Simulations of the galaxy population
constrained by observations from z=3 to present
day: implications for galactic winds and fate of their
ejecta
Bruno Henriques
Simon White, Peter Thomas, Raul Angulo,
Qi Guo, Gerard Lemson, Volker Springel
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.
Guo2011
The evolution of the stellar mass function
The model fits the present day distribution of masses but predicts the dwarf galaxy
population to build up too early.
colour
Dwarf galaxies are too clustered
clustering
Massive galaxies are too blue and dwarf
galaxies too red
SSFR
Dwarf galaxies are too old and
are not forming enough stars
3. Self-consistent model of galaxy
formation across cosmic time
Henriques et al. (2009), Henriques & Thomas (2010), Henriques et al. (in prep.)
Complex galaxy
formation physics
Large Volume
Across Cosmic
Time
Semi-analytic
modelling
MCMC
Robust statistical method to explore the
allowed likelihood regions in highdimensional parameter spaces
Choose parameters to sample
Star formation, SN feedback, AGN feedback efficiency, Metals yield
Constrain the model at multiple redshifts
Wide and narrow surveys
combined to achieve good
statistics and large
dynamical range.
Maximum and minimum
observational errors used
to estimate systematic
uncertainties.
Stellar Mass Function, K-band & B-band
Luminosity Functions
Time varying parameters
Reincorporation of gas after ejection by
SN feedback needs to increase towards
low redshift
All other parameters have consistent
regions at all redshifts
Reincorporation time scaling with Mvir, similar to Oppenheimer et al. (2008, 2010)
Strong ejection + no reincorporation set
the low mass end at high-z
Strong reincorporation at later times
produces the required build up for z<1
Colors and SFR
The delayed reincorporation of gas shifts star formation in dwarfs to lower redshifts.
A population of low mass galaxies
with blue colours remains down to
z=0
Low mass galaxies have higher star
formation rates and younger ages.
Satellite galaxies in massive halos
have lower mass, hence reducing
clustering at fixed mass
Galaxy formation physics, and not
just cosmology/merging, have a
strong impact on galaxy clustering.
Conclusions
Phenomenological models provide a fast method to describe the formation and
evolution of galaxies in a cosmological volume, with high resolution and across
cosmic time.
MCMC methods can be used to learn exactly how specific descriptions of a
physical process affect galaxy observables at different epochs in a self-consistent
way. The allowed likelihood regions in parameter space can be explored for any
combination of observations at multiple epochs.
In order to explain the observed evolution of the number density of
intermediate/low-mass galaxies, the reincorporation of ejected gas should
scale approximately with Mvir, being negligible at low mass at z>2 and rapid
for most galaxies at low redshift.
Low-galaxies form later and are significantly younger at z=0
Evolution of the massive end is reproduced across all redshifts
Luminosity Function
No feedback
The halo mass function is much steeper at both ends
than the galaxy stellar mass function
Observations
low mass
high mass
Supernova feedback has the right scale to make star formation
sufficiently inefficient in small haloes
Supernova feedback
The reheated gas would eventually cool in massive
haloes producing an excessive number of bright
galaxies
Observations
high mass
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low mass
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Z=2.0
Z=1.0
Z=0.0
Massive galaxies have more gas fuel than small ones
No ongoing star formation
Older populations than small galaxies
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The Munich Model
Reincorporation
Hot Gas
Reheating
Ejected Gas
Ejection
Recycling
Cooling
Stars
Stars
Cold Gas
Star
Formation
1.The Munich Model
Croton et al. 2006
AGN feedback model (suppression of cooling)
De Lucia & Blaizot 2007
dust model
SN feedback model - reheating + ejection + reincorporation
Guo et al. 2011
different supernova feedback (increased efficiency)
Merger treatment
Henriques et al. 2011, 2012
different stellar populations
Extended MCMC Capabilities
Observational constraints at multiple redshifts
Stellar mass and luminosity functions constraints from z=3 to z=0
Takes full advantage of the self-consistent evolution of galaxies
Time-evolution of parameters (pre-processing step)
If not needed, the current parametrisation is not ruled out by observations
If needed, a different parametrisation is required (it rules out any others)
If a good fit can not be found, the current model is ruled out
M05 vs BC03
Gas
TB-AGB
TB-AGB +
RHeB
GALFORMOD
Web-based, modeler & observer friendly semi-analytic model
Combine the most robust set of dark matter numerical simulations available
Stellar Mass resolution of 108M with a large enough volume to sample BAO
MS, MII & MXXL
Monte Carlo Markov Chain optimization +
Fit physical and cosmological parameters
Modular implementation of the physics
“Observer friendly” outputs
Choose IMF, SPS, Bands, Dust model
Chemical Enrichment
SN Ia + Stellar Winds
0.8 M
SN II
8M
Metals return timescale
<100 Myr
Rob Yates, Peter Thomas, Simon White,
Guinevere Kauffmann, Bruno Henriques
Far-Infrared Emission
Peter Thomas, Sorour Shamshir, Bruno Henriques, Qi Guo + Sussex Infrared
Use empirical templates from Herschel
to get an emission spectra for the light
re-emitted by dust
Full radiative transfer code
Cosmology Sampling with MCMC
Bruno Henriques, Marcel Van Daalen, Raul
Angulo, Simon White, Volker Springel, Fabio
Fontanot, Qi Guo
Incorporate the Angulo & White 2010
formalism into the semi-analytic model.
Include cosmological parameters in the
sampling.
Colours
Somerville
Ages of Galaxies
Light – Weighted Ages
M05
Mass – Weighted Ages
BC03
M05
Average!!!
TP-AGB
Henriques, Maraston, Monaco, et al. (Astro-ph: 1009.1392)
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
8 April 2015
Henriques, Maraston, Monaco, et al. (Astro-ph: 1009.1392)
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