1 / 27

Outline

The Physics of Large Scale Structure and New Results from the Sloan Digital Sky Survey Beth Reid ICC Barcelona. arXiv:0907.1659 arXiv:0907.1660* Colloborators: Will Percival* Daniel Eisenstein Licia Verde David Spergel SDSS TEAM. Outline.

keilah
Download Presentation

Outline

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. The Physics of Large Scale Structure andNew Results from the Sloan Digital Sky Survey Beth Reid ICC Barcelona arXiv:0907.1659arXiv:0907.1660*Colloborators: Will Percival*Daniel EisensteinLicia VerdeDavid SpergelSDSS TEAM

  2. Outline • Physics of Large Scale Structure (LSS): lineary theory • The “theory” of observing LSS • Real world complications: galaxy redshift surveys to cosmological parameters • SDSS DR7: New Results • The Near Future of LSS

  3. The Physics of LSS: Primordial Density Perturbations • Either parameterized like this: • Or reconstructed using a “minimally-parametric smoothing spline technique” (LV and HP, JCAP 0807:009, 2008) • Contains information about the inflationary potential WMAP3+SDSS MAIN

  4. Physics of LSS: CDM, baryons, photons, neutrinos I Effective number of relativistic species; 3.04 for std neutrinos Completely negligible • bh2, mh2/rh2 = 1+zeq well-constrained by CMB peak height ratios. • During radiation domination, perturbations inside the particle horizon are suppressed: keq = (2mHo2 zeq)1/2 ~ 0.01 Mpc-1 [e.g., Eisenstein & Hu, 98] • Other important scale: sound horizon at the drag epoch rs Eisenstein et al. (2005) ApJ 633, 560 k (h/Mpc)

  5. BAO For those of you who think in Real space Courtesy of D. Eisenstein

  6. BAO Observe photons Photons coupled to baryons “See” dark matter If baryons are ~1/6 of the dark matter these baryonic oscillations should leave some imprint in the dark matter distribution (gravity is the coupling) Courtesy L Verde For those of you who think in Fourier space

  7. Physics of LSS: CDM, baryons, photons, neutrinos II • Linear matter power spectrum P(k) depends on the primordial fluctuations and CMB-era physics, represented by a transfer function T(k). Thereafter, the shape is fixed and the amplitude grows via the growth factor D(z) • Cosmological probes span a range of scales and cosmic times Superhorizon during radiation domination Tegmark et al. (2004), ApJ 606, 702 keq

  8. Physics of LSS: CDM, baryons, photons, neutrinos III • Massive neutrinos  m<~ 1 eV become non-relativistic AFTER recombination and suppress power on small scales Courtesy of W. Hu

  9. Physics of LSS: Summary • WMAP5 almost fixes* the expected Plin(k) in Mpc-1through c h2 (6%) and b h2 (3%), independent of CMB (and thus curvature and DE). • In the minimal model (Neff = 3.04, m= 0), entire P(k) shape acts as a “std ruler” and provides an impressive consistency check -- same physics that generates the CMB at z=1100 also determines clustering at low z. BAO turnover scale

  10. “Theory” of Observing LSS: Geometry • We measure , z; need a model to convert to co-moving coordinates. • Transverse: Along LOS: • Spherically averaged, isotropic pairs constrain • Redshift Space Distortions -- later, time permitting

  11. BAO in SDSS DR7 + 2dFGRS power spectra • Combine 2dFGRS, SDSS DR7 LRG and Main Galaxies • Assume a fiducial distance-redshift relation and measure spherically-averaged P(k) in redshift slices • Fit spectra with model comprising smooth fit × damped BAO • To first order, isotropically distributed pairs depend on • Absorb cosmological dependence of the distance-redshift relation into the window function applied to the model P(k) • Report model-independent constraint on rs/DV(zi) Percival et al. (2009, arXiv:0907.1660)

  12. SDSS DR7 BAO results:modeling the distance-redshift relation Parameterize distance-redshift relation by smooth fit: can then be used to constrain multiple sets of models with smooth distance-redshift relation For SDSS+2dFGRS analysis, choose nodes at z=0.2 and z=0.35, for fit to DV Percival et al. (2009, arXiv:0907.1660)

  13. results can be written as independent constraints on a distance measure to z=0.275 and a tilt around this consistent with ΛCDM models at 1.1σ when combined with WMAP5 Reduced discrepancy compared with DR5 analysis more data revised error analysis (allow for non-Gaussian likelihood) more redshift slices analyzed improved modeling of LRG redshift distribution BAO in SDSS DR7 + 2dFGRS power spectra Percival et al. (2009, arXiv:0907.1660)

  14. Comparing BAO constraints against different data flat wCDM models ΛCDM models with curvature Percival et al. (2009: arXiv:0907.1660) Percival et al. (2009: arXiv:0907.1660) Union supernovae WMAP 5year BAO Constraint on rs(zd)/DV(0.275)

