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1. The galactic dust-up: modelling dust evolution in FIRE

   https://doi.org/10.1093/mnras/stac1542  

   Choban, Caleb R.; Kereš, Dušan; Hopkins, Philip F.; Sandstrom, Karin M.; Hayward, Christopher C.; Faucher-Giguère, Claude-André (June 2022, Monthly Notices of the Royal Astronomical Society)

   ABSTRACT Recent strides have been made developing dust evolution models for galaxy formation simulations but these approaches vary in their assumptions and degree of complexity. Here, we introduce and compare two separate dust evolution models (labelled ‘Elemental’ and ‘Species’), based on recent approaches, incorporated into the gizmo code and coupled with fire-2 stellar feedback and interstellar medium physics. Both models account for turbulent dust diffusion, stellar production of dust, dust growth via gas-dust accretion, and dust destruction from time-resolved supernovae, thermal sputtering in hot gas, and astration. The ‘Elemental’ model tracks the evolution of generalized dust species and utilizes a simple, ‘tunable’ dust growth routine, while the ‘Species’ model tracks the evolution of specific dust species with set chemical compositions and incorporates a physically motivated, two-phase dust growth routine. We test and compare these models in an idealized Milky Way-mass galaxy and find that while both produce reasonable galaxy-integrated dust-to-metals (D/Z) ratios and predict gas-dust accretion as the main dust growth mechanism, a chemically motivated model is needed to reproduce the observed scaling relation between individual element depletions and D/Z with column density and local gas density. We also find the inclusion of theoretical metallic iron and O-bearing dust species are needed in the case of specific dust species in order to match observations of O and Fe depletions, and the integration of a sub-resolution dense molecular gas/CO scheme is needed to both match observed C depletions and ensure carbonaceous dust is not overproduced in dense environments. 

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2. Dust attenuation, dust emission, and dust temperature in galaxies at z ≥ 5: a view from the FIRE-2 simulations

   https://doi.org/10.1093/mnras/stz1324  

   Ma, Xiangcheng; Hayward, Christopher C; Casey, Caitlin M; Hopkins, Philip F; Quataert, Eliot; Liang, Lichen; Faucher-Giguère, Claude-André; Feldmann, Robert; Kereš, Dušan (May 2019, Monthly Notices of the Royal Astronomical Society)
3. Imprints of the Local Bubble and Dust Complexity on Polarized Dust Emission

   https://doi.org/10.3847/1538-4357/ad61e0  

   Halal, George; Clark, S_E; Tahani, Mehrnoosh (September 2024, The Astrophysical Journal)

   Abstract Using 3D dust maps and Planck polarized dust emission data, we investigate the influence of the 3D geometry of the nearby interstellar medium (ISM) on the statistics of the dust polarization on large ( $80\prime$) scales. We test recent models that assume that the magnetic field probed by the polarized dust emission is preferentially tangential to the Local Bubble wall, but we do not find an imprint of the Local Bubble geometry on the dust polarization fraction. We also test the hypothesis that the complexity of the 3D dust distribution drives some of the measured variation of the dust polarization fraction. We compare sight lines with similar total column densities and find that, on average, the dust polarization fraction decreases when the dust column is substantially distributed among multiple components at different distances. Conversely, the dust polarization fraction is higher for sight lines where the dust is more concentrated in 3D space. This finding is statistically significant for the dust within 1.25 kpc, but the effect disappears if we only consider dust within 270 pc. In conclusion, we find that the extended 3D dust distribution, rather than solely the dust associated with the Local Bubble, plays a role in determining the observed dust polarization fraction at 80′. This conclusion is consistent with a simple analytical prediction and remains robust under various modifications to the analysis. These results illuminate the relationship between the 3D geometry of the ISM and tracers of the interstellar magnetic field. We discuss implications for our understanding of the polarized dust foreground to the cosmic microwave background. 

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4. Single-scattering properties of ellipsoidal dust aerosols constrained by measured dust shape distributions

   https://doi.org/10.5194/acp-23-2557-2023  

   Huang, Yue; Kok, Jasper F; Saito, Masanori; Muñoz, Olga (January 2023, Atmospheric Chemistry and Physics)

   Abstract. Most global aerosol models approximate dust as sphericalparticles, whereas most remote sensing retrieval algorithms approximate dust as spheroidal particles with a shape distribution that conflicts withmeasurements. These inconsistent and inaccurate shape assumptions generatebiases in dust single-scattering properties. Here, we obtain dustsingle-scattering properties by approximating dust as triaxial ellipsoidalparticles with observationally constrained shape distributions. We findthat, relative to the ellipsoidal dust optics obtained here, the sphericaldust optics used in most aerosol models underestimate dust single-scattering albedo, mass extinction efficiency, and asymmetry parameter for almost all dust sizes in both the shortwave and longwave spectra. We further find that the ellipsoidal dust optics are in substantially better agreement with observations of the scattering matrix and linear depolarization ratio than the spheroidal dust optics used in most retrieval algorithms. However, relative to observations, the ellipsoidal dust optics overestimate the lidar ratio by underestimating the backscattering intensity by a factor of ∼2. This occurs largely because the computational method used to simulate ellipsoidal dust optics (i.e., the improved geometric optics method) underestimates the backscattering intensity by a factor of ∼2 relative to other computational methods (e.g., the physical geometric optics method). We conclude that the ellipsoidal dust optics with observationally constrained shape distributions can help improve global aerosol models and possibly remote sensing retrieval algorithms that do not use the backscattering signal. 

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5. Cleaning our own dust: simulating and separating galactic dust foregrounds with neural networks

   https://doi.org/10.1093/mnras/staa3344  

   Aylor, K; Haq, M; Knox, L; Hezaveh, Y; Perreault-Levasseur, L (December 2020, Monthly Notices of the Royal Astronomical Society)

   null (Ed.)

   ABSTRACT Separating galactic foreground emission from maps of the cosmic microwave background (CMB) and quantifying the uncertainty in the CMB maps due to errors in foreground separation are important for avoiding biases in scientific conclusions. Our ability to quantify such uncertainty is limited by our lack of a model for the statistical distribution of the foreground emission. Here, we use a deep convolutional generative adversarial network (DCGAN) to create an effective non-Gaussian statistical model for intensity of emission by interstellar dust. For training data we use a set of dust maps inferred from observations by the Planck satellite. A DCGAN is uniquely suited for such unsupervised learning tasks as it can learn to model a complex non-Gaussian distribution directly from examples. We then use these simulations to train a second neural network to estimate the underlying CMB signal from dust-contaminated maps. We discuss other potential uses for the trained DCGAN, and the generalization to polarized emission from both dust and synchrotron. 

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