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Andy McDonough is a freelance writer, photographer, educator, and consultant with more than 20 years of experience in production technology, arts and entertainment, computers and communications, ecology, and education.
Context. Dust is formed out of stellar material and it is constantly affected by different mechanisms occurring in the interstellar medium. Depending on their size, the behaviour of dust grains vary under these mechanisms and, therefore, the dust grain size distribution evolves as part of the dust evolution itself. Following how the grain size distribution evolves is a difficult computing task that has only recently become the subject of consideration. Smoothed particle hydrodynamic (SPH) simulations of a single galaxy, together with cosmological simulations, are producing the first predictions of the evolution of dust grain size distribution.
Aims. We compare, for the first time, the evolution of the dust grain size distribution as predicted by SPH simulations and results from observations. We are able to validate not only the predictions of the evolution of the small-to-large grain mass ratio (DS/DL) within a galaxy, but we also provide observational constraints for recent cosmological simulations that include the grain size distribution in the dust evolution framework.
Methods. We selected a sample of three spiral galaxies with different masses: M 101, NGC 628, and M 33. We fitted the dust spectral energy distribution across the disc of each object and derived the abundance of the different grain types included in the dust model. We analysed how the radial distribution of the relative abundance of the different grain size populations changes over the whole disc within each galaxy. The DS/DL ratio as a function of the galactocentric distance and metallicity is directly compared to what has been predicted by the SPH simulations.
Results. We find a good agreement between the observed radial distribution of DS/DL and what was obtained from the SPH simulations of a single galaxy. The comparison agrees with the expected evolutionary stage of each galaxy. We show that the central parts of NGC 628 at a high metallicity and with a high molecular gas fraction are mainly affected not only by accretion, but also by the coagulation of dust grains. The centre of M 33, having a lower metallicity and lower molecular gas fraction, presents an increase in the DS/DL ratio, demonstrating that shattering is very effective for creating a large fraction of small grains. Finally, the observational results provided by our galaxies confirm the general relations predicted by the cosmological simulations based on the two-grain size approximation. However, we also present evidence that the simulations could be overestimating the amount of large grains in high massive galaxies.
The physical properties of dust are directly linked to those of the given interstellar medium (ISM) in which it is found. The dust is not only heated by the interstellar radiation field (ISRF) but it is also affected by other mechanisms at play in the ISM, which can lead to a change in its physical properties and even the destruction of a particular dust grain type. The following processes dominate the evolution of the dust content and the grain size distribution (Hirashita 2015): (i) dust stellar production; (ii) dust destruction by supernova (SN) shocks in the ISM via sputtering; (iii) grain growth via accretion of metals in the gas phase and (iv) coagulation1; as well as (v) grain disruption or fragmentation (shattering). All these processes impact large and small grains differently: (i) supernovae (SNe) and asymptotic giant branch (AGB) stars are predicted to supply mostly large grains2 (Nozawa et al. 2007; Ventura et al. 2012; Bevan et al. 2017; Gall et al. 2014; Priestley et al. 2019); (ii) dust destruction by sputtering affect both large and small grains, with thermal sputtering in SN shocks mostly affecting smaller grains and non-thermal sputtering affecting large grains (Hu et al. 2019); (iii) grain growth via accretion is favoured when the number of small grains is large, as small grains have a larger surface-to-volume ratio (Hirashita 2012); (iv) grain growth via coagulation occurs in the dense ISM and moves the grain size distribution towards larger grain sizes (Ormel et al. 2009); and (v) fragmentation associated with shattering creates a large number of small grains (Jones et al. 1996).
Modelling the evolution of each dust grain with a particular size is a very expensive computing task. Hirashita (2015) proposes a two-size approximation of the grain size distribution that alleviates the computing cost while retaining a description of the main features of the evolution of the grain size distribution (see also Aoyama et al. (2020) and Hirashita & Aoyama (2019) for a recent analysis, including a more sophisticated functional form of the grain size distribution). This approach has been very recently applied to cosmological simulations, leading to a breakthrough in the field (Aoyama et al. 2017, 2018; McKinnon et al. 2018; Hirashita & Aoyama 2019; Hou et al. 2017, 2019; Gjergo et al. 2018). Aoyama et al. (2020) have been able to follow the full dust grain size distribution for a single galaxy and have confirmed the results provided by the two grain size approximation. Snapshots of the simulations at young ages seems to explain the extinction curves in high-redshift quasars (Hou et al. 2017). These SPH simulations need to be confronted by observational data, but so far no observational constrains have been available. Comparing the results from the simulations with the observations presented here will allow us to test the assumptions adopted in the simulations.
In Sect. 2, we present the data and fitting technique applied to the observations. The results of the fitting across the disc of our three galaxy sample is compared with the SPH simulations of a single galaxy in Sect. 3. In Sect. 4, we compare the predictions of cosmological simulations with the results from fitting the integrated spectral energy distributions (SEDs) of a large sample of galaxies. We discuss the main agreements and disagreements between the observations and simulations in Sect. 5. Conclusions are presented in Sect. 6.
In this study, we analyse the data in two different ways: one based on a spatially resolved analysis for three individual galaxies and the other based on an analysis of the integrated SED of a sample of galaxies. The first approach allows us to study how the relative contributions of the different grain types changes with metallicity and radius within the galactic disc; the second approach provides information about the relative grain size distributions of galaxies as a whole and, therefore, it is useful when comparing the results of the evolution of the grain size distribution in a cosmological volume. In this last approach, we have included galaxies from two different surveys in order to cover a wide range of morphological types, along with other physical properties of galaxies, such as metallicity, mass, and star formation rate (SFR).
We used infrared data from the KINGFISH collaboration (Kennicutt et al. 2011) for M 101 and NGC 628 and from HerM33es (Kramer et al. 2010) for M 33 to derive dust mass maps over the discs of these galaxies. We fit the infrared spectral energy distributions from 3.6 μm to 500 μm at each location of the disc of these spiral galaxies on a pixel-by-pixel basis. We take only those pixels with reliable SEDs, that is, pixels with fluxes in all bands from 3.6 μm to 500 μm with values over three times the standard deviation of the background value in each filter. We applied another mask to cover a wide area of the disc with diffuse and star-forming regions while avoiding low surface brightness areas that would lead to unreliable fits.
We used the classical Desert et al. (1990) dust model, which consists of three different grain populations: polycyclic aromatic hydrocarbons (PAHs), VSGs, and big silicate grains (BGs), and assumed an ISRF with the shape as the solar neighbourhood given in Mathis et al. (1983). The fitting procedure uses a Bayesian approach (see Fig. 1 for a schematic representation of the procedure). We first created a library of models with different values of the input parameters, covering a wide range of possible solutions for each galaxy. Convolution of the modelled SEDs with the corresponding filter bandpass of our observations allows us to obtain the fluxes in each band for each model in the library. With the observed and modelled fluxes, we computed the χ2 value associated to each model. We then built up the probability density function to obtain the best parameter value and its uncertainty. The fitting procedure gives us not only the dust mass but also the relative mass fraction for each grain type, as well as the scale factor of the ISRF. With this information, we created maps of the dust abundance for each grain type across the discs of our three-galaxy sample. Using HI and CO observations, we also produced gas-to-dust mass ratio maps of the disc of each individual galaxy. A detailed explanation of the fitting procedure and the derivation of the gas-to-dust mass ratio maps is presented in Vlchez et al. (2019) for M 101 and NGC 628 and Relao et al. (2018) for M 33.
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