The GaiaESO Survey C Allende Prieto Instituto de

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The Gaia-ESO Survey C. Allende Prieto Instituto de Astrofísica de Canarias

The Gaia-ESO Survey C. Allende Prieto Instituto de Astrofísica de Canarias

NGC 7331 IR Spitzer Smith et al. (2004); image courtesy NASA/JPL – Caltech/STSc. I

NGC 7331 IR Spitzer Smith et al. (2004); image courtesy NASA/JPL – Caltech/STSc. I LMU, October 8, 2007

The Milky Way blue: 12 m green: 60 m red: 100 m LMU, October

The Milky Way blue: 12 m green: 60 m red: 100 m LMU, October 8, 2007 IRAS – ipac/Cal. Tech

Formation of the Milky Way • Cold dark matter simulations predict a bottom-up scenario

Formation of the Milky Way • Cold dark matter simulations predict a bottom-up scenario for galaxy formation. • There is secular evolution as well. • Galaxies evolved chemically, under the right conditions, since each generation of stars progressively enriches the gas.

Galaxy assembly • Small galaxies merge to build larger and larger galaxies • Central

Galaxy assembly • Small galaxies merge to build larger and larger galaxies • Central black holes grow in that process • Feedback mechanisms can even stop star formation

Chemical evolution • Big bang nucleosynthesis • Stellar nucleosynthesis: hydrostatic equilibrium, AGB • Explosive

Chemical evolution • Big bang nucleosynthesis • Stellar nucleosynthesis: hydrostatic equilibrium, AGB • Explosive nucleosynthesis • ISM spallation • Also destruction…

Chemical evolution • Star formation (t, m) • SFR • IMF Mc. William 1994

Chemical evolution • Star formation (t, m) • SFR • IMF Mc. William 1994 • elements primarily contributed from massive stars and Type II SNe • Type Ia start to contribute >~1 Gyr • Direct indicator of early star formation rate (SFR))

 • Accretion history: mergers, infalling gas (outgoing too, enough mass to retain gas?

• Accretion history: mergers, infalling gas (outgoing too, enough mass to retain gas? ) Reddy et al. 2006 Thick disk Thin disk

Chemical evolution • Secular evolution: stellar migration, inside out formation Schoenrich & Binney 2009

Chemical evolution • Secular evolution: stellar migration, inside out formation Schoenrich & Binney 2009

Chemical evolution • ISM mixing Pan, Scannapieco, Scalo 2009

Chemical evolution • ISM mixing Pan, Scannapieco, Scalo 2009

Structure of the Milky Way

Structure of the Milky Way

-Thin Disk -Thick Disk -Bulge (+bar) -Stellar Halo -Dark Halo Picture from Gene Smith’s

-Thin Disk -Thick Disk -Bulge (+bar) -Stellar Halo -Dark Halo Picture from Gene Smith’s astron. tutorial

Thin and thick disk

Thin and thick disk

Reddy et al. 2003

Reddy et al. 2003

Thick-disk and halo: SDSS

Thick-disk and halo: SDSS

Bulge and bar • Old and metal-rich populations • Most spectroscopic studies to date

Bulge and bar • Old and metal-rich populations • Most spectroscopic studies to date in Baade’s window (extinction is a big problem) • 2 MASS, WISE provided extensive data sets in the IR (photometry) • Recent VLT and AAT spectroscopic surveys at low resolution show a wide range of metallicities • APOGEE/SDSS providing massive spectroscopy (1 e 5 stars) at high resolution (R=22, 500) in the IR (1. 5 -1. 7 µm)

Observational tools • Astrometry: parallax, proper motion • Photometry: brightness, space distributions • Spectroscopy:

Observational tools • Astrometry: parallax, proper motion • Photometry: brightness, space distributions • Spectroscopy: radial velocity, chemical composition Gaia will do the three

Spectroscopy Low-resolution 1. Spectral typing 2. Coarse Radial velocities 3. Parameters, especially logg and

Spectroscopy Low-resolution 1. Spectral typing 2. Coarse Radial velocities 3. Parameters, especially logg and Teff -- but beware of E(B-V) High-resolution 1. Parameters 2. Very precise radial velocities 3. Detailed chemical compositions

Gaia spectroscopy • BP/RP: spectrophotometry (very low resolution) • RVS: high resolution, but limited

