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The Star Formation History

of Late-Type Galaxies

Roberto Cid FernandesUFSC – Florianópolis -Brasil

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Flori-where?

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Outline1- 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

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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

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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

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1 – Why study stellar pops in galaxies?

To clean starlight pollution from my spectra!

Tremonti 04 Li 05

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1 – Why study stellar pops in galaxies?

CF 04Savaglio 05

Scattered Broad H in a Sey 2

To clean starlight pollution from my spectra!

z ~ 0.7 composite

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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 ofintegrated stellar

populations:

“...a subject with bad reputation. Too much has been claimed, and too few

have been persuaded.”

(Searle, 1986)

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2 – How?

’s (+ gas + dust

+ ...)

Fgal()F*()

The Fundamental Theorem of Population synthesis:

+ extinction x 10-0.4 A()

& kinematics x LOSVD (v*,*,vrot)

• Individual Stars• Observed clusters• Model SSPs• Continuous models

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2a – How? The discrete approach

x1 + x2 + x3 + ...

• Empirical Pop. Synthesis: SSP = Observed Clusters

≈ SSPj 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)

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2a – How? The discrete approach

xj FSSP( ; tj,Zj ; IMF, tracks, libs...)

• SSP = Model “clusters” from evolutionary synthesis

≈ SSPj j = 1...N

: Wider coverage of (t,Z) space & -range: Models are always models...

Models: GALAXEV, SED, STABURST99, PEGASE, Maraston, ...

population vector

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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,- ...

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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)

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2b – Observables: Indices x Full Spectrum

Kauffmann 03, ...

Instantaneous Bursts

Continuous SF

Compare Index(t,Z,SFH) models to data to constrain SFH parameters.

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2b – Observables: Indices x Full Spectrum

Mathis 06 CF 05

Rectified spectrum (“high pass”)

Nolan 06

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2b – Observables: Indices x Full Spectrum

Mayya 06Walcher 06

Reichardt 01

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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

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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

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2c – How? From Observables to SFH...5 indices: D4000, H, H+H, [MgFe]’ & [Mg2Fe]Bayesian comparison to a large library of models

Gallazzi 05

PDF of light

weighted mean age

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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*Mass

assembly

histories: M(t)

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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(t) & Z(t) of Star-Forming

galaxiesPop.

vector=

SFH

Downsizing

22 Corbin 06

2c – How? From Observables to SFH...

UCBD galaxies

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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 / speed1000 “Technicalities” (masks, kinematics, extinction, ...)

Physical ingredientsInput & Output...

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• (a) Global relations:Synthesis parameters X other things:• <t>, <Z>, <SFR>, <SSFR>, ...• Zgas, M*, Mdyn, environment, ...

• (b) Daring one step further: SFH(t)!

• (c) Sanity checks Caveats

• (d) Closing words

3 – So What? A few miscelaneous results

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3a – Global relations

Tremonti 04, Gallazzi 05 CF 05, Mateus 06, Asari 07M*

<t> x Z(gas)

<Z> x Z(gas)

<t> x Z(gas) Z(gas) x Mass <Z> x

Z(gas)

<Z> & <t> x Mass

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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)

AG

NSF

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3b – Going one step further: Evolution

Result

Low Z(gas) galaxies are much

slower in their mass assembly and chemical

evolution

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3b – Going one step further: Evolution

M*Mass

assembly

histories: M(t)Downsizing

SFR(t)/Vol

Panter 06

Mathis 06

M*

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3c – Sanity checks: good news

Different ingreedients

yield ~ similar result !!

SFR(Synt) ~ SFR(H)

Panter 06

Asari 07

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3c – Sanity checks: good news

Nebular exctinction – NaD ISM

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3c – Sanity checks: good news

AV (Balmer) ~ 2 AV (Stellar)

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3c – Warning:

–enhancement is not only an E-gal problem...

Asari 07Sodre 05

Ellipticals

SF-galaxies

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3c – Warning: AZD still present in full

spectral fits

CF 05, Gomes 05

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3c – Residuals: ~ Within errors, but ...

H–troff: Low amplitude, but systematic. ~ 100 Myr pops. STELIB?

Ellipticals SF-galaxies

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• (a) Ingreedients & methods have matured a lot!

• (b) Global properties <t>, <Z>, SFR, SSFR, ...in very good shape

• (b) Evolution ... Looking good!

• (c) Caveats & Future• /Fe issue• Realistict dust models• ...

3 – So What? Conclusions

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Spectral synthesis ofintegrated stellar

populations:

“...a subject with bad reputation. Too much has been claimed, and too few

have been persuaded.”

(Searle, 1986)

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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)

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

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M*, *, t* & Z* x nebular Z

... etc, etc & etc!

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STARLIGHT & its many applications

HE0450-2958 – The “homeless” QSO

CaII Triplet velocity dispersions

Vega 2004, Garcia-Rissman et al 2005

Merritt et al 2006

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CF, Gu, Melnick, Terlevich2, 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

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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