The Gaia-ESO Survey

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The Gaia-ESO Survey

• C. Allende Prieto
• Instituto de Astrofísica de Canarias

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NGC 7331 IR Spitzer
Smith et al. (2004) image courtesy NASA/JPL
Caltech/STScI
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The Milky Way
blue 12 ?m green 60 ?m red 100 ?m
IRAS ipac/CalTech
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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.

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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

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Chemical evolution

• Big bang nucleosynthesis
• Stellar nucleosynthesis hydrostatic equilibrium,
  AGB
• Explosive
• nucleosynthesis
• ISM spallation
• Also destruction

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Chemical evolution

• Star formation (t, m)
• SFR
• IMF

McWilliam 1994

• ? elements primarily contributed from massive
  stars and Type II SNe
• Type Ia start to contribute gt1 Gyr
• Direct indicator of early star formation rate
  (SFR))?

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

Reddy et al. 2006
Thick disk
Thin disk
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Chemical evolution

• Secular evolution stellar migration, inside out
  formation

Schoenrich Binney 2009
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Chemical evolution

• ISM mixing

Pan, Scannapieco, Scalo 2009
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Structure of the Milky Way
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• Thin Disk
• Thick Disk
• Bulge (bar)
• Stellar Halo
• Dark Halo

Picture from Gene Smiths astron. tutorial
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Thin and thick disk
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Reddy et al. 2003
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Thick-disk and halo SDSS
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Bulge and bar

• Old and metal-rich populations
• Most spectroscopic studies to date in Baades
  window (extinction is a big problem)
• 2MASS, WISE provided extensive data sets in the
  IR (photometry)
• Recent VLT and and AAT spectroscopic surveys at
  low resolution show a wide range of metallicities
• APOGEE/SDSS providing massive spectroscopy (1e5
  stars) at high resolution (R22,500) in the IR
  (1.5-1.7 µm)

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Observational tools

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

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Spectroscopy

• Low-resolution
• Spectral typing
• Coarse Radial velocities
• Parameters, especially logg and Teff -- but
  beware of E(B-V)

• High-resolution
• Parameters
• Very precise radial velocities
• Detailed chemical compositions

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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

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Gaia
Blue photometer 330 680 nm Red
photometer 640 1000 nm

Figure courtesy EADS-Astrium
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Photometry Measurement Concept
RP spectrum of M dwarf (V17.3) Red box data
sent to ground White contour sky-background
level Colour coding signal intensity
Figures courtesy Anthony Brown
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Ideal tests

• Shot, electronics (readout) noise
• Synthetic spectra
• Logg fixed (parallaxes will constrain luminosity)

S/N per pixel
G18.5
G20
Bailer-Jones 2009 GAIA-C8-TN-MPIA-CBJ-043
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(Spectro-)photometry

• ILLIUM algorithm (Bailer-Jones 2008). Dwarfs
• G15 s(Fe/H)0.21 s(Teff)/Teff0.005
• G18.5 s(Fe/H)0.42 s(Teff)/Teff0.008
• G20 s(Fe/H)1.14 s(Teff)/Teff0.021

G20
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Radial Velocity Measurement Concept
Spectroscopy 847874 nm (resolution 11,500)
Figures courtesy EADS-Astrium
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Radial Velocity Measurement Concept
RVS spectrograph
CCD detectors
Field of view
RVS spectra of F3 giant (V16) S/N 7 (single
measurement) S/N 77 (40x3 transits)
Figures courtesy David Katz
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RVS S/N ( per transit and ccd)

• 3 window types Glt7, 7ltGlt10 (R11,500), Ggt10
  (R4500)
• s (S rdn2)
• Most of the time RVS is working with S/Nlt1
• End of mission spectra will have S/N gt 10x higher

G magnitude
Allende Prieto 2009, GAIA-C6-SP-MSSL-CAP-003
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RVS produce

• Radial velocities down to V17 (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
  V12-13 (few 106 stars)
• Extinction (DIB at 862.0 nm) down to V13 (e.g.
  Munari et al. 2008)
• 40 transits will identify a large number of new
  spectroscopic binaries with periods lt 15 yr (CU4,
  CU6, CU8)

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Atmospheric parameters (Ideal tests)

• Solid absolute flux
• Dashed absolute flux, systematic errors
  (S/N1/20)
• Dash-dotted relative flux

MATISSE algorithm to be used on these data
(Recio-Blanco 06)
Allende Prieto (2008)
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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

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The Gaia-ESO Survey

• Homogeneous spectroscopic survey of 105 stars in
  the Galaxy
• FLAMES_at_VLT 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

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High-resolution UVES
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High-resolution UVES
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High-resolution UVES
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High-resolution UVES
Hill et al. 2002 An r-element enriched
metal-poor giant
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Low-resolution GIRAFFE
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Low-resolution GIRAFFE
MEDUSA mode
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Low-resolution GIRAFFE
100 stars
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Low-resolution GIRAFFE
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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

