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A Method for Obtaining Detailed Abundances of Extragalactic Globular Clusters

A Method for Obtaining Detailed Abundances of Extragalactic Globular Clusters. LMC- NGC 2005. MW- 47Tuc. NGC 5128. w/ Andy McWilliam (Carnegie Obs.) Scott Cameron, Janet Collucci (UM). The goal: formation histories of galaxies. Galaxy #1, Milky Way:

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A Method for Obtaining Detailed Abundances of Extragalactic Globular Clusters

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  1. A Method for ObtainingDetailed Abundances of Extragalactic Globular Clusters LMC- NGC 2005 MW- 47Tuc NGC 5128 w/ Andy McWilliam (Carnegie Obs.) Scott Cameron, Janet Collucci (UM)

  2. The goal: formation histories of galaxies Galaxy #1, Milky Way: Formation: halo  bulge/thick disk  thin disk Evidence: abundances (Fe,O,Mg,Eu…) & kinematics (bulk, streams) (1) Stars : *timescales*, substructure (recent: Ivans et al 2003) halothickbulgethin Prochaska et al 2004 Yanny et al 2003

  3. The goal: formation histories of galaxies Galaxy #1, Milky Way: Formation: halo  bulge/thick disk  thin disk Evidence: abundances & kinematics (2) Globular clusters: easy targets! date-able! old! Parmentier et al 2000

  4. Formation history of other galaxies: Local Group: getting details (limitation: flux) Evidence: Supergiants (Venn et al 04, McWilliam & Smecker-Hanes 04) bright = young! (no history) Venn et al 2004

  5. Formation history of other galaxies: Beyond…: different tools (limitation: flux & resolution) Evidence: integrated light - broad-band colors + [stellar population models] general: red (old/metal-rich)blue (young/metal-poor) - line indices + [stellar population models] Lick System (Worthey et al, Trager et al, Gonzalez et al), Rose

  6. Formation history of other galaxies: Beyond: low resolution spectra (>2Å) +stellar population models Limitations: 1-Age/metallicity degenerate (young/z-rich  old/z-poor) 2- z vs Fe ? Mg, O,Ca…? calibration: abundances ratios? * multiple generations of star formation. blue Age Z Worthy 1998

  7. Formation history of other galaxies : Age Beyond: low resolution spectra (>2Å) +stellar population models Limitations: 1-Age/metallicity degenerate (young/z-rich  old/z-poor) 2- z vs Fe ? Mg,O,Ca…? calibration: abundances ratios? Recent: Principle component analysis: PC1 metallicity Strader,Brodie ’04,Burstein et al 04 Globular clusters* Z Forbes et al. 04

  8. Formation history of other galaxies : • Beyond: integrated light of GCs • Principle component analysis: PC1 metallicity • Forbes et al.’04, Strader,Brodie ’04, Burstein et al 04 • [Fe/H] ( or z):  0.1 dex (optimistic?) • Age: 3 Gyrs • [E/Fe]:  0.1-0.2 (?) (“” or “enhanced”) • C,N; O,Mg,Si,Ca; Cr; Na • produced in SNII, SNI, and AGB stars • Missing: z vs. Fe vs. , self-enrichment, IMF • **M31: young (0.5-5Gyr), disk GC system • (Beasley 04, Burstein 04, Morrison 04) Forbes et al. 04

  9. Why high resolution? Globular cluster spectra: [Fe/H]  -1 Mg2 Mgb 0.17 Å Perrett et al 2002, M31 5.1 Å

  10. Why globular clusters? Milky Way GCs: v 2-18 (R  7-60 k) -7 > Mv > -9 10,000 < R < 30,000 E, Sa galaxies: v 150km (R  850)

  11. Why get detailed abundances? Element-yield review: < 2M: H C 2-8M: H C/O/Ne, n-capture (s-process) [binary] SN Type I: Fe-peak 8-30M: HFe, SN Type II: Fe-peak, -elements, n-capture (r-process) Punch line: “-elements” ………………… SN II:fast (Myrs) (O,Mg, Si,S,Ca, Ti; Al,Na?) Fe:………………………………… SN I: slow(Gyrs) SN II:fast Fe-peak (21-30p) :………… SN I: slow (Sc, V, Cr, Mn,SN II:fast Co, Ni, Cu, Zn) Fe-dep. yields? Heavy (Ba, Y, Zr, La, Sr…) ………… SN I: slow (Eu, Sm, Nd…)………………… SN II:fast halothickbulge thin Prochaska et al 2000, Bensby et al 2004

