3d dust mapping with ps1

Gregory Green (Harvard/CfA)


  • 2D dust maps already exist
  • Determine dust density throughout Galaxy in 3D
  • Give reddening at any point on sky, at any distance


Divide detected stars into ~6'x6' pixels. 

Assume each pixel has a different line-of-sight dust column. 


Infer distance, reddening & stellar type for each star


Probability density in distance & reddening for each star in pixel


Find distance-reddening curves consistent with all stars


Obtain many possible disance-reddening profiles in one pixel

Better Stellar Inferences

Line-of-sight dust informs stellar reddenings & distances.

Detection Density

  • Require 4-band detection, including 2 bands in PS1
  • Aperture - PSF magnitude cut in two PS1 bands
  • 800 million stars

Total Detections

PS1 vs 2MASS

Bands Per Star



Visualize dust from different positions in Galaxy & directions.

Local Dust

Zooming Out

Voxel Shape

High angular resolution, low radial resolution.

Touring the Galaxy


3π Footprint

Future Avenues

  • Assume spatial correlation between lines of sight
  • Incorporate proper motions, parallaxes
  • Gaia, LSST should allow much improved 3D dust maps

3D Dust with PS1

By Gregory Green

3D Dust with PS1

I present a 3D dust map of the Milky Way, based on Pan-STARRS 1 photometry of over half a billion stars. Our 3D dust map covers the footprint of the 3pi survey, tracing dust out to a distance of several kiloparsecs and a depth of a few magnitudes of reddening in E(B-V). In each pixel in the map, we infer the distance and reddening of each star, and then determine the range of reddening versus distance profiles that are consistent with all the stars along the line of sight. The map has a typical angular resolution of 7', varying with the surface density of stars across the sky, and a distance resolution of about 25%. At large distances, our map agrees well with 2D maps of dust, such as Schlegel, Finkbeiner & Davis (1998) and the newer Planck dust maps. At intermediate distances, it reveals structure from fine filamentary scales up to gross features in the Galaxy. In addition to PS1 photometry, we use near-infrared photometry from 2MASS. This allows us to peer through deeper clouds, where PS1 optical photometry is heavily extinguished. In the future, we will be able to leverage new datasets, such as LSST and GAIA, to produce the next generation of 3D maps of our Galaxy.

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