explore new hidden correlations with many relevant physical properties such as the dust luminosity, dust temperature, dust mass, bolometric luminosity, star formation rate (SFR), stellar mass, specific SFR, dust-to-stellar mass ratio, the fraction of absorbed stellar luminosity by dust (fabs), and metallicity. We find that 95 per cent of the variance in our sample can be described by two principal components (PCs). The first component controls the wavelength of the peak of the SED, while the second characterizes the width. The physical quantities that correlate better with the coefficients of the first two PCs, and thus control the shape of the FIR SED are the dust temperature, the dust luminosity, the SFR, and fabs. Finally, we find a weak tendency for low-metallicity galaxies to have warmer and broader SEDs, while on the other hand high-metallicity galaxies have FIR SEDs that are colder and narrower.

The ultraviolet (UV) to sub-millimetre (submm) spectral energy distribution of galaxies can be roughly divided into two sections: the stellar emission (attenuated by dust) at UV to near-infrared wavelengths and dust emission at longer wavelengths. In Dobbels et al. (2020), we show that these two sections are strongly related, and we can predict the global dust properties from the integrated UV to mid-infrared emission with the help of machine learning techniques. We investigate if these machine learning techniques can also be extended to resolved scales. Our aim is to predict resolved maps of the specific dust luminosity, specific dust mass, and dust temperature starting from a set of surface brightness images from UV to mid-infrared wavelengths. We used a selection of nearby galaxies retrieved from the DustPedia sample, in addition to M31 and M33. These were convolved and resampled to a range of pixel sizes, ranging from 150 pc to 3 kpc. We trained a random forest model which considers each pixel individually. We find that the predictions work well on resolved scales, with the dust mass and temperature having a similar root mean square error as on global scales (0.32 dex and 3.15 K on 18" scales respectively), and the dust luminosity being noticeably better (0.11 dex). We find no significant dependence on the pixel scale. Predictions on individual galaxies can be biased, and we find that about two-thirds of the scatter can be attributed to scatter between galaxies (rather than within galaxies). A machine learning approach can be used to create dust maps, with its resolution being only limited to the input bands, thus achieving a higher resolution than Herschel. These dust maps can be used to improve global estimates of dust properties, they can lead to a better estimate of dust attenuation, and they can be used as a constraint on cosmological simulations that trace dust., Comment: 16 pages, 13 figures, accepted by A&A

We present the first nonparametric morphological analysis of a set of spiral galaxies from UV to submm wavelengths. Our study is based on high-quality multi-wavelength imaging for nine well-resolved spiral galaxies from the DustPedia database, combined with nonparametric morphology indicators calculated in a consistent way using the {\tt{StatMorph}} package. We measure the half-light radius, the concentration index, the asymmetry index, the smoothness index, the Gini coefficient and the $M_{20}$ indicator in various wavebands from UV to submm wavelengths, as well as in stellar mass, dust mass and star formation rate maps. We find that the interstellar dust in galaxies is distributed in a more extended, less centrally concentrated, more asymmetric, and more clumpy way than the stars. This is particularly evident when comparing morphological indicators based on the stellar mass and dust mass maps. This should serve as a warning sign against treating the dust in galaxies as a simple smooth component. We argue that the nonparametric galaxy morphology of galaxies from UV to submm wavelengths is an interesting test for cosmological hydrodynamics simulations., 9 pages, 5 figures, accepted for publication in A&A

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. We aim to constrain the relative distribution of dust and stellar populations in the spiral galaxy M81 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. 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. We obtain a realistic 3D radiative transfer model of the face-on galaxy M81. We find that only 50.2\% of the dust heating can be attributed to young stellar populations. 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 M31 and M51. We conclude that... (abridged), 23 pages, 16 figures, accepted for publication in A&A

