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Clustering of galaxies in the two-year BOSS sample

Clustering of galaxies in the two-year BOSS sample. A.Klypin (NMSU) with friends. S. Nuza, A.Sanchez, F.Prada, A.Klypin + BOSS collaboration 2012 Not BAO clustering on 0.5-100Mpc scales observations and theory. History of discoveries with wrong motivation.

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Clustering of galaxies in the two-year BOSS sample

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  1. Clustering of galaxies in the two-year BOSS sample A.Klypin (NMSU) with friends

  2. S. Nuza, A.Sanchez, F.Prada, A.Klypin + BOSS collaboration 2012 Not BAO clustering on 0.5-100Mpc scales observations and theory

  3. History of discoveries with wrong motivation Neyman, Scott, Shane 1953 Angle (degrees)

  4. Davis & Peebles 1983 (CfA) Davis, Groth, Peebles 1977

  5. Angular correlation function: SDSS results Two contributions: - number-density profile of galaxies inside the same halo 2-halo - clustering of halos 1-halo Zehavi et al. (astro-ph/0301280)

  6. Zehavi et al 2011 SDSS DR7 500K galaxies

  7. 1-halo 2-halo BAO Zero crossing Negative TΔN/N = b σ8 =1.3x0.82 =1.07 What we should expect: Theory Bolshoi + bigBolshoi + Linear

  8. Correlation function for large halos: Note dump at ~300kpc 350 km/s 300 km/s BDM vs. RockStar

  9. Simulations: LCDM with sensible parameters • bigBolshoi = MultiDark: • 1Gpc 8.6G particles, 7 kpc, 13M halos complete to circular velocity 180 km/s = 1012Msun • Carmen: • 40 realizations 1.9G particles 25kpc 6 times larger mass/particle

  10. Bridging the gap between halos and galaxies: Two ways of populating halos with galaxies: • Halo Occupation Distribution: • probability to find Ngalaxies in a distinct halo of • mass M: P(Ngalaxies|Mhalo) • - need to know how to get P(Ngalaxies|Mhalo) • - need to know how to place ‘galaxies’ • - P(N|M) may depend on halo environment and • dynamical state (e.g. merging ...) • Halo Abundance Matching (HAM): • - take the same number density of halos as observed. • - small non-monotonic selection of (sub)halos => galaxies

  11. bigMD 2.5Gpc 17G particles

  12. bigBolshoi 1Gpc 8G particles

  13. Small Galaxy Group

  14. Small Galaxy Group Central Region

  15. Bridging the gap between halos and galaxies: We do not do and do not recommend using Halo Occupation Distribution: too much freedom • Halo Abundance Matching (HAM): • - no free parameters. Model can fail. • - Requires high resolution to detect subhalos • - Do not use virial masses for HAM: we use Vmax => closer to galaxies

  16. Fraction of satellites

  17. BOSS CMASS S. Nuza, A.Sanchez, F.Prada, A.Klypin + BOSS collaboration 2012 Not BAO: clustering on 0.5-100Mpc 320,000 galaxies Mass = 1013 Msun z = 0.53

  18. Comparison with 44,000 - first semester White et al - Better statistics: 320k -- 44k - Improvement in treatment of systematics - Signal went down by 10-20% on 10-20 Mpc scale - Improvement of theory: no free-parameter HODs

  19. Redshift space correlation function Red - South Blue - North Black - LCDM

  20. Projected correlation function Red - South Blue - North Black - LCDM

  21. Systematics? Fibre collisions South/North asymmetry Projected correlation function - integral ±200Mpc Red - South Blue - North Black - LCDM

  22. Redshift space correlation function Red - South Blue - North Black - LCDM No (clear) signatures of systematics. No South/North differences Agreement of LCDM with BOSS: ➨ extremely good on 0.5-10 Mpc scales with errors less than 5% ➨ 10-15% disagreement, a 3σ effect

  23. Power Spectrum and Biases: Theory

  24. Power Spectrum and Biases: theory Correct for shot noise and density assignment Test against much higher res. simulation

  25. Power Spectrum and Biases BAO peaks Vmax> 360km/s (BOSS) Vmax> 200km/s (MW) Plinear Plinear

  26. Bias: scale dependence for CMASS bigBolshoi with the same number-density as BOSS-CMASS Analytical model with 2% accuracy Note spikes at k=0.1-0.3 h/Mpc

  27. Dips in bias at positions of BAO peaks

  28. Biases: dependence on scale and Vmax and number-density Vmax = 200-400 km/s

  29. Redshift distortions Standard redshift distortions: Kaiser b-dependent long-wave approx. is extremely accurate Lorenzian exp(-kσ) is ... see yourself. Cannot be worse. Gaussian exp(-k2σ2) is lot better, but fails at k>0.5 or r<2Mpc e-x Dips of bias at BAOs e-x2

  30. ---- 320,000 galaxies at z=0.5 • Redshift-space xi: clear results, no asymmetries. South/North show the same correlation functions. • Projected xi shows some defects, which are likely due to ... projections • LCDM with HAM: no HOD, no free parameters. Matching by circular velocity, not mass. Small stochasticity. Works remarkably good. • Comparison in redshift space: small disagreement at 20-50Mpc scales • Overall: very good Clustering of galaxies in the two-year BOSS sample

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