A Novel Approach to 3D Dust Mapping of the Central Molecular Zone
Abstract
The 3D distribution of dust and gas in the Milky Way's Central Molecular Zone (CMZ) is key to understanding gas inflows toward the Galactic Centre (GC), the process of star formation in this extreme environment, and the propagation of energetic cosmic rays originating from Sgr A*. However, while recent efforts have combined datasets in a Bayesian framework to estimate the near/far positions of individual molecular clouds in the CMZ, conflicts between different methodologies still remain and we are still lacking a comprehensive, model-independent map of all of the gas and dust in the CMZ, which is critical to address key science questions. Here we develop a new methodology to infer the 3D dust distribution of the CMZ. The key idea of the method is to use \emph{stellar} proper motions to get probabilistic information about the unknown stellar distances through a model of the distribution of star positions and velocities of the nuclear stellar disc (NSD), co-spatial to the CMZ. Taking \emph{stellar} proper motions and extinctions as input, the latter adopted as a proxy of the dust column density, the method returns the 3D dust distribution. It is non parametric, makes no a-priori assumption on the dust distribution, and is fundamentally distinct and largely independent of all existing methods. We show that the method can robustly and effectively reconstruct the mock 3D CMZ structure by testing it on a range of mock dust distributions, both analytically generated and taken from hydrodynamical simulations. Finally, we discuss the prospects for applying the method to real data.
Related
- Isotopic ratios as probes of star formation and the origin of molecular gas in the Central Molecular Zone
- The Central Molecular Zone of our Galaxy, a chemical complexity factory: first interstellar detections of molecules towards G+0.693
- A Collimated Protostellar Outflow Likely Driven by Jet and Reshaped by Environment in the Sagittarius C Cloud of the Central Molecular Zone
- Sulphur within the extreme environment of the central molecular zone of NGC 253: a chemical modelling approach
- Sulphur within the extreme environment of the central molecular zone of NGC253: A chemical modelling approach
BibTeX
@misc{vasini2026novel,
title = {{A Novel Approach to 3D Dust Mapping of the Central Molecular Zone}},
author = {Arianna Vasini and Mattia C. Sormani and Jason L. Sanders and Adam Ginsburg and Cara Battersby and Francisco Nogueras-Lara and Rainer Schödel and Eva Deliporanidou and Marco Donati and Zi-Xuan Feng and Karl Fiteni and Savannah Gramze and Xingchen Li and Dani R. Lipman and Perry H. Hatchfield},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.10782},
eprint = {2609.10782},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.10782},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - A Novel Approach to 3D Dust Mapping of the Central Molecular Zone
AU - Arianna Vasini
AU - Mattia C. Sormani
AU - Jason L. Sanders
AU - Adam Ginsburg
AU - Cara Battersby
AU - Francisco Nogueras-Lara
AU - Rainer Schödel
AU - Eva Deliporanidou
AU - Marco Donati
AU - Zi-Xuan Feng
AU - Karl Fiteni
AU - Savannah Gramze
AU - Xingchen Li
AU - Dani R. Lipman
AU - Perry H. Hatchfield
PY - 2026
DA - 2026/09/09
PB - arXiv
DO - 10.48550/arxiv.2609.10782
UR - https://arxiv.org/abs/2609.10782
AB - The 3D distribution of dust and gas in the Milky Way's Central Molecular Zone (CMZ) is key to understanding gas inflows toward the Galactic Centre (GC), the process of star formation in this extreme environment, and the propagation of energetic cosmic rays originating from Sgr A*. However, while recent efforts have combined datasets in a Bayesian framework to estimate the near/far positions of individual molecular clouds in the CMZ, conflicts between different methodologies still remain and we are still lacking a comprehensive, model-independent map of all of the gas and dust in the CMZ, which is critical to address key science questions. Here we develop a new methodology to infer the 3D dust distribution of the CMZ. The key idea of the method is to use \emph{stellar} proper motions to get probabilistic information about the unknown stellar distances through a model of the distribution of star positions and velocities of the nuclear stellar disc (NSD), co-spatial to the CMZ. Taking \emph{stellar} proper motions and extinctions as input, the latter adopted as a proxy of the dust column density, the method returns the 3D dust distribution. It is non parametric, makes no a-priori assumption on the dust distribution, and is fundamentally distinct and largely independent of all existing methods. We show that the method can robustly and effectively reconstruct the mock 3D CMZ structure by testing it on a range of mock dust distributions, both analytically generated and taken from hydrodynamical simulations. Finally, we discuss the prospects for applying the method to real data.
ER -