Morphology and SED modelling of high redshift galaxies in deep Fields

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Morphology and SED modelling of high redshift
galaxies in deep Fields in very distant
Clusters
Alessandro Rettura
arettura_at_eso.org

• Ph.D. Thesis Advisors
• Brigitte Rocca (IAP,Paris)
• Piero Rosati (ESO,Munich)
• Robert Fosbury (ESO,Munich)

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• Open Questions
• Where, When and How did the Hubble sequence of
  morphological types form?
• Evolution of Morphological types fractions? What
  kind?
• Studying Quantitative Morphology of 1.0 ltz lt1.5
  galaxies in function of the environment to be
  compared with local results (SDSS) or
  intermediate redshift (0.2ltzlt1.0) results (GEMS,
  COMBO17, K20, etc...).
• __________________________________________________
  _________
• Do you believe that most massive objects form
  last from the gradual assembly of smaller
  galaxies?
• Hierarchical or monolithic?
• Do Cluster or Field galaxies assemble their mass
  in the same way at the same time?
• Modelling SEDs on cluster and field samples in
  the same redshift range to estimate masses and
  ages probing environmental effects.

Alessandro Rettura - Institute Seminar
Dip.scienze Fisiche - December 22th 2004 -
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Introduction PART I

• MORPHOLOGY

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Introduction (1).

• A galaxy morphology is often our first insight to
  its physical state, and in this view, changes in
  morphology can be used to infer evolution in a
  galaxys history.

• Studies of galaxy evolution are often based on
  the global changes of their morphological
  properties, as function of redshift.

• (Brinchmann et al., 1998) have shown how the
  fraction of irregular/peculiar galaxies increases
  with redshift

In high redshift universe there are predominantly
young galaxies and several interactions and
merging occur.
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• In the following plot we present the evolution
  of the morphological fractions of galaxies as
  shown by Brinchmann et al.(1998).
• These fractions are related to the Frei sample
  at low redshift (0ltzlt0.2) and to HST observations
  for higher redshift values.

Selection Biases????
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• Galaxy appearence can vary strongly with
  wavelenghts according to the relative abundance
  of young or old stellar populations.

This effect is known as morfological K correction.
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Modelling galaxy Morphology

• To analyze quantitative morphology of a sample of
  Highz galaxies we study the surface photometry
  distribution.

• The shape of the surface brightness light profile
  varies with morphological types

• Elliptical galaxies light profile with a R¼ law
  (De Vaucouleurs law)

• Spiral galaxies 2 component light profile disk
  bulge

• We analyze the surface photometry of galaxies
  using GIM2D (Simard et al.1998), a fitting
  algorithm that produces a 2 component
  bidimensional light profile of a galaxy image.

• An exponential disk

• To estabilish the relevance of one component with
  respect to the other one, we evaluate the bulge
  fraction, B/T .

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2D Modelling of galaxy surface Brightness profile

• From an image I(x,y) of a given galaxies, we
  model analitically the M(x,y) surface brigthness
  distribution using a 2 component bidimensional
  fitting algorithm of the galaxy light profile.

From the best model M is possible to obtain a
residual image R(x,y) I(x,y) - M(x,y)
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Rest-frame luminosity-size relations (McIntosh et
al.04)

• Shen et al.,2003 ridgeline provides a reasonable
  fit out to z0.5
• At larger redshift the relation starts to deviate
  with the largest evolution appearing for the
  smallest galaxies.

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Luminosity evolution of early-type galaxies at
fixed size (McIntosh et al.04)

• Significant luminosity evolution. Its strength,
  at a given size, depends inversely on early-type
  galaxy size.
• These results would be consistent with passive
  evolution of the galaxy population as predicted
  by the monolithic collapse scenario.

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Introduction PART II

• SPECTRAL ENERGY DISTRIBUTION
• (SED)

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Modelling galaxy spectra

• The understanding of galaxy evolution requires
  models of spectral evolution.
• We aim at following the evolution on very rapid
  (1 Myr) and very long timescales (20 Gyr) to
  provide constraints on the weights of various
  stellar populations in starbursts and evolved
  galaxies.
• This is a spectrophotometric evolution model for
  starbursts and evolved galaxies of the Hubble
  sequence.

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Spectral synthesis modelling in a nutshell

• The PÉGASE.2 code (FiocRocca-Volmerange,97) is
  based on stellar evolutionary tracks from the
  "Padova" group, extended to the thermally
  pulsating asymptotic giant branch (AGB) and
  post-AGB phases these tracks cover all the
  masses, metallicities and phases of interest for
  galaxy spectral synthesis. 
• For a given evolutionary scenario (typically
  characterized by a star formation law, an initial
  mass function and, possibly, infall or galactic
  winds), the code consistently computes the star
  formation rate and the metallicity of gas and
  stars at any time. 
• The nebular component (continuum and lines) due
  to HII regions is roughly calculated and added to
  the stellar component. 
• Depending on the type of galaxy (disk or
  spheroidal), the attenuation of the spectrum by
  dust is then computed using the outputs of a
  radiative transfer code this model takes into
  account scattering.
• PÉGASE.2 uses the BaSeL (Lejeune et al.
  1997,1998) library of stellar spectra and can
  therefore synthesize low-resolution (R200)
  ultraviolet to near-infrared spectra of Hubble
  sequence galaxies as well as of starbursts. (220
  Å- 5micron)