Gaia spectroscopy • BP/RP: spectrophotometry (very low resolution) • RVS: high resolution, but limited wavelength range (847 -874 nm) and, more important, low signal-to-noise

Gaia Blue photometer: 330 – 680 nm Red photometer: 640 – 1000 nm Figure

Gaia Blue photometer: 330 – 680 nm Red photometer: 640 – 1000 nm Figure courtesy EADS-Astrium

Photometry Measurement Concept RP spectrum of M dwarf (V=17. 3) Red box: data sent

Photometry Measurement Concept RP spectrum of M dwarf (V=17. 3) Red box: data sent to ground White contour: sky-background level Colour coding: signal intensity Figures courtesy Anthony Brown

Ideal tests • Shot, electronics (readout) noise • Synthetic spectra • Logg fixed (parallaxes

Ideal tests • Shot, electronics (readout) noise • Synthetic spectra • Logg fixed (parallaxes will constrain luminosity) G=18. 5 G=20 Bailer-Jones 2009 GAIA-C 8 -TN-MPIA-CBJ-043 S/N per pixel

(Spectro-)photometry • ILLIUM algorithm (Bailer-Jones 2008). Dwarfs: G=15 σ([Fe/H])=0. 21 σ(Teff)/Teff=0. 005 G=18. 5

(Spectro-)photometry • ILLIUM algorithm (Bailer-Jones 2008). Dwarfs: G=15 σ([Fe/H])=0. 21 σ(Teff)/Teff=0. 005 G=18. 5 σ([Fe/H])=0. 42 σ(Teff)/Teff=0. 008 G=20 σ([Fe/H])=1. 14 σ(Teff)/Teff=0. 021 G=20

Radial Velocity Measurement Concept Spectroscopy: 847– 874 nm (resolution 11, 500) Figures courtesy EADS-Astrium

Radial Velocity Measurement Concept Spectroscopy: 847– 874 nm (resolution 11, 500) Figures courtesy EADS-Astrium

Radial Velocity Measurement Concept Field of view RVS spectrograph CCD detectors RVS spectra of

Radial Velocity Measurement Concept Field of view RVS spectrograph CCD detectors RVS spectra of F 3 giant (V=16) S/N = 7 (single measurement) S/N = 77 (40 x 3 transits) Figures courtesy David Katz

RVS S/N ( per transit and ccd) • 3 window types: G<7, 7<G<10 (R=11,

RVS S/N ( per transit and ccd) • 3 window types: G<7, 7<G<10 (R=11, 500), G>10 (R~4500) • σ ~ (S + rdn 2) • Most of the time RVS is working with S/N<1 • End of mission spectra will have S/N > 10 x higher G magnitude Allende Prieto 2009, GAIA-C 6 -SP-MSSL-CAP-003

RVS produce • Radial velocities down to V~17 (108 stars) • Atmospheric parameters (including

RVS produce • Radial velocities down to V~17 (108 stars) • Atmospheric parameters (including overall metallicity) down to V~ 13 -14 (several 106 stars) (MATISSE algorithm, Recio-Blanco, Bijaoui & de Laverny 06) • Chemical abundances for several elements down to V~1213 (few 106 stars) • Extinction (DIB at 862. 0 nm) down to V~13 (e. g. Munari et al. 2008) • ~ 40 transits will identify a large number of new spectroscopic binaries with periods < 15 yr (CU 4, CU 6, CU 8)

Atmospheric parameters (Ideal tests) Solid: absolute flux Dashed: absolute flux, systematic errors (S/N=1/20) Dash-dotted:

Atmospheric parameters (Ideal tests) Solid: absolute flux Dashed: absolute flux, systematic errors (S/N=1/20) Dash-dotted: relative flux MATISSE algorithm to be used on these data (Recio-Blanco+ 06) Allende Prieto (2008)

Observational tools • Astrometry: parallax, proper motion • Photometry: brightness, space distributions • Spectroscopy:

Observational tools • Astrometry: parallax, proper motion • Photometry: brightness, space distributions • Spectroscopy: radial velocity, chemical composition Gaia will do the three, but additional data are needed on spectroscopy, due to very low resolution for BP/RP and limited spectral coverage, S/N, and depth for RVS

The Gaia-ESO Survey • Homogeneous spectroscopic survey of 105 stars in the Galaxy •

