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Lightcones for Munich Galaxies
Bruno Henriques
Outline
1. Model to data - stellar populations and photometry
2. Model to data - from snapshots to lightcones
3. Results - pencil beams
4. Results - all-sky cones
Mass to Light
Stellar Population Synthesis
Metallicity + Age +IMF
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Luminosity of a stellar
population
Dust Model
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Full Emission Spectra
Direct comparison to
observed frame
apparent magnitudes
Test SED fitting /
K-corrections
Reliability of assumed
star formation histories
Test determinations
of mass
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Different Stellar populations
Test the impact of stellar populations modelling in the observed galaxy properties.
In past evolutionary population
synthesis codes, the K-band was
mostly determined by old populations
(e.g. Bruzual & Charlot 2003,
PEGASE, Starburst99)
i z
J
K
The inclusion of the TP-AGB phase
means that intermediate-age
populations will contribute
significantly to the near infra-red
emission from galaxies (Marasto 2005,
Charlot & Bruzual 2007)
(see also Henriques, Maraston, Monaco et al. (2010))
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The semi-analytic is built on top of the
dark matter distribution and has outputs
only at given snapshots.
(despite galaxy properties being
computed in smaller steps ~ 6 Myr )
z=5.7
z=1.4
From snapshot/box output
z=0
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to lightcones
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Lightcones
dcom
zn
zi
Comoving distance
Redshifts - snapshots
(zi+zi-1)/2<z<(zi+zi+1)/2
Lightcones
only few replications, distant in redshift
Mass to light
obs_frame
rest_frame
Number Counts & Zdist
First tests can be performed directly in the
observed frame with only few derivations
applied to data.
bright near-by and faint distant galaxies
Intermediate redshifts
dominated by faint objects
Henriques, White, Lemson, et al. 2012
Rest-frame Colours and LFs
More informative tests can be done
for rest-frame properties in order to
obtain a comprehensive picture.
Optical-near-infrared color,
separates passive from dust
obscured galaxies
Large differences
between stellar
populations
Allsky Lightcones
Selection in iAB< 21.0 - 100deg2 - comparable to modern wide surveys
BOSS
observed-frame color
selection criteria can be
matched
The model can be
used to analyze the
selection in terms of
fundamental
quantities
Maraston, Pforr, Henriques, et al. 2012
Stellar Mass of Massive Ellipticals
The numbers of massive galaxies are similar in model and data reflecting
the slow evolution of these objects at later times
Conclusions
Narrow and wide lightcones constructed to match modern
surveys.
Wide photometric coverage that can be used to test derivation of
fundamental quantities from observations.
Large range of properties can be closely compared with available
data to identify possible tensions in theory.
Simulations to Observations
Mass to light
Boxes to cones
Motivation
Why use a phenomenological approach to study galaxy
formation?
Because we should. The physics of galaxy formation are
complex but observations suggest they must obey simple relations.
Still, we do not have a good understanding and cannot work from first
principles, so models must be observationally based.
Fast method to compute the evolution of the galaxy population
across cosmic time for samples as large as modern surveys.
Scaling Relations
Tully-Fisher
Many aspects of the physics that govern galaxy formation
depend simply on galaxy and dark matter properties as
indicated by observed scaling relations.
BlackHoleBulgeMass
SFR-Gas
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Even if direct simulations reach high resolution and significant
volumes they face the same problems due to un-resolved physics!
TB-AGB
TB-AGB +
RHeB
Van der Wel, Franx, Wuyts, et al. 2006
SSP
Chandra Deep Field - South
ACS+IRAC+J&H filters
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Maraston, Daddi, Renzini, et al. 2006
Older then the Universe!
Undetected in MIPS!
What are the implications for
galaxy formation models?
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Marchesini 2009
Optical to mid-infrared data
GOODS – Giavalisco et al. 2004
MUSYC – Gawiser et al. 2006
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CB07
M05
CB07
BC03
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Henriques, Maraston, Monaco, et al. (Astro-ph: 1009.1392)
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