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Published September 10, 2012 | Published
Journal Article Open

Modeling Dust and Starlight in Galaxies Observed by Spitzer and Herschel: NGC 628 and NGC 6946

Abstract

We characterize the dust in NGC 628 and NGC 6946, two nearby spiral galaxies in the KINGFISH sample. With data from 3.6 μm to 500 μm, dust models are strongly constrained. Using the Draine & Li dust model (amorphous silicate and carbonaceous grains), for each pixel in each galaxy we estimate (1) dust mass surface density, (2) dust mass fraction contributed by polycyclic aromatic hydrocarbons, (3) distribution of starlight intensities heating the dust, (4) total infrared (IR) luminosity emitted by the dust, and (5) IR luminosity originating in regions with high starlight intensity. We obtain maps for the dust properties, which trace the spiral structure of the galaxies. The dust models successfully reproduce the observed global and resolved spectral energy distributions (SEDs). The overall dust/H mass ratio is estimated to be 0.0082 ± 0.0017 for NGC 628, and 0.0063 ± 0.0009 for NGC 6946, consistent with what is expected for galaxies of near-solar metallicity. Our derived dust masses are larger (by up to a factor of three) than estimates based on single-temperature modified blackbody fits. We show that the SED fits are significantly improved if the starlight intensity distribution includes a (single intensity) "delta function" component. We find no evidence for significant masses of cold dust (T ≲ 12 K). Discrepancies between PACS and MIPS photometry in both low and high surface brightness areas result in large uncertainties when the modeling is done at PACS resolutions, in which case SPIRE, MIPS70, and MIPS160 data cannot be used. We recommend against attempting to model dust at the angular resolution of PACS.

Additional Information

© 2012 American Astronomical Society. Received 2012 March 14; accepted 2012 June 19; published 2012 August 23. We are grateful to R. H. Lupton for availability of the SM graphics program, and to the anonymous referee for helpful suggestions. This research was supported in part by JPL grants 1329088 and 1373687, and by NSF grant AST1008570.

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