The Gaia-ESO Survey • Homogeneous spectroscopic survey of 105 stars in the Galaxy • [email protected]: simultaneous GIRAFFE + UVES observations • 2 GIRAFFE spectral settings for 105 stars • Unbiased sample of 104 G-type stars within 2 kpc • Target selection based on VISTA (JHK) photometry • Stars in the field and in ~ 100 clusters

High-resolution: UVES

High-resolution: UVES

High-resolution: UVES

High-resolution: UVES

High-resolution: UVES

High-resolution: UVES

High-resolution: UVES Hill et al. 2002: An r-element enriched metal-poor giant

High-resolution: UVES Hill et al. 2002: An r-element enriched metal-poor giant

Low-resolution: GIRAFFE

Low-resolution: GIRAFFE

Low-resolution: GIRAFFE MEDUSA mode

Low-resolution: GIRAFFE MEDUSA mode

Low-resolution: GIRAFFE 100 stars

Low-resolution: GIRAFFE 100 stars

Low-resolution: GIRAFFE

Low-resolution: GIRAFFE

Relevant parameters • Atmospheric parameters: those needed for interpreting spectra, sually: Teff, logg, [Fe/H]

Relevant parameters • Atmospheric parameters: those needed for interpreting spectra, sually: Teff, logg, [Fe/H] (Sometimes: R, micro/macro, E(B-V), v sin i) • Chemical abundances Li, Be, B, C, N, O, F, Na, Mg, Al, Si …

Basics: radiative transfer d. I/dτ = I – S S (and τ) includes microphysics

Basics: radiative transfer d. I/dτ = I – S S (and τ) includes microphysics (S includes an integral of I) T, P, ρ

Basics: Model atmospheres • Hydrostatic equilibrium (d. P/dz = -gρ) • Radiative equilibrium (or

Basics: Model atmospheres • Hydrostatic equilibrium (d. P/dz = -gρ) • Radiative equilibrium (or energy conservation) • Local Thermodynamical equilibrium (source function = Planck function) • Scaled solar composition

Teff • F = σTeff 4 • F R 2 = f d 2

Teff • F = σTeff 4 • F R 2 = f d 2 • Can be directly determined from bolometric flux measurements f and angular diameters (2 R/d) hard but spectacular progress recently • Photometry: model colors, IRFM • Spectroscopic: line excitation, Balmer lines • Spectrophotometric: model fluxes

Teff • IRFM • Multiple implementations Oxford (Blackwell+) 80 s, Alonso+ 90 s, Ramírez&

Teff • IRFM • Multiple implementations Oxford (Blackwell+) 80 s, Alonso+ 90 s, Ramírez& Meléndez / González-Hernández+ / Casagrande+ • Fairly model independent • Scales in fair agreement on the metal-rich end but conflicts for halo turn-off stars • Issues know for cool (K and beyond) spectral types (see Allende Prieto+ 04, S 4 N) • Now in good shape based on solar-analog calibrations

 • Multiple implementations Oxford (Blackwell+) 80 s, Alonso+ 90 s, Ramírez& Meléndez /

• Multiple implementations Oxford (Blackwell+) 80 s, Alonso+ 90 s, Ramírez& Meléndez / González-Hernández+ / Casagrande+ 00 s • Fairly model independent • Scales in fair agreement on the metal-rich end but conflicts for halo turn-off stars • Issues know for cool (K and beyond) spectral types (see Allende Prieto+ 04, S 4 N) • Now in good shape based on solar-analog calibrations

Teff • IRFM • Multiple implementations Oxford (Blackwell+) 80 s, Alonso+ 90 s, Ramírez&

Teff • IRFM • Multiple implementations Oxford (Blackwell+) 80 s, Alonso+ 90 s, Ramírez& Meléndez / González-Hernández+ / Casagrande+ 00 s • Fairly model independent • Scales in fair agreement on the metal-rich end but conflicts for halo turn-off stars • Issues know for cool (K and beyond) spectral types (see Allende Prieto+ 04, S 4 N) • Now in good shape based on solar-analog calibrations

Teff • IRFM • Multiple implementations Oxford (Blackwell+) 80 s, Alonso+ 90 s, Ramírez&

