High redshift cluster search(SA22 field)

KIAS SSG workshop

2013. 2. 15.

Jae-Woo Kim (SNU) M. Im, S.-K. Lee & M. Hyun (SNU)

Galaxy cluster

• A few words describing galaxy clusters- Gravitationally bound

- The most massive object

- Laboratory for investigating the galaxy evolution

- Density peak : halo abundance- Large-scale structure

What we need- Wide & deep surveys : clusters are rare objects

Many clusters have been found from various surveys

Main science of future wide surveys. (e.g., DES)

From NASA APOD

Galaxy cluster @ z>1

• At 1<z<2, the Universe changed and completed various phenomena.

• Important period to understand the evolution of Universe.

• Galaxy clusters? Cluster galaxies?• BUT not many known clusters at z>1 – lack of wide

NIR• A NIR dataset plays an important role to identify

z>1 clusters due to the redshifted stellar emission.

Madau 1998

Darkenergysurvey.org

NIR surveys

• UKIDSS Deep eXtragalactic Survey- four 8.75deg2 with J and K band using UKIRT- clustering of galaxies at z>1- searching for galaxy clusters at z>1- LAS, GPS, GCS, DXS & UDS

• Infrared Medium-deep Survey- mapping 138deg2

- Y and J band survey using UKIRT- discovering high-z quasars- galaxy cluster at z>1

http://www.vikdhillon.staff.shef.ac.uk/teaching/phy217/telescopes/ukirt.jpg

We try to find galaxy clusters at z>1 using multiwavelength datasets.

Catalogues

• Observed- DXS+IMS+CFHTLS- ugrizJK- Swarp, SExtractor

- 18.44deg2

- i<24.2, J<23.2

- photo-z : Δz/(1+z)~0.038

• Mock - GALFORM (Cole+00)

- GALEX, SDSS, Subaru, UKIDSS filters

- 22.06deg2 & K=24

- i<24.2, J<23.2

z=0.8 z=1.2

Algorithm Select galaxies in redshift bins : z±(1+z)0.038 Count the number of galaxies within 500h-1 kpc Gaussian fit & select >3σ galaxies Reject galaxies if ND300<ND500 Merge candidates- connected z-bins- separation < 0.0238 deg Properties of candidates- Centre : mean of candidates in connect bins- Redshift : median of gals. within 500 h-1 kpc and in photo-z uncertainty- Richness : ngal, nbg, LF 626 candidates in 0.8<z<1.2

For the mock catalogue- Apply the same algorithm- to reproduce photo-z, the uncertainty was assigned randomly

(Muzzin+07)

Based on Mock

z dependence Mass vs. richness Recovery rate

previous result- Low z- No z dependence We found the z dependence But the slope is independent on mass

~100% for logM=14.2 ~10% for logM=13.5

Richness is a good proxy for a cluster mass. BUT large scatter.

100%

10%

Preliminary results

Normalised richness dist. Clustering of clusters

Overall, they look similar. BUT the observation shows more halos with larger richness.

Angular correlation fn. Similar shape with ΛCDM on the linear regime Bias=9.84 with logB>3.3 Bias=8.98 with 3.0<logB<3.3

logB>3.3

3.0<logB<3.3

Summary We try to discover new galaxy cluster at z~1.

The algorithm is successful.

Probably more massive halos than ΛCDM

Clustering shape is matched to that by ΛCDM on

the linear regime with bias~9

The wide, deep survey provides an opportunity to

identify galaxy clusters.

The NIR dataset is important to find clusters at

z>1.

Thank you for listening!!!