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Unveiling Galaxies: Secrets of Stellar Populations Synthesis

Explore a new era in stellar populations synthesis with a focus on active and non-active galaxies. Learn about spectral fits, star formation histories, age correlations, and more. Discover the magic behind galaxy evolution studies.

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Unveiling Galaxies: Secrets of Stellar Populations Synthesis

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  1. The New Era in Stellar Populations Synthesis:Black Magic +Applications to active & not-so-active galaxies R. Cid Fernandes UFSC – Florianópolis -Brasil GH2004

  2. The team(s) • Witchcraft: L Sodré, J Gomes, Merlin, H. Potter, ... • Seyfert 2s: Q Gu, J Melnick, E & R Terlevich, D Kunth, • R Rodrigues Lacerda & B Joguet • LLAGN: R González Delgado, H Schmitt, L Martins, • T Storchi-Bergmann, E Pérez, T Heckman, • C Leitherer • SDSS:A Mateus, L Sodré, G Stasinska, J Gomes • Ca-Triplet:L Vega, N Asari, A Garcia-Rissman,...

  3. The talk: Witchcraft & applications • 1 Witchcraft: Spectral fits using evolutionary synthesis models • How • What it can(’t) do for you • 2 Seyfert 2s: Spectral fits using stars + FC (=AGN power-law) • Residual spectra • 3 LLAGN: Spectral fits using template galaxies + dust • Radial variations (long-slit) • 4 SDSS: Mass, age, Z*, s*, ... • Correlations, correlations & correlations • Comparison with Kauffman et al • Ca-Triplet: Stellar velocity dispersions & EW(CaT)

  4. The Conclusions • 1 Witchcraft: It works!! (= it fools people!) • Recovers well M*, <t*>, <Z*>, s*, AV, ... • Don’t recover details (but who cares?!) • 2 Seyfert 2s: Heterogeneous Star-Formation history • Fits uncover reflected AGN! (BLR & FC) • 3 LLAGN: LINERS are all OLD & boring • Transition Objects: OLD or “YOUNG” • Young-TOs are dusty • Young-TOs = S(Duper)SC at 108–109 yr? • 4 SDSS: A posteriori sanity check on synthesis! • Correlations, correlations & correlations  • Comparison with Kauffman et al: 

  5. 1 – Witchcraft: Examples

  6. 1 – Witchcraft: The recipe = S’s (+ gas + dust + ...)≈ SSSP’s • x1 + x2 + x3 + ...

  7. 1 – Witchcraft: The ingredients • 45 SSPs from Bruzual & Charlot (2003) • 15 ages: t = 1 Mr – 13 Gyr • 3 metallicites: 0.2 – 2.5 Zo • 1 Reddening law (Cardelli et al 1989) • 1 Gaussian LOSVD: G(v*,s*) • 2 or 3 smart collaborators • 1 tea spoon of huitlacoche • 5 galons of tequila

  8. 1 – Witchcraft: The parameters x = x(t,Z) = lightFRACTION at l0 from population t,Z = “population vector” = (x1,x2,...xN) = Star Formation History Other parameters: AV = dust (only 1 so far...) v* = “redshift” s* = velocity dispersion

  9. 1 – Witchcraft: The nuts & bolts • Data:Ol± sl ; l = 3650 – 8000 Ǻ – observed spectrum • Model:Ml(x,AV,v*,s*) – model spectrum • Problem: How to estimate x1...xN, AV, v* e s*? • ~ 45 + 3 = 48 paramerters!  • Method:Markov Chain Monte Carlo • Metropolis-Hastings + Simulated-annealing • Likelyhood guided “random” walk Prob(x,AV,v*,s*| Data) ~ exp –{c2 / 2} c2 = S {Ol – Ml(x,AV,v*,s*)}2 lsl2 + Movies! 08 , 32 , 39

  10. Simulations: output ~ input 

  11. Simulations: but ... 

  12. 2 – The SF-History of Sey 2 nuclei CF, Gu, Melnick, Terlevich2, Kunth, Rodrigues Lacerda, Joguet 04 Strong FC in this Sey 1  • 79 galaxies • 65 Sey 2s • ~ 200 pc • Base = BC03 + FC