Context. Investigating the dust heating mechanisms in galaxies provides a deeper understanding of how the internal energy balance drives their evolution. Over the last decade radiative transfer simulations based on the Monte Carlo method have emphasised the role of the various stellar populations heating the diffuse dust. Beyond the expected heating through ongoing star formation, older stellar populations (≥8 Gyr) and even active galactic nuclei can both contribute energy to the infrared emission of diffuse dust. Aims. In this particular study we examine how the radiation of an external heating source, such as the less massive galaxy NGC 5195 in the M 51 interacting system, could affect the heating of the diffuse dust of its parent galaxy NGC 5194, and vice versa. Our goal is to quantify the exchange of energy between the two galaxies by mapping the 3D distribution of their radiation field. Methods. We used SKIRT, a state-of-the-art 3D Monte Carlo radiative transfer code, to construct the 3D model of the radiation field of M 51, following the methodology defined in the DustPedia framework. In the interest of modelling, the assumed centre-to-centre distance separation between the two galaxies is ∼10 kpc. Results. Our model is able to reproduce the global spectral energy distribution of the system, and it matches the resolved optical and infrared images fairly well. In total, 40.7% of the intrinsic stellar radiation of the combined system is absorbed by dust. Furthermore, we quantify the contribution of the various dust heating sources in the system, and find that the young stellar population of NGC 5194 is the predominant dust-heating agent, with a global heating fraction of 71.2%. Another 23% is provided by the older stellar population of the same galaxy, while the remaining 5.8% has its origin in NGC 5195. Locally, we find that the regions of NGC 5194 closer to NGC 5195 are significantly affected by the radiation field of the latter, with the absorbed energy fraction rising up to 38%. The contribution of NGC 5195 remains under the percentage level in the outskirts of the disc of NGC 5194. This is the first time that the heating of the diffuse dust by a companion galaxy is quantified in a nearby interacting system.

Context. Dust in late-type galaxies in the local Universe is responsible for absorbing approximately one third of the energy emitted by stars. It is often assumed that dust heating is mainly attributable to the absorption of ultraviolet and optical photons emitted by the youngest (≤100 Myr) stars. Consequently, thermal re-emission by dust at far-infrared wavelengths is often linked to the star-formation activity of a galaxy. However, several studies argue that the contribution to dust heating by much older stellar populations might be more significant than previously thought. Advances in radiation transfer simulations finally allow us to actually quantify the heating mechanisms of diffuse dust by the stellar radiation field. Aims. As one of the main goals in the DustPedia project, we have developed a framework to construct detailed 3D stellar and dust radiative transfer models for nearby galaxies. In this study, we analyse the contribution of the different stellar populations to the dust heating in four nearby face-on barred galaxies: NGC 1365, M 83, M 95, and M 100. We aim to quantify the fraction directly related to young stellar populations, both globally and on local scales, and to assess the influence of the bar on the heating fraction. Methods. From 2D images we derive the 3D distributions of stars and dust. To model the complex geometries, we used SKIRT, a state-of-the-art 3D Monte Carlo radiative transfer code designed to self-consistently simulate the absorption, scattering, and thermal re-emission by the dust for arbitrary 3D distributions. Results. We derive global attenuation laws for each galaxy and confirm that galaxies of high specific star-formation rate have shallower attenuation curves and weaker UV bumps. On average, 36.5% of the bolometric luminosity is absorbed by dust in our galaxy sample. We report a clear effect of the bar structure on the radial profiles of the dust-heating fraction by the young stellar populations, and the dust temperature. We find that the young stellar populations are the main contributors to the dust heating, donating, on average ∼59% of their luminosity to this purpose throughout the galaxy. This dust-heating fraction drops to ∼53% in the bar region and ∼38% in the bulge region where the old stars are the dominant contributors to the dust heating. We also find a strong link between the heating fraction by the young stellar populations and the specific star-formation rate.

