Blue Supergiants in the E-ELT Era Extragalactic Stellar Astronomy
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1 Blue Supergiants in the E-ELT Era Extragalactic Stellar Astronomy Norbert Przybilla Institute for Astro- and Particle Physics
2 Supergiants BSGs evolved progeny of OB main-sequence stars T eff : ~ K M: ~ M L: ~ L R: ~ R BSGs: M V ~M J > -9.5 mag RSGs: M J > -11 mag with VLT/Keck: spectroscopy@high-res throughout Local out to 7-8Mpc
3 Blue Supergiants (BSGs) Meynet & Maeder (2000) BSGs evolved progeny of OB main-sequence stars B0-A5 T eff : ~ K M: ~ M L: ~ L R: ~ R BSGs: M V ~M J > -9.5 mag with VLT/Keck: spectroscopy@high-res throughout Local Group matters: B.C. & out to 7-8Mpc log RSGs Miguel Urbaneja
4 BSGs BSGs: how to find them? Bresolin et al. (2002) target selection photometrically BSG NGC300 easy to identify with ground-based/hst imaging RSG NGC300 Bresolin et al. (2005)
5 BSGs: high-quality observations Diagnostics Firnstein & Przybilla (2012) high-s/n Echelle spectra: FEROS, FOCES, CAFE, FIES, UVES R = λ/ λ= 40, , Å < λ< 9000Å
6 BSGs: what information can be extracted? quantitative spectroscopy via model atmospheres Diagnostics atmospheric parameters:. T eff, log g, ξ, vsin i, ζ, Y, Z, v rad stellar wind parameters: M, v, β fundamental stellar parameters: M, R, L, age elemental abundances: - He, CNO - α-process elements - iron group elements - s-process elemnets -(r-process elements) reddening, reddening law, ISM lines distances BSGs: what science can be addressed? spectral line formation under non-lte conditions stellar wind physics stellar evolution galaxy evolution ISM studies cosmic distance scale
7 Modelling Codes: hydrostatic: ATLAS/DETAIL/SURFACE hydrodynamic: FASTWIND & CMFGEN
8 Level populations: modelling approaches Modelling usually: LTE: Local Thermodynamic Equilibrium Saha-Boltzmann-Formulae, gf-values, line broadening Limited Tremendous Error hot, luminous stars: strong radiation field, low densities non-lte: non-local Thermodynamic Equilibrium rate equations, gf-values, line broadening, detailed level-coupling, millions of atomic cross-sections non-limited Tremendous Error
9 (Restricted) Non-LTE transfer equation Non-Local Thermodynamic Equilibrium Modelling statistical equilibrium: radiative rates: non-local collisional rates: local excitation, ionization, charge exchange, dielectronic recombination, etc. MgII Przybilla et al. (2001) model atoms
10 Atomic data Example: collisional excitation by e - -impact CII Modelling replacing approximations by experimental or ab-initio data Schrödinger equation Ω=1 Van Regemorter Formula LS-coupling: low-z Breit-Pauli Hamiltonian huge amounts of atomic data: OP/IRON Project & own Methods: R-matrix/CC approximation MCHF/MCDHF CCC
11 Modelling
12 Modelling: visual wavelengths HD92207 (A0 Iae) Modelling Przybilla et al. (2006) several 10 4 lines: ~30 elements, 60+ ionization stages complete spectrum synthesis in visual (& near-ir) ~70-80% in non-lte close match of models and observations
