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DESI DR2 Results III: The Mass of the Milky Way

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DESI Collaboration: C. Aganze, J. Aguilar, S. Ahlen, C. Allende Prieto, E. Armengaud, A. Aviles, S. Bailey, A. Bault
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J. Behera, L. Beraldo e Silva, J. R. Bermejo-Climent, F. Beutler, D. Bianchi, S. Brieden, A. Brodzeller, D. Brooks, A. Byström, T. M. Callingham, R. Canning, A. Carnero Rosell, F. J. Castander, E. Chaussidon, J. Chaves-Montero, X. Chen, Yingtian Chen, A. P. Cooper, A. Cuceu, Tamara M. Davis, K. S. Dawson, A. de la Macorra, J. Della Costa, Arjun Dey, Biprateep Dey, Z. Ding, P. Doel, G. M. Eadie, H. Ebina, V. A. Fawcett, S. Ferraro, A. Font-Ribera, J. E. Forero-Romero, C. S. Frenk, C. Garcia Palau, E. Gaztañaga, Oleg Y. Gnedin, Satya Gontcho A Gontcho, A. X. Gonzalez-Morales, G. Gutierrez, J. Guy, Jiaxin Han, H. K. Herrera-Alcantar, C. Holm-Hansen, K. Honscheid, D. Huterer, M. Ishak, S. Juneau, T. Karim, S. Kent, D. Kirkby, N. Kizhuprakkat, S. E. Koposov, A. Kremin, A. Krolewski, O. Lahav, C. Lamman, M. Landriau, L. Le Guillou, A. Leauthaud, M. E. Levi, Q. Li, S. Li, Ting S. Li, Z. Li, K. Lodha, Y. Luo, M. Manera, P. Martini, G. E. Medina, A. Meisner, R. Miquel, J. Moustakas, A. D. Myers, S. Nadathur, J. Najita, G. Niz, E. Paillas, N. Palanque-Delabrouille, W. J. Percival, A. Porredon, F. Prada, I. Pérez-Ràfols, J. Ratajczak, C. Ravoux, N. Rehemtulla, A. H. Riley, A. Rocher, C. Rockosi, G. Rossi, E. Sanchez, C. Saulder, D. Schlegel, M. Schubnell, A. Shafieloo, R. Sharples, J. Silber, M. Siudek, T. Tan, G. Tarlé, R. Vaisakh, M. Valluri, W. Wang, B. A. Weaver, R. H. Wechsler, J. Yu, Y. Zhou

Astrophysics of Galaxies · Submitted 3 Nov 2026 · 299 references

Pith's verdict: A well-executed, transparent Milky Way mass measurement using the largest halo-star sample to date, but the headline M200c precision depends heavily on one method (GME) that systematically overestimates the enclosed mass profile — a tension the paper reports but doesn't fully resolve.

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arXiv ID2611.05518 (version 1)
Pith IDHED7XAHQ, Pith's permanent record of this paper and its review
CitationA. Aviles, A. Bault, A. Brodzeller, A. Bystr\"om, A. Carnero Rosell, A. Cuceu, A. de la Macorra, A. D. Myers, A. Font-Ribera, A. H. Riley, A. Kremin, A. Krolewski, A. Leauthaud, A. Meisner, A. P. Cooper, A. Porredon, Arjun Dey, A. Rocher, A. Shafieloo, A. X. Gonzalez-Morales, B. A. Weaver, Biprateep Dey, C. Allende Prieto, C. Garcia Palau, C. Holm-Hansen, C. Lamman, C. Ravoux, C. Rockosi, C. Saulder, C. S. Frenk, D. Bianchi, D. Brooks, DESI Collaboration: C. Aganze, D. Huterer, D. Kirkby, D. Schlegel, E. Armengaud, E. Chaussidon, E. Gazta\~naga, E. Paillas, E. Sanchez, F. Beutler, F. J. Castander, F. Prada, G. E. Medina, G. Gutierrez, G. M. Eadie, G. Niz, G. Rossi, G. Tarl\'e, H. Ebina, H. K. Herrera-Alcantar, I. P\'erez-R\`afols, J. Aguilar, J. Behera, J. Chaves-Montero, J. Della Costa, J. E. Forero-Romero, J. Guy, Jiaxin Han, J. Moustakas, J. Najita, J. Ratajczak, J. R. Bermejo-Climent, J. Silber, J. Yu, K. Honscheid, K. Lodha, K. S. Dawson, L. Beraldo e Silva, L. Le Guillou, M. E. Levi, M. Ishak, M. Landriau, M. Manera, M. Schubnell, M. Siudek, M. Valluri, N. Kizhuprakkat, N. Palanque-Delabrouille, N. Rehemtulla, O. Lahav, Oleg Y. Gnedin, P. Doel, P. Martini, Q. Li, R. Canning, R. H. Wechsler, R. Miquel, R. Sharples, R. Vaisakh, S. Ahlen, Satya Gontcho A Gontcho, S. Bailey, S. Brieden, S. E. Koposov, S. Ferraro, S. Juneau, S. Kent, S. Li, S. Nadathur, Tamara M. Davis, Ting S. Li, T. Karim, T. M. Callingham, T. Tan, V. A. Fawcett, W. J. Percival, W. Wang, X. Chen, Yingtian Chen, Y. Luo, Y. Zhou, Z. Ding, Z. Li. "DESI DR2 Results III: The Mass of the Milky Way." arXiv:2611.05518 (2026). https://pith.science/paper/HED7XAHQ
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The paper

