A New Milestone in Starburst SED Modeling: Using 30 Doradus as a Benchmark Rafael Martínez-Galarza...

A New Milestone in Starburst SED Modeling: Using 30 Doradus as a Benchmark

Rafael Martínez-Galarza

Leiden Observatory

Brent Groves (Leiden/MPIA)Bernhard Brandl (Leiden)

Genevieve de Messieres (Virginia)Remy Indebetouw (Virginia)

FLASH Talk. NOAO. November 19, 2010

Overview

Starbursts in the Universe SED Modeling of Starburst The Mid-IR properties of Starbursts 30 Doradus IRS Spectral map The models Fitting routine Results


What is a starburst galaxy?

Burst in the Star Formation Rate (SFR) of a galaxy, lasting 107-108 years and involving up to 5% of the total stellar mass (Larson & Tinsley, 1978).

Many HII regions concentrated in time and usually also in space.

This translates into SFRs of tens, hundreds, or even thousands of M/yr, in the case of ULIRGs.

For comparison, the SFR of the Milky Way is 1 M/yr.

M82 has a SFR of ~10 M/yrCredit: NASA/ESA


Why studying starbursts?

Starburst form many massive stars and hence: Help us understand the conditions for

massive star formation. Are bright enough to be seen at early stages

of the Universe, when they were also more common, and hence help us understanding the formation of galaxies.

Can give insight into the stellar Initial Mass Function (IMF).


Mid-IR properties of Starburst Galaxies

SF occurs in very dusty environments.

Lots of stellar UV radiation reprocessed by dust and emitted in the IR.

Mid-IR spectrum contains useful information on the physical conditions.

Some mid-IR spectral features: Spectral continuum Silicate absorption Nebular lines Emission from Polycyclic

Aromatic Hydrocarbons (PAHs)

Brandl et al., 2006FLASH Talk. NOAO. November 19, 2010

Spectral Energy Distributions (SEDs) Modeling

If a galaxy is unresolved, its integrated SED is our primary source of information.

Each physical process leaves its imprint on the shape of the galactic spectrum.

Processes related to starlight dominate de UV to IR portion of the spectrum.

SED modeling is the art of predicting the SED of a starburst from a set of physical assumptions.

Brandl et al., 2006

Groves et al., 2008FLASH Talk. NOAO. November 19, 2010

SED Fitting

Models predict the SED based on physical assumptions.

Fitting is the opposite: given the SED, extract physical information from the model parameters that produce best fit.

However: Quality and amount of data insufficient. Models have intrinsic uncertainties Lack of independent checks of the derived physical

parameters. As long as those caveats are not taken care of, SED

fitting of starbursts is useless, as far as the parameter uncertainties are concerned.


Our goal

Build a robust fitting routine that quantifies the uncertainties in the parameters and calibrates a specific model, by solving the three mentioned issues.

First two issues: We use a Bayesian inference approach.

Third issue: We choose a well known benchmark with independent checks for its parameters.


Our benchmark is 30 Doradus

Giant star forming region located at 53kpc, in the LMC

Building block of a starburst: Star cluster + HII region + PDR

Several stellar populations Different regions spatially

resolved. Extensively studied at

optical (Hunter et al, 1995; Walborn et al., 1995) at infrared (Indebetouw et al., 2009) wavelengths

500 pc

ESO


The Spitzer-IRS spectral map

Low resolution (R ~ 60-120) modules.

Wavelength coverage: 5.2-38m

3440 slit pointings covering an area of about 40.5 square arcminutes.

Spatial resolution in the SL module is about 0.5 pc

Wavelengths shown: 33.4 mm : [SIII] nebular

line 10.5 mm : [SIV] nebular

line 6.2 mm : PAH emission

Indebetouw et al., 2009 FLASH Talk. NOAO. November 19, 2010

Individual Regions

R136: Central ionizing cluster Mcl ~ 5 × 104 M Recently reported to have

stars more massive than 150 M (Crowther et al., 2010).

Compact, bright [SIV] source. IR bright.

