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Star formation & mass-assembly evolution of galaxies Fossil methods & applications to Mega data-sets. www.starlight.ufsc.br. – What do you mean “ fossil methods ”??. The 2 ways to study galaxy evolution. The time-machine method: Go back & find out how things were!.

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  1. Star formation & mass-assembly evolution of galaxiesFossil methods & applications to Mega data-sets www.starlight.ufsc.br

  2. – What do you mean “fossil methods”??

  3. The 2 ways to study galaxy evolution The time-machine method: Go back & find out how things were! G. Pal (1960) / H. G. Wells (1895)

  4. The 2 ways to study galaxy evolution The astronomical time-machine: redshift  time Cimatti 04 z =1.7! t • Get information directly from the past! • Compare properties of galaxies at different z’s • (CAVEAT: Not the same galaxy at different z’s, of course!!)

  5. The 2 ways to study galaxy evolution The fossil method:Retrace history of each galaxy SFH S SSPs

  6. The 2 ways to study galaxy evolution The fossil method: Example results SFH(t) of 1 Galaxy! M(t) / M(now) : Mass assembly history as a function of M* SFH(t) of the universe <Z*>(t) : Chemical Evolution x M* Panter 03, Heavens 04, ... Asari 07, CF 07, ...

  7. The rest of this talk: 1 – Fossil Methods / Inverse Population Synthesis: Decomposing galaxy spectra Basic concepts: Observables + Base + SFH Methods, methods, methods... 2 – Selected results / sanity checks / caveats & etc 3 – Amazing things you can do nowadays! The avalanche of information.... www.starlight.ufsc.br

  8. M1 + M2 + M3 + ... 1 – Fossil Methods: A quick tour SFH S SSPs

  9. M1 + M2 + M3 + ... Decomposing galaxy spectra: 3 Basic concepts Lgal(l) = SMSSP(t,Z)x SSP(l ; t,Z) t,Z Observables Full spectrum or Indices  Spectral Base Model or Observed SSPs / star-clusters Star Formation History + Chemical Evolution  How to derive it??

  10. Only 1 Z? Z = Z(t)? Al = ? Dust geometry? Al(t,Z)? Kinematics? Which base? (clusters, models,...) Which SFH parameters? Hypothese space (“priors”) 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? Method Inverse Population Synthesis: How? Parameter space Observables space

  11. Inverse Population Synthesis: How? • Many methods! • STEllar Content via Maximum A Posteriori – Ocvirk 05, Koleva 07 • Active Instance-Based Machine Learning – Solorio 05 • Bayesian Latent Variable modelling – Nolan 06 • Principal Component Analysis – Li 05, Wild 07 • Direct fitting – Tadhunter 05, Moustakas 06, Chilingarian 07 • GASPEX, DINBAS2D – Mateu + Martinez + Magris • Brute Force – Bush 01, 02, 03, 04, 05, 06, 07, 08 • ... Huge diversity in: Math / elegance / speed 1000 “Technicalities” (masks, kinematics, extinction, ...) Physical ingredients Input & Output ...

  12. Evolutionary Synthesis: The High Resolution Era  Improvements in spectral librariesPredictions on ~ Å scales! Gonzalez Delgado 05 Le Borgne 04 Bruzual & Charlot 03

  13. The post-2003 boom in Full Spectral Synthesis Koleva 07: Fit globular clusters & find same t & Z as from CMD  OBS: rectified spectra = continuum-less

  14. Inverse Population Synthesis: Input • Observed spectrum • eg, a SF galaxy from the SDSS (B) Spectral Base eg, N >> 1 SSPs from BC03

  15. Inverse Population Synthesis: Output Observed spectrum + Base + Inversion method  SFH • (A) Observables: • - full spectrum • Nl~ 1000–4000 pixels • (B) Spectral base: • - N* = 25 x 6 = 150 (!) • SSP(l)’s from BC03 • (C) Inversion method: • - Markov Chains • exploration of • parameter space • (D) Tricks / Details: • - 1 extinction model • - kinematics: s* & v* • - 25 ages x 6 Z’s SFH

  16. 2 – Some Results, Sanity checks & etc

  17. Spectral Synthesis with MOPED Multiple Optimized Parameter Estimation and Data compression • (A) Observables: • - full spectrum compressed to Nl = 23 pixels... • (B) Spectral base: • - N* = 12 “finite bursts” • of different ages (BC03) • (C) Inversion method: • - Fit 23 parameters... • (D) Tricks / Details: • - 1 extinction model • - NO kinematics  • - Z = Z(t) = one Z per age SFH Panter 03, 07, Heavens 04 ...