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Basics radiative transfer

• dI/dt I S
• S (and t) includes microphysics
• (S includes an integral of I)

T, P, ?
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Basics Model atmospheres

• Hydrostatic equilibrium (dP/dz -g?)
• Radiative equilibrium (or energy conservation)
• Local Thermodynamical equilibrium (source
  function Planck function)
• Scaled solar composition

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Teff

• F sTeff4
• F R2 f d2
• Can be directly determined from bolometric flux
  measurements f and angular diameters (2R/d)
• hard but spectacular progress recently
• Photometry model colors, IRFM
• Spectroscopic line excitation, Balmer lines
• Spectrophotometric model fluxes

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Teff IRFM

• Multiple implementations
• Oxford (Blackwell) 80s, Alonso 90s,
  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, S4N)
• Now in good shape based on solar-analog
  calibrations

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• Multiple implementations
• Oxford (Blackwell) 80s, Alonso 90s,
  Ramírez Meléndez / González-Hernández /
  Casagrande 00s
• 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, S4N)
• Now in good shape based on solar-analog
  calibrations

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Teff IRFM

• Multiple implementations
• Oxford (Blackwell) 80s, Alonso 90s,
  Ramírez Meléndez / González-Hernández /
  Casagrande 00s
• 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, S4N)
• Now in good shape based on solar-analog
  calibrations

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Teff IRFM

• Multiple implementations
• Oxford (Blackwell) 80s, Alonso 90s,
  Ramírez Meléndez / González-Hernández /
  Casagrande 00s
• 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, S4N)
• Now in good shape based on solar-analog
  calibrations

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Teff IRFM

• Multiple implementations
• Oxford (Blackwell) 80s, Alonso 90s,
  Ramírez Meléndez / González-Hernández /
  Casagrande 00s
• 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, S4N)
• Now in good shape based on solar-analog
  calibrations

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Teff IRFM

• Multiple implementations
• Oxford (Blackwell) 80s, Alonso 90s,
  Ramírez Meléndez / González-Hernández /
  Casagrande 00s
• 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, S4N)
• Now in good shape based on solar-analog
  calibrations

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Teff IRFM

• Multiple implementations
• Oxford (Blackwell) 80s, Alonso 90s,
  Ramírez Meléndez / González-Hernández /
  Casagrande 00s
• 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, S4N)
• Now in good shape based on solar-analog
  calibrations

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Teff weak-line excitation

• Classical method
• lines of different formation
• depth (excitation energy)
• are very sensitive
• Model dependent ltT(t)gt,
• turbulence, NLTE
• Observationally friendly

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Teff Balmer lines

• Perfected by Fuhrmann in the 90s

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Teff Balmer lines

• Perfected by Fuhrmann in the 90s
• Applied to echelle spectra by Barklem

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Teff Balmer lines

• Perfected by Fuhrmann in the 90s
• 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 the thermal atmospheric
• structure -- need 3D or an
• external calibration
• But NLTE effects may be involved (Barklem 2007)

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Teff spectrophotometry

• Combines photometry and spectroscopy
• Hard to get very high-quality spectra (lt2-3).
  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)

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Teff spectrophotometry

• Combines photometry and spectroscopy
• Hard to get very high-quality spectra (lt2-3).
  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
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Teff spectrophotometry

• Combines photometry and spectroscopy
• Hard to get very high-quality spectra (lt2-3).
  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)
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Teff spectrophotometry

• Combines photometry and spectroscopy
• Hard to get very high-quality spectra (lt2-3).
  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)
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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)

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Logg Photometry

• Intermediate or narrow band filters (Strömgren,
  Mg 520 nm) taking advantage of pressure-sensitive
  features

Majewski 2000
Image Michael Richmond
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Logg Spectroscopy

• Ionization balance model dependent
• Strong lines (Na D, Mg b, Ca II IR triplet)

Ramirez 2006
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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 )

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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
  (Vlt9, dlt100 pc) stars, but likely not the case
  for Gaia
• Now statistically solid (Reddy 03, Jørgensen
  Lindegren 05, Pont Eyer )

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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
  (Vlt9, dlt100 pc) stars, but likely not the case
  for Gaia
• Now statistically solid (Reddy 03, Jørgensen
  Lindegren 05, Pont Eyer )

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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

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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

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Finally, chemical abundances

• UV Atomic continuum opacities
• Line absorption coefficients damping wings
• Atomic and molecular data

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Lawler, Sneden Cowan 2004
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Spectral line formation

• UV Atomic continuum opacities
• Line absorption coefficients damping wings
• Atomic and molecular data
• NLTE

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Na I
Allende Prieto, Hubeny Lambert 2003
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MISSMultiline Inversion of Stellar Spectra
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3 Observation/Analysis

• Ø (8m 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)

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Using the chemical abundance informationThe
Golden Rule
The Surface Composition of a star reflects that
of the ISM at theTime the star formed
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Golden rule applies? yes