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z0 galaxies from Kennicut (1992) catalog
compared with model spectra
E
Sa
Sd
Sbc
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• What is the template fitting technique?
• The technique can be divided into five steps
• The photometric data for each galaxy are
  converted into spectral energy distributions
  (SEDs).
• A set of template spectra of all Hubble types and
  redshifts ranging from z0 to z(maximum relevant
  redshift, eg z7) is compiled.
• The redshifted spectra were reduced to the
  passband averaged fluxes at the central
  wavelengths of the passbands, in order to compare
  the template spectra with the SEDs of the
  observed galaxies.
• The spectral energy distribution derived from the
  observed magnitudes of each object is compared to
  each template spectrum in turn.
  The best matching spectrum, and hence ages,
  masses, metallicities, are determined by
  minimizing c2.
• Errors are estimated by 1,2,3s sampling of
  confidence regions in the parameter space

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Rest-frame Stellar Mass-size relations (McIntosh
et al.,2004)

• Sizes and stellar masses follow a correlation
  that is consistent with the local relation out to
  z0.8, where the COMBO-17 reliability limit
  begins to cut into the observed relations.
• Under the assumption of simple passive luminosity
  evolution, we expect galaxies of a given sizes to
  maintain a constant stellar mass.

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Stellar mass evolution of early-type galaxies at
fixed size

• Stellar mass difference relative to the z0
  relation as a function of redshifts, accounting
  for selection effects , S(MV,z).

• There is no significant Stellar Mass evolution.
• These results would be consistent with passive
  evolution of the galaxy population as predicted
  by the monolithic collapse scenario.

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Applying models to real data samples

• FIELD galaxies (GOODS-CDFS)
• CLUSTER galaxies (cl1252)

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• IDEA
• ACS Clusters GTO (VLT/ACS/ISAAC/Spitzer) Survey
  of z1.2 Clusters
• The GOODS (VLT/ACS/ISAAC/Spitzer) Field galaxies
  public survey at z1.2
• represent a deep, multiband and homogeneus
  database to analyze both morphological
  properties and spectral energy distributions of
  cluster field galaxies at such an high-z .

Alessandro Rettura - Institute Seminar
Dip.scienze Fisiche - December 22th 2004 -
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Cluster Cl1252 at z1.234 (Blakeslee2003,Lidman
2003,Rosati2004)

• Deep ACS images (i , z) of CL1252-2927 (z1.23).
• High sensitivity and angular resolution
• over the central 2.5 Mpc region of this
  cluster
• 37 spectroscopic (FORS2) members
• Deep Optical (FORS2ACS/HST), Near-Infrared
  (ISAAC)-Infrared (IRAC/SST) photometry

Alessandro Rettura - Institute Seminar
Dip.Scienze Fisiche - December 22th 2004 -
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FIELD CDF-S-GOODS-FORS2 Sample
The Great Observatories Origins Deep Survey is a
public, multiwavelength survey that will cover
two 150 arcmin2 fields. These fields are centered
around the HDF-N and the CDF-S.

• Imaging Spectroscopy
• Xray Imaging (Chandra/XMM)
• Deep Optical Imaging (ACS/HST),
• Near Infrared Imaging (ISAAC),
• Mid-Infrared Imaging (IRAC/SST),
• VLT/FORS2 Spectroscopy more than 1000 redshifts
  (Vanzella,2004).

For this project

• We selected 292 galaxies in the FORS2 sample at
  1.0ltzlt1.5 (spectroscopic).

We use GOODS as a control field to contrast
Cluster properties and probing environmental
effects.
Alessandro Rettura - Institute Seminar
Dip.scienze Fisiche - December 22th 2004 -
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FIELD GOODS-FORS2 Selection (Vanzella et
al.,2004, submitted)

• Colour Selection
• Primary catalogue (i-z) gt 0.6, z lt 24.5
• Secondary cat 0.45 lt (i-z) lt 0.6, z lt 24.5
• Plus fillers plus V, i dropouts plus other
  interesting objects (e.g., SN)
• Aim obtain spectra at z gt 0.9, i.e. use
  red-sensitive FORS-2 CCD.

Mean redshift 1.02
For this project

• We selected 292 galaxies in the FORS2 sample at
  1.0ltzlt1.5.

• We are now enlarging our sample by including
  morphological analysis of 98 galaxies selected in
  the VIMOS_VVDS sample at 1.0ltzlt1.5

Alessandro Rettura - Institute Seminar
Dip.scienze Fisiche - December 22th 2004 -
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Applying models to real data preliminary results

• Morphological models on Field Cluster galaxies
• SED modelling on cluster galaxies

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Conclusions Ongoing Analysis for Field
Cluster data at z1.2
Alessandro Rettura - Institute Seminar
Dip.scienze Fisiche - December 22th 2004 -
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GRAZIE