CLASH London 2013
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CLUSTER VIEWS OF THE HIGH
REDSHIFT UNIVERSE
Leonidas Moustakas, JPL/Caltech
© 2013 California Institute of Technology. Government sponsorship acknowledged
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Two goals in the high-redshift game
Identify individual high-z galaxies
1.
Break records
b) Study their individual stellar populations and emission features
c) Explore scaling relations based on their compactness, structure,
and surface brightness
=> Probability of identifying objects will depend on the volume and
luminosity threshold of a survey
a)
Study ensemble properties
2.
Luminosity functions versus predicted mass functions
b) Galaxy formation efficiency
c) Luminosity density / photon budget versus buildup of global stellar
mass
=> Knowledge of the survey volume versus luminosity threshold (and
associated uncertainties) is key, in addition to the usual selection
function
a)
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Evaluating properties across cosmic time
• The space or luminosity density requires knowledge of the
selection function (based on the color/etc selection), and
the corresponding volume.
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Numbers & volumes at low luminosities
Bouwens+
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Field observations of high redshift
• The survey volume depends on the selection function
p(m,z) => Effective volume (Steidel 1999).
• In field surveys, the cosmological transformation from
area to comoving volume (dV/dz) is simply cosmology
dependent.
• With cluster lenses, we must also consider the
magnification mapping between area and volume
elements, as well as the luminosity threshold
transformation: Both p(m,z), and dV/dz are modified.
CLASH London 2013
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Field observations of high redshift
• Review deep field surveys, and how their properties map
into comoving volume and luminosity threshold sensitivity
as a function of redshift.
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L Moustakas+ 2013
CLASH London 2013
With John Moustakas
leonidas@jpl.nasa.gov
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L Moustakas+ 2013
CLASH London 2013
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L Moustakas+ 2013
CLASH London 2013
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Observations of high redshift galaxies
• Field observations versus galaxy clusters
• HUDF
• CLASH
• Frontier Fields
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Galaxy cluster lens modeling
• See the overview of lens modeling tools at
http://www.masterlens.org/software.php? + Adi’s talk.
• An aside – note that in estimating magnification-corrected
luminosities and their uncertainties, the magnification
estimates depend on the second derivative of the
effective, projected potential. So substructure (galaxies,
groups, filaments, etc) can matter a great deal.
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CLASH lens model summary
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CLASH London 2013
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CLASH models montage
0647
1206
0744
1423
Zitrin+
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ACS and
WFC3 footprints
 NIR-based
high-redshift
galaxy
searches
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CLASH London 2013
ACS and
WFC3 footprints
 NIR-based
high-redshift
galaxy
searches
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<- approximate
luminosity limit
correspondence
^ Source redshift
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L Moustakas+ 2013
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CLASH (WFC3)
FF (WFC3)
L Moustakas+ 2013
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L Moustakas+ 2013
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L Moustakas+ 2013
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Frontier Fields
L Moustakas+ 2013
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Science enabled with these calculations
• Statistical estimate of host halo mass of detected high-redshift
galaxies
• Post-facto evaluation of detection probability of individual
objects
• C.f. Pacucci+ 2013 on WDM estimates
• MCMC estimates of luminosity function parameter fidelity at
different source redshifts
• Survey design or evaluation, e.g. for future projects that contain
high quality data of massive galaxy clusters
• Beyond the Frontier Fields with HST
• Large-area ground based surveys (DES, LSST)
• Future space-based missions (Euclid, WFIRST-AFTA)
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Conclusions
• The global volume/limit behaviors are not strongly model
dependent
• => Evaluating the relative power of clusters vs field is solid
• => However, local effects for individual objects can be strong!
Estimating this was one of the original goals of this project
• All uncertainty terms are identified and estimated, but not well. Modeling
efforts need to progress a bit more. With Adi in Pasadena, we’ll make
headway.
• CLASH’s traction in terms of volume and luminosity limit is
quantifiably stronger than the HUDF
• However, some clusters dominate this signal/traction!