• Galactic structure and chemical evolution

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Golden rule applies? yes

• Galactic structure and chemical evolution
• Solar Structure

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Golden rule applies? yes

• Galactic structure and chemical evolution
• Solar Structure
• Cosmology 1H, 2H, 3He, 4He, 7Li, 6Li

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BBN
Figure from Edward L. Wright
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Golden rule applies? yes

• Galactic structure and chemical evolution
• Solar Structure
• Cosmology 1H, 2H, 3He, 4He, 7Li, 6Li
• SN yields

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R-process is universal
Sneden et al. 2003
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Golden rule applies? NO

• Diffusion (Sun, CPs, accretion, SN yields again)

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Secondary stars in BH/NS binary systems
Centaurus X-4
Gonzalez-Hernandez et al. 2005
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Golden rule applies? NO

• Difusion (Sun M/H-0.07 dex, CPs, accretion, SN
  yields again)
• Mixing and destruction (Li, Be)

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Golden rule applies? NO

• Difusion (Sun M/H-0.07 dex, CPs, accretion, SN
  yields again)
• Mixing and destruction (Li, Be)
• RV Tauri stars

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Giridhar et al. 2005
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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)

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The field stars

• Mid-resolution GIRAFFE spectra (R12,000) for 105
  stars to V lt 20 (mostly in the Gaia RVS gap)
• GIRAFFE HR21 (Ca II IR triplet) HR10 (540 nm)
  with 10ltS/Nlt30 to yield atmospheric param.,
  radial velocities, limited chemistry
• UVES spectra for 104 G-type stars to Vlt15 with
  S/Ngt50 to yield detailed atmospheric parameters ,
  high-precision radial velocities and 11
  elemental abundances

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Breakdown by population

• Bulge bright (I15) K-giants with 2 GIRAFFE
  settings at 50ltS/Nlt100
• Halo/Thick disk F-type turn-off stars (SDSS
  17ltrlt19)
• Outer thick disk F-type turnoff (75) and K-type
  giants at intermediate galactic latitude
• Thin disk (I19) from 6 fields in the plane with
  HR21-only data ( UVES sample)

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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 (lt1.5 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 (HR03/05A/06/14A/15N/21) down
  to V19
• UVES sample down to V16

Open clusters Source http//ircamera.as.arizon
a.edu
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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 (lt1.5 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 (HR03/05A/06/14A/15N/21) down
  to V19
• UVES sample down to V16

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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

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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

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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

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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

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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

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An example, the IAC node

• FERRE optimization with interpolation on a
  pre-computed grid
• N-dimensional f90 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

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Abundances Stellar Parameters

• 3 (Teff, log g, Fe/H)
• 4 (Teff, log g, Fe/H, C/Fe)
• 5 (Teff, log g, Fe/H, C/Fe, micro)
• 5 (Teff, log g, Fe/H, C/Fe, O/Fe)
• 6 (Teff, log g, Fe/H, C/Fe, O/Fe, E(B-V))
• 6 (Teff, log g, Fe/H, C/Fe, C/Fe, N/Fe)

• For many/most targets (disk cool giants) -
  Teff, log g, Fe/H, C/Fe, N/Fe, O/Fe, maybe ?.
• Simplify for metal-poor stars (Fe/H lt -1 or
  -2) - Teff, log g, Fe/H, O/Fe, maybe ?.
• Simplify for warmer types (G-F) - Teff,
  log g, Fe/H, C/H, maybe ?.

A minute/star/processor (3.5 days on 20
processors for 100,000 stars)
S/N80
Fe/H C/Fe O/Fe
E(B-V) Teff
logg
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Abundances Stellar Parameters
Teff4408 K logg2.13 Logmicro0.33
Fe/H-0.56 C/Fe0.44 N/Fe0.02
O/Fe0.50
ASPCAP Fitting the Arcturus spectrum (Hinkle et
al.) smoothed to R30,000
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Automated analysis GIRAFFE

• Tests with MILES spectra (R2000) from the INT
  (Sanchez Blazquez et al. 2006)
• The same code (FERRE)
• Fitting data calibrated in flux and
  continuum-normalized

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Software

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

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

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

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Steering Committee
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Working groups
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Data Release

• All raw data immediately public
• 3-level data products with different time scales
• Level-1 1D 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)

107
Competition

• SDSS, SEGUE1/2
• BOSS
• SDSS-III APOGEE
• HERMES
• HETDEX
• After Sloan 3 (STREAMS, APOGEE-II/S)
• BigBOSS, 4MOST, MOONS, WEAVE

108
Recent trends in spectroscopic studies

• 3D 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, S4N)
• Analysis automation a beginning
• Breaking the Z barrier

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The Desirable future

• 3D model atmospheres
• full NLTE
• A pending observational test for solar-type
  stars center-to-limb 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?

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Gaia-ESO Summary

• 100,000 stars at mid-resolution (x2 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
  Gaias data
• Large european consortium
• Swift schedule for data reduction/processing/analy
  sis/delivery
• But serious competition!