Teff • IRFM • Multiple implementations Oxford (Blackwell+) 80 s, Alonso+ 90 s, Ramírez& Meléndez / González-Hernández+ / Casagrande+ 00 s • Fairly model independent • Scales in fair agreement on the metal-rich end but conflicts for halo turn-off stars • Issues know for cool (K and beyond) spectral types (see Allende Prieto+ 04, S 4 N) • Now in good shape based on solar-analog calibrations

Teff • IRFM • Multiple implementations Oxford (Blackwell+) 80 s, Alonso+ 90 s, Ramírez&

Teff • IRFM • Multiple implementations Oxford (Blackwell+) 80 s, Alonso+ 90 s, Ramírez& Meléndez / González-Hernández+ / Casagrande+ 00 s • Fairly model independent • Scales in fair agreement on the metal-rich end but conflicts for halo turn-off stars • Issues know for cool (K and beyond) spectral types (see Allende Prieto+ 04, S 4 N) • Now in good shape based on solar-analog calibrations

Teff • IRFM • Multiple implementations Oxford (Blackwell+) 80 s, Alonso+ 90 s, Ramírez&

Teff • IRFM • Multiple implementations Oxford (Blackwell+) 80 s, Alonso+ 90 s, Ramírez& Meléndez / González-Hernández+ / Casagrande+ 00 s • Fairly model independent • Scales in fair agreement on the metal-rich end but conflicts for halo turn-off stars • Issues know for cool (K and beyond) spectral types (see Allende Prieto+ 04, S 4 N) • Now in good shape based on solar-analog calibrations

Teff • IRFM • Multiple implementations Oxford (Blackwell+) 80 s, Alonso+ 90 s, Ramírez&

Teff • IRFM • Multiple implementations Oxford (Blackwell+) 80 s, Alonso+ 90 s, Ramírez& Meléndez / González-Hernández+ / Casagrande+ 00 s • Fairly model independent • Scales in fair agreement on the metal-rich end but conflicts for halo turn-off stars • Issues know for cool (K and beyond) spectral types (see Allende Prieto+ 04, S 4 N) • Now in good shape based on solar-analog calibrations

Teff • weak-line excitation • Classical method lines of different formation depth (excitation energy)

Teff • weak-line excitation • Classical method lines of different formation depth (excitation energy) are very sensitive • Model dependent: <T(τ)>, turbulence, NLTE • Observationally friendly

Teff • Balmer lines • Perfected by Fuhrmann+ in the 90 s

Teff • Balmer lines • Perfected by Fuhrmann+ in the 90 s

Teff • Balmer lines • Perfected by Fuhrmann+ in the 90 s • Applied

Teff • Balmer lines • Perfected by Fuhrmann+ in the 90 s • Applied to echelle spectra by Barklem+

Teff • Balmer lines • Perfected by Fuhrmann+ in the 90 s • Applied

Teff • Balmer lines • Perfected by Fuhrmann+ in the 90 s • Applied to echelle spectra by Barklem • Improved theoretical broadening calculations -- see poster and a recent paper by Cayrel+ Main remaining issue is the effect of convection on thermal atmospheric structure -- need 3 D or an external calibration

Teff • spectrophotometry • Combines photometry and spectroscopy • Hard to get very high-quality

Teff • spectrophotometry • Combines photometry and spectroscopy • Hard to get very high-quality spectra (<2 -3%). Need space observations to access the UV • Great progress in the last decade (Bohlin+ Cohen+) • HST flux calibration based on Oke V scale plus hot DA WD models. Consistency all around with Vega and solar analogs • ACCESS (Kaiser+ 2011)

Teff • spectrophotometry • Combines photometry and spectroscopy • Hard to get very high-quality

Teff • spectrophotometry • Combines photometry and spectroscopy • Hard to get very high-quality spectra (<2 -3%). Need space observations to access the UV • Great progress in the last decade (Bohlin+ Cohen+) • HST flux calibration based on Oke V scale plus hot DA WD models. Consistency all around with Vega and solar analogs. Solar analogs observed With STIS compared with solar-like Kurucz models

Teff • spectrophotometry • Combines photometry and spectroscopy • Hard to get very high-quality

Teff • spectrophotometry • Combines photometry and spectroscopy • Hard to get very high-quality spectra (<2 -3%). Need space observations to access the UV • Great progress in the last decade (Bohlin+ Cohen+) • HST flux calibration based on Oke V scale plus hot DA WD models. Consistency all around with Vega and solar analogs. HD 201091 (Observations from STIS NGSL)

