Highlights of Recent SDSS Sciences by JPG

1. Highlights of Recent SDSS Sciences by JPG Yasushi Suto Department of Physics, The University of Tokyo

2. JPG (Japan Participation Group) • Joined SDSS from the beginning • Major contributions • construction of the mosaic CCD camera • fabrication and test of the urgiz filters, electronics, etc. • establishing photometric reference systems • Simulation and verification of the photometric pipeline • Current members (14 in total) • Univ. of Tokyo: M.Doi, M.Fukugita, S.Okamura, K.Sato, K.Shimasaku, Y.Suto, N.Yasuda • Tohoku Univ.: T.Ichikawa • Nagoya Univ.: S.Ikeuchi, T.Matsubara • National Astron. Obs. of Japan: S.Ichikawa • Others: M.Hamabe, M.Sekiguchi, M.Watanabe

3. A slice of the universe: galaxy distribution from SDSS DR1 http://www.sdss.org/dr1/ from Japanese TV program “Science ZERO” (NHK)

4. Outline of the talk • Morphology and luminosity dependence of clustering of SDSS galaxies; two-point and three-point correlation functions (Kayo et al.) • Topology of large-scale structure from the Minkowski functional analysis of SDSS galaxies (Hikage et al.) • Phase correlation of SDSS galaxies (Hikage et al.) • SDSS QSO lens survey (Inada, Oguri, et al.) • Constraining the departure from Newtonian gravity using SDSS galaxy power spectrum (Shirata et al.)

5. major contributors of the results presented in this talk • Issha Kayo (Nagoya Univ.) • 2pt and 3pt galaxy clustering • Chiaki Hikage (Nagoya Univ.) • topology and non-Gaussianity of galaxy clustering • Naohisa Inada (Univ. of Tokyo) and Masamune Oguri (Univ. of Tokyo & Princeton Univ.) • QSO lens survey • Akihito Shirata (Tokyo Inst. Technology) • constraining deviation from Newtonian gravity • Kazuhiro Yahata (Univ. of Tokyo) • QSO clustering

6. Part 1 Morphology and luminosity dependence of clustering of SDSS galaxies; two-point and three-point correlation functionsKayo et al. PASJ 56 (2004) 415

7. SDSS DR1 galaxies: morphology dependent clustering • Late-types in blue • Early-types in red • Density-morphology relation is barely visible from Japanese TV program “Science ZERO” (NHK)

8. Morphology-dependence of galaxy bias from SDSS magnitude-limited sample early-type average late-type • Galaxy bias is fairly scale-independent • Clear morphology dependence with respect to ΛCDM (computed semi-analytically over light-cone) Redshift-space Real-space Kayo et al. (2003)

9. Morphology-dependence of galaxy biasin real space from SDSS magnitude-limited sample early-type average late-type • Galaxy bias is fairly scale-independent • Clear morphology dependence: b=1.2～1.5 for “early”-types and b=0.7～0.9 for “late”-typeswith respect to ΛCDM with s8=0.9 (computed semi-analytically using the light-cone average described before) Kayo, Suto, Fukugita, Nakamura, et al. (2003)

10. Previous predictions from SPH simulations with “galaxy” formation Dark matter “Galaxies” formed before z=1.7 (early-types ?) x(r) • Simulated “galaxies” formed earlier are more strongly biased • Recently formed galaxies preferentially avoid high-density regions • Quite consistent with the morphology- dependent galaxy bias derived from the recent SDSS DR1 ! “Galaxies” formed after z=1.7 (late-types ?) b(r) early-types late-types Yoshikawa, Taruya, Jing & Suto (2001)

11. Volume-limited samples of SDSS galaxies

12. Morphology and luminosity dependence of 2PCF of SDSS galaxies • Early > Late • Morphological dependence becomes weaker as galaxies become brighter

13. Luminosity and morphology dependence of 2PCF of SDSS galaxies • (all) More luminous, and stronger • (late-type) More luminous, and stronger • (early-type) Very weak luminosity dependence

