Statistics – Computation
Scientific paper
Jan 2012
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012aas...21934312h&link_type=abstract
American Astronomical Society, AAS Meeting #219, #343.12
Statistics
Computation
Scientific paper
We study dust and star formation in nearby galaxies by fitting the observed ultraviolet (UV) to infrared (IR) spectral energy distributions (SEDs) of regions of galaxies and entire galaxies using DIRTY - a 3D Monte Carlo dust radiative transfer model - and stellar evolutionary synthesis models. To our knowledge, this is the first systematic multi-wavelength study with a physically based radiative transfer model focused on dust and stars in galaxies. Due to the computational complexity of the problem, previous studies were not physically based. With various optimizations in our model and the availability of large computer clusters such as the TeraGrid, it has now become feasible. It is important to model both UV and IR simultaneously and self-consistently. Dust absorbs radiation strongly in the UV and re-emits the energy as a modified blackbody in the IR. Fitting UV and optical alone gives significant degeneracy between the stellar age and the amount of dust present, while fitting IR alone tells us very little about the underlying stellar populations. It is common to constrain observations using the UV and the total IR, but with the IR spectrum instead of the integrated IR we gain extra information such as dust temperature. Our model grid allows us to physically connect the stars and the dust and look at the full problem with the whole possible range of galaxies from dwarf galaxies to ultra-luminous galaxies.
Gordon Karl Douglas
Hei Law Ka
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