  12. Why get detailed abundances? Metal poor halothickbulge thin Element-yield review: e(X) = relative number = (x/H) = log (N(X)/N(H)) + 12 [Fe/H] = log(Fe/H) - log(Fe/H) [X/Fe] = e(X/Fe) - e(X/Fe) z = mass fraction beyond He z= 0.019 enriched deficient Prochaska et al 2000

  13. Why get detailed abundances? Metal poor halothickbulge thin [/Fe] vs [Fe/H] : formation timescale [Eu/Fe] : r-process (SNII) IMF, nucleosynthesis [Ba/Fe] : s-process (SNI, low-m), IMF, nucleosynthesis enriched *1- Detailed formation of galaxy #2 2- test stellar population models 3- understand the line indices deficient Prochaska et al 2000

  14. The goal: GC abundances outside the local group… Requirements: S/N  50 Ha R  10,000 – 30,000 3500-9500 A MIKE + Magellan: GC limit  18 V mag Bernstein, Shectman, Gunnels, installed Nov 2002

  15. The goal: Galaxies outside the local group… NGC 5128: S0 (Dec = -43) D = 3.5 Mpc m-M = 27.7 GCs: Mv 17-20 mag (RGB tip: v  25-26 mag) (young supergiants) Rejkuba 2001 (UVES/FORS imaging)

  16. The goal: Galaxies outside the local group… NGC 1313: SBd (Dec = -66) D = 4.4 Mpc m-M = 28 GC: v  17-20 mag (RGB tip: v  25-26 mag)

  17. High resolution analysis — A Training Set The Milky Way Globular Clusters (= 14-16 mag/asec2):

  18. High resolution analysis — A Training Set Milky Way GCs:GC Integrated Light Spectra (ILS) at different abundances & masses [Fe/H] = -2.0 v = 4km/s V = -6 mag vs [Fe/H]=-0.76 v = 12km/s V = -9 mag

  19. High resolution analysis — A Training Set Milky Way GCs: ILS spectrum vs single RGB NGC 104 (47Tuc): [Fe/H] = -0.76 v = 12 km/s V = -9 mag Eu in RGB: EW= 16 mÅ!

  20. A Training Set: • Milky Way: 7 clusters (= 14-16 mag/asec2): • [Fe/H] Mv • ngc 6397 -1.95 -6.6 • ngc 6093 -1.75 -8.23 • ngc 6752 -1.42 -7.7 • ngc 2808 -1.36 -9.35 • ngc 362 -1.16 -8.4 • ngc 104 (47Tuc) -0.76 -9.4 • ngc 6388 -0.60 -9.8 • LMC: 7 clusters to date (m-M=18.5, mv=10 mag, v= 14-16 mag/asec2) • ngc 2019, 2005 [Fe/H] ≈ -2.0 old (>5 Gyr) • ngc 1866, 1978 [Fe/H] ≈ ? intermediate (0.1-1.5 Gyr) • ngc 1711, 2002, 2100 [Fe/H] ≈ -0.6 young (<0.1 Gyr)

  21. Training Set: observations Milky Way (6) + LMC (8) : Integrated light spectra individual stars MW: 47Tuc 1”x4” slit 32”x32” LMC: n1711 1”x4” slit 12”x12”

  22. Training Set: analysis? • Individual stars:EWobs vs. Modeled stellar atmospheres • - Kurucz stellar atmosphere grids (ATLAS9) • Teff *(B-V)obs • log g *(V) obs •  *(1-2 km/s) • [Fe/H] •  mass,T,P,N(e-) • - MOOG (Sneden 1998), for each line: • , EP, loggf, (X) •  EWmod • *tune to get same (Fe) • for all FeI,II lines.

  23. Training Set: analysis Integrated light:EWobsvs ??? RESOLVED globular cluster --> observed CMD! Build up an atmosphere model.

  24. Training Set: analysis Integrated light:EWobsvs composite model atmosphere - Kurucz stellar atmosphere grids (ATLAS9) Teff (B-V)obs log g (V) obs   log g [Fe/H] - MOOG (Sneden v.1998), for each line: , EP, loggf, (X)  EW per box.  Combine to get light-weight EW * NO PARAMETER TUNING

  25. Training Set: step 0 - observed CMD RESOLVED globular cluster --> observed CMD! • Training set issues: • scanned core only! • rare stars not included.