14. Luminous galaxy .... Massive Host Dark Halo Luminosity dependence Physical interpretation ? Evolution of biasing!? During their long lives, ellipticals move around inside dark halos following dark matter potential of the dark halos. They may forget the original luminosity dependence. Elliptical ~ bright spirals Age of bright spirals might be old. Biasing is determined by formation epoch + Evolution ?? Physical picture of morphology and luminosity dependence remains to be understood…

15. Three-point correlation function 3 s31 s23 2 1 s12 Nonlinear gravity Gaussian Nonlinear bias Non-Gaussian • The simplest statistics to probe the non-Gaussianity (phase information) • Definite observational results (Groth & Peebles 1977) were obtained more than 25 years ago with no convincing theoretical explanation yet. • Very recent detailed nonlinear models (e.g., Takada & Jain 2003) on the basis of the halo approach

16. Q 0 180 Θ Q 0 180 Θ Physically expected shape-dependence of Q large scale: filamentary structure small scale: spherical halo structure

17. Expected scale-dependence of Q from 2PCF of SDSS galaxies (linear bias) If biasing is simple linear form, Qg relates to Qm as If biasing has non-linear form, such as then

18. Three-point correlation functions in redshift space equilateral triangles • Q ~ 0.5 – 1.5 • Weak dependence on scale of triangles(hierarchical ansatz is valid) • Weak dependence on Luminosity • Weak dependence on Morphology

19. Summary of 3-point correlation functions of SDSS galaxies • Hierarchical clustering relation holds (Q～const.) • Almost no luminosity/morphology dependence • In contrast, 2-point correlation function is very sensitive to both • b2 may be correlated with b1 • But redshift-space distortion effect makes significant difference

20. Part 2 Topology of large-scale structure from the Minkowski functional analysis of SDSS galaxiesHikage et al. PASJ 55 (2003) 911

21. Topological analyses of LSS in SDSS using Minkowski Functionals (MFs) • A complete set of morphological descriptors • d+1 functionals in d-dimensional pattern • In 3d spatial distribution, volume, surface area, mean curvature, and the Euler characteristic (genus) • Complementary statistics to the two-point correlation function (includes the phase information) • Analytic expressions known for Gaussian fields • Probe of the non-Gaussianity: • Primordial non-Gaussianity in the initial condition • the non‐linearity of the gravitational evolution • the non-linearity of the galaxy biasing

22. Topology of SDSS galaxy distribution Surface area Volume fraction • Topology of SDSS galaxy distribution (measured with Minkowski Functionals) is consistent with those originated from the primordial random-Gaussian field in LCDM (Hikage, Schmalzing, Buchert, Suto et al.2003PASJ). Integrated mean curvature Euler characteristic (genus)

23. Luminosity dependence of MFs is weak -21<Mr<-20 Surface area -20<Mr<-19 -19<Mr<-18 volume fraction • No significant luminosity dependence of MFs is detected so far Euler characteristic mean curvature

24. Morphological dependence of MFs is weak Surface area volume fraction • No significant morphological dependence of MFs is detected so far -21<Mr<-20 Euler characteristic mean curvature

25. SDSS data represent a fair sample of the universe ? volume fraction volume fraction Surface area Surface area mean curvature mean curvature Euler characteristic Sample 10 Euler characteristic Sample 12 Hikage et al. (2003) • Difference of MFs for two independent regions of SDSS • Two regions in Sample 12 barely converge within the error bars from Mock samples. Encouraging, but larger samples are needed.

26. Part 3 Phase correlation of SDSS galaxies(power-point file provided by C.Hikage)Hikage, Matsubara & SutoApJ 600 (2004) 553Hikage et al. in preparation

27. Fourier phases of cosmological density fluctuations Phase: not well studied inspite of its importance (difficult to quantify, mod. 2π) Amplitude: already extensively discussed in two-point statistics, i.e., two-point correlation function and power spectrum

28. Importance of phases in large scale structure of the universe Scale-independent amplitudes Randomize the phases Simulated density field on meshes Correlation of Fourier-phases is also essential in the pattern of large scale structure of the universe

