Simulating the dust content of galaxies: successes and failures

McKinnon, R.; Torrey, Paul; Vogelsberger, Mark; Hayward, Christopher C.; Marinacci, Federico

doi:10.1093/mnras/stx467

Cited by 155 publications

(198 citation statements)

References 166 publications

(321 reference statements)

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“…Other physics: Additional physical processes considered in some cosmological simulations of galaxy formation are, for example, dust physics [265][266][267][268][269][270][271][272][273] , thermal conduction 188,225,[274][275][276][277][278] , and viscosity [279][280][281][282] . Dust has typically been neglected in galaxy formation simulations since it contributes only about ∼ 1% to the mass budget of the interstellar medium.…”

Section: Radiation Hydrodynamics Equationsmentioning

confidence: 99%

Cosmological simulations of galaxy formation

et al. 2020

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Over the last decades, cosmological simulations of galaxy formation have been instrumental for advancing our understanding of structure and galaxy formation in the Universe. These simulations follow the nonlinear evolution of galaxies modeling a variety of physical processes over an enormous range of scales. A better understanding of the physics relevant for shaping galaxies, improved numerical methods, and increased computing power have led to simulations that can reproduce a large number of observed galaxy properties. Modern simulations model dark matter, dark energy, and ordinary matter in an expanding space-time starting from well-defined initial conditions. The modeling of ordinary matter is most challenging due to the large array of physical processes affecting this matter component. Cosmological simulations have also proven useful to study alternative cosmological models and their impact on the galaxy population. This review presents a concise overview of the methodology of cosmological simulations of galaxy formation and their different applications. arXiv:1909.07976v4 [astro-ph.GA] 23 Oct 2019 become important for cosmological studies since they can, for example, explore the impact of alternative cosmological models on the galaxy population. Cosmological simulations of galaxy formation therefore provide important insights into a wide range of problems in astrophysics and cosmology. The most important components of cosmological galaxy formation simulations are discussed in this review. A schematic overview of the different ingredients of cosmological simulations is presented in Figure 2. Cosmological FrameworkCosmological simulations of galaxy formation are performed within a cosmological model and start from specific initial conditions. Both of these ingredients are now believed to be known to high precision. Cosmological ModelVarious observations revealed that our Universe is geometrically flat and dominated by dark matter and dark energy accounting for about ∼ 95% of the energy density. Standard model particles make up for the remaining ∼ 5% and are collectively referred to as baryons. The leading model for structure formation assumes that dark matter is cold, with negligible random motions when decoupled from other matter, and collisionless, so-called cold dark matter, and dark energy is represented by a cosmological constant Λ, which drives the accelerated expansion of the Universe. This leads to the concordance ΛCDM model, which builds the framework for galaxy formation. Measurements of the cosmic microwave background combined with other observations such as the distance-redshift relation from Type Ia supernovae, abundances of galaxy clusters, and galaxy clustering constrain the fundamental parameters of the ΛCDM model 3 . Initial ConditionsInitial conditions for cosmological simulations specify the perturbations imposed on top of a homogeneous expanding background. The background model is generally taken to be a spatially flat Friedmann-Lemaître-Robertson-Walker space-time with a defined compositio...

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Section: Radiation Hydrodynamics Equationsmentioning

confidence: 99%

Cosmological simulations of galaxy formation

et al. 2020

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“…Popping et al 2017). A disagreement on the sources of dust production is also present: Popping et al (2017), McKinnon et al (2017), Aoyama et al (2018), assume that SN Ia can produce dust, while the remaining models are more conservative and exclude these supernovae as dust producers. Finally, dustyGadget is the only code that explicitly accounts for the contribution of PISN at the highest redshifts.…”

Section: Reference Theoretical Models and Observationsmentioning

confidence: 99%

“…Green empty squares and black asterisks 12 In accordance with the WMAP-7 cosmology adopted in our simulation the cosmic critical density at z = 0 is ρ c,0 ≈ 2.775 × 10 11 M ⊙ h 2 cMpc −3 . are values at z 4 taken from Aoyama et al (2018) and McKinnon et al (2017), respectively.…”

