1. New Developments in Starburst Modelling: 30 Doradus and NGC 604 as Benchmarks Rafael Martínez-Galarza Leiden Observatory Brent Groves (Leiden/MPIA) Bernhard Brandl (Leiden) Deidre Hunter (Lowell) Genevieve de Messieres (Virginia) Remy Indebetouw (Virginia) Kapteyn Astronomical Institute. January 26, 2011

2. Overview Starbursts in the Universe The Mid-IR properties of Starbursts Our benchmarks: 30 Dor and NGC 604 Data Models & Fitting Results Kapteyn Astronomical Institute. January 26, 2011

3. What is a starburst region? NGC 3603 in our Milky Way, Brandl et al., 1999  Region of space where the process of star formation is enhanced by particular conditions.  These are the places where most massive stars in galaxies are formed.  Up to ~10 5 M  of gas can be turned into stars simultaneously. (Engelbracht, 1996).  O stars interact with surrounding ISM.  IMF?? Galaxy Evolution?? Massive SF? Kapteyn Astronomical Institute. January 26, 2011

4. Mid-IR properties of Starbursts Brandl et al., 2006

5. Spectral Energy Distributions (SEDs) Modelling  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 SED. Brandl et al., 2006 Kapteyn Astronomical Institute. January 26, 2011

6. Ingredients of the SED modeling Based on sketch by Mike Bolte, Rick Waters & Brenda Wilden Kapteyn Astronomical Institute. January 26, 2011

7. SED Fitting  A grid of models given.  Given the observed SED, find best fit model.  However:  Robustness of results limited by quality and amount of data.  Many free model parameters.  Need to calibrate method (benchmarks).  Need objective method (results repeatable).  As long as those caveats are not taken care of, SED fitting will not provide unique and reliable results. Kapteyn Astronomical Institute. January 26, 2011

8. Our goal  Build a robust fitting routine that quantifies the uncertainties in the parameters and calibrates a specific model, by solving the mentioned issues.  We use a Bayesian inference approach.  We choose well known benchmarks with independent calibrations for its parameters. Kapteyn Astronomical Institute. January 26, 2011

9. Our benchmarks ESO Kapteyn Astronomical Institute. January 26, 2011 30 Doradus NGC 604 Similarities:  Two most luminous GHRs known to date.  Filamentary structure  IR luminosity -> ~ 4 × 10 7 L  (Brandl et al., 2005)  Stellar mass (few x 10 5 M , Bosch et al., 2009, Eldridge & Relaño, 2010) Differences  Different age distribution  Stellar density  H a luminosity 4 times bigger in 30 Doradus (1.5 × 10 40 erg s -1 ) than in NGC 604 (Hunter, 1999; Kennicutt, 1984)

10. A Multi-wavelength View [S IV]IRAC 8  mHST WFPC Kapteyn Astronomical Institute. January 26, 2011 30 Doradus NGC 604

11. The Spitzer-IRS spectral maps  Low resolution (R ~ 60-120) modules.  Wavelength coverage: 5.2- 38mm  Spatial resolution in the SL module is about 0.5 pc  Wavelengths shown:  33.4 um : [SIII]; I.P. = 34.8eV  10.5 um : [SIV]; I.P. = 47.30eV (ionized by most massive O3 stars)  6.2 um : PAH emission Indebetouw et al., 2009 Kapteyn Astronomical Institute. January 26, 2011

12. The two regions compared Kapteyn Astronomical Institute. January 26, 2011

13. Modelling expanding HII regions  Groves and collaborators.  How it works:  Stellar synthesis: Starburst99. Kroupa IMF, M cl = 10 6 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. Kapteyn Astronomical Institute. January 26, 2011

14. Model Parameters  Metallicity, Z  ISM pressure, P 0 /k  Cluster age, t  Stellar mass, M ★  ‘Embedded mass’, M emb  PDR covering, f PDR  Compactness, C Kapteyn Astronomical Institute. January 26, 2011 UCHIIRs SB99 synthetic spectra evolution of the HII region HII regions at 0 – 10 Myr impact of PDRs old stars & diffuse emission

