Cosmology with Photometric redsfhits

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Cosmology with Photometric redsfhits
Filipe Batoni Abdalla
M. Banerji, S. Bridle, E. Cypriano, O. Lahav, J
Tang, J Weller (UCL), A. Amara (Saclay), P.
Capak, J. Rhodes (Caltech/JPL), H.
Lin (Chicago)
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Outline

• Quick pass over photo-z weak lensing
• The DUNE mock catalogues
• Results from the Fisher analysis on the mocks
• More problems Intrinsic alignements
• Sensitivity of weak lensing to w(z)

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Photometric Redshifts

• Photometric redshifts (photo-zs) are determined
  from the fluxes of galaxies through a set of
  filters
• May be thought of as low-resolution spectroscopy
• Photo-z signal comes primarily from strong galaxy
  spectral features, like the 4000 Å break, as they
  redshift through the filter bandpasses
• All key projects depend crucially on photo-zs
• Photo-z calibrations will be
• optimized using both simulated catalogs and
  images.

Galaxy spectrum at 3 different redshifts,
overlaid on griz and IR bandpasses
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Training Set Methods
Template Fitting methods

• Use a set of standard SEDs - templates (CWW80,
  etc.)
• Calculate fluxes in filters of redshifted
  templates.
• Match objects fluxes (?2 minimization)
• Outputs type and redshift
• Bayesian Photo-z

• Determine functional relation

• Examples

Polynomial Nearest Neighbors (Cunha et al. in
prep. 2005)
Nearest Neighbors (Csabai et al. 2003)
Polynomial (Connolly et al. 1995)
Neural Network (Firth, Lahav Somerville 2003
Collister Lahav 2004)
Cross correlations (Newman)
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Background sources
Background sources
Background sources
Background sources
Dark matter halos
Dark matter halos
Dark matter halos
Dark matter halos
Dark matter halos
Observer
Observer

• Statistical measure of shear pattern, 1
  distortion
• Radial distances depend on geometry of Universe
• Foreground mass distribution depends on growth of
  structure

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Background sources
Background sources
Background sources
Background sources
Dark matter halos
Dark matter halos
Dark matter halos
Dark matter halos
Dark matter halos
Observer
Observer

• Statistical measure of shear pattern, 1
  distortion
• Radial distances depend on geometry of Universe
• Foreground mass distribution depends on growth of
  structure

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DUNE Dark UNiverse Explorer

• Mission baseline
• 1.2m telescope
• FOV 0.5 deg2
• PSF FWHM 0.23
• Pixels 0.11
• GEO (or HEO) orbit
• Surveys (3-year initial programme)
• WL survey 20,000 deg2 in 1 red broad band, 35
  galaxies/amin2 with median z 1, ground based
  complement for photo-zs
• Near-IR survey (Y,J,H). Deeper than possible
  from ground. Secures z gt 1 photo-zs
• Changes are currently being discussed at ESA
  i.e. merging of DUNE and SPACE
• (we will hear more about this in Talks thurs
  Rassat/Guzzo), inclusing of a small spectrograph
  on the near-IR plane

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Surveys considered galaxies withRIZlt25
considered
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JPL Simulated catalogue
Av
Type
z
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Know the requirements
Abdalla et al. astro-ph0705.1437

• A case study the DUNE satellite
• I have performed analysis within the DES
  framework as well VDES

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Mock dependence comparison to DES mocks.
DES (grizY)
DESVISTA(JHK)
M. Banerji, F. B. Abdalla, O. Lahav, H. Lin et
al.
In regions of interest photo-z are worst by 30
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FOM Results Number of spectra needed

• FOM prop 1/ dw x dw
• IR improves error on DE parameters by a factor of
  1.3-1.7 depending on optical data available
• If u band data is available improvement is
  minimal
• Number of spectra needed to calibrate these
  photo-z for wl is around 105 in each of the 5
  redshift bins
• Fisher matrix analysis marginalizing over errors
  in photo-z.

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Intrinsic alignements.
Additional contributions
What we measure
Cosmic shear
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Intrinsic-shear correlation (GI)
Galaxy at z1 is tidally sheared
Hirata Seljak
Dark matter at z1
Net anti-correlation between galaxy ellipticities
with no preferred scale
High z galaxy gravitationally sheared
tangentially
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Removing intrinsic alignments

• Finding a weighting function insensitive of
  shape-shear correlations. (P. Schneider)
• - Is all the information still there?
• Modelling of the intrinsic effects (Bridle
  King.)
• - FOM definitely will decreased as need to
  constrain other parameters in GI correlations.
• Using galaxy-shear correlation function.
• In any case there will be the need of a given
  photometric redshift accuracy.

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Different Cl contributions
Bridle King
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Are photo-zs good enough?

• The FOM is a slow function of the photo-z quality
  if we consider only the shear-shear term.
• If we consider modelling the shape-shear
  correlations this is not the case anymore.
• This does not include the galaxy-shear
  correlation function so reality is most likely
  in between this pessimistic result and the
  optimistic result of neglecting GI

Abdalla, Amara, Capak Cypriano, Lahav Rhodes
High demand on photo-z for intrinsic alignement
calibration
Bridle King
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PCA and Fisher Information Matrix

• Fisher Information Matrix is an efficient method
  to measure the covariance of the random variables
  
• Fisher information matrix F is defined as
• To combine different experiments FF_1F_2
• To marginalize over parameters
• We include a parameter set combined with
  cosmological parameters, w and other nuisance
  parameters

• In the e-vector basis, w is reconstructed as

For more details see posted by Tang, Where she
reproduced all the DETF report work using w
binning e-modes formalism
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Redshift information in e-modes
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Conclusions

• Today dw1/10 prospect dwxdw1/160 but there is
  a big demand on photometric redshifts, specially
  for future surveys such as DUNE alone.
• Need of around 105 spectra in 5 redshift bins
• Removing poor photo-z is possible, removes
  systematic effects and does not hit the
  statistical limits of certain surveys.
• IR data can significantly improve FOM form 1.3 to
  1.7
• Importance of the u band filter, potentially
  being as important as the IR.
• It is possible to measure intrinsic alignments
  with spectroscopic redshift surveys, need to
  assess it that is possible with photo-z.
• Map the redshift sensitivity to w for future wl
  surveys.