Person:

Green, Gregory Maurice

Distance measurements to molecular clouds are important but are often made separately for each cloud of interest, employing very different data and techniques. We present a large, homogeneous catalog of distances to molecular clouds, most of which are of unprecedented accuracy. We determine distances using optical photometry of stars along lines of sight toward these clouds, obtained from PanSTARRS-1. We simultaneously infer the reddenings and distances to these stars, tracking the full probability distribution function using a technique presented in Green et al. We fit these star-by-star measurements using a simple dust screen model to find the distance to each cloud. We thus estimate the distances to almost all of the clouds in the Magnani et al. catalog, as well as many other well-studied clouds, including Orion, Perseus, Taurus, Cepheus, Polaris, California, and Monoceros R2, avoiding only the inner Galaxy. Typical statistical uncertainties in the distances are 5%, though the systematic uncertainty stemming from the quality of our stellar models is about 10%. The resulting catalog is the largest catalog of accurate, directly measured distances to molecular clouds. Our distance estimates are generally consistent with available distance estimates from the literature, though in some cases the literature estimates are off by a factor of more than two.

I present a three-dimensional map of interstellar dust reddening, covering three-quarters of the sky out to a distance of several kiloparsecs, based on Pan-STARRS 1 and 2MASS photometry. The map reveals a wealth of detailed structure, from filaments to large cloud complexes. The map has a hybrid angular resolution, with most of the map at an angular resolution of 3.4′ to 13.7′ , and a maximum distance resolution of ∼25%. The three-dimensional distribution of dust is determined in a fully probabilistic framework, yielding the uncertainty in the reddening distribution along each line of sight, as well as stellar distances, reddenings and classifications for 800 million stars detected by Pan-STARRS 1. The method developed here compares observed stellar photometry with empirical stellar templates, incorporating prior knowledge about the structure of the Galaxy.

I validate the per-star reddening estimates by comparison with reddening estimates for stars with both SDSS photometry and SEGUE spectral classifications, finding per-star agreement to within ∼0.15 mag out to a stellar E(B−V) of 1 mag. I demonstrate the consistency of the resulting reddening estimates with those of two-dimensional emission-based maps of dust reddening. In particular, I find agreement with the Planck τ353 GHz-based reddening map to within 0.05 mag in E(B−V) to a depth of 0.5 mag, and explore systematics at reddenings less than E(B−V) ≈ 0.08 mag. I compare the 3D map developed here to two existing three-dimensional dust maps, by Marshall et al. (2006) and Lallement et al. (2013), exploring the strengths and weaknesses of the different 3D mapping methods. The map presented here has better angular resolution than both 3D maps compared, and it has better distance resolution than Marshall et al. (2006) within ∼3 kpc, but shows radial “finger-of-God” features not contained in Lallement et al. (2013).

The map can be queried or downloaded at http://argonaut.skymaps.info. I expect the three-dimensional reddening map presented here to find a wide range of uses, among them correcting for reddening and extinction for objects embedded in the plane of the Galaxy, studies of Galactic structure, calibration of future emission-based dust maps and determining distances to objects of known reddening. The method we present is not limited to the passbands of the Pan-STARRS 1 and 2MASS surveys, but may be extended to incorporate photometry from other optical and near-infrared surveys, such as WISE, Spitzer GLIMPSE, UKIDSS, SDSS (where available), and in the future, LSST and Gaia. The method can also be naturally extended to stellar kinematic data, such as that soon to be released by Gaia.

We present a map of the dust reddening to 4.5 kpc derived from Pan-STARRS1 stellar photometry. The map covers almost the entire sky north of declination −30◦ at a resolution of 7′–14′, and is based on the estimated distances and reddenings to more than 500 million stars. The technique is designed to map dust in the Galactic plane, where many other techniques are stymied by the presence of multiple dust clouds at different distances along each line of sight. This reddening-based dust map agrees closely with the Schlegel et al. (1998, SFD) far-infrared emission-based dust map away from the Galactic plane, and the most prominent differences between the two maps stem from known limitations of SFD in the plane. We also compare the map with Planck, finding likewise good agreement in general at high latitudes. The use of optical data from Pan-STARRS1 yields reddening uncertainty as low as 25 mmag E(B − V ).

We present a method to infer reddenings and distances to stars based only on their broad-band photometry, and show how this method can be used to produce a three-dimensional (3D) dust map of the Galaxy. Our method samples from the full probability density function of distance, reddening, and stellar type for individual stars, as well as the full uncertainty in reddening as a function of distance in the 3D dust map. We incorporate prior knowledge of the distribution of stars in the Galaxy and the detection limits of the survey. For stars in the Pan-STARRS 1 (PS1) 3π survey, we demonstrate that our reddening estimates are unbiased and accurate to ~0.13 mag in E(B – V) for the typical star. Based on comparisons with mock catalogs, we expect distances for main-sequence stars to be constrained to within ~20%-60%, although this range can vary, depending on the reddening of the star, the precise stellar type, and its position on the sky. A later paper will present a 3D map of dust over the three quarters of the sky surveyed by PS1. Both the individual stellar inferences and the 3D dust map will enable a wealth of Galactic science in the plane. The method we present is not limited to the passbands of the PS1 survey but may be extended to incorporate photometry from other surveys, such as the Two Micron All Sky Survey, the Sloan Digital Sky Survey (where available), and in the future, LSST and Gaia.