15. Compactness C  Can be defined from M cl and P 0 /k as: log C = 3/5 log(M cl ) + (2/5)log (P 0 /k)  Intuitively, it has to do with the proximity of the dust to the ionizing stars.  For a given value of C, a run of T dust with time is defined.  Controls the position of the IR bump. Kapteyn Astronomical Institute. January 26, 2011

16. 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) Kapteyn Astronomical Institute. January 26, 2011

17. Our priors  Grid size: ~9 x 10 5 models  We introduce bounded uniform priors for M ★, M emb, f PDR and C. Z = 0.4 Z_sun, P 0 /k remain fixed.  Boundaries are set to cover broad range of physical environments.  For example, log C 6.5 has never been measured. ParameterRangeResolution t (Myr)0-100.5 Log C3-6.50.5 f PDR 0.0-1.00.05 M★M★ 2 orders of magnitude0.13 dex M emb 1.2 orders of magnitude0.08 dex Kapteyn Astronomical Institute. January 26, 2011

18. Continuum fitting: Integrated spectrum  With the defined priors we run the routine for continuum (Thermal + PAH) fitting.  Routine input: Observed spectrum, observational errors, priors.  Routine output: best fit values and PDFs calculated over the multi-dimensional parameter space.  Fit is poor at ~15  m. Dust in hot component might be hotter. IRS data Model Embedded objects HII region PDR region Martinez-Galarza et al., in prep. Kapteyn Astronomical Institute. January 26, 2011

19. Probability Density Functions: Integrated Spectrum Martinez-Galarza et al., in prep. Kapteyn Astronomical Institute. January 26, 2011

20. 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.  For the integrated spectrum, used age derived from low-res line ratios.  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 Kapteyn Astronomical Institute. January 26, 2011

21. 30 Dor and NGC 604 compared Kapteyn Astronomical Institute. January 26, 2011 30 Doradus NGC 604 Best fit parameters t = 1.5 MyrM ★ = 2.8 × 10 5 M log C = 4.0M emb = 7.1 × 10 4 M f PDR =0.4 Best fit parameters t = 4.0 MyrM ★ = 2.1 × 10 5 M log C = 3.0M emb = 7.2 × 10 3 M f PDR =0.9

22. “Embedded” population exists  None of the spectra can be fitted without including this component.  Part of it could be related to the presence of embedded stars.  Embedded stars have been detected at centimeter wavelengths. Kapteyn Astronomical Institute. January 26, 2011 Maercker & Burtonl., 2005

23. Embedded mass  Time resolution is not enough to judge if the hot component of dust represented by f emb is related to embedded star formation.  Alternative explanation: 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 DorR136 30 Dor YSO candidate NGC 604 Stars NGC 604 IR bright f emb 0.310.200.360.020.010.04 Kapteyn Astronomical Institute. January 26, 2011

24. Independent measurements Kapteyn Astronomical Institute. January 26, 2011  NGC 604:  M* = 3.8 x 10 5 M  (Eldridge & Relaño, 2010)  Age = 3-5 Myr (Hunter et al., 1996)  30 Dor:  M* = 4.5 x 10 5 M  (Bosch et al, 2009, Selman et al., 1999)  Age = 2-3 Myr (Walborn & Blades, 1997)  f PDR and f emb consistent with NGC 604 being a more evolved system.

25. Summary  SED modeling provides a powerful tool to understand the physics of unresolved starbursts.  BUT: calibrated, repeatable method needed  We have presented state-of-the-art models and a fitting routine that provides a complete solution for the model parameters.  Calibration using 30 Doradus and NGC 604 suggest that a robust determination of mass, age, amount of PDR material and embedded population is possible for unresolved systems.  Continuum fitting is insufficient to constrain all parameters. Nebular line analysis needed.  NEXT step: Apply to set of unresolved star-forming galaxies Kapteyn Astronomical Institute. January 26, 2011

26. Individual Regions  Types of sources  Star clusters (R136)  IR-bright sources – IR excess  High Extinction sources – Deep silicate absorption  Strong ionization sources Kapteyn Astronomical Institute. January 26, 2011 NGC 60430 Doradus