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Mariangela Bernardi UPitt/UPenn Galaxies Properties in the SDSS: Evolution, Environment and Mass Galaxies Properties in the SDSS: Evolution, Environment.

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Presentation on theme: "Mariangela Bernardi UPitt/UPenn Galaxies Properties in the SDSS: Evolution, Environment and Mass Galaxies Properties in the SDSS: Evolution, Environment."— Presentation transcript:

1 Mariangela Bernardi UPitt/UPenn Galaxies Properties in the SDSS: Evolution, Environment and Mass Galaxies Properties in the SDSS: Evolution, Environment and Mass

2 The BIG picture Cosmology: from angular diameter distance (z): CMB from luminosity distance (z): SNae from time (z) relation: Galaxy formation/evolution from gravitational physics: ISW, Pk, Vpec Galaxy Formation and Evolution: Massive galaxies, Black Holes and QSOs QSOs and Re-ionization

3 Outline The SDSS sample Early-type galaxies: formation and evolution models Environment and Evolution ( Bernardi et al. 2004a ) Color-L-  Age and Metallicity ( Bernardi et al 2004b ) The Most Massive Galaxies: Double Trouble? ( Bernardi et al. 2004c )

4 2.5m Dedicated Telescope: 3 o field-of-view image scale of 0.4 arcsec/pixel Imaging Camera: Filters u’g’r’i’z’ ( A) Drift-scan mode: 55 sec exposures (m r* ~ 23) Spectrographs: 640 fibers ( 3 arcsec diameter ) Wavelength: ~ Å Resolution: 1800 Photometric Telescope: Fully Automated 0.6-m Telescope Establishes photometric system; monitors sky conditions SDSS 2.5m Telescope SDSS 0.6m Telescope ARC 3.5m Telescope SLOAN DIGITAL SKY SURVEY

5 The main Survey: North Galactic Cap + South Galactic Cap (three scans) --- Imaging Survey: 10,000 square degrees 100 million 5-band images to m r* ~ 22.5 photometric errors < 2% --- Spectroscopic Survey: brightest 1 million galaxies brightest 100,000 quasars The Southern Survey: equatorial stripe scanned ~ 10x (2 mag deeper, variability) SDSS Goals MAKE A DIGITAL 3-D MAP OF THE UNIVERSE to constrain cosmological models and models of galaxy formation and evolution Status: ~ 6300 square degrees of 5-band imaging ~ 600,000 object spectra (redshifts)

6 Galaxies

7 Late-type Galaxy Early-type Galaxy

8 PCA Spectral Classification Early-type Galaxies

9 Why study early-types? Very homogeneous, old stellar population  Bulge stars plausibly oldest in Universe Tight correlations between observables: R-L,  -L, color-L, R- , etc.  Strong constraints on models  Stars formed in single-burst—easier to build models Cosmology  Time(z) relation; also gravitational lensing  Homogeneity useful for peculiar velocity studies Joint formation of spheroids and Black Holes?

10 Early-type Galaxy Sample Selection Criteria Photometric parameter fracDev > 0.8 PCA spectral type ( eclass < 0 ) Magnitude limit ( 14.5 < m r < 17.6 ) Velocity dispersion available ( S/N > 10 ) From a sample of ~250,000 SDSS galaxies ~ 40,000 early-type galaxies

11 Outline The SDSS sample Early-type galaxies: formation and evolution models Environment and Evolution ( Bernardi et al. 2004a ) Color-L-  Age and Metallicity ( Bernardi et al 2004b ) The Most Massive Galaxies: Double Trouble? ( Bernardi et al. 2004c )

12 CDM: hierarchical gravitational clustering The formation time of “Elliptical galaxies” is the BIG problem!! The most massive galaxies are the last to form … … even though their stars could be the first to form

13 Galaxy formation models predict… 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 Kauffmann & Charlot 1998 see also De Lucia et al The key: measure Age & Metallicity

14 The optical portion of the galaxy spectrum is due to the light of stellar photospheres K giant star Typical elliptical galaxy

15 Galaxies composed of stars  1) Stellar Library 2) Star Formation History 3) Initial Mass Function  reproduce fluxes, colors, and spectra of galaxies e.g. Worthey 1994, Vazdekis 1999, Trager et al. 2000, Bruzual & Charlot 2003, Thomas, Maraston & Bender 2003

16 Complicated by the fact that stars evolve (change luminosity, color, spectral features)

17 For “single stellar populations” (SSP) the evolution is well understood  e.g. basis for understanding globular clusters Early-type galaxy properties dominated by the light of RGB Importance of various parts of stars evolution to a SSP’s total luminosity

18  metallicity changes increase of heavy elements due to SN explosions 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

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

22 How to disentangle age from metallicity? Stellar population models Absorption lines (e.g. Lick indices) H  Mg b Fe EW =   1  F I  F C  d 1  age metallicity Additional complication  [  /Fe] enhancement

23 The [  /Fe] enhancement problem SN, which produce most of the metals, are of two types:

24 Large  are  -enhanced --- z < < z < < z < < z < 0.15

25 Composite Spectra 2200 composite spectra S/N ~ 100 possible to measure Lick indices A la Bernardi et al From ~40,000 early-type galaxies