Dust emission, an important diagnostic of star formation and ISM mass throughout the Universe, can be powered by sources unrelated to ongoing star formation. In the framework of the DustPedia project we have set out to disentangle the radiation of the ongoing star formation from that of the older stellar populations. This is done through detailed, 3D radiative transfer simulations of face-on spiral galaxies. In this particular study, we focus on NGC 1068, which contains an active galactic nucleus (AGN). The effect of diffuse dust heating by AGN (beyond the torus) was so far only investigated for quasars. This additional dust heating source further contaminates the broadband fluxes on which classic galaxy modelling tools rely to derive physical properties. We aim to fit a realistic model to the observations of NGC 1068 and quantify the contribution of the several dust heating sources. Our model is able to reproduce the global spectral energy distribution of the galaxy. It matches the resolved optical and infrared images fairly well, but deviates in the UV and the submm. We find a strong wavelength dependency of AGN contamination to the broadband fluxes. It peaks in the MIR, drops in the FIR, but rises again at submm wavelengths. We quantify the contribution of the dust heating sources in each 3D dust cell and find a median value of 83% for the star formation component. The AGN contribution is measurable at the percentage level in the disc, but quickly increases in the inner few 100 pc, peaking above 90%. This is the first time the phenomenon of an AGN heating the diffuse dust beyond its torus is quantified in a nearby star-forming galaxy. NGC 1068 only contains a weak AGN, meaning this effect can be stronger in galaxies with a more luminous AGN. This could significantly impact the derived star formation rates and ISM masses for such systems., Comment: 18 pages, 11 figures, accepted for publication in A&A

Dust plays an important role in shaping a galaxy's spectral energy distribution (SED). It absorbs ultraviolet (UV) to near-infrared (NIR) radiation and re-emits this energy in the far-infrared (FIR). The FIR is essential to understand dust in galaxies. However, deep FIR observations require a space mission, none of which are still active today. We aim to infer the FIR emission across six Herschel bands, along with dust luminosity, mass, and effective temperature, based on the available UV to mid-infrared (MIR) observations. We also want to estimate the uncertainties of these predictions, compare our method to energy balance SED fitting, and determine possible limitations of the model. We propose a machine learning framework to predict the FIR fluxes from 14 UV-MIR broadband fluxes. We used a low redshift sample by combining DustPedia and H-ATLAS, and extracted Bayesian flux posteriors through SED fitting. We trained shallow neural networks to predict the far-infrared fluxes, uncertainties, and dust properties. We evaluated them on a test set using a root mean square error (RMSE) in log-space. Our results (RMSE = 0.19 dex) significantly outperform UV-MIR energy balance SED fitting (RMSE = 0.38 dex), and are inherently unbiased. We can identify when the predictions are off, for example when the input has large uncertainties on WISE 22, or when the input does not resemble the training set. The galaxies for which we have UV-FIR observations can be used as a blueprint for galaxies that lack FIR data. This results in a 'virtual FIR telescope', which can be applied to large optical-MIR galaxy samples. This helps bridge the gap until the next FIR mission., 25 pages, 16 figures, accepted by A&A. Interactive figures + jupyter notebooks at https://wdobbels.github.io/FIREnet/

The dust mass absorption coefficient, $\kappa_{d}$, is the conversion function used to infer physical dust masses from observations of dust emission. However, it is notoriously poorly constrained, and it is highly uncertain how it varies, either between or within galaxies. Here we present the results of a proof-of concept study, using the DustPedia data for two nearby face-on spiral galaxies M74 (NGC 628) and M83 (NGC 5236), to create the first ever maps of $\kappa_{d}$ in galaxies. We determine $\kappa_{d}$ using an empirical method that exploits the fact that the dust-to-metals ratio of the interstellar medium is constrained by direct measurements of the depletion of gas-phase metals. We apply this method pixel-by-pixel within M74 and M83, to create maps of $\kappa_{d}$. We also demonstrate a novel method of producing metallicity maps for galaxies with irregularly-sampled measurements, using the machine learning technique of Gaussian process regression. We find strong evidence for significant variation in $\kappa_{d}$. We find values of $\kappa_{d}$ at 500 $\mu$m spanning the range 0.11-0.25 ${\rm m^{2}\,kg^{-1}}$ in M74, and 0.15-0.80 ${\rm m^{2}\,kg^{-1}}$ in M83. Surprisingly, we find that $\kappa_{d}$ shows a distinct inverse correlation with the local density of the interstellar medium. This inverse correlation is the opposite of what is predicted by standard dust models. However, we find this relationship to be robust against a large range of changes to our method - only the adoption of unphysical or highly unusual assumptions would be able to suppress it., Comment: Corrected typographical error in Equation A1, as per erratum accepted by MNRAS on 20th April 2022. No results or conclusions effected by the error, or by this correction

