1. Environmental Effect on Mock Galaxy Quantities Juhan Kim, Yun-Young Choi, & Changbom Park Korea Institute for Advanced Study 2007/02/21

2. Content A model to make mock galaxies from N- body simulation Model test & Justification Model prediction

3. A Roadmap for Galaxy World Luminosity Function Choi & Park Spin Distribution Choi & Park Velocity Correlations Park & Park Topology of LRG & Galaxy Choi & Park Morphology/ Velocity dispersion Park & Park Cosmological Model Halo-to-galaxy model

4. How to build Mock Galaxies Directly implements algorithms & parameters for hydrodynamics. ( SAM ) Uses merging tree built by random realizations Merging  mass growth : M(t)  M’(t’) Uses galaxy formation recipe mass growth  star-formation  L & chemical evolution Parameters: IMF, SF rate, metal enrichment…. ( HOD ) P(N|M): probability number of galaxies in an FoF halo of mass M Galaxy distribution inside a halo  to satisfy observed  gg ( MOC ) Subhalo  galaxy: every subhalo can host a galaxy Subhalo Mass  galaxy Luminosity

5. Pros & Cons Direct Hydro Simulation Can directly follow complex nonlinear evolution of gas particles. But uses ambiguous parameters for complicated nonlinear phenomena (IMF,SF). Lack in resolution  needs much more computer resources than currently available (Small-scale phenomena in Large-scale environments). SAM Can reproduce observables by introducing parameters. But needs too many parameters. Some parameter values can be degenerated in parameter space. HOD Can parameterize the spatial distribution of galaxies in clusters. Is a kind of descriptive methods and, therefore, restricted. Cannot predict phase-space distributions inside clusters. MOC Is simple & straightforward: very few parameters are needed. Because recently developed, it is not seriously tested in various fields.

6. MOC implementation to PSB halos Two (simple & reasonable) assumptions One subhalo may host only one galaxy One-to-one correspondence A more massive subhalo has a more luminous galaxy Luminosity of a galaxy is a monotonic function of its host subhalo mass If halo mass is given, the luminosity of the inside galaxy is obtained. SDSS  : PSB  :

7. Subhalos in a halo

8. Cloud in Cloud

9. Mass Function of Dark Halos Press & Schechter Sheth & Tormen

10. Mass-to-light relation M<-18 M<-20

11. Model Test Local density distribution -21<Mr<-20 galaxies are used for density seeds. Variable size Spline kernel is used to measure local density. Luminosity functions of various sub-samples divided by local density criteria

12. M<-21 M<-20

13. Luminosity Function Total Void crowded

14. Schechter Parameters with Local Density

15. Spin Distributions Spin parameter: =1(rotation-supported) =0(pressure-supported) Spin distribution Log-normal Gamma

16. Universality of the Spin Shape

18. Characteristics of Spin distributions Shape (k) of spin distributions: nearly constant Origin of spins: off-center impact & inhomogeneous infall Depends on the number of local filament branches More massive halo: smaller spin In more crowded region: higher spin

19. Spin Dependence on Galaxy Mass Less massive galaxies: more anisotropic merging more massive galaxies: more isotropic merging

20. Spin Dependence on Local Density Under dense region: accretion dominated Overdense region: merging dominated

21. Summary MOC is more powerful than other traditional methods. Simple implementation to create mock galaxies A model with less parameters is more powerful!!!!!! SDSS density distributions & LF’s are well recovered. Spin distributions of mock galaxies Distribution shape is constant and shift parameter depends on local & merging environments.  hints at a possible statistical explanation on the spin & merging history of halos?