  26. Training Set: step 0 - observed CMD (n6397) NGC 6397: Stable FeI solution: Is (Fe) stable with lines’ Excitation Potential Checks Teff, reddening: Population of energy state depends on T

  27. Training Set: step 0 - observed CMD (n6397) NGC 6397: Stable FeI solution: Is (Fe) stable with lines’ wavelength Checks fraction of flux from hot/cool stars: blue light -- from hot stars with weak lines red light -- cool stars with strong lines.

  28. Training Set: step 0 - observed CMD (n6397) NGC 6397: Stable FeI solution: Is (Fe) stable with lines’ EW. Checks  ( log g, 1-2 km/s) Microturbulence decreases saturation of strong lines. (0km/s larger covering factor in wavelength space. Larger velocities “spread” the atoms in wavelength space, decreasing saturation.)

  29. Training Set: step 0 - observed CMD (n6397) Balmer lines: equivalent widths (EW) and profiles example: NGC 6397 - member RGB star NGC 6397 - ILS 47 Tuc - ILS Broadened by hot stars Age/Metallicity: Old/metal-rich = red (cool) Young/metal-poor = blue (hot)

  30. Training Set: step 0 - observed CMD (n6397) Balmer lines: H, H, H, H — EW and profiles —ILS NGC 6397 —synthesized lines from the observed CMD (w/ BHB) (w/o BHB) Age/Metallicity + HB morphology Observational constraint: flux in / color of HB (otherwise, HB is a wild card…Age? mass loss?)

  31. Training Set: step 0 - observed CMD (n6397) NGC 6397: Derived abundances — consistent with results from single stars! ILS analysis [Fe/H] x (x) N-lines /N[X/Fe] [X/Fe] Cr 2.93 3 0.26 0.18 -0.53 FeI 5.30 63 0.26 0.03 -2.2 -1.97 FeII 5.35 8 0.35 0.12 -2.15 -2.20 NiI 4.18 2 0.09 0.09 0.13 a-elements: MgI 5.47 4 0.45 0.23 0.10 CaI 4.43 8 0.15 0.06 0.28 0.64 TiI,II 3.20 13 0.38 0.11 0.37 0.36 n-capture BaII 0.02 7 0.22 0.08 0.02 0.10 (Castihlo 2000)

  32. RECAP — What (we think) we know from analysis of a RESOLVED GC (n6397): 1. the composite stellar models can work! 2. We have tools to identify problems! Balmer lines  Teff (CMD: reddening, {age, [Fe/H]}, HB morph) FeI (EW, EP, ) FeI vs Fe II log g (CMD: giants vs dwarfs, age) (ionized lines sensitive to N(e-))

  33. Training Set: step 1 - isochrone CMD (47Tuc) What if the cluster is unresolved? (e.g. NGC 1313 -379) GCs are a single age population! Isochrones - stellar evolution models predict cluster CMD at given age. Padova (Girardi et al 2000) BaSTI (Pietrinferni et al 2004) + Kroupa IMF (Kroupa & Boily 2002), flattens below 0.5M + Normalize #’s of stars to observed Mv (In the case of a faint cluster, don’t make boxes w/ <1 star)

  34. Training Set: step 1 - isochrone CMD (47Tuc) Do they reproduce the CMD? 2 problems: 1. mass segregation (for training set) 47Tuc 2. AGB bump (general) Spitzer & Hart 1971 MW: eg. Ferraro 1997 LMC: eg.Grijs et al 2002 Schiavon et al 2002

  35. Training Set: step 1 - isochrone CMD (47Tuc) Do they reproduce the CMD? Adjustments: 1- remove stars 3 mag below turn-off. 2- increase fraction in AGB bump.

