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Massive star feedback – from the first stars to the present

Massive star feedback – from the first stars to the present. Jorick Vink (Imperial College London, UK). Outline. Why predict dM/dt ? (as a function of Z?) Methods: CAK & Monte Carlo Results OB, LBV & WR winds Cosmological implications? Look into the Future. Why predict Mdot ?.

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Massive star feedback – from the first stars to the present

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  1. Massive star feedback – from the first stars to the present Jorick Vink (Imperial College London, UK)

  2. Outline • Why predict dM/dt ? (as a function of Z?) • Methods: CAK & Monte Carlo • Results OB, LBV & WR winds • Cosmological implications? • Look into the Future

  3. Why predict Mdot ? • Energy & Momentum input into ISM

  4. Why predict Mdot ? • Energy & Momentum input into ISM • Stellar Evolution

  5. Evolution of a Massive Star B[e] O

  6. Why predict Mdot ? • Energy & Momentum input into ISM • Stellar Evolution • Explosions: SN, GRBs

  7. Why predict Mdot ? • Energy & Momentum input into ISM • Stellar Evolution • Explosions: SN, GRBs • Final product: Neutron star, Black hole

  8. Why predict Mdot ? • Energy & Momentum input into ISM • Stellar Evolution • Explosions: SN, GRBs • Final product: Neutron star, Black hole • X-ray populations in galaxies

  9. Why predict Mdot ? • Energy & Momentum input into ISM • Stellar Evolution

  10. Why predict Mdot ? • Energy & Momentum input into ISM • Stellar Evolution • Stellar Spectra

  11. Why predict Mdot ? • Energy & Momentum input into ISM • Stellar Evolution • Stellar Spectra • Analyses of starbursts

  12. Why predict Mdot ? • Energy & Momentum input into ISM • Stellar Evolution • Stellar Spectra • Analyses of starbursts • Ionizing Fluxes

  13. Why predict Mdot ? • Energy & Momentum input into ISM • Stellar Evolution • Stellar Spectra

  14. Why predict Mdot ? • Energy & Momentum input into ISM • Stellar Evolution • Stellar Spectra • Stellar “Cosmology”

  15. From Scientific American

  16. Why predict Mdot ? • Energy & Momentum input into ISM • Stellar Evolution • Stellar spectra • “Stellar cosmology”

  17. Observations of the first stars

  18. Goal: quantifying mass loss a function of Z (and z) What do we know at solar Z ?

  19. Radiation-driven wind by Lines Lucy & Solomon (1970) Castor, Abbott & Klein (1975)  CAK STAR Fe dM/dt = f (L, Mass, Temp, Z)

  20. 1. CAK Formalism

  21. 1. CAK Formalism

  22. 1. CAK Formalism  dM/dt & V(r)

  23. 1. CAK Formalism

  24. Momentum problem in O star winds A systematic discrepency

  25. 2. Monte Carlo approach (Abbott & Lucy 1985)

  26. Assumptions in line-force models • Static • One fluid • Spherical • Homogeneous, no clumps

  27. Two O-star approaches 1. CAK-type  Line force approximated  v(r) predicted CAK, Pauldrach (1986), Kudritzki (2002) 2. Monte Carlo  V(r) adopted  Line force computed – for all radii  multiple scatterings included Abbott & Lucy (1985) Vink, de Koter & Lamers (2000,2001)

  28. Monte Carlo Mass loss comparison (Vink et al. 2000) No systematic discrepency anymore !

  29. Wind momentum-Luminosity relation O stars (Vink et al. 2000)

  30. B Supergiants Wind-Momenta Vink et al. (2000)

  31. The mass loss of LBVs Vink & de Koter (2002)

  32. Success of Monte Carlo at solar Z • O-star Mass loss rates • Prediction of the bi-stability jump • Mass loss behaviour of LBVs  Monte Carlo mass-loss used in stellar models in Galaxy

  33. dM/dt = f(Z): potential effects • In CAK: dM/dt proportional to k = f(Z) • Power-law exponent: log(dM/dt) = m log(Z) • More ionization changes? (bi-stability) • Power-law for all Z? • Power-law flattening?

  34. O star mass-loss Z-dependence (Vink et al. 2001)

  35. O star mass-loss Z-dependence

  36. O star mass-loss Z-dependence

  37. Which metals are important? solar Z Fe CNO H,He low Z At lower Z : Fe  CNO

  38. Z-dependence of WR winds Vink & de Koter (2005) astro-ph/0507352

  39. Conclusions • Successful MC Models at solar Z • O star winds are Z-dependent (Fe) • WR winds are Z-dependent (Fe)  GRBs • Low-Z WC models: flattening of this dependence • Below log(Z/Zsun) = -3  “Plateau”  Mass loss may play a role in early Universe

  40. Future Work • Solving momentum equation • Compute Mdot at Z=0 • Wind Clumping • Wind geometry at low Z

  41. 2-step Approach: • Compute model atmosphere, ionization stratification, level populations • Monte Carlo to compute radiative force (line and continuum opacity)

  42. The bistability Jump  dM/dt increases by factor 5  Wind Density by factor 10 (Vink et al. 1999)

  43. Mass loss Recipe

  44. Consistent mass-loss rate

  45. Non-consistent velocity law WC8 Beta = 1

  46. The First Stars Credit: V. Bromm

  47. Why predict Mdot ? • Stellar evolution - X-ray populations in galaxies - Gamma-ray bursts • Stellar spectra & ionizing fluxes - Analyses of galaxy spectra - Reionization of Universe • Energy & Momentum input into ISM

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