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GOODS K-band mosaic

Making Sense of Restframe Mid-UV Spectra of Galaxies Using Hubble’s Next Generation Spectral Library Sally Heap, NASA/Goddard Granada, 3 Oct 2007. BC03. GOODS K-band mosaic. Daddi et al. 2005. The major spectral diagnostics, Mg UV , D4000, and H d

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GOODS K-band mosaic

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  1. Making Sense of Restframe Mid-UV Spectra of Galaxies Using Hubble’s Next Generation Spectral Library Sally Heap, NASA/GoddardGranada, 3 Oct 2007 BC03 GOODS K-band mosaic Daddi et al. 2005

  2. The major spectral diagnostics, MgUV, D4000, and Hd are all visible in the spectra of galaxies at z~0.4-1.0 z=

  3. Age(z, zf) Age(MSTO Teff, [Fe/H]) MgUV l>3500<8000 logZ -2.0 -1.5 -1.0 -0.5 +0.5

  4. z~1 galaxies • oldest stars <6 Gyr • wide spread in restframe B-V • restframe near-UV comes into view De Lucia & Blaizot 2006, astro-ph z=0.36 z=0.62 z=1.0 z=1.7

  5. The Mid-UV (2000-3000 Å) flux is produced mainly* by MSTO stars, the clock for stellar evolution Hottest stars =MSTO • Dealing with MSTO stars simplifies things greatly: • Observed spectrum looks like that of a single F-type MS star • Modeling of the atmosphere and spectrum is easier for MS F-type stars • Modeling of the interior structure is easier for F-type MS stars.

  6. * Except that blue HB stars may contaminate the UV spectrum of very old, metal-poor stellar populations Blue HB

  7. At z~1, blue HB stars should not be a problem

  8. The spread in Teff increases with lower metallicities [Fe/H]=0 [Fe/H]=-1.01 [a/Fe]=0.3 Isochrone log g Teff V-R isochrones

  9. The primary mid-UV feature is MgUV (composed of MgII, FeI, FeII, etc.) BC03 models Kurucz library HST UDF Daddi et al. 2005

  10. The MgUV feature can distinguish between a dusty, star-forming galaxy and an older, passively evolving galaxy but it cannot tell its age because of the age-metallicity degeneracy. Can we do better? BC03 Models of the Evolution of MgUV Adapted from Daddi et al. 2005

  11. Line blanketing, especially in the UV, distinguishes high-metallicity stars Can UV colors help?

  12. Problems with Spectral Models: Assumption of LTE, Missing Opacities B2640 MgII 2800 MgI 2850 Munari Castelli Chromospheric Emission

  13. NextGenerationSpectralLibrary HD 16031 HD 2665 (G5 IIIw) Teff=5004 log g=2.27 log Z= -1.96 ELODIE Teff log g log Z 6341 4.19 -1.12 (this study) 6114 4.07 -1.79 (Clem et al. 2004)

  14. Estimating the Stellar Parameters: Teff, logg, logZ, E(B-V) • Set up: • Resample STIS spectrum to resolution of Castelli’s models • Normalize observed & model spectra over 0.4-0.7 m • Make c2 fit to spectrum (Dl=0.20 -1.00 m) forTeff, logZ, and E(B-V) • Determine Lv range corresponding to V, p, ep • Calculate Lbol from BCv(Teff, logZ, E(B-V)) • Derive possible ilogg from comparison with • V-R evolutionary models • Make c2 fit for Teff, logg, logZ, and E(B-V) with • wt =1 for l=0.2-1.0 m, and wt =10 for Mgb • wt = 0 for MgII and CaII resonance lines ilogg cube (DT x DL x DZ)

  15. The most important stars for the UV-blue spectrum have Teff=5000-8000 K, log g ~ 3.8-4.5 Flux Contributions to stellar population at 6 Gyr, [Fe/H]=0

  16. Mid-UV colors are good distinguishers of metallicity among MSTO stars having similar line spectra 2500 2600 2700 2800 2900 3000

  17. BC03 Predictions

  18. Even fine spectral analyses have their uncertainties! (1)

  19. Even fine spectral analyses have their uncertainties! (2) Valenti & Fischer 2005 Log gSME – iso log g ~ +0.1

  20. MSTO stars can have the same Teff and log g but very different ages if they have different metallicities log g Teff

  21. MSTO MSTO

  22. 0.1 0.3 1 3 10 Gyr

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