13 Elemental Abundances Przybilla et al. (2006) HD87737 (A0 Ib) VIS results absolute abundances relative to Cosmic Abundance Standard Nieva & Przybilla (2012) NLTE/LTE neutral ionized LTE: abundance pattern? - large uncertainties
14 Elemental Abundances Przybilla et al. (2006) HD87737 (A0 Ib) VIS results absolute abundances relative to Cosmic Abundance Standard Nieva & Przybilla (2012) NLTE/LTE neutral ionized no NLTE abundance corrections NLTE: consistency & reduced uncertainties
15 Summary: non-lte Modelling VIS results using robust analysis methodology& comprehensive model atoms ionization equilibria T eff /log g elements: e.g. C I/II, N I/II, O I/II, Mg I/II, Si II/III, S II/III, Fe I/II T eff / T eff ~ 1 2% usually: 5 10% Stark broadened hydrogen lines log g/t eff log g ~ 0.05 (cgs) usually: 0.2 microturbulence, helium abundance, metallicity + other constraints, where available: SED s, near-ir, minimising systematics! abundances: logε ~ dex(1σ stat.) usually: factor ~2 logε~ dex(1σ sys.) usually:??? + automatisation: tens to hundreds of stars analysable IAU Symposium 224: The A-Star Puzzle Poprad July 10, 2004
16 CNO mixing: objective quality test for analyses supergiants throughout MW nuclear physics: tight trend VIS results Przybilla et al. (2010), Nieva & Przybilla (2012), Firnstein & Przybilla (in prep.) OB-MS stars in solar neighbourhood
17 Preparing for E-ELT: Galactic BSGs with CRIRES Hi-res NIR CRyogenic high-resolution Infrared Echelle Spectrograph high resolving power R = λ/ λ 100,000 wavelength coverage 0.95 to 5.3 µm ~ 200 settings for full spectral coverage CRIRES+ detector: 4 x 4096 x 512 Aladdin III InSn Pilot program: 3 A-SGs HD87737 (A0 Ib) HD (A2 Iabe) HD92207 (A0 Iae) -(partial) coverage of J, H, K, L band
18 Near-IR: Telluric Line Correction Hi-res NIR Przybilla et al. (in prep.) high-resolution: detailed line profiles telluric lines resolved HD (A2 Iabe) telluric line removal via modelling: -radiative transfer code LBLRTM & HITRAN molecular database -GDAS atmospheric profiles adaptation expertise of Innsbruck ESO In-Kind Project
19 Przybilla et al. (in prep.) Near-IR spectra H + He atmospheric parameters metal lines in near-ir: C, N,O, Mg, Si, Fe, Sr+ He stellar evolution galactochemical evolution Hi-res NIR HD (A2 Iabe)
20 Przybilla et al. (in prep.) Near-IR spectra H + He atmospheric parameters metal lines in near-ir: C, N,O, Mg, Si, Fe, Sr+ He stellar evolution galactochemical evolution Hi-res NIR modelling: - extension of previous modelling - strong NLTE effects - good agreement with visual but adjustment of some model atoms necessary (NLTE amplification) improved atomic data HD (A2 Iabe) preparation for E-ELT ()
21 Extragalactic Stellar Astronomy Extragalactic Abundances so far: HII regions only indicators for abundances in nearby galaxies: He, N, O, Ne, S verification and extension via stars
22 Nebular abundances Extragalactic Stellar Astronomy strong line method: R 23 = f[n(o)/n(h)] Pagel et al. (1979) simple empirical calibration, but... R 23 depends on T electron, n electron, nature of ionizing stars, gas inhom., filling factors, depletion onto dust, velocity distribution,...
