Revealing the Dark Matter Profile of the Milky Way

Credit: ESA/Gaia/DPAC

(Can you) Infer the dark matter profile of the

Milky Way from its circular velocity curve

Xiaowei Ou

MIT

In collaboration with Anna-Christina Eilers, Lina Necib, and Anna Frebel

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Vera Rubin         Credit: NASA/NOIRLab

Rubin et al. (1980)

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Vera Rubin         Credit: NASA/NOIRLab

Rubin et al. (1980)

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Rubin et al. (1980)

Evidence

Probe

Vera Rubin         Credit: NASA/NOIRLab

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Local dark matter density

DM

DM

SM

SM

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Local dark matter density

Galactic center 

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-factor

Core vs. Cusp

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DM

SM

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Ou et al. (2024a); arXiv:2303.12838

Infer the dark matter profile

Goal

: 

Measure the circular velocity curve

 for the

Milky Way

Stellar tracers

9

6D

kinematics

Velocities

Positions

Sky

Coordinates

Distances

Proper

Motions

Line-of-sight

Velocities

Ou et al. (2024a); arXiv:2303.12838

Stellar tracers

10

6D

kinematics

Velocities

Positions

Sky

Coordinates

Distances

Proper

Motions

Line-of-sight

Velocities

✓

✓

 APOGEE

Gaia

✓

✓

(

✗

)

Credit: APOGEE

Credit: Gaia/ESA

Ou et al. (2024a); arXiv:2303.12838

A data-driven model for more precise distances*

*: parallax

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Model

Photometry

Spectroscopy

Astrometry

Distances

Features

Labels

Precise

~40% improvement in

relative uncertainty

Ou et al. (2024a); arXiv:2303.12838

12

Ou et al. (2024a); arXiv:2303.12838

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Decline!

Ou et al. (2024a); arXiv:2303.12838

Modeling the curve: generalized NFW vs. Einasto profiles

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Ou et al. (2024a); arXiv:2303.12838

Modeling the curve: generalized NFW vs. Einasto profiles

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gNFW profile 

cannot

 model

the decline

Ou et al. (2024a); arXiv:2303.12838

Modeling the curve: Einasto vs. generalized NFW profiles

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Exponential drop-off in dark matter density outside of R~10 kpc 

needed to explain the decline*

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Ou et al. (2024a); arXiv:2303.12838

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Local dark matter density

Galactic center 

J

-factor

Core vs. Cusp

DM

DM

SM

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Local dark matter density

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Both gNFW and Einasto results are consistent

and also agreeable with literature results

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Credit: de Salas & Widmark (2021)

Ou et al. (2024a); arXiv:2303.12838

Galactic center 

J

-factor

Consistently lower normalized average 

J

-

factor 

Integrated 

J

-factor at 15° from the 

Einasto

an order of magnitude lower

 than from the

fiducial NFW profile

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Caveats

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Ou et al. (2024a); arXiv:2303.12838

Parametric

model

Caveats

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Ou et al. (2024a); arXiv:2303.12838

Parametric

model

Axisymmetry

+

Dynamical

Equilibrium

Caveats

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Parametric

model

Axisymmetry

+

Dynamical

Equilibrium

Negligible higher

order correction

+

Unbiased stellar

population

Ou et al. (2024a); arXiv:2303.12838

23

Infer the dark matter profile

Goal

: 

Measure the circular velocity curve

 for the

Milky Way

(Can you)

How can we understand this measurement?

24

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Non-axisymmetric potential 

Dynamical disequilibrium from recent

mergers

Uncertainty in tracer population profile

Underestimated asymmetric drift

correction 

Observational selection function

Milky Way

mass profile

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:

Non-axisymmetric potential 

Dynamical disequilibrium from recent

mergers

Uncertainty in tracer population profile

Underestimated asymmetric drift

correction 

Observational selection function

How can we understand this measurement?