The paper claims

DESI DR2 uses over 10,000 distant halo stars to measure the Milky Way's mass with combined dynamical methods.

The reading

The paper aims to establish a precise and accurate mass of the Milky Way by applying four independent dynamical modeling methods to the largest sample of distant halo stars ever used: blue horizontal branch stars and RR Lyrae stars from DESI DR2. By validating each method on mock surveys drawn from cosmological simulations that include realistic observational uncertainties and selection effects, the authors quantify and correct systematic biases that would otherwise be hidden. They then combine the four methods using a rigorous statistical formalism that accounts for per-method biases and correlations, yielding a joint mass profile that is significantly more reliable than any single method. If correct, this measurement provides a fundamental constraint on the dark matter halo of the Milky Way, with implications for dark matter models, galaxy formation, and local dark matter detection.

What carries the argument

The central mechanism is a multi-method calibration and combination framework: four independent spherical dynamical modeling tools (emPDF, GME, NIMBLE-A, NIMBLE-B) are each applied to the same set of 24 mock surveys based on the Auriga cosmological simulations with realistic observational effects. Per-method biases and covariances between methods are measured from the mocks and used to correct the Milky Way results. The four methods are then combined into joint estimates of the enclosed mass profile and virial mass using a maximum-likelihood formalism that includes systematic error floors, shrinkage of the covariance matrix to avoid overfitting with only 24 mocks, and a hierarchical Bayesian model for the total mass extrapolation.

Extended reading notes

Core claim

The paper finds that the Milky Way's enclosed mass within 80 kpc is $M(r < 80\,\mathrm{kpc}) = 6.36^{+0.53}_{-0.48} \times 10^{11}\,M_\odot$ and its virial mass (defined at the overdensity 200c) is $M_{\mathrm{200c}} = 1.19^{+0.14}_{-0.12} \times 10^{12}\,M_\odot$. These are joint estimates from four dynamical methods (emPDF, GME, NIMBLE-A, NIMBLE-B) applied to 10,036 RR Lyrae and blue horizontal branch stars with 6D phase-space coordinates, after correcting each method using 24 mock realizations from the Auriga cosmological simulations that include DESI and Gaia-like uncertainties and selection functions. The joint estimates have uncertainties of 7--8%, roughly half that of the tightest individual method, and are consistent whether using only RR Lyrae or only blue horizontal branch stars as tracers.

Load-bearing premise

The calibration of per-method biases and the correlation structure between methods is derived from only 24 mock realizations (six Auriga halos at four viewing angles), and the corrections are assumed to transfer to the real Milky Way despite known differences such as the presence of the Large Magellanic Cloud and the specific baryonic physics in Auriga.

