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We build a rigorous statistical framework to provide constraints on the chemical and dust evolution parameters for nearby late-type galaxies with a wide range of gas fractions ($3%<f_g<94%$). A Bayesian Monte Carlo Markov Chain framework provides statistical constraints on the parameters used in chemical evolution models. Nearly a million one-zone chemical and dust evolution models were compared to 340 galaxies. Relative probabilities were calculated from the $chi^2$ between data and models, marginalised over the different time steps, galaxy masses and star formation histories. We applied this method to find `best fitting model parameters related to metallicity, and subsequently fix these metal parameters to study the dust parameters. For the metal parameters, a degeneracy was found between the choice of initial mass function, supernova metal yield tables and outflow prescription. For the dust parameters, the uncertainties on the best fit values are often large except for the fraction of metals available for grain growth, which is well constrained. We find a number of degeneracies between the dust parameters, limiting our ability to discriminate between chemical models using observations only. For example, we show that the low dust content of low-metallicity galaxies can be resolved by either reducing the supernova dust yields and/or including photo-fragmentation. We also show that supernova dust dominates the dust mass for low metallicity galaxies and grain growth dominates for high metallicity galaxies. The transition occurs around $12+log({rm O/H})=7.75$, which is lower than found in most studies in the literature.
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We study the dust properties of 192 nearby galaxies from the JINGLE survey using photometric data in the 22-850micron range. We derive the total dust mass, temperature T and emissivity index beta of the galaxies through the fitting of their spectral energy distribution (SED) using a single modified black-body model (SMBB). We apply a hierarchical Bayesian approach that reduces the known degeneracy between T and beta. Applying the hierarchical approach, the strength of the T-beta anti-correlation is reduced from a Pearson correlation coefficient R=-0.79 to R=-0.52. For the JINGLE galaxies we measure dust temperatures in the range 17-30 K and dust emissivity indices beta in the range 0.6-2.2. We compare the SMBB model with the broken emissivity modified black-body (BMBB) and the two modified black-bodies (TMBB) models. The results derived with the SMBB and TMBB are in good agreement, thus applying the SMBB, which comes with fewer free parameters, does not penalize the measurement of the cold dust properties in the JINGLE sample. We investigate the relation between T and beta and other global galaxy properties in the JINGLE and Herschel Reference Survey (HRS) sample. We find that beta correlates with the stellar mass surface density (R=0.62) and anti-correlates with the HI mass fraction (M(HI)/M*, R=-0.65), whereas the dust temperature correlates strongly with the SFR normalized by the dust mass (R=0.73). These relations can be used to estimate T and beta in galaxies with insufficient photometric data available to measure them directly through SED fitting.
Estimating the temperature and mass of dust in high-$z$ galaxies is essential for discussions of the origin of dust in the early Universe. However, this suffers from limited sampling of the infrared spectral-energy distribution. Here we present an algorithm for deriving the temperature and mass of dust in a galaxy, assuming dust to be in radiative equilibrium. We formulate the algorithm for three geometries: a thin spherical shell, a homogeneous sphere, and a clumpy sphere. We also discuss effects of the mass absorption coefficients of dust at ultraviolet and infrared wavelengths, $kappa_{rm UV}$ and $kappa_{rm IR}$, respectively. As an example, we apply the algorithm to a normal, dusty star-forming galaxy at $z=7.5$, A1689zD1, for which three data points in the dust continuum are available. Using $kappa_{rm UV}=5.0times10^4$ cm$^2$ g$^{-1}$ and $kappa_{rm IR}=30(lambda/100mu m)^{-beta}$ cm$^2$ g$^{-1}$ with $beta=2.0$, we obtain dust temperatures of 38--70~K and masses of $10^{6.5-7.3}$ M$_odot$ for the three geometries considered. We obtain similar temperatures and masses from just a single data point in the dust continuum, suggesting the usefulness of the algorithm for high-$z$ galaxies with limited infrared observations. In the clumpy-sphere case, the temperature becomes equal to that of the usual modified black-body fit, because an additional parameter describing the clumpiness works as an adjuster. The best-fit clumpiness parameter is $xi_{rm cl}=0.1$, corresponding to $sim10$% of the volume filling factor of the clumps in this high-$z$ galaxy if the clump size is $sim10$ pc, similar to that of giant molecular clouds in the local Universe.
We aim to characterize the relationship between dust properties. We also aim to provide equations to estimate accurate dust properties from limited observational datasets. We assemble a sample of 1,630 nearby (z<0.1) galaxies-over a large range of Mstar, SFR - with multi-wavelength observations available from wise, iras, planck and/or SCUBA. The characterization of dust emission comes from SED fitting using Draine & Li dust models, which we parametrize using two components (warm and cold ). The subsample of these galaxies with global measurements of CO and/or HI are used to explore the molecular and/or atomic gas content of the galaxies. The total Lir, Mdust and dust temperature of the cold component (Tc) form a plane that we refer to as the dust plane. A galaxys sSFR drives its position on the dust plane: starburst galaxies show higher Lir, Mdust and Tc compared to Main Sequence and passive galaxies. Starburst galaxies also show higher specific Mdust (Mdust/Mstar) and specific Mgas (Mgas/Mstar). The Mdust is more closely correlated with the total Mgas (atomic plus molecular) than with the individual components. Our multi wavelength data allows us to define several equations to estimate Lir, Mdust and Tc from one or two monochromatic luminosities in the infrared and/or sub-millimeter. We estimate the dust mass and infrared luminosity from a single monochromatic luminosity within the R-J tail of the dust emission, with errors of 0.12 and 0.20dex, respectively. These errors are reduced to 0.05 and 0.10 dex, respectively, if the Tc is used. The Mdust is correlated with the total Mism (Mism propto Mdust^0.7). For galaxies with Mstar 8.5<log(Mstar/Msun) < 11.9, the conversion factor alpha_850mum shows a large scatter (rms=0.29dex). The SF mode of a galaxy shows a correlation with both the Mgass and Mdust: high Mdust/Mstar galaxies are gas-rich and show the highest SFRs.
Aims: Mapping the interstellar medium in 3D provides a wealth of insights into its inner working. The Milky Way is the only galaxy for which detailed 3D mapping can be achieved in principle. In this paper, we reconstruct the dust density in and around the local super-bubble. Methods: The combined data from surveys such as Gaia, 2MASS, PANSTARRS, and ALLWISE provide the necessary information to make detailed maps of the interstellar medium in our surrounding. To this end, we used variational inference and Gaussian processes to model the dust extinction density, exploiting its intrinsic correlations. Results: We reconstructed a highly resolved dust map, showing the nearest dust clouds at a distance of up to 400pc with a resolution of 1pc. Conclusions: Our reconstruction provides insights into the structure of the interstellar medium. We compute summary statistics of the spectral index and the 1-point function of the logarithmic dust extinction density, which may constrain simulations of the interstellar medium that achieve a similar resolution.
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.
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