Milky Way

mass profile

Test with simulation and 

synthetic surveys 

 (Nguyen & Ou et al. 2024)

Test the robustness of the same method 

From stellar sample selection to Jean’s equation

calculation

Compare with underlying truth from the

simulation

26

Wetzel et al. (2023)

arXiv:2306.16475; 

http://ananke.hub.yt/

; 

https://github.com/trivnguyen/ananke_dr3

;

https://github.com/athob/py-ananke

;

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:

Non-axisymmetric potential 

Dynamical disequilibrium from recent

mergers

Uncertainty in tracer population profile

Underestimated asymmetric drift

correction 

Observational selection function

Test with simulation and synthetic surveys

Preliminary

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:

Non-axisymmetric potential 

Dynamical disequilibrium from recent

mergers

Uncertainty in tracer population profile

Underestimated asymmetric drift

correction 

Observational selection function

Test with simulation and synthetic surveys

Preliminary

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:

Non-axisymmetric potential 

Dynamical disequilibrium from recent

mergers

Uncertainty in tracer population profile

Underestimated asymmetric drift

correction 

Observational selection function

Test with simulation and synthetic surveys

Preliminary

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:

Non-axisymmetric potential 

Dynamical disequilibrium from recent

mergers

Uncertainty in tracer population profile

Underestimated asymmetric drift

correction 

Observational selection function

Test with simulation and synthetic surveys

Preliminary

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:

Non-axisymmetric potential 

Dynamical disequilibrium from recent

mergers

Uncertainty in tracer population profile

Underestimated asymmetric drift

correction 

Observational selection function

Test with simulation and synthetic surveys

Preliminary

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Non-axisymmetric potential 

Dynamical disequilibrium from recent

mergers

Uncertainty in tracer population profile

Underestimated asymmetric drift

correction 

Observational selection function

Test with simulation and synthetic surveys

Preliminary

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Test with simulation and synthetic surveys: summary

Preliminary

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Test with simulation and synthetic surveys: summary

Preliminary

Preliminary

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Test with simulation and synthetic surveys: summary

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Preliminary

Preliminary

Preliminary

Conservatively increase the uncertainties:

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Dark matter density: before and after

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38

Infer the dark matter profile

Goal

: 

Measure the circular velocity curve

 for the

Milky Way

(Can you)

39

Infer the dark matter profile

Simulation 

+ 

Synthetic Survey

Goal

: 

Measure the circular velocity curve

 for the

Milky Way

40

Infer the dark matter profile

Simulation 

+ 

Synthetic Survey

Non-parametric

Profiles

Goal

: 

Measure the circular velocity curve

 for the

Milky Way

41

Infer the dark matter profile

Simulation 

+ 

Synthetic Survey

Non-parametric

Profiles

Additional

Probes

Goal

: 

Measure the circular velocity curve

 for the

Milky Way

42

Summary:

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Backup slides

Comparison with the current literature

44

Comparison

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46

More tests on the robustness of the curve and the fit

Varying baryonic models yields

consistent dark matter halo

fitting results

Credit: Jiao et al. (2023)

47

Dynamical mass of the Milky Way from different tracers

Credit: Wang et al. (2020)

Ou et al. (2024a); arXiv:2303.12838

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Dynamical mass 

of the Milky Way

 from different tracers

(Courtesy of Eugene Vasiliev)

Best-fit model from Ou et al. (2024a)

Annihilation cross section

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Tension with dwarf galaxy constraint!

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Dark matter models in general

Self-interacting dark matter

Fuzzy dark matter

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Baryonic feedback

●

intense star formation episodes

with decreased rate of dark

matter accretion rate at the

center

Non-equilibrium stellar kinematics

●

non-axisymmetric potential; 

●

recent mergers;

●

tracer population profile;

●

underestimated asymmetric

drift correction from vertical

motion

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Ren et al. (2019)

Bernal et al. (2018)

Test with simulation and synthetic surveys

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Preliminary

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Preliminary

Test with simulation and synthetic surveys

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Preliminary

Test with simulation and synthetic surveys

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Preliminary

Test with simulation and synthetic surveys

Xiaowei Ou and collaborators aim to infer the dark matter profile of the Milky Way by measuring its circular velocity curve. By utilizing stellar tracers and data-driven models for precise distances, they seek to improve our understanding of dark matter distribution in our galaxy. Their research involves detailed kinematics, proper motions, and line-of-sight velocities, providing valuable insights into the elusive nature of dark matter. This groundbreaking study promises a significant advancement in the field of astrophysics.