Teff • spectrophotometry • Combines photometry and spectroscopy • Hard to get very high-quality

Teff • spectrophotometry • Combines photometry and spectroscopy • Hard to get very high-quality spectra (<2 -3%). Need space observations to access the UV • Great progress in the last decade (Bohlin+ Cohen+) • HST flux calibration based on Oke V scale plus hot DA WD models. Consistency all around with Vega and solar analogs. HD 10780 (observations from STIS NGSL)

logg • Gravitational field compresses the gas giving a nearly exponential density structure (pressure)

logg • Gravitational field compresses the gas giving a nearly exponential density structure (pressure) • Hard to get with accuracy: the spectrum is only weakly sensitive to gravity • Photometry: ionization edges (Saha), molecular bands, or damping wings of strong metal lines • Spectroscopy: ionization balance (e. g. Fe/Fe+) or colisionally-dominated line wings • Stellar structure models (luminosity)

Logg • Photometry • Intermediate or narrow band filters (Strömgren, Mg 520 nm) taking

Logg • Photometry • Intermediate or narrow band filters (Strömgren, Mg 520 nm) taking advantage Majewski + 2000 of pressure-sensitive features Image: Michael Richmond

Logg • Spectroscopy • Ionization balance: model dependent • Strong lines (Na D, Mg

Logg • Spectroscopy • Ionization balance: model dependent • Strong lines (Na D, Mg b, Ca II IR triplet…) Ramirez+ 2006

Logg • Stellar structure • Need good luminosity determination (i. e. distance) • Relies

Logg • Stellar structure • Need good luminosity determination (i. e. distance) • Relies on interior models, fairly reliable but with caveats (solar conumdrum, convection recipes, difusion) • Need M and R, not age • Now statistically solid (Reddy+ 03, Jørgensen & Lindegren 05, Pont & Eyer …)

Logg • Stellar structure • Need good luminosity determination (i. e. distance) • Relies

Logg • Stellar structure • Need good luminosity determination (i. e. distance) • Relies on interior models, fairly reliable but with caveats (solar conumdrum, convection recipes, difusion) • Need M and R, not age • Dominated by errors in parallaxes for Hipparcos (V<9, d<100 pc) stars, but likely not the case for Gaia • Now statistically solid (Reddy+ 03, Jørgensen & Lindegren 05, Pont & Eyer …)

Logg • Stellar structure • Need good luminosity determination (i. e. distance) • Relies

Logg • Stellar structure • Need good luminosity determination (i. e. distance) • Relies on interior models, fairly reliable but with caveats (solar conumdrum, convection recipes, difusion) • Need M and R, not age • Dominated by errors in parallaxes for Hipparcos (V<9, d<100 pc) stars, but likely not the case for Gaia • Now statistically solid (Reddy+ 03, Jørgensen & Lindegren 05, Pont & Eyer …)

[Fe/H] • An oversimplification • High sensitivity of the spectrum (can also be derived

[Fe/H] • An oversimplification • High sensitivity of the spectrum (can also be derived from photometry including blue/UV), but highly model dependent • Need many weak lines, good atomic data, good spectra, and a good model

More… R, micro/macro E(B-V), v sin i • R needed for spherical models •

More… R, micro/macro E(B-V), v sin i • R needed for spherical models • Micro- macro-turbulence needed for hydrostatic models • E(B-V) needed in photometry/spectrophotometry data are involved • Rotation cannot be ignored, but hard to disentangle from other broadening mechanisms in late-type stars

Finally, chemical abundances • UV Atomic continuum opacities • Line absorption coefficients: damping wings

Finally, chemical abundances • UV Atomic continuum opacities • Line absorption coefficients: damping wings • Atomic and molecular data

Lawler, Sneden & Cowan 2004

Lawler, Sneden & Cowan 2004

Spectral line formation • • UV Atomic continuum opacities Line absorption coefficients: damping wings

Spectral line formation • • UV Atomic continuum opacities Line absorption coefficients: damping wings Atomic and molecular data NLTE

