Dust Grain Models

Literature review and thoughts on dust grain models and modeling for ISM*@ST group.

Transcript

1. Dust Grain Models Karl D. Gordon Astronomer STScI, Baltimore, MD ISM*@ST Group Meeting 5 Oct 2020 kgordon@stsci.edu @karllark2000 karllark@github
2. Outline • Bare grain models • Coated grain models • Some thoughts • Not an exhaustive review – more illustrative
4. Bare Grain Models • Mathis, Rumpl, & Nordseik 1977 • Draine & Lee 1984 • Kim et al. 1994, 1995 • Weingartner & Draine 2001 • Clayton et al. 2003 • Zubko, Dwek, & Ardent 2004 • Draine & Li 2007 • Siebenmorgen et al. 2014
6. MRN • Has the elements of most grain models since 1977 • 6 materials – Graphite – Silicon carbide, SiC, Enstatite (Fe,Mg)SiO 3, Olivine (Fe,Mg) 2 SiO 4 – Iron, Magnetite Fe 3 O 4 • Grain shapes: spheres and infinite cylinders • Fit size distribution n(a) as 18 discrete bins from 0 to 1 micron • Constrained by UV/optical extinction and C, Si, Mg, Fe abundances • All fits require C, no strong constraints on the other material (only two components required by data) • Discuss polarization
7. Mathis, Rumpl, & Nordsieck (1977, ApJ, 217, 425)
8. Mathis, Rumpl, & Nordsieck (1977, ApJ, 217, 425)
10. Kim, Martin, & Hendry • 2 components – graphite and silicates – Later work: graphite and modified astronomical silicate • Grain shapes: spheres – Later work: oblate and prolate spheriods w/ a range of axial ratios • Fit mass distributions as 60 discrete bins – Use Maximum Entropy Method • Constrained by extinction, abundances, & (later work) polarization – consistent w/ scattering and IR emission)
14. Weingartner & Draine • 2 components • Grain shapes: spheres • Fit analytic size distributions • Constrained by extinction & abundances – MW, LMC, and SMC averages
19. Zubko, Dwek, & Arendt • 6 possible components – PAHs, graphite, 3 types of amorphous carbon – Silicates – Composites of silicates, organics, water ice, and voids • Grain shapes: spheres • Fit size distributions with discrete bins w/ regularization (smoothness) – Provide analytical fits to resulting distributions • Constrained by extinction, abundances, and IR emission • All models investigated fit the constraints used – additional constraints needed
23. Coated Grain Models • Greenberg et al. 1966, 1980, 1997 • Desert et al. 1990 • Jones et al. 2013 (and later)
25. Greenberg+ (Li) • 3 components – Large silicate core-organic refractory mantle – Very small carbonaceous particles – PAHs • Grain shapes: spheres and finite cylinders • Fit exponential size distributions • Constrained by UV-MIR extinction, polarization, and C, Si, Mg, Fe, O, & N abundances
29. Desert, Boulanger, & Puget • 3 components – Big silicate grains coated with carbonaceous material – PAH (molecules) – Very small grains of amorphous carbon • Grain shapes • Fit to powerlaw size distributions • Constrained by extinction & emission • Introduces “astronomical PAHs”
33. Jones, et al. • 3 components (families of grains – dust evolution model) – Amorphous carbon with size dependent properties – Amorphous silicates with amorphous carbon mantles – Coagulated carbonaceous/silicate grains • Grain shapes: spheres • Fit analytic size distributions (chi-by-eye?) • Constrained by extinction, abundances, emission, and albedo – Also explains trends seen in extinction characteristics
34. Coated Grains Model Jones et al. (2013)
36. Chiar et al. (2013, ApJ, 770, 78)
37. Some Thoughts
38. Geography Matters • Mostly Americans → Bare grains – Influence of Mathis? • Mostly Europeans → Coated grains – Influence of Greenberg?
39. Astrodust? • Draine & Hensley (2020, ApJ, submitted) • 3 components – Astrodust: composite of silicates, hydrocarbons, + – Nanoparticles of PAHs and silicates
41. Ideal grain model • Fit MW/SMC/LMC(/other LG) – averages and variations • Uses all available data – Extinction, abundances, thermal and non-thermal emissions, scattering, polarization
42. DGFit Motivation • Calculate how new observations affect our understanding of dust grains – Bigger/smaller grains, new materials, ... • Quantitatively compare different grain materials – Bayesian statistics may help (Bayes Factors) • Add additional observational constraints – E.g., albedo and scattering phase function asymmetry
43. MW Diffuse Dataset
44. DGFit Gordon & Misselt (202x, in prep)
45. Updated Obs & Albedo
49. Backup
51. Draine & Lee • Mainly introducing “astronomical silicate” and “astronomical graphite” based on heterogeneous lab data • 2 components • Grain shapes: spheres • Test MRN powerlaw size distributions • Constrained by extinction & emission
56. Clayton et al. • 3 components – Graphite, amorphous carbon – Silicates • Grain shapes: spheres • Fit mass distributions as 60 discrete bins (MEM) • Constrained by extinction & abundances • Fit MW, LMC, SMC and individual sightlines
60. Draine & Li • Update “astronomical PAHs” to match Spitzer Obs • 2 components – Silicates – Carbonaceous (PAH/graphite) • Grain shapes: spheres • Fit analytic size distributions – Tweaks to Weingartner & Draine results • Constrained by extinction, abundances, & emission
63. Siebenmorgen et al. • 2 components – Amorphous carbon – Amorphous silicates • Grain shapes: spheroids • Fit mass distributions as 60 discrete bins (MEM) • Constrained by extinction, abundances, emission, & polarization • Fit individual sightlines