Revealing the Dark Matter Profile of the Milky Way

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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.

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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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