Na I Allende Prieto, Hubeny & Lambert 2003

Na I Allende Prieto, Hubeny & Lambert 2003

MISS Multiline Inversion of Stellar Spectra

MISS Multiline Inversion of Stellar Spectra

3 Observation/Analysis • Ø (8 m VLT), Coverage (broad UVES coverage, at least 2

3 Observation/Analysis • Ø (8 m VLT), Coverage (broad UVES coverage, at least 2 GIRAFFE setups), multiplexing (~100 objects on GIRAFFE and ~10 on UVES), R (low and high) • Data Reduction (ESO pipelines, completed with software at CASU/Univ. of Cambridge and ARCETRI) • Analysis: From Ews to line profiles (classical) • Neural networks, genetic algorithms and other optimization schemes (some teams)

Using the chemical abundance information The Golden Rule The Surface Composition of a star

Using the chemical abundance information The Golden Rule The Surface Composition of a star reflects that of the ISM at the. Time the star formed

Golden rule applies? yes • Galactic structure and chemical evolution

Golden rule applies? yes • Galactic structure and chemical evolution

Golden rule applies? yes • Galactic structure and chemical evolution • Solar Structure

Golden rule applies? yes • Galactic structure and chemical evolution • Solar Structure

Golden rule applies? yes • Galactic structure and chemical evolution • Solar Structure •

Golden rule applies? yes • Galactic structure and chemical evolution • Solar Structure • Cosmology: 1 H, 2 H, 3 He, 4 He, 7 Li, 6 Li

BBN Figure from Edward L. Wright

BBN Figure from Edward L. Wright

Golden rule applies? yes • • Galactic structure and chemical evolution Solar Structure Cosmology:

Golden rule applies? yes • • Galactic structure and chemical evolution Solar Structure Cosmology: 1 H, 2 H, 3 He, 4 He, 7 Li, 6 Li SN yields

R-process is universal Sneden et al. 2003

R-process is universal Sneden et al. 2003

Golden rule applies? NO • Diffusion (Sun, CPs, accretion, SN yields again)

Golden rule applies? NO • Diffusion (Sun, CPs, accretion, SN yields again)

Secondary stars in BH/NS binary systems Centaurus X-4 Gonzalez-Hernandez et al. 2005

Secondary stars in BH/NS binary systems Centaurus X-4 Gonzalez-Hernandez et al. 2005

Golden rule applies? NO • Difusion (Sun [M/H]-0. 07 dex, CPs, accretion, SN yields

Golden rule applies? NO • Difusion (Sun [M/H]-0. 07 dex, CPs, accretion, SN yields again) • Mixing and destruction (Li, Be)

Golden rule applies? NO • Difusion (Sun [M/H]-0. 07 dex, CPs, accretion, SN yields

Golden rule applies? NO • Difusion (Sun [M/H]-0. 07 dex, CPs, accretion, SN yields again) • Mixing and destruction (Li, Be) • RV Tauri stars

Giridhar et al. 2005

Giridhar et al. 2005

Gaia-ESO main Science Objectives • • • Galactic phase-space substructure Chemical evolution Star migration

Gaia-ESO main Science Objectives • • • Galactic phase-space substructure Chemical evolution Star migration Disk gradients and their time evolution Cluster evolution (formation, dissolution, self-polution)

The field stars • Mid-resolution GIRAFFE spectra (R~12, 000) for 105 stars to V

The field stars • Mid-resolution GIRAFFE spectra (R~12, 000) for 105 stars to V < 20 (mostly in the Gaia RVS gap) • GIRAFFE HR 21 (Ca II IR triplet) + HR 10 (~540 nm) with 10<S/N<30 to yield atmospheric param. , radial velocities, limited chemistry • UVES spectra for 104 G-type stars to V<15 with S/N>50 to yield detailed atmospheric parameters , high-precision radial velocities and 11+ elemental abundances

Breakdown by population • Bulge: bright (I~15) K-giants with 2 GIRAFFE settings at 50<S/N<100

Breakdown by population • Bulge: bright (I~15) K-giants with 2 GIRAFFE settings at 50<S/N<100 • Halo/Thick disk: F-type turn-off stars (SDSS 17<r<19) • Outer thick disk: F-type turnoff (75%) and K-type giants at intermediate galactic latitude • Thin disk (I~19) from 6 fields in the plane with HR 21 -only data (+ UVES sample)

The cluster stars • Cluster selection from Dias et al. (2002), Kharchenko et al.