26 Stellar Population Synthesis Models Thomas, Maraston & Bender 2003 Calibrated to the Lick system  --- lower resolution --- no flux calibration!! Corrected for  -enhancement ☺ [  /Fe] > [  /Fe]  Age Metallicity

27 Problems with models Can we learn something just from the absorption lines?

28 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

29 Outline The SDSS sample Early-type galaxies: formation and evolution models Environment and Evolution ( Bernardi et al. 2004a ) Color-L-  Age and Metallicity ( Bernardi et al 2004b ) The Most Massive Galaxies: Double Trouble? ( Bernardi et al. 2004c )

30 Environment …. C4 Cluster Catalog (Miller et al. 2004) L > 3L* L cl > 1.75 x h -2 L  ~ 10L * From ~ 25,000 early-types at z < in high density regions 4500 in low density regions Bernardi et al. (2004a)

31 Cluster galaxies 0.1 mag fainter than field galaxies Cluster galaxies older than field by ~ 1Gyr BCGs more homogeneous --- Cluster --- Field --- BCG The Fundamental Plane The virial theorem: Three observables + M/L M/L ~ L 0.14 FP is combination with minimum scatter oldyoung

32

33

34 ….. Evolution Z ~ 0.05 Z~ 0.17  t ~ 1.3Gyr D4000 increases with time; H , H  decreases

35 Flux calibration problems? Kelson et al SDSS

36 Bernardi et al SDSS

37 Bender et al SDSS

38 Evolution as a clock

39

40

41 Some implications: early-type galaxies in the field should be younger than those in clusters Observed differences cluster-field small (~ 1 Gyr)

42 Outline The SDSS sample Early-type galaxies: formation and evolution models Environment and Evolution ( Bernardi et al. 2004a ) Color-L-  Age and Metallicity ( Bernardi et al 2004b ) The Most Massive Galaxies: Double Trouble? ( Bernardi et al. 2004c )

43 Color-Magnitude

44 Color-Magnitude is a consequence of Color-  & L- 

45 Age – Metallicity from Color-Magnitude Models from Bruzual & Charlot (2003) 12 4 Age [Z/H]=0.6 [Z/H]=0 9 1 [Z/H]=0.6 [Z/H]= Age [Z/H]=0 [Z/H]= Age Bernardi et al. (2004b) L ↑ Age↑ [Z/H] ↑ L ↑ Age↑ [Z/H] ↓

46 Kodama et al. (1998) Slope of C-M independent of redshift out to z~1 C-M due to Mass-[Z/H] not Mass-Age

47 C-M due to Mass-[Z/H]  residuals from C-M due to Age In contrast to published semi- analytic galaxy formation models Bernardi et al. (2004b) Age  Age of stellar population increases with galaxy mass: Massive galaxies are older

48 At fixed L/Mass: 1) more massive galaxies are older 2) fainter galaxies are older 3) galaxies with smaller R are older 4) higher  galaxies are older

49 Some implications: early-type galaxies in the field should be younger than those in clusters Observed differences cluster-field small (~ 1 Gyr) More massive galaxies are coeval or younger than the less massive ones SDSS indicates opposite: smaller galaxies are younger

50 Outline The SDSS sample Early-type galaxies: formation and evolution models Environment and Evolution ( Bernardi et al. 2004a ) Color-L-  Age and Metallicity ( Bernardi et al 2004b ) The Most Massive Galaxies: Double Trouble? ( Bernardi et al. 2004c )

51 The Most Massive Galaxies: Double Trouble? 105 objects with (  > 350 km/s) Single/Massive?  Galaxy formation models assume  < 250 km/s  BHs (2 x 10 9 M  ) Superposition?  interaction rates  dust content  binary lenses

52 ● Single/Massive ڤ Double ◊ BCG Sheth et al Expect 1/300 objects to be a superposition Bernardi et al. 2004c

53 ‘Double’ from spectrum and image

54 ‘Double’ from spectrum, not image

55 ‘Single’ ?

56 ● Single/Massive ڤ Double ◊ BCG Doubles are outliers BCGs are bluer than main sample at fixed 

57 Dry Mergers?

58 HST images: with ACS-HRC SDSS HST  = 407 ± 27 km/s SDSS J ” 1’

59 SDSS J  = 404 ± 32 km/s HST SDSS 1’ 3’

60 HST: ACS-HRC 6 single4 multiple  = 369 ± 22  = 383 ± 27  = 385 ± 34  = 385 ± 24  = 395 ± 27  = 402 ± 35  = 404 ± 32  = 407 ± 27  = 408 ± 39  = 413 ± 35 Single galaxies with  ~ 400 km/s  Semi-analytic models use a cut at V c = 350 km/s (i.e.  = 350/√2 ~ 250 km/s)  Cut should be at higher V c ??

61 Conclusions Problems with galaxy formation models  Dependence on environment weak  Low  galaxies are younger (future work: quantify differential evolution) C-M  C-  & M-  Follow-up Most Massive Galaxies  Analysis of HST images underway  Increase the sample  Submitting follow-up proposals with 8m


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