A parsec-scale Galactic 3D dust map out to 1.25 kpc from the Sun (2308.01295v2)

Abstract: High-resolution 3D maps of interstellar dust are critical for probing the underlying physics shaping the structure of the interstellar medium, and for foreground correction of astrophysical observations affected by dust. We aim to construct a new 3D map of the spatial distribution of interstellar dust extinction out to a distance of 1.25 kpc from the Sun. We leveraged distance and extinction estimates to 54 million nearby stars derived from the Gaia BP/RP spectra. Using the stellar distance and extinction information, we inferred the spatial distribution of dust extinction. We modeled the logarithmic dust extinction with a Gaussian process in a spherical coordinate system via iterative charted refinement and a correlation kernel inferred in previous work. In total, our posterior has over 661 million degrees of freedom. We probed the posterior distribution using the variational inference method MGVI. Our 3D dust map has an angular resolution of up to 14' (Nside = 256), and we achieve parsec-scale distance resolution, sampling the dust in 516 logarithmically spaced distance bins spanning 69 pc to 1250 pc. We generated 12 samples from the variational posterior of the 3D dust distribution and release the samples alongside the mean 3D dust map and its corresponding uncertainty. Our map resolves the internal structure of hundreds of molecular clouds in the solar neighborhood and will be broadly useful for studies of star formation, Galactic structure, and young stellar populations. It is available for download in a variety of coordinate systems online and can also be queried via the publicly available dustmaps Python package.

• The paper employs Gaia BP/RP spectral data and Gaussian process modeling to construct a high-resolution 3D dust map up to 1.25 kpc.
• It reveals refined dust structures by reducing line-of-sight artifacts, enhancing clarity in the study of molecular clouds.
• The research offers a robust methodology that aids future astrophysical analysis and improved modeling of cosmic dust distributions.

A Parsec-scale Galactic 3D Dust Map Extending to 1.25 kpc from the Sun

The presented paper focuses on constructing a highly detailed 3D dust map of the Galactic interstellar medium (ISM) up to a distance of 1.25 kpc from the Sun. This map plays a crucial role in examining the structure of dust in the ISM and correcting for the foreground attenuation in astrophysical observations.

Motivation and Methodology

This research leverages data from Gaia’s BP/RP spectrum, which provides stellar distance and extinction estimates for approximately 54 million nearby stars. Using this extensive dataset, the authors inferred the spatial distribution of dust extinction. A Gaussian Process (GP) model was employed, utilizing an iterative chart refinement with a spherical coordinate system, contributing to a fine-grained angular resolution of up to 14'. The dust was sampled in 516 logarithmically spaced bins ranging from 69 to 1250 parsecs. The variational inference technique MGVI was used to probe the posterior distribution, encompassing 661 million degrees of freedom.

Results of the Study

The resulting 3D dust map provides significant insight into the internal structures of numerous molecular clouds within the solar neighborhood. It processes a high angular and parsec-scale distance resolution akin to the achievements detailed in studies such as Leike et al. (2020). The map not only delineates high latitude features with more clarity without the pronounced "fingers-of-god" artifacts but also identifies many smaller density structures of influence in star formation processes.

Comparison to Existing Maps

The integration of the Gaussian process framework and Gaia data in this paper provides a clearer visualization of dust structures compared to existing 3D maps. In contrast to other efforts like Bayestar19 and the works by Lallement and Vergely, this approach optimizes both distance and angular resolution, hence reducing the smearing of dust structures along the line of sight.

Conclusions and Implications

This dust map is an invaluable resource for dissecting the structural attributes of the Galactic ISM, notably in aiding the refinement of models on star formation and understanding the Galactic structure and kinematics. Potential future research could extend this methodology to broader distances to encapsulate more extensive structural interactions on a Galactic scale and explore varying reddening laws in more localized settings.

Furthermore, the methodological advancements in GP inference and iterative refinement offer a practical blueprint for similar high-dimensional astronomical reconstructions with diverse datasets. This could lead to future developments in AI applications, such as enhanced star classification algorithms and improved cosmic dust distribution models, fostering a more robust understanding of Galactic environments.

This substantial map distribution is available online in multiple coordinate systems and can be accessed via the dustmaps Python package, facilitating widespread utilization in ongoing and future astronomical analysis.