BAO and Tomography of the SDSS

1. BAO and Tomography of the SDSS Alex SzalayHaijun TianTamas BudavariMark Neyrinck

2. SDSS Redshift Samples • Main Galaxies • 800K galaxies, high sampling density, but not too deep • Volume is about 0.12 Gpc3 • Luminous Red Galaxies • 100K galaxies, color and flux selected • mr < 19.5, 0.15 < z < 0.45, close to volume-limited • Quasars • 20K QSOs, cover huge volume, but too sparse

3. Finding the Bumps – DR4 • Eisenstein et al (2005) – LRG sample

4. Primordial Sound Waves in SDSS Power Spectrum (Percival et al 2006, 2007) SDSS DR6+2dF SDSS DR5 800K galaxies

5. (r) from linear theory + BAO • Mixing of 0 , 2 and 4 • Along the line of sight  r 

7. 2D Symmetry • There is a planar symmetry: • Observer+ 2 galaxies • Thus 2D correlation of a slice is the same • We usually average over cos • Very little weight along the  axis: • Sharp of features go away

8. Tomography of SDSS • SDSS DR7 Main Galaxy Sample • Limit distances to 100<r<750 h-1Mpc • Cut 3D data into thin angular slices • Project down to plane (only 2D info) • Different widths (2.5, 5, 10 deg) • Rotate slicing direction by 15 degrees • Analyze 2D correlation function (,) • Average over angle for 1-D correlations

9. Why correlation function? • For a homogeneous isotropic process,the correlation function in a lower dimsubset is identical • There are subtleties: • With redshift space distortions the process is not fully homogeneous and isotropic • Redshift space distortions and ‘bumps’ • Distortions already increase the ‘bumps’ • Any effects from the ‘slicing’?

10. Projection and Slicing Theorem The basis of CAT-SCAN / Radon xform

12. Slices of finite thickness • Project redshift-space power spectrum with a corresponding window functionsinc(kzR) • Anisotropic power spectrum • There is a thickness-dependent effect • Thinner slices give bigger boost

13. Millennium 64Mpc

14. Millennium 16Mpc

15. Millennium 4Mpc

16. Millennium 1Mpc

17. 2.5 deg slices (702 total)

18. 5 deg slices

19. 10 deg slices

20. 10 deg, in 3D

21. Full 3D correlation function

22. Full 3D no Great Wall

23. 2.5 deg slices (702 total)

24. (r) along the line of sight Average of all 2.5 degree slices

25. 3D along the line

26. No Great Wall

27. (r) along the line of sight • The correlation function along a 1D line: • Pencilbeam • Corresponding power spectrum • Projection of P(s)(k) onto a single axis

28. Computations on GPUs • Generated 16M randoms with correctradial and angular selection for SDSS-N • Done on an NVIDIA GeForce 260 card • 400 trillion galaxy/random pairs • Brute force massively parallel code muchfaster than tree-code • All done inside the JHU SDSS database • 2D correlation function is now DB utility

29. Summary • Redshift space distortions amplify features • Lower dimensional subsets provide further amplification of ‘bumps’ at 107-110h-1Mpc • Boost much stronger along the line of sight • Using these techniques we have strong detection of BAO in SDSS DR7 MGS • Effect previously mostly seen in LRGs • Trough at 55h-1Mpc is a harmonic, sharpness indicates effects of nonlinear infall • Bump at 165h-1Mpc puzzling

30. Millennium galaxies

31. Cosmology used M = 0.279 L = 0.721 K = 0.0 h= 0.701 w0 = -1