SIMULATING THE GROUP FINDING IN THE DEEP2 SURVEY WITH PHOTOMETRIC REDSHIFT INFORMATION

H.-Y. Baobab Liu1, B.-C. Paul Hsieh2, L.-H. Lin3

1. NTU; 2. ASIAA; 3. UC Santa CruzABSTRACTABSTRACTWe developed a modified friend-of-friend method for galaxy group/cluster finding by considering the probability of two objects to be physically associated based on their redshift information and projected position on the sky. This method is currently tested using the DEEP2 mock catalog. In the future work, we will use it to identify galaxy groups in DEEP2 survey, which has an averaged redshift ~1.

INTRODUCTIONINTRODUCTION

In the previous work of DEEP2 group (Gerke et at., 2005), they identified galaxy groups using only galaxies with successful spectroscopic redshift. From DEEP2 mock catalog (Yan et al. 2004), we can see the total number of groups drops by an order of magnitude if we neglect those galaxies without spectroscopic redshift measurement ( After mask-making in FIGURE 1.) .

Now we want to combine the spectroscopic catalog with photometric redshift information( Magnitude-limited in FIGURE 1.) to obtain a group catalog with richness that is less affected by the selection effect and incompleteness problem. The improved richness can reduce the uncertainty for the study of the dependence of galaxy and galaxy group aproperties on the environment.

(Gerke et al., 2005)

After mask making, the total number of group

DROP by around ONE ORDER OF MAGNITUDE, in comparison with magnitude-limited sample.

THE MODIFIED FRIEND OF FRIEND(FOF) METHODTHE MODIFIED FRIEND OF FRIEND(FOF) METHOD

BASIC IDEABASIC IDEA Instead of comparing the absolute separation of two galaxies to the linking length, whether the two galaxies belong to the same galaxy group is determined by their PROBABILITY OF BEING WITHIN LINKING LENGTH. FIGURE 2. illustrates our modification. PDF1 and PDF2 are the probability distributions of position of object1 and object2 respectively.

ADVANTAGEADVANTAGE I. Galaxies with and without spectroscopic redshift have EQUAL FOOTING IN THIS ALGORITHM. II. Spectroscopic data help to CONSTRAINT THE POSITION OF GROUP

DISADVANTAGEDISADVANTAGE The probability threshold has weak physical meaning, and is optimized empirically.

ReferenceGerke, et al.,2005, ApJ, 625:6-22Yan, R., White, M., & Coil, A. C. 2004, ApJ, 607, 739

Linking Length: plan-of-sky :100 kpc

line-of-sight: 3Mpc

Probability threshold 1% 0.1% 0.01% 0.001%

# of mock group 159 159 159 159

# of reconstructed group

13 93 166 166

# of group not idenfied

150 126 95 95

# of extra identification

4 56 95 95

# of identical group 4 10 12 12

FUTURE WORKFUTURE WORK

Those parameters in our algorithm Those parameters in our algorithm need further optimization. In addition, need further optimization. In addition, the weighting of physical quantities of the weighting of physical quantities of each members in the groups, such as each members in the groups, such as its position and and velocity, need to its position and and velocity, need to be modified to obtain the unbiased be modified to obtain the unbiased determination of center positions and determination of center positions and velocity dispersions of galaxy velocity dispersions of galaxy groups/clusters.groups/clusters.

RESULTRESULT

FIGURE 3. is our group finding result for DEEP2 mock catalog, projected to the RA and DEC coordinates on the sky. The reconstructed group and real group are correlated. And some reconstructed groups are found to be false detection.

TALBE 1. shows our preliminary results of group finding in mock catalog with different parameters used in algorithm. Probability threshold is the Pth as in FIGURE 2. . # of mock group is the total number of groups given in the DEEP2 mock catalog, and # of reconstructed group is the number of groups identified by our algorithm. # of Group not identified are the number of real group we didn’t find; while extra identification are the # of reconstruct groups which can’t be identified with real groups. Identical groups are those reconstructed groups with same number of members and members with a real group.

MODIFICATION

object1 object2

LINKING LENGTH

Mean position of object1

LINKING LENGTH

Mean position of object2

PDF1 PDF2(probability distribution)

LVVVV 2112

OLD LINKING CRITERIA

V12: distance of two object

VL : linking length

thL PVzzzPdz )|( 1211

NEW LINKING CRITERIA

P : probability

Pth : threshold for probability

FIGURE 1.

FIGURE 2.

TABLE 1.

FIGURE 3. CONCLUSIONCONCLUSION

We have developed a modified FWe have developed a modified FOF algorithm which can be used tOF algorithm which can be used to identify galaxy group/clusters usio identify galaxy group/clusters using the photometric redshift and/or ng the photometric redshift and/or spectroscopic redshift information spectroscopic redshift information together with their projected coorditogether with their projected coordinates on the sky. This group-findinnates on the sky. This group-finding method has been tested using thg method has been tested using the DEEP2 mock catalog. Our prelie DEEP2 mock catalog. Our preliminary results , however, suggest minary results , however, suggest that the false detection rate can be that the false detection rate can be as high as 60% while the completas high as 60% while the completeness is around 40%, which can beness is around 40%, which can be a result of wrong choices of the le a result of wrong choices of the linking length and the probability thinking length and the probability threshold. We plan to address this isreshold. We plan to address this issue in the near future. sue in the near future.