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Investigating Galaxy Evolution with Empirical Population Synthesis

Investigating Galaxy Evolution with Empirical Population Synthesis. Laerte Sodré Jr. Departamento de Astronomia Instituto de Astronomia, Geofísica e Ciências Atmosféricas Universidade de São Paulo Challenges of New Physics in Space Campos do Jordão, 25 – 30 April 2009. log [OIII] / H b.

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Investigating Galaxy Evolution with Empirical Population Synthesis

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  1. Investigating Galaxy Evolution with Empirical Population Synthesis Laerte Sodré Jr. Departamento de Astronomia Instituto de Astronomia, Geofísica e Ciências Atmosféricas Universidade de São Paulo Challenges of New Physics in Space Campos do Jordão, 25 – 30 April 2009

  2. log [OIII] / Hb log [NII] / Ha SEAGal Collaboration(Semi-Empirical Analysis of Galaxies) • Roberto Cid Fernandes (Florianópolis) • Grazyna Stasinska (Meudon) • LSJ (SP) • Abílio Mateus (SP, Florianópolis) + several PhD students: • Natalia Asari (Florianópolis, Meudon) • Juan Torres-Papaqui (INAOE, Florianópolis) • William Schoenell (Florianópolis) • Jean M. Gomes (Florianópolis) • Luis Vega Neme (Córdoba) • Tiago F. Triumpho (SP) • Marcus V. Costa Duarte (SP) • ... • Cid Fernandes et al., 2005; Sodré et al. 2006; Mateus et al., 2006; Stasinska et al., 2006; Mateus et al., 2007; Cid Fernandes et al., 2007; Asari et al. 2008; Stasinska et al. 2008

  3. some questions about galaxy evolution: • how star formation evolved? • how metallicity evolved? • what is the role played by galaxy mass? • ...

  4. some questions about galaxy evolution: • how star formation evolved? • how metallicity evolved? • what is the role played by galaxy mass? • ... • these are examples of problems that can be addressed by spectral synthesis

  5. Empirical Population Synthesis • Fitting of a set of observables of a given galaxy by means of a linear combination of simpler systems of known characteristics, like individual stars or Simple Stellar Populations (SSP) to recover galaxy properties

  6. Why spectral synthesis? • SS allows to retrieve the stellar history of galaxies from galaxy spectra • galaxy spectrum: encodes information on the age and metallicity distributions of the constituent stars • it is an expression of the galaxy star-formation and chemical history

  7. energy flux per wavelength interval continuum + absorption lines: stars emission lines: ionized gas produced by star-forming regions or AGNs what is a galaxy spectrum?

  8. Why spectral synthesis? • SS provides information on: - Stellar population mix – galaxy history: star-formation, metallicity - Gas properties – ionizing source: stars x AGN - Kinematics & Dust – σ* , AV

  9. our approach: code Starlight – chi2 fitting Mλ0: synthetic flux at the normalization wavelength λ0 = 4020A Model spectrum b j,λ: spectrum of the j-th SSP normalized at λ0 (N* SSP) Gaussian with dispersion σ* reddening term (foreground dust): rλ = dex[-0.4(Aλ-Aλ0)] (Cardelli, Clayton & Mathis 1989) x j: fractional contribution of the j-th SSP to the model flux at λ0

  10. Spectral base (B&C03): • N* =45-150 SSP • 3-6 metallicities 0.2, 1, 2.5 Zsun (+ 0.005, 0.02, 0.4) • 15 - 25 ages 0.001 to 13 Gyr (now: up to 18 Gyr) STELIB library + Padova (1994) tracks + Chabrier (2003) IMF

  11. The SDSS sample • SDSS: enormous amount of good quality, homogeneously obtained spectra • Data from DR2 to DR7 samples from 20,000 to ~1,000,000 galaxies • Median S/N ~14 (range 5 – 30)

  12. Examples: Observed spectrum, model spectrum, error spectrum, masked pixels

  13. Emission line measurements • Emission lines are measured from the “pure emission”, residual spectra • Intensities are computed for many lines • Galaxies with emission lines are classified according to their position in the BPT diagram ([OIII]/Hβ x [NII]/Hα): - normal star-forming galaxies - AGNs

  14. Empirical relations(useful to constrain models and for sanity checks) relation between the mean stellar metallicity and the nebular metallicity [O/H]: “empirical methods” (= Tremonti et al. 2004)

  15. Empirical relations relation between velocity dispersion and stellar mass

  16. Empirical relations AV (Balmer) ~ 2 AV (Stellar)

  17. Bimodality of the galaxy population sequence x bimodality “Early and late, in spite of their temporal connotations, appear to be the most convenient adjectives available for describing relative positions in the sequence”(Hubble 1926) • SDSS: Strateva et al. (2001), Kauffmann et al. (2003), ... • Here: Mateus et al. (2006) * Volume limited sample (M(r) < -20.5) * ~50,000 galaxies (DR2)

  18. Bimodality of the galaxy population • Many galaxy properties present a bimodal distribution: early-type / late-type • AGN hosts: preference for passive populations, but everywhere

  19. Bimodality of the galaxy population • The mean light-weighted stellar age provides a better separation between classes than stellar mass

  20. Galaxy downsizing • Massive galaxies stoped to form stars more than • 10 Gyr ago • Galaxies forming stars today tend to have low • masses

  21. A nature via nurture scenario for galaxy evolution • Light (SF) is more sensitive to environment than stellar mass

  22. A nature via nurture scenario for galaxy evolution • Galaxies in dense environments are older and more massive

  23. A nature via nurture scenario for galaxy evolution • Galaxies in dense environments have more metals

  24. A nature via nurture scenario for galaxy evolution • PCA: <log t>L log M* log Σ10 log Lr M* /Lr • Most of the variance in galaxy properties are due to 1) environment and 2) age • Galaxy evolution is accelerated in denser environments • Galaxy evolution is accelerated for higher masses • “Nature” necessarily acts via “nurture” effects (c.f. Abilio)

  25. Chemical enrichment and mass-assembly histories of SF galaxies Cid Fernandes et al. (2007), Asari et al. (2007) Bins in Zneb

  26. Chemical enrichment and mass-assembly histories of SF galaxies mass Z

  27. Chemical enrichment and mass-assembly histories of SF galaxies • Cid Fernandes et al. (2007), Asari et al. (2007): • Low Zneb galaxies are slow in forming stars and reached Z* ~1/3 Zsun in the last ~100 Myr • High Zneb galaxies formed most of their stars long ago, reaching Z* ~1 Zsun several Gyr ago • Actually, more evidence of downsizing

  28. technical challenges: Residuals ~ within errors, but systematic! Ellipticals SF-galaxies a-bands not fitted in massive ellipticals ...  new models will fix this! Hb–missfit with STELIB ...  MILES fixes this!

  29. What changes with the new spectral bases??? Ellipticals Refits using CB07 models (MILES + Martins libraries) 2003 2007 Residuals are smaller ie., spectral fits are better!! • SFHs are smoother • Mean ages decrease a bit • <Z> increase a bit SF-galaxies 2007 2003

  30. new surveys • SDSS/DR7 • new photometric callibration! • ~1,000,000 galaxies • ... more to come! EUCLID, WFMOS, ...

  31. some scientific challenges: • uncertain stages of stellar evolution • downsizing • initial mass function • chemical evolution • dust evolution • ...

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