Aims: We compare the far-infrared to sub-millimetre dust emission properties measured in high Galactic latitude cirrus with those determined in a sample of 204 late-type DustPedia galaxies. The aim is to verify if it is appropriate to use Milky Way dust properties to derive dust masses in external galaxies. Methods: We used Herschel observations and atomic and molecular gas masses to estimate the disc-averaged dust emissivity at 250 micrometres, and from this, the absorption cross section per H atom and per dust mass. The emissivity requires one assumption, which is the CO-to-H_2 conversion factor, and the dust temperature is additionally required for the absorption cross section per H atom; yet another constraint on the dust-to-hydrogen ratio D/H, depending on metallicity, is required for the absorption cross section dust mass. Results: We find epsilon(250) = 0.82 +/- 0.07 MJy sr^-1 (1E20 H cm^-2)^-1 for galaxies with 4 < F(250)/F(500) < 5. This depends only weakly on the adopted CO-to-H_2 conversion factor. The value is almost the same as that for the Milky Way at the same colour ratio. Instead, for F(250)/F(500) > 6, epsilon(250) is lower than predicted by its dependence on the heating conditions. The reduction suggests a variation in dust emission properties for spirals of earlier type, higher metallicity, and with a higher fraction of molecular gas. When the standard emission properties of Galactic cirrus are used for these galaxies, their dust masses might be underestimated by up to a factor of two. Values for the absorption cross sections at the Milky Way metallicity are also close to those of the cirrus. Mild trends of the absorption cross sections with metallicity are found, although the results depend on the assumptions made., 13 pages, 6 figures, 2 tables, A&A accepted

One of the most important properties of a galaxy is the total stellar mass, or equivalently the stellar mass-to-light ratio (M/L). It is not directly observable, but can be estimated from stellar population synthesis. Currently, a galaxy's M/L is typically estimated from global fluxes. For example, a single global g - i colour correlates well with the stellar M/L. Spectral energy distribution (SED) fitting can make use of all available fluxes and their errors to make a Bayesian estimate of the M/L. We want to investigate the possibility of using morphology information to assist predictions of M/L. Our first goal is to develop and train a method that only requires a g-band image and redshift as input. This will allows us to study the correlation between M/L and morphology. Next, we can also include the i-band flux, and determine if morphology provides additional constraints compared to a method that only uses g- and i-band fluxes. We used a machine learning pipeline that can be split in two steps. First, we detected morphology features with a convolutional neural network. These are then combined with redshift, pixel size and g-band luminosity features in a gradient boosting machine. Our training target was the M/L acquired from the GALEX-SDSS-WISE Legacy Catalog, which uses global SED fitting and contains galaxies with z ~ 0.1. Morphology is a useful attribute when no colour information is available, but can not outperform colour methods on its own. When we combine the morphology features with global g- and i-band luminosities, we find an improved estimate compared to a model which does not make use of morphology. While our method was trained to reproduce global SED fitted M/L, galaxy morphology gives us an important additional constraint when using one or two bands. Our framework can be extended to other problems to make use of morphological information., 17 pages, 8 figures, accepted by A&A

We study the fraction of stellar radiation absorbed by dust, f_abs, in 814 galaxies of different morphological types. The targets constitute the vast majority (93%) of the DustPedia sample, including almost all large (optical diameter larger than 1'), nearby (v, 21 pages, 14 figures, A&A accepted. Template SEDs available at the DustPedia Archive: http://dustpedia.astro.noa.gr/