The cluster stars • Cluster selection from Dias et al. (2002), Kharchenko et al. (2005), WEBDA catalogues, supplemented by exploratory program at Geneva • Only clusters with membership information considered • Nearby (<1. 5 kpc; down to M-dwarfs) and distant clusters (giants only) will be observed, sampling a wide range in age, [Fe/H], galactocentric distance and mass • 6 GIRAFFE settings (HR 03/05 A/06/14 A/15 N/21) down to V~19 Open clusters: * • +http: //ircamera. as. arizona. edu UVES sample down to V~16 Source:

The cluster stars • Cluster selection from Dias et al. (2002), Kharchenko et al.

The cluster stars • Cluster selection from Dias et al. (2002), Kharchenko et al. (2005), WEBDA catalogues, supplemented by exploratory program at Geneva • Only clusters with membership information considered • Nearby (<1. 5 kpc; down to M-dwarfs) and distant clusters (giants only) will be observed, sampling a wide range in age, [Fe/H], galactocentric distance and mass • 6 GIRAFFE settings (HR 03/05 A/06/14 A/15 N/21) down to V~19 • + UVES sample down to V~16

Observations and Calibration • Visitor mode observations -- started December 2011 • 300 nights

Observations and Calibration • Visitor mode observations -- started December 2011 • 300 nights over 5 years (~1500 pointings) • Target selection will be largely based on VISTA VHS photometry + additional information for clusters • ESO Archive (on-going analysis) • Calibration fields to control/match parameter/abundance scale across surveys

Data reduction/analysis • Data reduction performed at Cambridge and Arcetri likely based on ESO

Data reduction/analysis • Data reduction performed at Cambridge and Arcetri likely based on ESO pipeline • Radial velocity derivation • Object classification • Spectral analysis: atmospheric parameters and abundances • Gaia-ESO archive

Spectral analysis • • • UVES spectra of normal FGK stars GIRAFFE spectra of

Spectral analysis • • • UVES spectra of normal FGK stars GIRAFFE spectra of normal FGK stars Pre-MS and cool stars Hot (OBA-type) stars Funny things Survey parameter homogenization

Automation • Classical analysis methods can be coded in the computer • These will

Automation • Classical analysis methods can be coded in the computer • These will have limitations: need to reliably measure equivalent widths (EW) • Ultimately, the use of EW is related to simplify the calculations (scalar quantities instead of arrays) but is also somewhat blind, I. e. full spectral analysis preferred

Automation II • Optimization methods: local (gradient, Nelder. Mead…), global (metropolis, genetic algorithms…) •

Automation II • Optimization methods: local (gradient, Nelder. Mead…), global (metropolis, genetic algorithms…) • Projection methods (ANN, MATISSE, PCA, SVM…) • Bayesian methods • But many combinations possible • Spectral model can be calculated on the fly or interpolated • Issues are sometimes continuum normalization, complicated PSF, large number of dimensions, degeneracies

An example, the IAC node • FERRE optimization with interpolation on a pre-computed grid

An example, the IAC node • FERRE optimization with interpolation on a pre-computed grid • N-dimensional f 90 code • Various algorithms: Nelder-Mead (Nelder & Mead 1965), uobyqa (Powell 2002), Boender-Rinnooy Kan-Strougie. Timmer algorithm (1982) • Linear, quadratic, cubic spline interpolation • Spectral library on memory or disk • PCA compression • Handling of complex PSF w/o compression • Flexible: SDSS/SEGUE, WD surveys, APOGEE, STELLA, Gaia-ESO…

Abundances Stellar Parameters • • • 3 (Teff, log g, [Fe/H]) • For many/most

Abundances Stellar Parameters • • • 3 (Teff, log g, [Fe/H]) • For many/most targets (disk cool giants): 4 (Teff, log g, [Fe/H], [C/Fe]) - Teff, log g, Fe/H, C/Fe, N/Fe, O/Fe, maybe . 5 (Teff, log g, [Fe/H], [C/Fe], micro) • Simplify for metal-poor stars ([Fe/H] < -1 or -2): 5 (Teff, log g, [Fe/H], [C/Fe], [O/Fe]) - Teff, log g, Fe/H, O/Fe, maybe . 6 (Teff, log g, [Fe/H], [C/Fe], [O/Fe], E(B-V)) • Simplify for warmer types (G-F): 6 (Teff, log g, [Fe/H], [C/Fe], [N/Fe]) - Teff, log g, Fe/H, C/H, maybe . … A minute/star/processor (3. 5 days on 20 processors for 100, 000 stars) S/N=80 97 [Fe/H] [C/Fe] [O/Fe] E(B-V) Teff logg

Abundances Stellar Parameters Teff=4408 K logg=2. 13 Logmicro=0. 33 [Fe/H]=-0. 56 [C/Fe]=+0. 44 [N/Fe]=+0.