Editorial extensions

If this is right

  • The joint mass measurement provides a benchmark for testing the cold dark matter model on galactic scales, particularly for predicting the number and properties of Milky Way satellite galaxies.
  • The work establishes a template for future large spectroscopic surveys (e.g., DESI DR3, WEAVE, 4MOST) to combine multiple dynamical methods in a statistically rigorous way, moving beyond single-method results.
  • The measurement strongly favors Milky Way masses $M_{\mathrm{200c}} \gtrsim 1 \times 10^{12}\,M_\odot$, which is in tension with recent declining rotation curve measurements that suggest lower masses, pointing to possible biases in those rotation curve analyses.
  • The systematic uncertainties derived from the mocks are larger than the formal statistical uncertainties of individual methods, implying that most single-method Milky Way mass estimates in the literature are overconfident.
  • The mass profile and virial mass constrain the local dark matter density and velocity distribution, which are inputs for direct dark matter detection experiments.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The paper's demonstration that no single method is unbiased without mock calibration suggests that future studies should adopt similar multi-method validation on cosmological simulations before attaching high confidence to a result.
  • Because the Auriga simulations do not include a Magellanic Cloud analog on its current orbit, the effect of LMC-induced disequilibrium on the mass estimates is not captured by the 24 mocks; future work with LMC-like perturbations could increase the systematic uncertainty or shift the central value.
  • The fact that the NIMBLE-A RRL profile rises steeply while the BHB profile does not hints that the RRL number density reconstruction may be biased by non-uniform sampling; this could be tested by applying NIMBLE-A to the upcoming DESI DR3 with larger RRL sample.
  • The joint estimate's heavy weight (75%) on GME for $M_{200c}$ is concerning because GME is the most biased method at intermediate radii (20% high at 50-80 kpc); if the mock-based calibration fails to capture this bias perfectly, the total mass could be systematically high or low.
Original abstract

We present measurements of the mass of the Milky Way using distant halo stars selected from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2). We apply four dynamical modeling methods to 10,036 RR Lyrae (RRL) and blue horizontal branch (BHB) stars with 6D phase space coordinates that span from $\sim$10 to 95 kpc from the Galactic center, the largest samples of their kind. All methods are applied to mock surveys based on cosmological simulations that include generating individual tracer stars, convolving their phase-space coordinates with DESI and Gaia DR3-like uncertainties, and tailored models of the survey selection functions. By comparing the performance on these mocks, we quantify how systematic biases from both methodology assumptions and galaxy disequilibrium impact each estimate. The mock-based systematics, which differ by method and tracer, are used to correct the individual estimates and to derive joint estimates using a rigorous formalism that accounts for per-method biases and residual correlations between methods. We obtain a joint estimate of the mass within 80 kpc to be $M(r < 80 \mathrm{\,kpc}) = 6.36^{+0.53}_{-0.48} \times 10^{11}$ M$_\odot$ and a virial mass estimate of $M_\mathrm{200c} = 1.19^{+0.14}_{-0.12} \times 10^{12}$ M$_\odot$, with similar results when combining only RRL-based or BHB-based measurements. These results provide a roadmap for future DESI efforts, as well as those in other spectroscopic surveys, to reliably constrain the mass of our Galaxy.

The compiled record

The paper's own sentences, arranged, kept beside the review and separate from it. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-11-05: 1 request, 6,089 input tokens.

What the abstract itself states, as probabilities: claims first 0.12 · states limitation 0.51 · human participants 0.02 · controlled comparison 0.14 · randomized assignment 0.01 · states quantitative result 0.99 · compares with prior results 0.21 · mentions code or data availability 0.03.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