• Milky Way
• Dark Matter
• Galactic Dynamics
• Astrophysics
• Stellar Tracers

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1. (Can you) Infer the dark matter profile of the Milky Way from its circular velocity curve Xiaowei Ou MIT In collaboration with Anna-Christina Eilers, Lina Necib, and Anna Frebel Credit: ESA/Gaia/DPAC Xiaowei Ou 1

2. Vera Rubin Credit: NASA/NOIRLab Rubin et al. (1980) Xiaowei Ou 2

3. Vera Rubin Credit: NASA/NOIRLab Rubin et al. (1980) Xiaowei Ou 3

4. Vera Rubin Credit: NASA/NOIRLab Circular velocity curves Rubin et al. (1980) Dark matter Xiaowei Ou 4

5. Milky Way Xiaowei Ou 5

6. DM SM Direct detection Milky Way Local dark matter density DM SM Xiaowei Ou 6

7. DM SM Direct detection Milky Way Local dark matter density DM SM SM SM Indirect detection Galactic center J-factor Core vs. Cusp DM DM Xiaowei Ou 7

8. Goal: Measure the circular velocity curve for the Milky Way Infer the dark matter profile Xiaowei Ou Ou et al. (2024a); arXiv:2303.12838 8

9. Stellar tracers 6D kinematics Positions Velocities Sky Proper Motions Line-of-sight Velocities Distances Coordinates Xiaowei Ou Ou et al. (2024a); arXiv:2303.12838 9

10. Stellar tracers 6D kinematics Positions Velocities Sky Proper Motions Line-of-sight Velocities Distances Coordinates ( ) APOGEE Gaia Credit: Gaia/ESA Credit: APOGEE Xiaowei Ou Ou et al. (2024a); arXiv:2303.12838 10

11. A data-driven model for more precise distances* Features Photometry Precise Spectroscopy Model Distances Labels ~40% improvement in relative uncertainty Astrometry *: parallax Xiaowei Ou Ou et al. (2024a); arXiv:2303.12838 11

12. Xiaowei Ou Ou et al. (2024a); arXiv:2303.12838 12

13. Decline! Xiaowei Ou Ou et al. (2024a); arXiv:2303.12838 13

14. Modeling the curve: generalized NFW vs. Einasto profiles Xiaowei Ou Ou et al. (2024a); arXiv:2303.12838 14

15. Modeling the curve: generalized NFW vs. Einasto profiles gNFW profile cannot model the decline Xiaowei Ou Ou et al. (2024a); arXiv:2303.12838 15

16. Modeling the curve: Einasto vs. generalized NFW profiles Einasto (cored) gNFW Exponential drop-off in dark matter density outside of R~10 kpc needed to explain the decline* Ou et al. (2024a); arXiv:2303.12838 Xiaowei Ou 16

17. DM SM Direct detection Milky Way Local dark matter density DM SM SM SM Indirect detection Galactic center J-factor Core vs. Cusp DM DM Xiaowei Ou 17

18. Local dark matter density DM density at 8kpc in the MW: 0.45 GeV/cm3 Both gNFW and Einasto results are consistent and also agreeable with literature results Credit: de Salas & Widmark (2021) Xiaowei Ou Ou et al. (2024a); arXiv:2303.12838 18

19. Galactic center J-factor Consistently lower normalized average J- factor Integrated J-factor at 15 from the Einasto an order of magnitude lower than from the fiducial NFW profile Xiaowei Ou 19

20. Caveats Parametric model Xiaowei Ou Ou et al. (2024a); arXiv:2303.12838 20

21. Caveats Axisymmetry + Dynamical Equilibrium Parametric model Xiaowei Ou Ou et al. (2024a); arXiv:2303.12838 21

22. Caveats Axisymmetry + Dynamical Equilibrium Negligible higher order correction + Unbiased stellar population Parametric model Xiaowei Ou Ou et al. (2024a); arXiv:2303.12838 22

23. Goal: Measure the circular velocity curve for the Milky Way (Can you) Infer the dark matter profile Xiaowei Ou 23

24. How can we understand this measurement? Poses questions on these topics: Non-axisymmetric potential Dynamical disequilibrium from recent mergers Milky Way mass profile Uncertainty in tracer population profile Underestimated asymmetric drift correction Observational selection function Xiaowei Ou 24

25. How can we understand this measurement? Poses questions on these topics: Non-axisymmetric potential Dynamical disequilibrium from recent mergers Simulation + Synthetic Survey Milky Way mass profile Uncertainty in tracer population profile Underestimated asymmetric drift correction Observational selection function Xiaowei Ou 25