High extinction source Prominent Mid-IR point

source. High excitation.

Spectra extracted within a square aperture of 6 SL pixels in on the side. [SIV]10.5m map


Modeling expanding HII regions

Reference: Groves et al., 2008.

How it works: Stellar synthesis:

Starburst99. Kroupa IMF, Mcl = 106 M

Radiative transfer calculated in two cases: HII region only. PDR covering HII region.

Time evolution: Mass loss expanding bubble driven by stellar wind and/or SN (Castor et al., 1975).

Add a component of UCHIIRs (embedded objects, hot dust).

Ages up to 10 Myrs.


Model Parameters Metallicity, Z: fixed to the LMC

value. ISM pressure, P0/k: fixed to 105

K cm-3

Cluster age, t: <10 Myrs Stellar mass, M★

‘Embedded mass’, Memb

PDR covering, fPDR

Compactness, C

The PDR covering fraction derives from the relative contribution to the total flux from the PDR-covered models.

The compactness is related to the cluster mass (Mcl) and the ISM pressure (P0)

young

oldFLASH Talk. NOAO. November 19, 2010

Bayesian inference

The parameters are taken as random variables with associated probability distribution functions (PDFs).

The problem transforms: Find the PDFs given the data.

PDFs represent the complete solution to the problem.

The Bayes theorem states that:

PDF() ~ Likelihood * Prior If errors are Gaussian:

PDF ~ exp(-2/2)


Our priors

We introduce bounded uniform priors for M★, Memb, fPDR and C

Boundaries are set to cover broad range of physical environments.

For example, log C < 3: very diffuse material, not suitable for SF , while log C > 6.5 has never been measured.

Parameter Range Resolution

t (Myr) 0-10 0.5

Log C 3-6.5 0.5

fPDR 0.001-1.0 0.2 dex

M★ 2 orders of magnitude

0.2 dex

Memb 2 orders of magnitude

0.2 dex


Refining age priors:Nebular Line Ratios

We use line fluxes measured at high resolution with Spitzer-IRS (Lebouteiller et al., 2008). [SIV]10.5mm/S[III]18.7mm [NeIII]15.5mm/

[NeII]12.8mm We use Gaussian

distributions with standard deviations corresponding to the age uncertainties.

Extinction might have an effect on sulfur ratios, making the source appear older.

0 Myr

2 Myr

2.5 Myr

Young ages, < 2.5 Myrs


Continuum fitting: Integrated spectrum

With the defined priors we run the routine for continuum (Thermal + PAH) fitting.

Routine output: best fit values and PDFs calculated over the multi-dimensional parameter space.

Fit is poor at ~15m. Dust in hot component might be hotter.

IRS dataModelEmbedded objectsHII regionPDR regionPDR region

Best fit valuest = 1.5 Myr M★ = 2.8 × 105 Mlog C = 4.0 Memb = 7.1 × 104 MfPDR=0.4

Martinez-Galarza et al., in prep.FLASH Talk. NOAO. November 19, 2010

“Embedded” component is necessary.

None of the spectra can be fitted without including this component.

Part of it could be related to the presence of embedded protostars.

Protostars have been detected at centimeter wavelengths.


Probability Density Functions:Integrated Spectrum

Martinez-Galarza et al., in prep.FLASH Talk. NOAO. November 19, 2010

Summary of results

We list the results with the 1- level uncertainties. For C and fPDR we only provide upper or lower

limits. Data at longer wavelengths needed to further constrain them.

