# Presentation: 116020

## Zheng Zheng  

Institute for Advanced Study

- Institute for Advanced Study

**Cosmology and Galaxy Evolution from Galaxy Clustering**

## Halo Occupation Distribution (HOD)

Breaking the Degeneracies between Cosmology and Galaxy Bias

     With David Weinberg (Ohio State University)  
     (Zheng & Weinberg, astro-ph/0512071) 

Evolution of Galaxies from HOD Modeling of DEEP2 and SDSS Galaxy Clustering

     With 
     Alison Coil (University of Arizona)
     Idit Zehavi (Case Western Reserve University) 

**Breaking the Degeneracies between Cosmology and Galaxy Bias**
-      With David Weinberg (Ohio State University)
-      (Zheng & Weinberg, astro-ph/0512071)
**Evolution of Galaxies from HOD Modeling of DEEP2 and SDSS Galaxy Clustering**
-      With
-      Alison Coil (University of Arizona)
-      Idit Zehavi (Case Western Reserve University)

- Outline:

## Slide 3

## Slide 4

## Halo Occupation Distribution (HOD)

**P(N|M)**
-    Probability distribution of finding N galaxies in a halo of virial mass M
-      mean occupation <N(M)> + higher moments
**Spatial bias within halos**
-    Difference in the distribution profiles of dark matter and galaxies within halos
**Velocity bias within halos**
-      Difference in the velocities of dark matter and galaxies within halos

- e.g., Jing & Borner 1998; Ma & Fry 2000; Peacock & Smith 2000; Seljak 2000; Scoccimarro et al. 2001; Berlind & Weinberg 2002;
- Yang, Mo, & van den Bosch 2003; ...

## Slide 6

## Slide 7

## Cosmology from Galaxy Clustering?

## Halo populations from distinct cosmological models

- Zheng, Tinker,
- Weinberg, & Berlind
- 2002

- Changing m with 8, ns, and  Fixed

## 

****

## Flexible HOD parameterization 

- P(N|M)
- Motivated by galaxy
- formation models
- Spatial bias within halos
-        Different  concentrations of galaxy distribution
-        and dark matter distribution (c)
- Velocity bias within halos
-           vg= vvm

- Kravtsov et al. 2004; Zheng et al. 2005

## Observational quantities 

**Spatial Clustering**
-      Galaxy overdensity g(r)
-       Group multiplicity function ngroup(>N)
-       2-point and 3-point correlation function of galaxies
**Dynamically Sensitive Observables**
-       m0.6/bg
-        Pairwise velocity dispersion v(r)
-        Average virial mass of galaxy groups <Mvir(N)>
**Galaxy-mass cross-correlation function**
-       mgm(r)

## Constraints on HOD and cosmological parameters 

**Constraints on HOD and ****cosmological parameters **

- Changing m with 8, ns, and  Fixed

## Constraints on HOD parameters 

**Constraints on HOD parameters **

- Changing m with 8, ns, and  Fixed

## Constraints on cosmological parameters 

**Constraints on cosmological parameters **

**Changing ********m**** only**

**Changing ********8**** only**

**Cluster-normalized**

**Halo MF matched**

## Influence Matrix 

## Constraints on cosmological parameters 

**Constraints on cosmological parameters **

- Forecast :
-     ~10% on m
-     ~10% on 8
-     ~5% on 8 m0.75
- From 30 observables
- of 8 different statistics
- with 10% fractional errors

## Conclusion 

- Galaxy bias and cosmology are not degenerate with
- respect to galaxy clustering.
**    ******* HOD modeling can greatly increase the cosmological power of
-        galaxy redshift survey by taking the advantage of high-precision
-        clustering measurements at small and intermediate scales.
-     ***** Simultaneously, using galaxy clustering data, we can constrain
-        the HODs for different classes of galaxies, which provide
-        valuable tests of galaxy formation models.

## Slide 19

## Galaxy Evolution from Galaxy Clustering Galaxy Samples

- DEEP2, z~1 (Coil et al 2006)
- SDSS, z~0 (Zehavi et al 2005)
- Measurements of two-point correlation functions as a function of luminosity

## Two-point correlation function of galaxies

- 1-halo term

- 2-halo term

- Excess probability w.r.t. random distribution of finding galaxy pairs at a given separation

- Central

- Satellite

## Halo Occupation Distribution

- For a sample of galaxies
- more luminous than Lmin

## Modeling results

**L**

- DEEP2 galaxies

## Distribution of central galaxy luminosity 

## Mass scales of host halos

## Establishing an evolution link between DEEP2 and SDSS galaxies

## Stellar mass evolution

## Star formation efficiency vs Halo mass

## Stellar mass evolution (z~1 to z~0) as a function of halo mass

## z~1

- Merging

- z~0

- Star
- Formation

## Tentative conclusion:

- For central galaxies in z~0 M<1012 h-1Msun halos,
- ~80% of their stars form after z~1
- For central galaxies in z~0 M>1012 h-1Msun halos,
- ~20-40% of their stars form after z~1

## Summary & Future Work

-     HODs at z~1 and z~0 from modeling two-point correlation functions of
-     DEEP2 and SDSS galaxies
-     Evolution link through halo evolution
-     Stellar mass evolution from z~1 to z~0 for central galaxies as a function of halo mass (pure merger vs star formation)
-     Useful constraints to galaxy formation models
-     Clustering measurements for galaxy samples based on stellar mass
-     Galaxy samples at different redshifts
-     Evolution of satellite galaxies