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3D Dust map from Green et al. (2015)

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title 3D Dust map from Green et al. (2015)
 
Identifier https://doi.org/10.7910/DVN/40C44C
 
Creator Green, Gregory
 
Publisher Harvard Dataverse
 
Description A three-dimensional map of dust reddening, covering the three quarters of the sky surveyed by the Pan-STARRS 1 (PS1) survey. We use PS1 and 2MASS optical and near-infrared photometry to infer distances and reddenings to ~800 million stars. These stars trace the reddening along different lines of sight, allowing us to build up a map of reddening in 3D.



The map is structured as a set of sightlines, each of which contains multiple samples of the cumulative dust reddening as a function of distance. Each sightline is identified by a HEALPix nside parameter and nested pixel index. Within each sightline, cumulative reddening is given at discrete distances, spaced evenly in distance modulus. For each pixel, we provide multiple samples from the posterior on dust reddening.



Quality assurance information is given for each pixel, including:



  • Whether the fit converged in the pixel

  • The minimum/maximum reliable distance moduli in the pixel

  • The number of stars in the sightline

  • The number of stars in the sightline with good convergence, and which passed a cut on Bayesian evidence (termed "good" stars)

  • The number of "good" stars which are inferred to be Main-Sequence stars.




Note that the reddening is given in units of "SFD-like" E(B-V). They are meant to be comparable E(B-V), as reported by Schlegel, Finkbeiner & Davis (1998). In order to convert to extinction in different passbands, use the coefficients in Table 6 of Schlafly & Finkbeiner (2011).



The 3D map is described in more detail in Green et al. (2015), and tools for accessing the map are provided at argonaut.skymaps.info.
 
Subject Astronomy and Astrophysics
 
Contributor Green, Gregory