Evanthia Hatziminaoglou, ESO - Garching & VOTech Science Team

1. The Initial Mass Function of Massive Stars Evanthia Hatziminaoglou, ESO - Garching & VOTech Science Team http://www.euro-vo.org/pub/fc/workflows/IMF.html Astronomy with Virtual Observatories, Pune 15-19 October 2007

2. IMF of Massive Stars High mass stars: tracers of young populations in galaxies Bright-end IMF: crucial for determining mass upper limit and its connection to environment Exact mass of observed stars (from CMD) needed to compute IMF Stellar clusters: distance and extinction constant for all star members

3. What do we want to do? Identify massive stars, by colour • Look for them in open clusters, where distance and extinction is the same for all star members • Build their SEDs based on archival multi-colour data (SDSS, 2MASS) • Retrieve models of massive stars • Compare the observed SEDs of the candidates with the model SEDs and classify the stars

4. What do we need? • Access the data (catalogues) • Search for SDSS and 2MASS counterparts • Positional cross-matching of the data • Visualise the data • Select sample based on physical constraints • Conversion of magnitudes to fluxes • Homogenisation of units • Transpose columns and rows • Insert filters effective wavelength • Access model data • Compare observed SEDs with models • ...

5. The tools • Aladin: 1, (2, 3), • Topcat: (2), 3, 4, 5, 6, 7, 9, (11) • VOspec: 11 • conesearch.py: 2 • STILTS: 8 • SVO theoretical model web server: 10 • Astrogrid Workbench: PLASTIC, Astro Runtime

6. The actual science case

9. Sample Selection Dias et al. 2002 - 2005 contains 1689 open clusters and candidates • Low reddening: E(B-V) < 0.2 or $10<0.2 • Distance larger than 0.5kpc: Dist < 500 or $9<500 • Angular size smaller than 0.5 degrees: Diam < 30 or $8<30 • With over 30 known members: Nc > 30 or $16>30

11. Cone Search Python Workflow that replaced the original Astrogrid Workflow

14. Example: NGC2420

15. Example: NGC2420

16. (What do we want to do?) Identify massive stars, by colour • Look for them in open clusters, where distance and extinction is the same for all star members • Build their SEDs based on archival multi-colour data (SDSS, 2MASS) • Retrieve models of massive stars • Compare the observed SEDs of the candidates with the model SEDs and classify the stars

17. (What do we need?) • Access the data (catalogues) [Aladin] • Search for SDSS and 2MASS counterparts [ConeSearch Workflow] • Positional cross-matching of the data [Topcat] • Visualise the data [Topcat] • Select sample based on physical constraints [Topcat] • Conversion of magnitudes to fluxes • Homogenisation of units • Transpose columns and rows • Insert filters effective wavelength • Access model data [SVO model web service] • Compare observed SEDs with models

18. E(B-V) = 0.029; E(U-B) = 0.72*E(B-V) = 0.021 (Turner 1989) u-g = 0.75*(U-B) + 0.77*(B-V)+ 0.72 (Jordi et al. 2006) u-g < 1.02

19. 38 selected; 3 are galaxies according to SDSS “Type”

20. 2MASS AB corrections: J: 0.933 H: 1.407 K: 1.870 ABmag=Vega_mag + ABcorr fλ = c/λ2 * fν

22. (What do we want to do?) Identify massive stars, by colour • Look for them in open clusters, where distance and extinction is the same for all star members • Build their SEDs based on archival multi-colour data (SDSS, 2MASS) • Retrieve models of massive stars • Compare the observed SEDs of the candidates with the model SEDs and classify the stars

23. (What do we need?) • Access the data (catalogues) [Aladin] • Search for SDSS and 2MASS counterparts [ConeSearch Workflow] • Positional cross-matching of the data [Topcat] • Visualise the data [Topcat] • Select sample based on physical constraints [Topcat] • Conversion of magnitudes to fluxes [Topcat] • Homogenisation of units [Topcat] • Transpose columns and rows [STILTS] • Insert filters effective wavelength [Topcat] • Access model data [SVO model web service] • Compare observed SEDs with models

24. Comparison of observed and model SEDs • Topcat (visually) • VOSpec (semi-automatically) • Yafit (fully automatically but not very user-friendly yet) Are our candidates indeed hot stars?

28. Usage: fit [-help] [-debug] model=<model-file> [modelfmt=ymodel|galaxev|starburst99|svotar|sideways-vot] obs=<obs-file> [smoother=square|point] [scale=true|false] [fitcalc=chi2|poisson|unscaled] [gui=true|false] [summary=<out-file>] [bestfits=<out-table>] [bestfitsfmt=<out-format>] Usage: plotmodel [-help] [-debug] in=<model-file> [ifmt=ymodel|galaxev|starburst99|svotar|sideways-vot] Usage: plotobs [-help] [-debug] in=<obs-file> http://www.star.bris.ac.uk/~mbt/yafit/