Stars introduction and brief overview of properties

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Simulating galaxy formationat high redshifts
Andrey KravtsovKavli Institute for Cosmological
Physics (KICP)The University of Chicago
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The sexiest simulation?
http//www.this-wonderful-life.com
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The ultimate simulation should be able to
simulate this
SDSS survey By Mark SubbaRao (Adler/U.Chicago) Din
oj Surendran, and Randy Landsberg
(U.Chicago) http//astro.uchicago.edu/cosmus/
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While resolving this
SDSS survey By David Hogg and Michael Blanton
(NYU)
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Simulations are remarkably successful in
reproducing the observed LSS
ART code LCDM 60 h-1 Mpc s80.9
mp109h-1 Msun

e 0.5h-1 kpc
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Galaxy clustering in SDSS at z0 Is well
reproduced by simulations
n(gtVmax,acc)n(gtL)
projected 2-point correlation function
Conroy, Wechsler Kravtsov (astro-ph/0512234)
projected separation (chimps)
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and at z1 (DEEP2)
n(gtVmax,acc)n(gtL)
projected 2-point correlation function
Conroy, Wechsler Kravtsov (astro-ph/0512234)
projected separation (chimps)
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and at z4-5 (LBGs, Subaru)
n(gtVmax,acc)n(gtL)
angular 2-point correlation function
Conroy, Wechsler Kravtsov (astro-ph/0512234)
projected separation (arcsec/chimps)
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CDM paradigm must also be tested on smaller,
galactic scales
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Its a very difficult problem
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(some of) the reasons

• resolution and dynamic range required to
  simulate internal structure of galaxies, star
  formation, and feedback properly is enormous
• I would argue, we wont get very far until
  resolution element in star formation regions is
  10 pc (i.e., 106 dynamic range in a box of 10
  Mpc). The scale-height of star forming gas disk
  in the MW is 100 pc.
• Bar formation and dynamics requires 10 pc
  resolution and millions of stellar particles to
  resolve the relevant orbital resonances properly.
• currently, such dynamic range is achievable only
  at high redshifts
• high-zs also are less complicated in certain
  physical aspects (e.g., low dust content)

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GasdynamicsDM simulations of a MW-size system
Adaptive Refinement Tree (ART) code Eulerian
Adaptive Mesh Refinement hydrodynamics N-body
dynamics of DM and stellar particles radiative
cooling and heating Compton, UV background
heating, density and metallicity dependent net
cooling/heating equilibrium rates taking into
account line and molecular processes Star
formation using a phenomenological
recipe Thermal stellar feedback and metal
enrichment by SNII/Ia, stellar mass
loss Simulation followed formation of a MW-size
galaxy at z gt 3. A Lagrangian region
corresponding to 5 Rvir of the object at z0 was
followed. Peak resolution in this region was
50 pc particle mass 106 Msun
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Milky Way progenitor at z4
Kravtsov 2003 Kravtsov Gnedin 2005
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Density PDF and SF
Kravtsov 2003
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Stellar cluster mass function
Kravtsov Gnedin 2005
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Stellar cluster mass function in Antennae
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Exploring dependence on physicsnon-equilibrium
cooling and radiative transfer
visualization with IFRIT (http//home.fnal.gov/
gnedin/IFRIT/)
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Dwarf galaxies at z8
Ricotti Gnedin 2005
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Dwarf galaxies at high zShow correlations
observed locally
M/L metallicity correlation
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Dwarf galaxies at high zShow correlations
observed locally
metallicity-stellar mass correlation
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Dwarf galaxies at high zShow correlations
observed locally
surface brightness-stellar mass correlation
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Formation of a Milky Way-sized halo
z 10
z 7
z 5
z 3
time
z 2
z 1
z 0.5
z 0
ART code simulation (by Anatoly Klypin)
standard LCDM, s80.9 mp6x105h-1 Msun e
0.1h-1 kpc Mvir3x1012h-1 Msun
Rvir293h-1 kpc 5x106 particles within Rvir


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Survival probability for objects at z8
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Luminosity function of dwarfs in the Local Group
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Conclusions

• simulations of galaxy formation at high z have a
  number of advantages
• we can learn more about galaxy formation
  physics, with (arguably) fewer uncertainties in
  the modeling
• results are relevant for local observations of
  galaxies star formation law, stellar clusters,
  dwarf galaxies