Section: Cosmic Dust Density Parametermentioning

confidence: 99%

The assembly of dusty galaxies at z ≥ 4: statistical properties

Graziani

Schneider

Ginolfi

et al. 2020

Monthly Notices of the Royal Astronomical Society

104

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The recent discovery of high redshift dusty galaxies implies a rapid dust enrichment of their interstellar medium (ISM). To interpret these observations, we run a cosmological simulation in a 30h −1 cMpc/size volume down to z ≈ 4. We use the hydrodynamical code dustyGadget, which accounts for the production of dust by stellar populations and its evolution in the ISM. We find that the cosmic dust density parameter (Ω d ) is mainly driven by stellar dust at z 10, so that mass-and metallicity-dependent yields are required to assess the dust content in the first galaxies. At z 9 the growth of grains in the ISM of evolved systems (Log(M ⋆ /M ⊙ ) > 8.5) significantly increases their dust mass, in agreement with observations in the redshift range 4 z < 8. Our simulation shows that the variety of high redshift galaxies observed with ALMA can naturally be accounted for by modeling the grain-growth timescale as a function of the physical conditions in the gas cold phase. In addition, the trends of dust-to-metal (DTM) and dust-to-gas (D) ratios are compatible with the available data. A qualitative investigation of the inhomogeneous dust distribution in a representative massive halo at z ≈ 4 shows that dust is found from the central galaxy up to the closest satellites along polluted filaments with Log(D) −2.4, but sharply declines at distances d 30 kpc along many lines of sight, where Log(D) −4.0.

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“…As Khakhaleva-Li & Gnedin (2016) have noted, the details of dust production and destruction may have important implications for the UV and IR properties of simulated galaxies, especially in lowmetallicity galaxies at high redshift. It would thus be useful to perform an analysis similar to ours using simulations that include a detailed treatment of the relevant dust production and destruction channels (e.g., McKinnon et al 2016aMcKinnon et al , 2016b.…”

Section: Limitations and Future Workmentioning

confidence: 99%

The IRX–β Relation: Insights from Simulations

Safarzadeh

Hayward

Ferguson

2017

ApJ

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We study the relationship between the UV continuum slope and infrared excess ( º L L IRX IR FUV ) predicted by performing dust radiative transfer on a suite of hydrodynamical simulations of galaxies. Our suite includes both isolated disk galaxies and mergers intended to be representative of galaxies at bothz 0 and~-z 2 3. Our lowredshift systems often populate a region around the locally calibrated Meurer et al. relation but move above the relation during merger-induced starbursts. Our high-redshift systems are blue and IR luminous and therefore lie above the Meurer et al. relation. The value of β strongly depends on the dust type used in the RT simulation: Milky-Way-type dust leads to significantly more negative (bluer) slopes compared with Small-Magellanic-Cloudtype dust. The effect on β due to variations in the dust composition with galaxy properties or redshift is the dominant model uncertainty. The dispersion in β is anticorrelated with specific star formation rate (sSFR) and tends to be higher for the~-z 2 3 simulations. In the actively star-forming~-z 2 3 simulated galaxies, dust attenuation dominates the dispersion in β, whereas in thez 0 simulations, the contributions of star formation history (SFH) variations and dust are similar. For low-sSFR systems at both redshifts, SFH variations dominate the dispersion. Finally, the simulated~-z 2 3 isolated disks and mergers both occupy a region in the b -IRX plane consistent with observed~-z 2 3 dusty star-forming galaxies (DSFGs). Thus, contrary to some claims in the literature, the blue colors of high-z DSFGs do not imply that they are short-lived starbursts.

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Simulating the dust content of galaxies: successes and failures

Cited by 155 publications

References 166 publications

Cosmological simulations of galaxy formation

Cosmological simulations of galaxy formation

The assembly of dusty galaxies at z ≥ 4: statistical properties

The IRX–β Relation: Insights from Simulations

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