Abundances Stellar Parameters Teff=4408 K logg=2. 13 Logmicro=0. 33 [Fe/H]=-0. 56 [C/Fe]=+0. 44 [N/Fe]=+0. 02 [O/Fe]=+0. 50 98 ASPCAP Fitting the Arcturus spectrum (Hinkle et al. ) smoothed to R=30, 000

Automated analysis: GIRAFFE • Tests with MILES spectra (R~2000) from the INT (Sanchez Blazquez

Automated analysis: GIRAFFE • Tests with MILES spectra (R~2000) from the INT (Sanchez Blazquez et al. 2006) • The same code (FERRE) • Fitting data calibrated in flux and continuum -normalized

Software • • Gaussian LSF (fiber, wavelength) Quadratic interpolation of fluxes Normalization by blocks

Software • • Gaussian LSF (fiber, wavelength) Quadratic interpolation of fluxes Normalization by blocks Successful tests performed on MILES library

Continuum on This Work MILES parameters (Cenarro et al. 2009) [Fe/H] Teff logg Distributions

Continuum on This Work MILES parameters (Cenarro et al. 2009) [Fe/H] Teff logg Distributions of residuals

Continuum off This Work MILES parameters (Cenarro et al. 2009) [Fe/H] Teff logg Distributions

Continuum off This Work MILES parameters (Cenarro et al. 2009) [Fe/H] Teff logg Distributions of residuals

Consortium • • Over 300 people involved (90+ centers) 2 co-Pis (G. Gilmore and

Consortium • • Over 300 people involved (90+ centers) 2 co-Pis (G. Gilmore and S. Randich) A steering committee 17 working groups

Steering Committee

Steering Committee

Working groups

Working groups

Data Release • All raw data immediately public • 3 -level data products with

Data Release • All raw data immediately public • 3 -level data products with different time scales • Level-1: 1 D spectra, associated photometry, object classification and RVs (release every 6 months) • Level-2: RV variability info, atmospheric parameters and abundances (yearly releases) • Level-3: all of the above for final co-added data and mean cluster metallicities (end of survey)

Competition • • SDSS, SEGUE 1/2 BOSS SDSS-III APOGEE HERMES HETDEX After Sloan 3

Competition • • SDSS, SEGUE 1/2 BOSS SDSS-III APOGEE HERMES HETDEX After Sloan 3 (STREAMS, APOGEE-II/S) [Big. BOSS, 4 MOST, MOONS, WEAVE]

Recent trends in spectroscopic studies • 3 D model atmospheres: a beginning • full

Recent trends in spectroscopic studies • 3 D model atmospheres: a beginning • full NLTE: good progress for hot stars, but … • Data archival: survey projects going on with massive archives that become public (low-res: SDSS, SEGUE, GALEX) (high-res: Elodie, S 4 N) • Analysis automation: a beginning • Breaking the Z barrier

The Desirable future • 3 D model atmospheres • full NLTE • A pending

The Desirable future • 3 D model atmospheres • full NLTE • A pending observational test for solar-type stars: center-tolimb variation of the solar spectrum • Data archival: VOs (including both observations and models) • Stronger efforts to measure/compute atomic data • Stronger efforts to use the newly available atomic data • Full analysis automation • R – an ignored variable?

Gaia-ESO Summary • 100, 000 stars at mid-resolution (x 2 GIRAFFE settings) and 10,

Gaia-ESO Summary • 100, 000 stars at mid-resolution (x 2 GIRAFFE settings) and 10, 000 stars at high-resolution: 300 VLT nights over 5 yr • Field stars and open clusters • Uniform composition and radial velocity information across the Galaxy complementing Gaia’s data • Large european consortium • Swift schedule for data reduction/processing/analysis/delivery • But serious competition!