Milky Way Tomography IV: Dissecting Dust

Astronomy and Astrophysics – Astrophysics – Galaxy Astrophysics

Scientific paper

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Submitted to ApJ, 55 pages, 37 figures

Scientific paper

We use SDSS photometry of 73 million stars to simultaneously obtain best-fit main-sequence stellar energy distribution (SED) and amount of dust extinction along the line of sight towards each star. Using a subsample of 23 million stars with 2MASS photometry, whose addition enables more robust results, we show that SDSS photometry alone is sufficient to break degeneracies between intrinsic stellar color and dust amount when the shape of extinction curve is fixed. When using both SDSS and 2MASS photometry, the ratio of the total to selective absorption, $R_V$, can be determined with an uncertainty of about 0.1 for most stars in high-extinction regions. These fits enable detailed studies of the dust properties and its spatial distribution, and of the stellar spatial distribution at low Galactic latitudes. Our results are in good agreement with the extinction normalization given by the Schlegel et al. (1998, SFD) dust maps at high northern Galactic latitudes, but indicate that the SFD extinction map appears to be consistently overestimated by about 20% in the southern sky, in agreement with Schlafly et al. (2010). The constraints on the shape of the dust extinction curve across the SDSS and 2MASS bandpasses support the models by Fitzpatrick (1999) and Cardelli et al. (1989). For the latter, we find an $R_V=3.0\pm0.1$(random) $\pm0.1$(systematic) over most of the high-latitude sky. At low Galactic latitudes (|b|<5), we demonstrate that the SFD map cannot be reliably used to correct for extinction as most stars are embedded in dust, rather than behind it. We introduce a method for efficient selection of candidate red giant stars in the disk, dubbed "dusty parallax relation", which utilizes a correlation between distance and the extinction along the line of sight. We make these best-fit parameters, as well as all the input SDSS and 2MASS data, publicly available in a user-friendly format.

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