29. Difficulty of quantifying phase correlations in a direct manner • ２cyclic property • lose the information of the cumulative phase shift experienced by (nonlinear) gravitational evolution • Phases vary by the position of the origin in a given coordinate • Thus usually indirect statistics of phase correlations • higher-order correlation functions • Minkowski functionals

30. Distribution function of phase sum(Matsubara 2003) • Phase sum • invariant by the position of origin • perturbation formula for the distribution function of phase sum (Matsubara 2003) n=3 Order parameter (Hierarchical ansatz)

31. Application to SDSS galaxy distribution Sample 12 (now calculating using sample 14) Volume limited samples

32. Mock catalogs N-body simulations (Jing & Suto, Kayo) 2563,Gaussian initial condition Construct mock catalogs with • Same geometry as observation • Same number density as observation • Considering redshift distortion using velocity information

33. Luminosity/model dependence of p(3) Errors: Sample variance of mock (LCDM) results

34. Dependence on 8

35. Summary of the current status • First attempt to characterize the phase correlation of SDSS galaxies directly using the phase sum distribution function • So far the result in good agreement with LCDM model (8=0.9) • Analysis with sample 14 is in progress

36. Part 4 SDSS QSO lens survey(power-point file provided by M.Oguri)Inada, Oguri, Pindor, et al. Nature 426 (2003) 810 Oguri, Inada, Keeton, et al. ApJ 605 (2004) 78

37. Gravitationally lensed quasar lensed images lens object (galaxy or cluster) telescope source(quasar) • Strong gravitational field around a galaxy or cluster • will bend the light path (according to general relativity) • A quasar behind a galaxy or cluster can be split into several images (gravitationally lensed quasar)

38. SDSS(final, photo) SDSS (final, spec) 2dF (Miller et al.) SDSS (we are here) JVAS (Helbig et al.) CLASS (Myers et al.) HST (Maoz et al.) Compound (Kochanek) CFHT(Crampton et al.) exponential growth Number of target QSOs for lens survey

39. quasar 60" radius similar color object How to find lenses Inada et al, in preparation 1.0" <  < 3.5" (marginally resolved)  > 3.5" (resolved) search for extended quasars in the quasar catalog using: galaxy profile (de-Vau and exp-disk) fitting likelihood PSF fitting likelihood Search stellar objects with similar colors to the quasar Follow-up observations are needed to confirm if these candidates are really lenses or not !

40. D B A A C D C B B A B D C A Current status: new lensed quasars J1226 (Magellan, i) J0924 (Magellan, i) J1155 (Keck, K) J0903 (ARC, i) J1021 (Keck, K) J1004 (Subaru, i) J1335 (Subaru, i) J0246 (Keck, K) J1138 (Magellan, i) J1001 (UH88, I) J1206 (UH88, I) J1650 (WIYN, I)

41. SDSS J0924 Inada et al., AJ 126(2003)666 SDSS J0903 Johnston et al., AJ 126(2003)2281 SDSS J1004 Inada et al., Nature 426(2003)810 SDSS J1155 Pindor et al., AJ 127(2004)1318 SDSS J1335 Oguri et al., PASJ 56(2004)399 SDSS J1226 Inada et al., AJ submitted SDSS J0246 Inada et al., to be submitted SDSS J1021 Pindor et al., to be submitted SDSS J1001 SDSS J1206 SDSS J1138 Burles et al., in preparation SDSS J1650 Morgan et al., AJ 126(2003)2145 Oguri et al., to be submitted Summary of new SDSS lens (12) Papers by SDSS collaboration Paper by non-SDSS

42. A B C D A D B B A C Largest-separation lens: SDSS J1004 Inada, Oguri, Pindor, et al., Nature 426(2003)810 Oguri, Inada, Keeton, et al., ApJ 605(2004)78 15" SDSS (i band) Subaru (Sprime, gri) HST (ACS, I) First discovery of a quasar lensed by a cluster (and the LARGEST quasar lens discovered so far!) HST (NICMOS, H)

43. Prospect for the lens statistics • Expected constrains from lens statistics of all SDSS spec quasars (~80,000 at 0.6<z<4.0) • Constraints on WM–WL and WM–w (assuming a flat universe) planes • Comparable to current SN surveys