We present measurements of the mass of the Milky Way using distant halo stars selected from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2). We apply four dynamical modeling methods to 10,036 RR Lyrae (RRL) and blue horizontal branch (BHB) stars with 6D phase space coordinates that span from $\sim$10 to 95 kpc from the Galactic center, the largest samples of their kind. All methods are applied to mock surveys based on cosmological simulations that include generating individual tracer stars, convolving their phase-space coordinates with DESI and Gaia DR3-like uncertainties, and tailored models of the survey selection functions. By comparing the performance on these mocks, we quantify how systematic biases from both methodology assumptions and galaxy disequilibrium impact each estimate. The mock-based systematics, which differ by method and tracer, are used to correct the individual estimates and to derive joint estimates using a rigorous formalism that accounts for per-method biases and residual correlations between methods. We obtain a joint estimate of the mass within 80 kpc to be $M(r < 80 \mathrm{\,kpc}) = 6.36^{+0.53}_{-0.48} \times 10^{11}$ M$_\odot$ and a virial mass estimate of $M_\mathrm{200c} = 1.19^{+0.14}_{-0.12} \times 10^{12}$ M$_\odot$, with similar results when combining only RRL-based or BHB-based measurements. These results provide a roadmap for future DESI efforts, as well as those in other spectroscopic surveys, to reliably constrain the mass of our Galaxy.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 We present measurements of the mass of the Milky Way using distant halo stars selected from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2). contribution 1.00 0.97 0.05 asserted 1.00
s1 We apply four dynamical modeling methods to 10,036 RR Lyrae (RRL) and blue horizontal branch (BHB) stars with 6D phase space coordinates that span from $\sim$10 to 95 kpc from the Galactic center, the largest samples of their kind. method 0.82 0.96 0.03 asserted 1.00
s2 All methods are applied to mock surveys based on cosmological simulations that include generating individual tracer stars, convolving their phase-space coordinates with DESI and Gaia DR3-like uncertainties, and tailored models of the survey selection functions. method 0.99 0.92 0.02 asserted 0.99
s3 By comparing the performance on these mocks, we quantify how systematic biases from both methodology assumptions and galaxy disequilibrium impact each estimate. method 0.87 0.94 0.02 asserted 0.99
s4 The mock-based systematics, which differ by method and tracer, are used to correct the individual estimates and to derive joint estimates using a rigorous formalism that accounts for per-method biases and residual correlations between methods. method 0.98 0.95 0.04 asserted 1.00
s5 We obtain a joint estimate of the mass within 80 kpc to be $M(r < 80 \mathrm{\,kpc}) = 6.36^{+0.53}_{-0.48} \times 10^{11}$ M$_\odot$ and a virial mass estimate of $M_\mathrm{200c} = 1.19^{+0.14}_{-0.12} \times 10^{12}$ M$_\odot$, with similar results when combining only RRL-based or BHB-based measurements. result 1.00 0.98 0.93 asserted 1.00
s6 These results provide a roadmap for future DESI efforts, as well as those in other spectroscopic surveys, to reliably constrain the mass of our Galaxy. future work 0.93 0.30 0.04 asserted 0.88

What kind of paper the classifier reports this is: empirical study 1.00 · evidence from analysis of existing data 0.75.

What was examined, and what was not

sources read
  • arXiv listing abstract v1
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
levels run
  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

