Presentation is loading. Please wait.

Presentation is loading. Please wait.

1 The Star Formation History of Late-Type Galaxies Roberto Cid Fernandes UFSC – Florianópolis -Brasil.

Similar presentations


Presentation on theme: "1 The Star Formation History of Late-Type Galaxies Roberto Cid Fernandes UFSC – Florianópolis -Brasil."— Presentation transcript:

1 1 The Star Formation History of Late-Type Galaxies Roberto Cid Fernandes UFSC – Florianópolis -Brasil

2 2 Flori-where?

3 3 Outline 1- What & Why? Scope & disclaimer Motivations 2 – Who & How? Schools, Ingredients & Methods: - Based on indices - Based on full spectral fits 3 – So what? Miscelaneous results Caveats

4 4 1 – What & Why Two of the characteristics we expect of these reviews are the need to present a very balanced overview of the theme, in a manner which informs the audience without burying it in excessive technicalities. We are confident that you will be able to fulfil these criteria Mission Impossible! Focus on: optical spectroscopy stellar photons (ie, no em. line SFH diagnostics) late-type (= non-ellipticals) applications to large samples (= SDSS) the small print

5 5 1 – Why study stellar pops in galaxies? To learn about galaxy evolution: SFR(t), Z * (t), cosmology... Mathis 06 Heavens 04 Mass assembly history of a late type galaxy SFH(t) of the Universe

6 6 1 – Why study stellar pops in galaxies?  To clean starlight pollution from my spectra! Tremonti 04 Li 05

7 7 1 – Why study stellar pops in galaxies? CF 04 Savaglio 05 Scattered Broad H  in a Sey 2  To clean starlight pollution from my spectra! z ~ 0.7 composite

8 8 Basic Recipe (a) Discrete x continuous representations (b) Observables: Indices x Full spectrum (c) From observables to SFH: Methods, methods & methods... 2 – How? Spectral synthesis of integrated stellar populations: “...a subject with bad reputation. Too much has been claimed, and too few have been persuaded.” (Searle, 1986)

9 9 2 – How?  ’s (+ gas + dust +...) F gal ( )  F * ( ) The Fundamental Theorem of Population synthesis: + extinction x 10 -0.4 A( ) & kinematics x LOSVD (v *,  *,v rot ) Individual Stars Observed clusters Model SSPs Continuous models

10 10 2a – How? The discrete approach  x 1 + x 2 + x 3 +... Empirical Pop. Synthesis: SSP = Observed Clusters ≈  SSP j j = 1...N : Stellar evol, spectra & IMF given by Mother Nature  : Incomplete coverage of (t,Z) space & -range Bica 88, Schmidt 91, Ahumada 06... + Pelat 97, 98, CF 01 (math)

11 11 2a – How? The discrete approach   x j F SSP ( ; t j,Z j ; IMF, tracks, libs... ) SSP = Model “clusters” from evolutionary synthesis ≈  SSP j j = 1...N : Wider coverage of (t,Z) space & -range  : Models are always models... Models: GALAXEV, SED, STABURST99, PEGASE, Maraston,... population vector

12 12 2a – How? The discrete approach Models: GALAXEV, SED, STABURST99, PEGASE, Maraston,... WARNING: Models look great, but there are LOTS of assumptions & tricks in this business! - tracks, - spectral libraries, - interpolation schemes, -...

13 13 2a – How? The continuous approach : More general than  bursts  : Need to parametrize SF history & chemical evol.  : Models are always models... Fritze-v. Alvensleben 06, Bicker 04,... SFR(t)

14 14 2b – Observables: Indices x Full Spectrum Kauffmann 03,... Instantaneous Bursts Continuous SF Compare Index(t,Z,SFH) models to data to constrain SFH parameters.

15 15 2b – Observables: Indices x Full Spectrum Mathis 06 CF 05 Rectified spectrum (“high pass”) Nolan 06

16 16 2b – Observables: Indices x Full Spectrum Mayya 06 Walcher 06 Reichardt 01

17 17 2c – How? From Observables to SFH... Observables space Parameter space Hypothese space (“priors”) Only 1 Z? Z = Z(t)? A = ? Dust geometry? A (t,Z)? Kinematics? Which basis? (clusters, models,...) Which parameters? Method Brute force discrete grid search? Convex-algebra? Markov-Chains? PCA? AI-techniques? Compression on input or output? Comparions to library of models? How to deal with degeneracies? WARNING: Impossible to review all combinations! Will browse through a few examples

18 18 2c – How? From Observables to SFH... A very elegant method, yet largely overlooked because (?) of complex math (convex algebra) & few applications. Pelat 97, 98, Moultaka 00, 04 Observables: 2 EWs Parameters: 5 light fractions Reconstructed spectrum Boisson 00

19 19 2c – How? From Observables to SFH... 5 indices: D4000, H , H  +H , [MgFe]’ & [Mg 2 Fe] Bayesian comparison to a large library of models Gallazzi 05 PDF of light weighted mean age

