Lectures on Early-type galaxies PART II (M. Bernardi)

1. Lectures on Early-type galaxies PART II(M. Bernardi)

2. Plan for today: • Galaxy formation models • Stellar Populations • Age/Metallicity/a-enhancement • Lick Indices and Colors • Correlations with L, s and environment • Comparison between Models and Observations • Environment and Evolution in the SDSS • Constraints on galaxy formation models

3. Initial fluctuations are seeds of structure Growth is hierarchical; smaller dark matter ‘halos’ merge to form larger ones Gas cools within ‘halos’ Galaxies

4. Gastrophysics of galaxy formation

6. Hierarchical models predict the spatial distribution of galaxies (successfully) • Also describe galaxy formation and evolution

7. CDM: hierarchical gravitational clustering: The most massive galaxies are the last to be assembled, though their stars may be oldest

8. Age of stellar population may be different from that of host dark matter halo • Measure ages of stellar populations to constrain galaxy formation models

9. Theoptical portion of the galaxy spectrum is due to the light of stellar photospheres K giant star Typical elliptical galaxy

11. INGREDIENTS FOR STELLAR POPULATION MODELS • Stellar library (observables) • Stellar evolution codes (age/metal) • + • Star Formation Rate • Metal enrichment law • Initial Mass Function  MODEL Linear combination of models  galaxy properties (fluxes, colors, and spectra of galaxies)

12. INGREDIENTS FOR STELLAR POPULATION MODELS (Isochrone Synthesis) Spectral energy distribution at time t: • Star Formation Rate y(t) • Instantaneous burst: y(t) ~ d(t) • (usually called “single stellar population” model SSP) • Exponential declining: y(t) ~ t-1 exp(-t/t) • Single burst of length t: y(t) ~ t-1 for t ≤t; y(t) = 0 fort > t • Constant: y(t) = const • where t is the e-folding timescale

13. INGREDIENTS FOR STELLAR POPULATION MODELS (Isochrone Synthesis) Spectral energy distribution at time t: • Star Formation Rate y(t) • Metal enrichment law z(t) • Sl[t’,z(t-t’)] is the power radiated per unit wavelength per unit initial mass by a “single stellar population” (SSP) of age t’ and metallicity z(t-t’) • Sl[t’,z(t-t’)] is the sum of the spectra of stars defining the isochrone of a SSP of age t’ and metallicity z(t-t’) • It is computed by interpolating the isochrone at age t’ from the tracks in the HR diagram

14. INGREDIENTS FOR STELLAR POPULATION MODELS (Isochrone Synthesis) Spectral energy distribution at time t: • Star Formation Rate y(t) • Metal enrichment law z(t) • 3) Initial Mass Function f(m) defined such that f(m)dm is the number of stars born with masses between m and m+dm mc = 0.08 M s = 0.69

15. Evolution of the spectrum of a “single stellar population” (SSP) model Age (Gyrs)

16. Colors and M/L vs Age for a solar metallicity model

17. Comparison model/data --- model spectrum --- observed spectrum

18. Problem: Age-Metallicity degeneracy Stars weak in heavy elements are bluer than metal-rich stars (line blanketing effects and higher opacities) Galaxy models must account for  metallicity changes increase of heavy elements due to SN explosions

19. Different Age – Same Metallicity Easy to separate young and old populations of the same metallicity

20. Same Age – Different Metallicity Easy to separate coeval populations of different metallicity

21. Age – Metallicity degeneracy Hard to separate populations which have a combination of age and metallicity Degeneracy: (∂ lnt/∂ lnZ) ~ -3/2

22. BUT… Although the continuum spectrum is similar, the absorption lines are stronger for higher metallicity SO…

23. How to disentangle age from metallicity? • Absorption lines (e.g. Lick indices) Average pseudo-continuum flux level: Fp =  Fl dl/(l1 –l2) EW =  (1-FIl/FCl) dl where FCl represents the straight line connecting the midpoints of the blue and red pseudo-continuum levels Hb Mgb Fe l2 l1 l2 l1