Figures
Figure 1. Galactocentric radii of the DESI BHB and RRL samples used in this work. Note that individual methods may apply additional cuts to the data, see
Figure 2. Selection functions of the DESI RRL (top) and BHB (bottom) samples as a function of sky position. The BHB selection function is parameterized by the number of times a HEALPix pixel has been observed by DESI. In contrast, the RRL selection function is computed directly on the DESI observing tile grid. limit, which is reasonable given the quality of the Legacy Survey imaging (limit of 𝑟 = 23.9, uncertainties of ≲0.003 mag at 𝑟 = 20, A. Dey et al. 2019) that the selection is based on. In contrast, the RRL selection function is computed on the DESI observing tile grid, and is defined…
Figure 3. Calibration procedure of the emPDF method. Top: Best– fit halo mass and concentration from the mock BHB data versus the true values. Colors denote the simulated halo, while symbols denote the viewing angle. The green ellipse represents the average size of 1𝜎 formal error for each realization. The pink ellipse represents the size of the 1𝜎 statistical error for the 20 realizations, averaged over halo-view combinations. The gray ellipse marks the 1𝜎 total scatter of all halos, viewings, and realizations. The green and pink ellipses are placed arbitrarily, while the gray ellipse is…
Figure 4. Corner plot showing the marginal posterior probabilities and correlations for the GME model parameters applied to the DESI DR2 RRLs (red) and BHBs (blue). Vertical dashed lines show the 16, 50, and 84 percentiles, which are also shown in text above the 1-D histograms for the RRL results. scatter among the inferred parameters across all 480 mock systems (black ellipse) is larger than the formal error. The results of the calibration can be seen in the bottom panel of
Figure 5. The profiles for 𝛽, 𝜎𝑣𝑟 , and 𝜎𝑣tan from applying NIMBLE to one mock survey, compared to their true values. The mock corresponds to the RRL catalogue for Au-6 at the 30◦ viewing. 3.3. NIMBLE NIMBLE (Non-parametrIc jeans Modeling with B￾spLinEs) solves the spherical Jeans equation, using B-splines to fit the tracer density and velocity moments. Under the assumptions of spherical symmetry and dynamical equilib￾rium (c.f., J. Binney & S. Tremaine 2008), the spherical Jeans equation relates the enclosed mass profile 𝑀(< 𝑟) to the tracer density profile 𝜈(𝑟) and the second moments of the…
Figure 6. Example comparison between the four individual meth￾ods, along with the joint estimate, for one mock survey. The mock corresponds to the RRL catalogue for Au-6 at the 30◦ viewing. We present similar results for all mocks in Appendix A. is then included into the final posterior. The full details can be found in Appendix B.2. It is worth mentioning that the 𝑀200c masses are constrained jointly with a free concentra￾tion parameter (𝑐200c), such that the uncertainties are at least two-dimensional. The mass uncertainties quoted here fol￾low from marginalising over concentration. Because…
Figure 7. Performance of the individual methods on all AuriDESI mock catalogues. The mass estimates are shown for 𝑀(𝑟 < 30 kpc), 𝑀(𝑟 < 80 kpc), and 𝑀200c in the top, middle, and bottom panels, respectively. Each point shows the median value, while the error bar is the 16-84 per cent scatter. 5.1. Enclosed mass profile As an example of variation in mass profile recovery, in
Figure 8. Median bias and scatter of each method across all Au￾riDESI mock catalogues. Each row corresponds to an individual method, with the joint estimate at the bottom. The left panels show the bias for the enclosed mass 𝑀(< 𝑟) and the right panels show the bias for 𝑀200c. The GME method bias is only shown from 50 kpc outwards. for the estimate of 𝑀(< 80 kpc) in Au-27). We discuss these correlations in greater detail in Section 5.3. In
Figure 9. The correlation matrix of the eight method–tracer pairs, as measured from their residuals (i.e., after subtracting the relevant true quantity) on the 24 AuriDESI mocks. Correlations smaller than ±0.2 should be considered too small to be meaningful with our limited sample of mocks. file. This could mean that the assumptions baked into the GME method, combined with our extrapolation procedure, are more justified when estimating the total mass of a halo, rather than its profile. Similarly to the joint enclosed mass, the joint 𝑀200c esti￾mates have essentially no bias and the smallest…
Figure 10. Joint constraints on the Milky Way mass profile and the individual method estimates, separately for the RRL (left) and BHB (right) tracers. Shaded regions show the 68 per cent confidence intervals. The results for individual methods are corrected for their biases, following the procedure in Section 4.1
Figure 11. Joint DESI DR2 constraints on the Milky Way mass profile using only RRL-based estimates (dashed), only BHB-based estimates (dotted), and combining all estimates (solid). For GME, the RRL and BHB 𝑀(< 𝑟) results are in modest tension, with the RRL result having a lower mass. This is notable, as for the AuriDESI mocks the GME results were always very close between the two tracers. G. E. Medina et al. (2026) find that the BHB result is somewhat sensitive to a small number of stars with large tangential velocities (𝑣tan > 500km s−1 ), though most of these stars are removed by the RVS…
Figure 13. A comparison of the DESI DR2 joint 𝑀(< 𝑟) profile (solid) to results from the literature. We also show an extrapolated NFW profile (dashed), adopting the joint 𝑀200c constraint and a concentration of 𝑐200c = 12 (see text for details). Top Panel: The results of methods applied to field halo stars, with different colours representing the stellar population (RRL, BHB, K giant, and combined) and outer shapes indicating the methodology (spherical Jeans equations, escape velocity, and distribution function). Bottom Panel: The results of methods applied to different tracers, including…
Figure 14. Comparison of the 𝑀200c measurements from this work to literature values. We include the estimates from our four individual methods using either RRL or BHB tracers, as well as the joint RRL, BHB, and combined estimates. The joint combined estimate is also shown with a vertical line and shaded region. The literature results are grouped and coloured by the tracer used, while the central marker of each result denotes the methodology. References are listed in Appendix C
Figure 15. Performance of the individual methods on all AuriDESI mock RRL catalogues, in a similar manner as the top panel of

Showing 14 of the paper's 16 figures. See all figures in the PDF ↗ Figures reproduced from arXiv:2611.05518 by the authors.

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