  36. Training Set: step 1 - isochrone CMD (4 GCs) 1- Balmer lines - H, H, H, H EW and profile Models: age = 6.3 Gyr z = 0.0001-0.01 * note blends

  37. Training Set: step 1 - isochrone CMD (4 GCs) 1- Balmer lines - H, H, H, H EW’s Color = AGE NGC 6397 match: Age ≈ 6.3 Gyr [A/H] ≈ -2 Models change very little > 3 Gyrs

  38. Training Set: step 1 - isochrone CMD (4 GCs) 1- Balmer lines - H, H, H, H EW’s and profiles Models: age = 10 Gyr z = 0.0001-0.01 *note blends are worse!! (metal rich GC) Need to synthesize blended lines

  39. Training Set: step 1 - isochrone CMD (4 GCs) 1- Balmer lines - H, H, H, H EW’s 47Tuc match: Age ≈ 10-12 Gyr [A/H] ≈ -0.9

  40. Training Set: step 2 - isochrone CMD (47 Tuc) 2- FeI & FeII (Padova, unadjusted isochrones)

  41. Training Set: step 2 - isochrone CMD (47 Tuc) 2- FeI & FeII [FeI/H]  input [A/H]  input age (Padova, unadjusted isochrones)

  42. Training Set: step 2 - isochrone CMD (47 Tuc) 2- FeI & FeII [FeI/H]  input [A/H]  input age +/-0.1 !! at <1 Gyr: young = hot modeled lines=weak. at >1 Gyr: models not changing much (Padova, unadjusted isochrones)

  43. Training Set: step 2 - isochrone CMD (47 Tuc) FeI checks: no FeI slope w/ EP if: age > 2 & [A/H] < -1 w/  if: age > 3 w/ EW if: age > 3 Gyrs

  44. Training Set: step 2 - isochrone CMD (47 Tuc) 2- FeI & FeII [FeI/H]  input [A/H]  input age +/- 0.05 !! [FeII/H]  input [A/H]  input age (Padova, unadjusted isochrones)

  45. Training Set: step 2 - isochrone CMD (47 Tuc) The age-metallicity degeneracy!

  46. Training Set: step 2 - isochrone CMD (47 Tuc) 2- FeI & FeII [FeI/H]  input [A/H]  input age +/- 0.05 !! [FeII/H]  input [A/H]  input age expected age to increase giant:dwarf… g … N(e-). (Padova, unadjusted isochrones)

  47. Training Set: step 2 - isochrone CMD (47 Tuc) 2- FeI & FeII [FeI/H]  input [A/H]  input age +/-0.05 !! (statistical) [FeII/H]  input [A/H] ( N(e-))  input age [Fe/H]=[FeII/H]: [Fe/H]  -0.6 age = 5-16 Gyrs Best FeI solution: [Fe/H]  -0.6 (10Gyr, [A/H]=-0.68) (Padova, unadjusted isochrones)

  48. Training Set: step 2 - isochrone CMD (47 Tuc) Abundance results for 47Tuc! Isochrone analysis (w/ mass segregation + boosted AGB dump) CONSISTENT with solution from individual stars. unambiguous[Fe/H]=0.7 1- iron peak x (x)  N-lines[X/Fe][Fe/H] [X/Fe](C’04) Sc II 2.53 ... 1 +0.13 +0.13 V I 3.40 0.31 5 +0.11 +0.05 Cr I 4.87 0.14 3 -0.19 +0.11 Mn I 4.49 0.30 4 -0.31 -0.29 Fe I 6.78 0.24 71 -0.73 -0.67, -0.79 (KI’03) Fe II 6.81 0.15 8 -0.70 -0.56 Ni I 5.47 0.18 12* -0.05 +0.06 Carretta et al 2004 Kraft & Ivans 2003 (Padova, 10Gyr, [A/H]=-0.68, adjusted)

  49. Training Set: step 2 - isochrone CMD (47 Tuc) Abundance results for 47Tuc! (Padova, 10Gyr, [A/H]=-0.68, adjusted)

  50. Training Set: step 2 - isochrone CMD (47 Tuc) Abundance results for 47Tuc! 2. -elements x (x)  N-lines[X/Fe] [X/Fe](CG04) [O I] 8.45 ... 1 +0.45 +0.23 Mg I 7.02 ... 1 +0.17 +0.40 Si I 7.16 0.21 6 +0.33 +0.30 Ca I 5.81 0.24 12 +0.19 +0.20 Ti I 4.55 0.24 13 +0.34 +0.26 Ti II 4.68 0.16 3 +0.44 +0.38 3- non-alpha, light elements Na I 5.97 0.19 3 +0.38 +0.23 Al I 6.19 0.02 2 +0.43 Carretta & Gratton 2004  (Padova, 10Gyr, [A/H]=-0.68, adjusted)

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