23 Extragalactic Stellar Astronomy Bresolin, Kudritzki, Méndez & Przybilla (2001) NGC 3621 VLT/FORS1 d ~ 6.6 Mpc
24 Extragalactic Stellar Astronomy Bresolin, Kudritzki, Méndez & Przybilla (2001) NGC3621 a Bresolin, Kudritzki, Méndez & Przybilla (2001) NGC 3621 spectrum synthesis for 0.5 and 0.2 solar metallicity VLT/FORS1 d ~ 6.6 Mpc
25 6 B-SGs Extragalactic Stellar Astronomy Urbaneja et al. (2005) Zaritsky et al. (1994) Abundance Gradients NGC300 gradient (nebulae): to steep, offset Kobulnicky et al. (1999) gradient (nebulae): slope fine, offset Pilyugin (2001) radial trend of O abundances different trends for HII-regions from 3 different R 23 -calibrations independent verification and extension via stellar analyses systematic bias in published gradients? gradient (nebulae): agreement Talk Miguel Urbaneja
26 Mass-metallicity relationship Extragalactic Stellar Astronomy Tremonti et al. (2004) Rosetta Stone for understanding galaxy formation and chemical evolution
27 Mass-metallicity relationship Extragalactic Stellar Astronomy Tremonti et al. (2004) However... something must be wrong... based on simplified emission line analysis
28 Mass-metallicity relationship -the stellar case Extragalactic Stellar Astronomy Hosek et al. (2014) Andrews & Martini (2013) direct method on stacked SDSS data metallicities for 13 star-forming galaxies Kewley & Ellison (2008) different strong-line calibrations stellar Local Group and beyond stellar vs. strong line analyses of HII regions investigate and minimise systematic bias of extragalactic metallicities
29 H 0 uncertainty and universe equation of state Extragalactic Stellar Astronomy Hubble constant uncertainty EoS parameter w despite enormous effort still: δh 0 ~ 5-10% w ~ 10-20% compare Freedman et al. (2001) Saha et al. (2001), Sandage et al. (2006) Mould & Sakai (2008, 2009ab) Riess et al. (2009, 2011, 2012) δh 0 ~ 3% δh 0 ~ 1%
30 Complications for extragalactic distances Extragalactic Stellar Astronomy metal-rich patchy dust extinction metal-poor metallicity depencence of distance indicators
31 Extragalactic Stellar Astronomy Flux weighted Gravity Luminosity Relationship (FGLR) Kudritzki, Bresolin & Przybilla (2003) B0-A5 Meynet & Maeder (2000) L, M ~ const. M ~ g R 2 ~ L (g/t 4 ) = const. const. with L ~ M x ~ L x (g/t 4 ) x x ~ 3 L 1-x ~ (g/t 4 ) x or with M bol ~ -2.5log L M bol = a log (g/t 4 ) + b FGLR a = 2.5 x/(1-x) ~ 3.75
32 Calibration of the FGLR Extragalactic Stellar Astronomy Kudritzki et al. (2008) M bol = 3.41 { log (g/t 4 eff,4) 1.5 } σ= 0.32 mag 10 objects per galaxy ( m M ) ~ 0.1 mag
33 Reddening, reddening law, extinction Extragalactic Stellar Astronomy Kudritzki et al. (2008) A2 Ia Teff = 9500 K log g = 1.45 FORS1 SED fit E(B-V), R V, A V HST/ACS
34 Reddening & impact on distances Extragalactic Stellar Astronomy M33 U et al. (2009) distance too large Kudritzki et al. (2012) M81 distance too short adopted by HST Key Project Freedman et al. (1994, 2001)
35 Distance determination with FGLR Extragalactic Stellar Astronomy Kudritzki et al. (2012) calibrated FGLR Kudritzki et al. (2008) shift to reach best match btw. observation & calibration DM d = 3.47 ±0.16 Mpc
36 The E-ELT perspective NGC from the Local Group to Virgo & Fornax Extragalactic Stellar Astronomy Field of View: several arcmin ideal NGC NGC CenA Target density O(100) in FoV depends on galaxy 16 M100 (Virgo) 22 NGC1365 (Fornax) R ~ 5000 sufficient for quantitative work on BSGs 12
37 M100 in Virgo Extragalactic Stellar Astronomy Stellar Spectroscopy in Virgo & Fornax problem: spatial resolution ~80pc diffraction-limited observation with ELT using AO (near-ir) starfield around Sk in LMC 5.5 x 5.5 in LMC 1 x Virgo deployable IFUs S/N constraints: S/N >
38 Summary Summary: BSGs are unique tools stellar atmosphere physics: non-lte, winds,... stellar evolution: metallicity effects He, CNO ISM studies in other galaxies galactic evolution: abundance patterns/gradients galaxies in Hubble sequence in field, groups & clusters 4 cosmic distance scale: FGLR L ~ log g/t eff Flux-weighted Gravity-Luminosity Relationship
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