24. Lick Indices

25. The central velocity dispersion s appears to play a stronger role in determining the stellar population

26. Correlation Mg-s tight over large range in galaxy size and all types of hot stellar systems ■▲♦●▪ galaxies with anisotropic kinematics □∆◊○ galaxies rotationally flattened ■ Giant ellipticals (GE) (M < -20.5 mag) ▲Ellipticals of intermediate L (IE) (-20.5 < M < -18.5 mag) ● Compact galaxies (CE) ♦ Bright dwarf galaxies (BDW) (M > -18.5 mag) ▪ Faint dwarf galaxies (FDW) x Bulges of S0/Sa (B)

27. Galaxies with larger s are older and/or more metal rich Stellar population evolves SDSS Bender et al. 1996 --- 0.05 < z < 0.07 ---0.07 < z < 0.09 --- 0.09 < z < 0.12 ---0.12 < z < 0.15 --- 0.15 < z < 0.20

28. Vice-versa galaxies with larger s have weaker Balmer absorption lines Strong evolution hi –z (younger population) low –z (older population)

29.  No correlation between Fe and L --- only with s • Differential evolution? more massive galaxies evolve differently (slower?) than less massive ones?

30. Stellar population models How to disentangleagefrommetallicity? Lick Indices vs Age • Absorption lines (e.g. Lick indices)

31. Stellar population models How to disentangle age from metallicity? • Absorption lines (e.g. Lick indices) metallicity age Additional complication  [a/Fe] enhancement

32. The [a/Fe] enhancement problem SN, which produce most of the metals, are of two types:

33. Additional complication  [a/Fe] enhancement • -elements: Ne, Mg, Si, S, A, Ca (so-named because formed by adding 2,3,…a-particles, i.e. 4He nuclei, to 16O) Large s are a-enhanced --- z < 0.07 ---0.07 < z < 0.09 --- 0.09 < z < 0.12 ---0.12 < z < 0.15

34. Formation time and timescale • SNae Type II from massive stars/short lives • Top-heavy IMF or short formation timescales at high redshift

35. Stellar Population Synthesis Models Some recent models Age Metallicity Corrected for a-enhancement ☺ [a/Fe] > [a/Fe] But …… do not match well all the observed parameters !!  !!

37. Problems?? D Hd ~ 1.5Ǻ

39. Big correction in D4000! D D4000 ~ 0.3!

40. Problems with models Can we learn something just from the observed absorption lines?

41. Testing predictions of galaxy formation models … • Early-type galaxies in the field should be younger than those in clusters • Metallicity should not depend on environment • The stars in more massive galaxies are coeval or younger than those in less massive galaxies

42. Environment …. From ~ 25,000 early-types at z < 0.14 4500 in low density regions 3500 in high density regions L > 3L* SDSS C4 Cluster Catalog (Miller et al. 2005) Lcl > 1.75 x 1011 h-2 L ~ 10L*

43. The Fundamental Plane The virial theorem: • Three observables + M/L • M/L ~ L0.14 • FP is combination with minimum scatter young old Cluster galaxies 0.1 mag fainter than field galaxies Cluster galaxies older than field by ~ 1Gyr? BCGs more homogeneous --- Cluster --- Field --- BCG

46. Bernardi et al. 1998 No differences in the Mg2-s relation If Mg2 is a indicator of the age of the stellar population  Stars in field and cluster early-type galaxies formed mostly at high redshift

47. Mg2-s shows no differences because: Galaxies in the field • are younger • but have higher metallicity Kuntschner et al. 2002

48. ….. Evolution Z ~ 0.05 Dt ~ 1.3Gyr D4000 increases with time; Hd, Hg decreases Z~ 0.17

49. Evolution as a clock Over small lookback times, metallicity cannot have changed significantly; hence observed evolution is due entirely to age differences, not metallicity!

50. Comparison of environmental differences with evolution measurement allows one to quantify effect of age difference between environments; so calibrate mean metallicity difference too!