  13. Coarse (but robust) description of the st pop INTERMEDIATE 108-9 yr • Population vector: • Reduce x from • N* ~ 20 => 3 components • x = (xY,xI,xO) YOUNG (+ FC) 106–7 yr xY+ xI+ xO = 1 plane OLD 1010 yr CF et al 01, 04, GD et al 04

  14. Result #1: SFH of Sey 2s is very heterogenous! • Population Vector: • x = flux-fraction • x = ( Y+FC , I , O ) • Y/FC = 5 Myr + n-1.5 FC • I = 100 Myr – 1 Gyr • O = 1 – 10 Gyr Old pop + burst

  15. Result #1: SFH of Sey 2s is very heterogenous! ~ 40% Starburst + Seyfert 2 composites “pure/boring” Seyfert 2

  16. Result #1: SFH of Sey 2s is very heterogenous! Instantaneous Bursts ?! Continuous SF “Broad Line Sey 2s” or “Sey 3s” Power-Law + E-gal

  17. Result #2: Weak (scattered) BLR & FC! • Starlight-subtracted spectra reveal weak broad Hb in 10/65 Seyfert 2s! • Most of these have Hidden BLRs revealed in polarized spectra (Tran 95, 01) • Spectral synthesis finds a strong FC component (~ 20%) in these “Broad Line Seyfert 2s” Conclusion: Scattered light!

  18. WKX [OI]/Ha 3 – LINERs & Transition Objects AGN Old LINERs Young LINERs Old TOs Young TOs CF etal 04 GD etal 04 05, 06 ... Young Old

  19. 3 – LINERs & TOs • Long-slit spec. of ~ 50 LLAGN • Spatial Resolution ~ 1” ~ 100 pc • Spectral synthesis of 521 extractions • Base of template galaxies representing Y, I & O populations St pop, extinction & brightness profiles

  20. 3 – Radial Gradients in LLAGN WK(r)

  21. 3 – Dust in LLAGN: AV(r) x(r) AV(r)

  22. 3 – Dust in LLAGN: AV(r) • Young-TOs have much more dust than Old-TOs or Old-LINERs Young-TOs Old-TOs & LINERs

  23. 3 – Dust & St pops in LLAGN • Young-TOs have much more dust than Old-TOs or Old-LINERs • Central 108-9 yr population is compact R ≤ 100 pc • M* ~ 107 Mo • Super Duper SC?? Young-TOs Old-TOs & LINERs

  24. 2 + 3 = Evolution of (stars in) AGN? <t*(Sey2)> < <t*(Young-TO)> < <t*(Old-TO)> =<t*(LINER)> <t*(Starburst)> < <t*(Young-TO)> < <t*(Old-TO)> To be continued....

  25. 4 – Synthesis of 50k SDSS galaxies Abílio Mateus (IAG), Jean Michel Gomes (UFSC) Laerte Sodré (IAG) & Grazyna Stasinska (Meudon)

  26. 4 – SDSS: 1st results (including yesterday!) • Products of the synthesis • x = x(t,Z) : Star-formation & chemical histories • M* : stellar Mass • t* & Z* : mean stellar age & metallicity • s* : velocity dispersion • AV : extinction • Observed – Model F(l) = pure emission spectrum • Emission line fluxes • Nebular metallicity, extinction, ...

  27. Stellar versus nebular extinction AV (Balmer) = 0.3 + 1.8 AV (Stellar) Normal Emission Line Galaxies (= non-AGN)

  28. Stellar age x stellar age indicator

  29. Stellar age x nebular age indicator

  30. Stellar age x stellar mass

  31. Stellar mass x stellar metallicity

  32. Stellar X nebular metallicity blablablabla Roberto: Can you read this? hahahahaha

  33. Us X Them

  34. 4 – SDSS: 1st results • Too much information! Parameter brigad!! ? • But great results!! Can’t be too wrong!

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