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PreprintCC BY 4.0arXiv

Mapping the Milky Way in Six Dimensions: A contiguous, homogenised, phase-space catalogue of \textit{Gaia} DR3 tracers up to 250 kpc

Abstract

We present a comprehensive, homogenised catalogue of 32,552,876 stellar sources with full 6D phase-space information, spanning Galactocentric distances from the inner galaxy (≳ 5\,kpc) to the outer halo (∼ 250\,kpc). By cross-matching \textit{Gaia} DR3 astrometry with spectrophotometric distances and line-of-sight velocities from 14 surveys (including \textsc{desi}, \textsc{sdss-boss}, \textsc{apogee}, \textsc{lamost}, \textsc{galah}, and \textsc{ges}), we achieve median fractional distance uncertainties of ≈2.7% for dhelio≤15\,kpc, and ≈29% for 15<dhelio≤250\,kpc. The catalogue-wide median fractional radial velocity uncertainty is ≈8.31%. \textit{Gaia}-anchored zero-point corrections and statistical normalisation suppress both random and systematic errors. Furthermore, we derive spectrophotometric parallaxes from joint photometric and spectroscopic data. Overlapping survey data is aggregated to replace unreliable values and supplement absent velocities, improving completeness and internal consistency. This multi-survey synthesis is externally validated against globular clusters, dwarf galaxies, and stellar streams, yielding precise kinematics. Notably, the sample features 517,123 halo stars extending well beyond the \textit{Gaia} parallax limit (≳ 10\,kpc). These predominantly faint (G > 17) and metal-poor ([Fe/H] < −1) tracers, including RR~Lyrae, blue horizontal-branch, and K~giant stars, constitute the largest well-calibrated sample of outer-halo tracers to date. This unique dataset is ideal for multi-component mass modelling, galactic archaeology, and dark matter searches across the Milky Way.

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BibTeX
@misc{mukherjee2026mapping,
  title = {{Mapping the Milky Way in Six Dimensions: A contiguous, homogenised, phase-space catalogue of \textitGaia DR3 tracers up to 250 kpc}},
  author = {Sutirtha Mukherjee and Amogh Srivastav and Subhabrata Majumdar},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.28652},
  eprint = {2609.28652},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.28652},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Mapping the Milky Way in Six Dimensions: A contiguous, homogenised, phase-space catalogue of \textit{Gaia} DR3 tracers up to 250 kpc
AU  - Sutirtha Mukherjee
AU  - Amogh Srivastav
AU  - Subhabrata Majumdar
PY  - 2026
DA  - 2026/09/23
PB  - arXiv
DO  - 10.48550/arxiv.2609.28652
UR  - https://arxiv.org/abs/2609.28652
AB  - We present a comprehensive, homogenised catalogue of 32,552,876 stellar sources with full 6D phase-space information, spanning Galactocentric distances from the inner galaxy (≳ 5\,kpc) to the outer halo (∼ 250\,kpc). By cross-matching \textit{Gaia} DR3 astrometry with spectrophotometric distances and line-of-sight velocities from 14 surveys (including \textsc{desi}, \textsc{sdss-boss}, \textsc{apogee}, \textsc{lamost}, \textsc{galah}, and \textsc{ges}), we achieve median fractional distance uncertainties of ≈2.7% for d_helio≤15\,kpc, and ≈29% for 15<d_helio≤250\,kpc. The catalogue-wide median fractional radial velocity uncertainty is ≈8.31%. \textit{Gaia}-anchored zero-point corrections and statistical normalisation suppress both random and systematic errors. Furthermore, we derive spectrophotometric parallaxes from joint photometric and spectroscopic data. Overlapping survey data is aggregated to replace unreliable values and supplement absent velocities, improving completeness and internal consistency. This multi-survey synthesis is externally validated against globular clusters, dwarf galaxies, and stellar streams, yielding precise kinematics. Notably, the sample features 517,123 halo stars extending well beyond the \textit{Gaia} parallax limit (≳ 10\,kpc). These predominantly faint (G > 17) and metal-poor ([Fe/H] < −1) tracers, including RR~Lyrae, blue horizontal-branch, and K~giant stars, constitute the largest well-calibrated sample of outer-halo tracers to date. This unique dataset is ideal for multi-component mass modelling, galactic archaeology, and dark matter searches across the Milky Way.
ER  -