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DC Field | Value | Language |
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dc.contributor.advisor | Draine, Bruce T | en_US |
dc.contributor.author | Aniano Porcile, Gonzalo Jorge | en_US |
dc.contributor.other | Astrophysical Sciences Department | en_US |
dc.date.accessioned | 2012-11-15T23:53:56Z | - |
dc.date.available | 2012-11-15T23:53:56Z | - |
dc.date.issued | 2012 | en_US |
dc.identifier.uri | http://arks.princeton.edu/ark:/88435/dsp010p096695n | - |
dc.description.abstract | We are in a very special moment for the study of the interstellar medium (ISM). The Spitzer Space Telescope had provided, and currently Herschel Space Observatory is providing, invaluable infrared (IR) observations of a variety of astrophysical systems. These observations allow us to model several ongoing processes in the ISM, and in particular to study the physical properties of the interstellar dust. Determining the dust properties accurately is an extremely difficult task: even the overall amount of dust in other galaxies has often been very uncertain. In the current work, we develop ``state of the art'' tools for image processing and dust modeling that allows study of the interstellar dust in other galaxies using the new infrared data. We start by developing, the now ``industry-standard'', convolution kernels. They allow us to accurately combine data from several space- and ground-based telescopes, to perform multi-wavelength studies. They are a key development for doing resolved studies of astrophysical systems. We follow by analyzing the performance of ``modified blackbody'' (MBB) dust models when applied to realistic spectral energy distributions (SEDs), where we use a specific physical model, the Draine and Li (2007, DL07) dust model, to generate the synthetic SEDs. We show that MBB models can have a large bias in the inferred dust parameters, and therefore it is important to use more realistic dust models. We provide ``correction'' formulae to compensate for the MBB bias, useful when the more sophisticated dust modeling is not available. Using the DL07 dust model, which contains amorphous silicate and carbonaceous grains, we perform careful modeling of the dust properties in a large sample of well-resolved galaxies observed by the KINGFISH survey. With data from 3.6um to 500um, dust models are strongly constrained. 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 structure of the galaxies. The dust models successfully reproduce the observed global and resolved spectral energy distributions (SEDs). We find no evidence for significant masses of cold dust (T<12K). For two galaxies studied in detail (NGC628 and NGC6946) the derived dust maps correlates extremely well with independent observations of emission in the HI 21cm line and CO1-0 line. The derived dust/gas mass ratio are in excellent agreement with dust/gas ratios infered from other lines of evidence. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Princeton, NJ : Princeton University | en_US |
dc.relation.isformatof | The Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the <a href=http://catalog.princeton.edu> library's main catalog </a> | en_US |
dc.subject | Convolution | en_US |
dc.subject | Dust | en_US |
dc.subject | Infrared | en_US |
dc.subject | Interstellar medium | en_US |
dc.subject | Modeling | en_US |
dc.subject | Spectral energy distribution | en_US |
dc.subject.classification | Astrophysics | en_US |
dc.subject.classification | Astronomy | en_US |
dc.subject.classification | Physics | en_US |
dc.title | Modeling Dust in the Interstellar Medium | en_US |
dc.type | Academic dissertations (Ph.D.) | en_US |
pu.projectgrantnumber | 690-2143 | en_US |
Appears in Collections: | Astrophysical Sciences |
Files in This Item:
File | Description | Size | Format | |
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AnianoPorcile_princeton_0181D_10397.pdf | 160.13 MB | Adobe PDF | View/Download |
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