30 Dor R136 [SIV] Bright

High AV

t (Myr) 1.5 ± 1.5 2.5 ± 2.0 1.0 ± 1.5 3.0 ± 2.5

log C <4.5 <4.5 <4.5 <4.0

fPDR >0.1 <0.3 >0.2 >0.2

log M★ (M) 5.4 ± 0.4 3.4 ± 0.6 4.0 ± 0.4 4.1 ± 0.4

log Memb (M) 4.9 ± 0.1 2.7 ± 0.2 3.4 ± 0.1 2.7 ± 0.2

log Mtot (M) 5.5 ± 0.4 3.4 ± 0.4 4.1 ± 0.4 4.1 ± 0.4

femb 0.31 0.20 0.25 0.04FLASH Talk. NOAO. November 19, 2010

Independent Checks

ParameterParameter ValueValue LiteratureLiterature

tt 2.5 +/- 2.0 Myr2.5 +/- 2.0 Myr ~1-2 Myr: Massey & Hunter et al. (1998),

log Mlog M★★ 3.4 +/- 0.6 solar 3.4 +/- 0.6 solar massesmasses

4.3 for R136 alone: Walborn & Apellaniz (2002)

Time resolution is not enough to judge if the hot component of dust represented by femb is related to embedded star formation.

We interpret it as dust that has not been pushed away by the stellar wind of the cluster and is associated to individual stars.

This component might imply that the modeling of the attenuation would be more complex than a simple dusty screen.

30 Dor R136 [SIV] Bright

High AV

femb 0.31 0.20 0.25 0.04

Other individual sources:

R136:


Next: NGC604 a higher metallicity environment

FLASH Talk. NOAO. November 19, 2010NGC 604 Spectral map at 8um

Summary

SED modeling provides a powerful tool to understand the physics of unresolved starbursts.

Interpretation of the results needs a robust fitting method that accounts for: Lack of sufficient data Model degeneracies Lack of independent checks

We have presented state-of-the-art models and a fitting routine that provides a complete solution for the model parameters

We applied the fitting routine to the mid-IR spectrum of 30 Doradus and found that: A component of ‘hot dust’ is necessary to fit the continuum slope. We associate this component to remaining dust in the vicinity of individual

stars. Continuum fit only is insufficient for constraining the hardness of the radiation

field. Nebular line analysis necessary Total cluster mass well constrained.


Summary

We applied the fitting routine to the mid-IR spectrum of 30 Doradus and found that: A component of ‘hot dust’ is necessary to fit

the continuum slope. We associate this component to remaining

dust in the vicinity of individual stars. Continuum fit only is insufficient for

constraining the hardness of the radiation field.

Nebular line analysis necessary Total cluster mass well constrained. Multi-wavelength analysis is necessary to

fully constrain all model parameters.


Mid-IR SFR indicators

With the advent of IR observatories, mid-IR diagnostics of SF have been proposed.

They trace the amount of OBSCURED star formation in starbursts.

Combined with optical diagnostics, they can trace the total SF.

Calzetti et al., 2007


Properties of 30 DoradusProperty Value Reference

Distance 50 ± 2.5 kpc Schaefer, 2008

Metallicity 0.4 Z Westerlund, 1997

Mass of ionized gas

8 × 105 M Kennicutt, 1984

H Luminosity 1.5 × 1040 erg s-1 Kennicutt, 1984

FIR Luminosity 4 × 107 L Werner et al., 1978

Mass of molecular gas

few × 105 M Johansson et al., 1998

Stellar mass of central cluster

5 × 104 M Andersen et al., 2009

Phase Location Stellar types Age

“Orion” near center (N&W) IR sources 1 Myr

“Carina” center (R136) O, WN stars 2-3 Myr

“Scorpius OB1” everywhere OB SGs 4-6 Myr

“Hodge 301” 3' NW of R136 B/A/M SGs 8-10 MyrWalborn & Blades, 1997FLASH Talk. NOAO. November 19, 2010

Individual Regions

IRAC 8m

Stellar Continuum

H

R136 High AVBright [SIV]


Spectra from individual regions


Ingredients of the SED modeling

Stars: source of ionizing radiation UV stellar continuum.

ISM Ionized gas: HII region PDR material Dust: silicates,

carbonaceous material, PAHs

Time evolution: mechanical luminosity.

MultiplicityBased on sketch by Mike Bolte, Rick Waters & Brenda Wilden


Individual regions


A New Milestone in Starburst SED Modeling: Using 30 Doradus as a Benchmark Rafael Martínez-Galarza...

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