Constraining the Milky Way Mass profile with data driven distribution function using DESI DR2 halo stars
Abstract
We employ a novel data-driven dynamical modeling method, the empirical distribution function (emPDF), to constrain the Milky Way mass profile using a large sample of halo stars from the Dark Energy Spectroscopic Instrument Milky Way Survey (DESI MWS). The method does not assume any functional form of the tracer distribution. Deviations from the steady-state assumption and the effects of observational errors are further tested and calibrated using a number of realistic mock observations (AuriDESI). Applying the calibrated method to two classes of tracers in DESI, we derive a best-constrained virial mass and concentration of log M200c/M⊙=12.05−0.12+0.21(−0.18+0.26) and log c200c=1.20−0.16+0.11(−0.24+0.20) for BHBs. For RR Lyrae stars we derive log M200c/M⊙=12.15−0.14+0.22(−0.19+0.26) and log c200c=1.16−0.12+0.09(−0.18+0.16). The uncertainties quoted outside and within brackets are statistical and total errors including systematic errors calibrated from AuriDESI, respectively. The two tracer populations provide overall consistent measurements of the MW halo mass profile. Combining the halo star constraints with the independent constraint from satellite dynamics, we derive a robust and precise final measurement of the MW halo parameters of log M200c/M⊙=12.12−0.05+0.05(−0.04+0.06) and log c200c=1.16−0.03+0.05(−0.07+0.05), with correlation coefficients of ρ=−0.90(−0.54).
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BibTeX
@misc{zhou2026constraining,
title = {{Constraining the Milky Way Mass profile with data driven distribution function using DESI DR2 halo stars}},
author = {Yanrui Zhou and Jiaxin Han and Wenting Wang and Zhaozhou Li and Alexander H. Riley and Monica Valluri and Amanda Byström and Gustavo E. Medina and Sergey E. Koposov and Ting S. Li and Leandro Beraldo e Silva and Oleg Y. Gnedin and N. Kizhuprakkat and N. Sandford and C. S. Frenk and Binbin Gao and Yiran Wei and J. Aguilar and S. Ahlen and C. Allende Prieto and F. Beutler and D. Bianchi and D. Brooks and A. Carnero Rosell and T. Claybaugh and A. P. Cooper and A. de la Macorra and Arjun Dey and Biprateep Dey and J. E. Forero-Romero and E. Gaztañaga and Satya Gontcho A Gontcho and G. Gutierrez and M. Ishak and S. Juneau and T. Karim and R. Kehoe and O. Lahav and A. Lambert and M. Landriau and L. Le Guillou and A. Leauthaud and M. E. Levi and A. Meisner and R. Miquel and S. Nadathur and E. Paillas and N. Palanque-Delabrouille and W. J. Percival and F. Prada and I. Pérez-Ràfols and C. Ravoux and G. Rossi and E. Sanchez and C. Saulder and D. Schlegel and J. Silber and M. Siudek and G. Tarlé and B. A. Weaver},
howpublished = {arXiv},
year = {2026},
month = nov,
doi = {10.48550/arxiv.2611.05520},
eprint = {2611.05520},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2611.05520},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Constraining the Milky Way Mass profile with data driven distribution function using DESI DR2 halo stars
AU - Yanrui Zhou
AU - Jiaxin Han
AU - Wenting Wang
AU - Zhaozhou Li
AU - Alexander H. Riley
AU - Monica Valluri
AU - Amanda Byström
AU - Gustavo E. Medina
AU - Sergey E. Koposov
AU - Ting S. Li
AU - Leandro Beraldo e Silva
AU - Oleg Y. Gnedin
AU - N. Kizhuprakkat
AU - N. Sandford
AU - C. S. Frenk
AU - Binbin Gao
AU - Yiran Wei
AU - J. Aguilar
AU - S. Ahlen
AU - C. Allende Prieto
AU - F. Beutler
AU - D. Bianchi
AU - D. Brooks
AU - A. Carnero Rosell
AU - T. Claybaugh
AU - A. P. Cooper
AU - A. de la Macorra
AU - Arjun Dey
AU - Biprateep Dey
AU - J. E. Forero-Romero
AU - E. Gaztañaga
AU - Satya Gontcho A Gontcho
AU - G. Gutierrez
AU - M. Ishak
AU - S. Juneau
AU - T. Karim
AU - R. Kehoe
AU - O. Lahav
AU - A. Lambert
AU - M. Landriau
AU - L. Le Guillou
AU - A. Leauthaud
AU - M. E. Levi
AU - A. Meisner
AU - R. Miquel
AU - S. Nadathur
AU - E. Paillas
AU - N. Palanque-Delabrouille
AU - W. J. Percival
AU - F. Prada
AU - I. Pérez-Ràfols
AU - C. Ravoux
AU - G. Rossi
AU - E. Sanchez
AU - C. Saulder
AU - D. Schlegel
AU - J. Silber
AU - M. Siudek
AU - G. Tarlé
AU - B. A. Weaver
PY - 2026
DA - 2026/11/03
PB - arXiv
DO - 10.48550/arxiv.2611.05520
UR - https://arxiv.org/abs/2611.05520
AB - We employ a novel data-driven dynamical modeling method, the empirical distribution function (emPDF), to constrain the Milky Way mass profile using a large sample of halo stars from the Dark Energy Spectroscopic Instrument Milky Way Survey (DESI MWS). The method does not assume any functional form of the tracer distribution. Deviations from the steady-state assumption and the effects of observational errors are further tested and calibrated using a number of realistic mock observations (AuriDESI). Applying the calibrated method to two classes of tracers in DESI, we derive a best-constrained virial mass and concentration of log M_200c/M_⊙=12.05_−0.12^+0.21(_−0.18^+0.26) and log c_200c=1.20_−0.16^+0.11(_−0.24^+0.20) for BHBs. For RR Lyrae stars we derive log M_200c/M_⊙=12.15_−0.14^+0.22(_−0.19^+0.26) and log c_200c=1.16_−0.12^+0.09(_−0.18^+0.16). The uncertainties quoted outside and within brackets are statistical and total errors including systematic errors calibrated from AuriDESI, respectively. The two tracer populations provide overall consistent measurements of the MW halo mass profile. Combining the halo star constraints with the independent constraint from satellite dynamics, we derive a robust and precise final measurement of the MW halo parameters of log M_200c/M_⊙=12.12_−0.05^+0.05(_−0.04^+0.06) and log c_200c=1.16_−0.03^+0.05(_−0.07^+0.05), with correlation coefficients of ρ=−0.90(−0.54).
ER -