  18. M* Mass assembly histories: M(t) Spectral Synthesis with MOPED • Compressed F(l) fits • Light (Mass) in N ~ 10 age bins & 1 Z for each age • Compress INPUT! Downsizing SFH of the Universe! Panter 07 Mathis 06

  19. Spectral Synthesis with STARLIGHT Full pixel-by-pixel F(l) fits - Light (Mass) in N ~ 50–150 SSPs - Compress OUTPUT! Downsizing M* M(t) & Z(t) of Star-Forming galaxies Pop. vector = SFH CF 05, 07, Mateus 06, Asari 07, Sodre 08

  20. Sanity checks: good news  SFR(Synt) ~ SFR(Ha) !!! Asari 07

  21. Sanity checks: problems & solutions! Residuals ~ witihin errors, but systematic! Ellipticals SF-galaxies a-bands not fitted in massive ellipticals ...  Paula will fix this! Hb–missfit with STELIB ...  MILES fixes this!

  22. 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 • AV > 0 .... • Mean ages decrease a bit • <Z> increase a bit ... Jean Michel Gomes thesis... SF-galaxies 2007 2003

  23. 3 – Amazing things you can do nowadays A journey through the SDSS + STARLIGHT databases www.starlight.ufsc.br

  24. Physical Properties: Stellar Mass log M* HII < Sey 2 < LINERs log MO

  25. Physical Properties: Mean Age <log t*> HII < Sey 2 < LINERs log yr

  26. Cloning technology applied to galaxy evolution 1st experiments / preliminary results

  27. The fossil time machine

  28. Experiments in galaxy cloning

  29. Experiments in galaxy cloning

  30. www.starlight.ufsc.br

  31. Left-over slides...

  32. TWINS: Galaxies with the same SFH

  33. Compression: Smooth output SFH on scales of D log t ~ 0.5 – 1 dex

  34. The 2 ways to study galaxy evolution The astronomical time-machine: redshift  time z =1.7! t  Get information directly from the past! Compare properties of galaxies at different z’s (CAVEAT: Not the same galaxy at different z’s, of course!!)

  35. The 2 ways to study galaxy evolution The time-machine method: Example results Spectra of galaxies @ z ~ 1.7 The “Lilly-Madau plot” SFH(t) of the Universe Cimatti 04 Hopkins 05 + ...

  36. The 2 ways to study galaxy evolution The fossil method / paleontology of galaxies Observer Data: galaxy spectrum Inverse Population Synthesis Telescope SFH: Evolution  Dig information about the past from fossils found here & now!

  37. Sanity checks: good news  Ha / Hb As found by Calzetti et al 94 in detailed studies of nearby galaxies  CAVEAT: Treatement of dust is still too naive... AV (gas) ~ 2 AV (Stellar) CF 05

  38. The post-2003 boom in Full Spectral Synthesis Nolan 06 Walcher 06 Mayya 06

  39. Global Relations Z(gas) x Mass <Z*> x Z(gas) <t> x Z(gas) <t> x Z(gas) <Z*> x Z(gas) <Z*> & <t> x Mass M* Tremonti 04, Gallazzi 05, 06 The SEAGal’s

  40. Physical Properties: Stellar Mass log M* HII < Sey 2 < LINERs log MO

  41. Physical Properties: Mean Age <log t*> HII < Sey 2 < LINERs log yr

  42. Physical Properties: Metallicity <Z*> HII < Sey 2 < LINERs log ZO

  43. Physical Properties: a/Fe “a-enhancement” Sey 2 < LINERs DMg

  44. Physical Properties: AGN Power L[OIII] Sey 2 > LINERs log LO

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