A 3D Dust Map Based on Gaia, Pan-STARRS 1 and 2MASS (1905.02734v1)

Abstract: We present a new three-dimensional map of dust reddening, based on Gaia parallaxes and stellar photometry from Pan-STARRS 1 and 2MASS. This map covers the sky north of a declination of -30 degrees, out to a distance of several kiloparsecs. This new map contains three major improvements over our previous work. First, the inclusion of Gaia parallaxes dramatically improves distance estimates to nearby stars. Second, we incorporate a spatial prior that correlates the dust density across nearby sightlines. This produces a smoother map, with more isotropic clouds and smaller distance uncertainties, particularly to clouds within the nearest kiloparsec. Third, we infer the dust density with a distance resolution that is four times finer than in our previous work, to accommodate the improvements in signal-to-noise enabled by the other improvements. As part of this work, we infer the distances, reddenings and types of 799 million stars. We obtain typical reddening uncertainties that are ~30% smaller than those reported in the Gaia DR2 catalog, reflecting the greater number of photometric passbands that enter into our analysis. Our 3D dust map can be accessed at https://doi.org/10.7910/DVN/2EJ9TX or through the Python package "dustmaps," and can be queried interactively at http://argonaut.skymaps.info. Our catalog of stellar parameters can be accessed at https://doi.org/10.7910/DVN/AV9GXO.

• The paper introduces a 3D dust map that integrates Gaia parallaxes with Pan-STARRS1 and 2MASS photometry for enhanced distance estimations.
• It employs a spatial Gaussian process prior to produce a smoother dust distribution and notably reduce distance uncertainties, particularly within 1 kpc.
• The study achieves a fourfold improvement in resolution, cataloging 799 million stars with about 30% smaller reddening uncertainties than earlier maps.

Overview of "A 3D Dust Map Based on Gaia, Pan-STARRS 1 and 2MASS"

The paper authored by Green et al. presents a novel three-dimensional map of dust reddening within the Galaxy, integrating data from Gaia DR2 parallaxes, Pan-STARRS 1, and 2MASS photometry. The map spans over three-quarters of the sky, extending out to multiple kiloparsecs, and is an advance over the authors' previous efforts due to several significant improvements.

Key Enhancements and Methodology

The presented map incorporates several methodological enhancements:

1. Incorporation of Gaia Parallaxes: The inclusion of Gaia parallaxes enhances distance estimation for stars, especially improving accuracy for nearby stellar distances, allowing for more precise mapping compared to reliance on photometric distances alone.
2. Spatial Prior Implementation: A spatial Gaussian process prior is applied, which correlates dust densities in proximate sightlines, resulting in a smoother and more isotropic distribution of dust clouds. This innovation reduces distance uncertainty across sightlines, particularly within 1 kpc of the Solar System.
3. Improved Resolution: The paper achieves a fourfold improvement in distance resolution compared to previous iterations, allowing for a more granular mapping of dust density variations due to the enhancement in signal-to-noise ratios.

With these advancements, the paper provides a catalog of distances, reddening, and types for 799 million stars, achieving typical reddening uncertainties that are approximately 30% smaller than those reported in Gaia DR2, due to the utilization of multiple photometric passbands.

Results and Comparisons

The generated 3D dust map reveals the spatial distribution of dust and highlights significant structures like molecular clouds and star-forming regions across varying distances. When compared to the Planck 2014 radiance-based dust map and previous versions (such as Bayestar 2017), the new map shows superior precision at low reddenings and greater agreement at higher extinctions. The use of Gaia parallax data plays a pivotal role in resolving the distance-reddening relation for individual sightlines.

Notably, the application of the Gaussian process prior effectively constrains the map's distance errors and eliminates noise, often observable as "holes" in uncorrelated maps. This provides a clear advantage by enabling a more consistent and accurate interpretation of Galactic structure, essential for studies of star formation and interstellar medium characterization.

Future Developments

This paper demonstrates that further enhancements in dust mapping can be realized with deeper infrared photometry and optimized kernels for spatial priors facilitating a more comprehensive understanding of the Galactic structure. Integrating data from forthcoming surveys (e.g., DECaPS) and addressing variations in extinction curves across the Galaxy could lead to more precise absolute extinction maps, which are crucial for extragalactic and cosmological studies.

In conclusion, the 3D dust map presented by Green et al. is a substantial contribution to Galactic modeling, offering significant practical applications in determining star formation regions and tracing spiral arms within the Milky Way. The map and stellar catalog are both made available for use through an openly accessible platform, fostering ongoing research in Galactic and extragalactic astronomy.