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

Environmental Effect on Mock Galaxy Quantities

Juhan Kim, Yun-Young Choi, & Changbom Park

Korea Institute for Advanced StudyKorea Institute for Advanced Study

2007/02/21

Content

• A model to make mock galaxies from N-body simulation

• Model test & Justification• Model prediction

A Roadmap for Galaxy World

Luminosity FunctionChoi & Park

Spin DistributionChoi & Park

Velocity CorrelationsPark & Park

Topology of LRG & Galaxy

Choi & Park

Morphology/Velocity dispersion

Park & Park

Cosmological Model

Halo-to-galaxy model

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-formationL & 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

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.

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 :

€

φ(M ')dM '−∞

M

∫ = Φ(mh )dmhm

∞

∫

€

φ(M) = 0.4 ln10φ*10−0.4(M −M * )(α +1) exp[−10−0.4(M −M * )]

€

M* − 5log10 h = −20.22,φ* =1.847 ×10−2h3Mpc−3,α = −0.81

€

f (ν ) = Aa

2π1+

1

aν

⎛

⎝ ⎜

⎞

⎠ ⎟p ⎡

⎣ ⎢

⎤

⎦ ⎥1

νexp −

aν

2

⎛

⎝ ⎜

⎞

⎠ ⎟

€

a = 0.923, p = 0.0121,A = 0.368

€

cf .a = 0.707, p = 0.3,A = 0.322

Subhalos in a halo

• Cloud in Cloud

Mass Function of Dark Halos

Press & Schechter

Sheth & Tormen

Mass-to-light relation

€

Υ=Mh

L= Ψml

Mh

M*

⎛

⎝ ⎜

⎞

⎠ ⎟

γ

expM*

M

⎛

⎝ ⎜

⎞

⎠ ⎟

Ψml = 31.3,M* = 2.07 ×1011,γ = 0.690

M<-18

M<-20

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

M<-21

M<-20€

Ξ(Δ) = Ae−(ln Δ−μ )2 / 2σ 2

2πσ

Luminosity FunctionTotal

Void

crowded

Schechter Parameters with Local Density

Spin Distributions• Spin parameter:

=1(rotation-supported)=0(pressure-supported)

• Spin distribution• Log-normal

• Gamma

€

=J −E

GM 5 / 2

€

Pl =1

λ 2πσ λexp[−

ln2(λ /λ 0)

2σ λ2

]

€

PG =(λ /θ)k−1

θΓ(k)exp(−λ /θ),

k : shape parameter

θ : shift parameter

Universality of

the Spin Shape

€

PGθ =(λ /θ)k−1

Γ(k)exp(−λ /θ),

€

M < −19.8

M < −20.3

M < −20.6

M < −21.0

M < −21.3

€

PG =(λ /θ)k−1

θΓ(k)exp(−λ /θ),

k : shape parameter

θ : shift parameter

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

€

M < −19.8

M < −20.3

M < −20.6

M < −21.0

M < −21.3

Spin Dependence on Galaxy Mass

Less massive galaxies: more anisotropic merging

more massive galaxies: more isotropic merging

Spin Dependence on Local Density

•Under dense region: accretion dominated

•Overdense region: merging dominated

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?