26. Test with simulation and synthetic surveys (Nguyen & Ou et al. 2024) Test the robustness of the same method From stellar sample selection to Jean s equation calculation Compare with underlying truth from the simulation Wetzel et al. (2023) arXiv:2306.16475; http://ananke.hub.yt/; https://github.com/trivnguyen/ananke_dr3; https://github.com/athob/py-ananke; Xiaowei Ou 26

27. Test with simulation and synthetic surveys Poses questions on these topics: Non-axisymmetric potential Dynamical disequilibrium from recent mergers Uncertainty in tracer population profile Underestimated asymmetric drift correction Observational selection function Xiaowei Ou 27

28. Test with simulation and synthetic surveys Poses questions on these topics: Non-axisymmetric potential Dynamical disequilibrium from recent mergers Uncertainty in tracer population profile Underestimated asymmetric drift correction Observational selection function Xiaowei Ou 28

29. Test with simulation and synthetic surveys Poses questions on these topics: Non-axisymmetric potential Dynamical disequilibrium from recent mergers Uncertainty in tracer population profile Underestimated asymmetric drift correction Observational selection function Xiaowei Ou 29

30. Test with simulation and synthetic surveys Poses questions on these topics: Non-axisymmetric potential Dynamical disequilibrium from recent mergers Uncertainty in tracer population profile Underestimated asymmetric drift correction Observational selection function Xiaowei Ou 30

31. Test with simulation and synthetic surveys Poses questions on these topics: Non-axisymmetric potential Dynamical disequilibrium from recent mergers Uncertainty in tracer population profile Underestimated asymmetric drift correction Observational selection function Xiaowei Ou 31

32. Test with simulation and synthetic surveys Poses questions on these topics: Non-axisymmetric potential Dynamical disequilibrium from recent mergers Uncertainty in tracer population profile Underestimated asymmetric drift correction Observational selection function Xiaowei Ou 32

33. Test with simulation and synthetic surveys: summary Xiaowei Ou 33

34. Test with simulation and synthetic surveys: summary Xiaowei Ou 34

35. Test with simulation and synthetic surveys: summary Dominant source of uncertainty varies across simulated galaxies Xiaowei Ou 35

36. Conservatively increase the uncertainties: Einasto (cored) gNFW Both Einasto and gNFW fits are plausible. Xiaowei Ou 36

37. Dark matter density: before and after DM density at 8kpc in the MW: 0.37 vs. 0.49 GeV/cm3 gNFW fit is consistent with the fiducial NFW profile. Cusp or Cored? Xiaowei Ou 37

38. Goal: Measure the circular velocity curve for the Milky Way (Can you) Infer the dark matter profile Xiaowei Ou 38

39. Goal: Measure the circular velocity curve for the Milky Way Simulation + Synthetic Survey Infer the dark matter profile Xiaowei Ou 39

40. Goal: Measure the circular velocity curve for the Milky Way Simulation + Synthetic Survey Infer the dark matter profile Non-parametric Profiles Xiaowei Ou 40

41. Goal: Measure the circular velocity curve for the Milky Way Simulation + Synthetic Survey Additional Probes Infer the dark matter profile Non-parametric Profiles Xiaowei Ou 41

42. Summary: Measuring circular velocity curve alone is not sufficient to understand the nature of dark matter in the Milky Way. Xiaowei Ou 42

43. Backup slides Xiaowei Ou

44. Comparison with the current literature Xiaowei Ou 44

45. Comparison Xiaowei Ou 45

46. More tests on the robustness of the curve and the fit Varying baryonic models yields consistent dark matter halo fitting results Credit: Jiao et al. (2023) Xiaowei Ou 46

47. Dynamical mass of the Milky Way from different tracers Credit: Wang et al. (2020) Xiaowei Ou Ou et al. (2024a); arXiv:2303.12838 47

48. Dynamical mass of the Milky Way from different tracers Best-fit model from Ou et al. (2024a) (Courtesy of Eugene Vasiliev) Xiaowei Ou 48

49. Annihilation cross section Lower J-factor increases the inferred annihilation cross section Tension with dwarf galaxy constraint! Leane et al. (2022) Xiaowei Ou 49

50. Dark matter models in general Baryonic feedback intense star formation episodes with decreased rate of dark matter accretion rate at the center Ren et al. (2019) Self-interacting dark matter Non-equilibrium stellar kinematics Fuzzy dark matter non-axisymmetric potential; recent mergers; tracer population profile; underestimated asymmetric drift correction from vertical motion Bernal et al. (2018) Xiaowei Ou 50

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