1. Simon Lilly (ETH Zurich), Angela Iovino, Valentina Presotto (INAF Brera) + zCOSMOS Team COSMOS Meeting, Honolulu 10.06.2010 Christian Knobel (ETH Zurich)

2. Basic strategy x z spec phot I AB ≤ 22.5

3. Friends-of-friends (FOF) Voronoi (VDM) Basic group catalog 1-way-matched sample (1WM) pure but less complete subset Spectroscopic component

4. Published & publicly available: Knobel, Lilly, Iovino, Cucciati + zCOSMOS team et al. (2009) Applications of the catalog: Role of groups in the density field (Kovac et al. 2010) Color as a function of environment (Iovino et al. 2010) Morphology as function of group environment (Kovac et al. 2009) AGN in groups (Silverman et al. 2009) Contribution to lensing analysis (Anguita et al. 2009, Faure et al. in preparation) Sample: 10k catalog 800 groups, 2310 group galaxies 502 groups for N ≥ 5

5. 20k spectroscopic catalog 10k 1WM 20k FOF 20k mocks 10k 20k Groups: 800 1681 Members: 2310 5102 N ≥ 5: 102 213 N ≥ 10 N ≥ 2 N ≥ 5

6.  for N ≥ 3: ≳ 85 % complete ≳ 80 % pure  for N = 2 completeness & purity ~5-10 % lower  group purity parameter (GRP) 1WM  group robustness  velocity dispersion (for N ≥ 5)  flux (abs. mag.) limited richness  mock calibrated mass („fudge mass“) 20k spectroscopic catalog very high confidence subsamples Properties/features:

7. Δz = |z gr – z phot | ΔrΔr σzσz r gr Including photo-z Photometric component

8. empirical fraction f(,,N) |Δz| / σ phot Δr / r gr Including photo-z |Δz| / σ phot 2 ≤ N ≤ 4 N ≥ 10 Δr / r gr Assigning probabilties |Δz| / σ phot Δr / r gr 5 ≤ N ≤ 9 f ΔrΔr r gr ΔzΔz σzσz f f

9. 1. Estimate fraction f(,,N) empirically by the mocks using only galaxies associated to a single group 2. Assign probabilities to all galaxies: p = f(,,N) 3. For galaxies associated to more than one group, the probability must be modified: Including photo-z Scheme of estimating probabilities: Assigning probabilties ΔrΔr r gr ΔzΔz σzσz ΔrΔr ΔzΔz σzσz

10. Including photo-z N real N est rel. median rel. quartiles N real real groups Estimated richness: Basic strategy

11. Including photo-z Most massive galaxy  Introduce probability of a spectroscopic member to be associated to a group  Straightforward scheme to compute probability of each member (spec AND phot) to be the most massive: Sort galaxies in descending order after M such that M i-1 ≥ M i ≥ M i+1 : How to determine the most massive (= central?, dominant?) galaxy in a group?

12. Most massive galaxy 5 ≤ N ≤ 9 3 ≤ N ≤ 4 N ≥ 10 pMpM pMpM pMpM # galaxies Most groups have a clearly identifiable „most massive galaxy“

13. Group center voronoi vol. & stellar mass weighted stellar mass weighted geometrical mean voronoi vol. weighted Voronoi vol. & stellar mass weighted Stellar mass weighted geometrical mean Voronoi vol. weighted Only spectroscopic component: Spec + phot components: Used by Alexis

14. Group center Spec + phot components: Selecting the position of the galaxy with the largest… voronoi volume probability * stellar mass voronoi volume probability

15. Future work/applications within zCOSMOS If you have other ideas/suggestions you are welcome to bring them in!  Analyzing central/satellite/isolated galaxies  Optical/Xray group selection comparison  Masses of optical groups (group-galaxy cross-correlation, weak lensing, N(z)-σ relation,…)  Optical/spectroscopic properties of Xray selected group members  Investigating passives (and actives?) around log M = 10.2 as f(env)  distinction between mass‐quenching and environment quenching  "Super‐group" stacked spectra, looking for radial dependence etc of quenching ages etc. Future work (zCOSMOS)

16.  20k group catalog with ~1,600 groups and ~5,100 spectroscopic members  Overall high completeness and high purity  We are able to select extremely pure subsamples  We are able to assign probabilities to photometric galaxies with I AB < 22.5 (or I AB < 24) to be members of spectroscopic groups  Complete membership for I AB < 22.5  We are able to find for each group the most massive member at high confidence  We can investigate the central-satellite issues  Combining spec and phot components yields improved group properties such as group centers Summary

17. Appendix

18. ≥ probability completeness Completeness 2 ≤ N ≤ 4 5 ≤ N ≤ 9 N ≥ 10 Completeness for phot

19. Group robustness One-to-one correspondence „too big“ (over-merged) No association „too small“ (fragmented) Method to find robust groups: increase or decrease linking length by 20% Consider the increase or decline of the richness N Group robustness

20. 1-1 correspondence „too big“ (over-merged) No association „too small“ (fragmented) Subsample of groups …exhibiting less than 40% change in N by the 20% change of the linking lenght … GRP ≥ 0.8 Group robustness

21. g2g2 completeness purity Interloper fraction 10k 20k 20k spectroscopic catalog

22. Mass completeness 20k