20 20 2c – How? From Observables to SFH... Panter 03 F( ) fitting with MOPED Multiple Optimized Parameter Estimation & Dta cmpsn Mass & Z in N ~ 10 time-bins Mathis 06 M*M* Mass assembly histories: M(t)

21 21 2c – How? From Observables to SFH... F( ) fitting with STARLIGHT - Light (Mass) in N ~ 100 time & Z SSPs - Compress output CF 04. 05, 06, Mateus 06, Asari 07 M*M* M(t) & Z(t) of Star-Forming galaxies Pop. vector = SFH DownsizingDownsizing

22 22 Corbin 06 2c – How? From Observables to SFH... UCBD galaxies

23 23 2c – How? From Observables to SFH... Many other methods! STEllar Content via Maximum A Posteriori – Ocvirk 05 + Koleva +... Active Instance-Based Machine Learning – Solorio 05 Bayesian Latent Variable modelling – Nolan 06 Principal Component Analysis – Li 05, Wild Direct fitting – Tadhunter 05, Holt 06, Moustakas 06... + MacArthur... Brute Force – Bush 01, 02, 03, 04, 05, 06, 07, 08... Diversity in: Math / elegance / speed 1000 “Technicalities” (masks, kinematics, extinction,...) Physical ingredients Input & Output...

24 24 (a) Global relations: Synthesis parameters X other things:,,,,... Z gas, M *, M dyn, environment,... (b) Daring one step further: SFH(t)! (c) Sanity checks Caveats (d) Closing words 3 – So What? A few miscelaneous results

25 25 3a – Global relations Tremonti 04, Gallazzi 05CF 05, Mateus 06, Asari 07 M*M* x Z(gas) Z(gas) x Mass x Z(gas) & x Mass

26 26 3b – Going one step further: Evolution Idea: Dissect the SFH = SFR(t) & Z * (t) along the left wing of the Seagull (normal SF galaxies) Z(gas) AGN SF

27 27 3b – Going one step further: Evolution Result Low Z(gas) galaxies are much slower in their mass assembly and chemical evolution

28 28 3b – Going one step further: Evolution M*M* Mass assembly histories: M(t) DownsizingDownsizing SFR(t)/Vol Panter 06 Mathis 06 M*M*

29 29 3c – Sanity checks: good news Different ingreedients yield ~ similar result !! SFR(Synt) ~ SFR(H  ) Panter 06 Asari 07

30 30 3c – Sanity checks: good news Nebular exctinction – NaD ISM 

31 31 3c – Sanity checks: good news  A V (Balmer) ~ 2 A V (Stellar)

32 32 3c – Warning:   –enhancement is not only an E-gal problem... Asari 07 Sodre 05 Ellipticals SF-galaxies 

33 33 3c – Warning:  AZD still present in full spectral fits CF 05, Gomes 05

34 34 3c – Residuals: ~ Within errors, but... H  –troff: Low amplitude, but systematic. ~ 100 Myr pops. STELIB? EllipticalsSF-galaxies

35 35 (a) Ingreedients & methods have matured a lot! (b) Global properties,, SFR, SSFR,... in very good shape (b) Evolution... Looking good! (c) Caveats & Future  /Fe issue Realistict dust models... 3 – So What? Conclusions

36 36 Spectral synthesis of integrated stellar populations: “...a subject with bad reputation. Too much has been claimed, and too few have been persuaded.” (Searle, 1986)

37 37 Spectral synthesis of integrated stellar populations: “...a subject with a not so bad reputation anymore. By not claiming too much, we’re now able to convince quite a few people.” (At least we managed to fool Scott!) (A bunch of us, 2006)

38 38 Public version of STARLIGHT + results for 572581 SDSS galaxies soon @ www.starlight.ufsc.br & www.inaoep.mxwww.starlight.ufsc.brwww.inaoep.mx

39 39

40 40 M *,  *, t * & Z * x nebular Z... etc, etc & etc!

41 41 STARLIGHT & its many applications HE0450-2958 – The “homeless” QSO CaII Triplet velocity dispersions Vega 2004, Garcia- Rissman et al 2005 Merritt et al 2006

42 42 CF, Gu, Melnick, Terlevich 2, Kunth, Rodrigues Lacerda, Joguet 2004, MNRAS 2 – The SF-History of Sey 2 nuclei 79 galaxies 65 Sey 2s ~ 200 pc Base = BC03 + FC Strong FC in this Sey 1

43 43 6 – Synthesis of 582k SDSS galaxies N Asari, J Gomes, W Schoenell, J P Papaqui (UFSC) A Mateus (IAG), L Sodré (IAG) & G Stasinska (Meudon) The SEAGal Collaboration: Semi-Empirical Analysis of Galaxies


Download ppt "1 The Star Formation History of Late-Type Galaxies Roberto Cid Fernandes UFSC – Florianópolis -Brasil."

Similar presentations


Ads by Google