  15. Cosmological Constraints flat wCDM models ΛCDM models with curvature Percival et al. (2009: arXiv:0907.1660) Percival et al. (2009: arXiv:0907.1660) WMAP5+BAO CDM: m = 0.278 ± 0.018, H0 = 70.1 ± 1.5 WMAP5+BAO+SN wCDM + curvature: tot = 1.006 ± 0.008, w = -0.97 ± 0.10 Union supernovae WMAP 5year rs(zd)/DV(0.2) & rs(zd)/DV(0.35)

  16. Modeling Pgal(k): Challenges • density field goes nonlinear • uncertainty in the mapping between galaxy and matter density fields • galaxy positions observed in redshift space “Finger-of-God” (FOG) Real space Redshift space z

  17. From: Tegmark et al 04

  18. Interlude: the Halo Model • Galaxy formation from first principles is HARD! • Linear bias model insufficient! • gal = bgal m Pgal(k) = bgal2 Pm(k) • Halo Model Key Assumptions: • Galaxies only form/reside in halos • N-body simulations can determine the statistical properties of halos • Halo mass entirely determines key galaxy properties • Provides a non-linear, cosmology-dependent model and framework in which to quantify systematic errors

  19. Luminous Red Galaxies • DR5 analysis: huge deviations from Plin(k) • nP ~ 1 to probe largest effective volume • Occupy most massive halos large FOG features • Shot noise correction important Tegmark et al. (2006, PRD 74 123507) Tegmark et al. (2006, PRD 74 123507)

  20. Luminous Red Galaxies • DR5 analysis: huge deviations from Plin(k) • nP ~ 1 to probe largest effective volume • Occupy most massive halos large FOG features • Shot noise correction important Tegmark et al. (2006, PRD 74 123507) Statistical power compromised by QNL at k < 0.09

  21. DR7: What’s new? • nLRG small find “one-halo” groups with high fidelity • Provides observational constraint on FOGs and “one-halo” excess shot noise • NEW METHOD TO RECONSTRUCT HALO DENSITY FIELD • Better tracer of underlying matter P(k) • Replace heuristic nonlinear model (Tegmark et al. 2006 DR5) with cosmology-dependent, nonlinear model calibrated on accurate mock catalogs and with better understood, smaller modeling systematics • Increase kmax = 0.2 h/Mpc; 8x more modes! Reid et al. (2009, arXiv:0907.1659)

  22. Phalo(k) Results • Constrains turnover (mh2 DV) and BAO scale (rs/DV) mh2 (ns/0.96)1.2= 0.141 ± 0.011 DV(z=0.35) = 1380 ± 67 Mpc

  23. WMAP+Phalo(k) Constraints: Neutrinos in CDM • Phalo(k) constraints tighter than P09 BAO-only • Massive neutrinos suppress P(k) • WMAP5:  m< 1.3 eV (95% confidence) • WMAP5+LRG:  m< 0.62 eV • WMAP5+BAO:  m< 0.78 eV • Effective number of relativistic species Nrel alters turnover and BAO scales differently • WMAP5: Nrel = 3.046 preferred to Nrel = 0 with > 99.5% confidence • WMAP5+LRG: Nrel = 4.8 ± 1.8 Reid et al. (2009, arXiv:0907.1659)

  24. Summary & Prospects • BAOs provide tightest geometrical constraints • consistent with ΛCDM models at 1.1σ when combined with WMAP5 • improved error analysis, n(z) modeling, etc. • DR7 P(k) improvement: We use reconstructed halo density field in cosmological analysis • Halo model provides a framework for quantifying systematic uncertainties • Result: 8x more modes, improved neutrino constraints compared with BAO-only analysis • Likelihood code available here: • http://lambda.gsfc.nasa.gov/toolbox/lrgdr/ • Shape information comes “for free” in a BAO survey!

  25. Near future… • BAO reconstruction (Eisenstein, Seo, Sirko, Spergel 2007, Seo et al. 2009) • Fitting for the BAO in two dimensions: get DA(z) and H(z) [ask Christian] • Extend halo model modeling to redshift space distortions to constrain growth of structure and test GR or dark coupling (e.g., Song and Percival 2008) • Constraining primordial non-Gaussianity with LSS [ask Licia] • Technical challenge -- extract P(k), BAO, & redshift distortion information simultaneously, and understand the covariance matrix

  26. BAO reconstruction • In linear theory, velocity and density fields are simply related. • Main idea: compute velocity field from measured density field, and move particles back to their initial conditions using the Zel’dovich approximation • It works amazingly well: • reduces the “damping” of the BAO at low redshifts (Eisenstein et al. 2007, and thereafter) • removes the small systematic shift of the BAO to below the cosmic variance limit, <0.05% (Seo et al. 2009 for DM, galaxies in prep)

  27. Redshift space distortions • In linear theory, modes are amplified along the LOS by peculiar velocities: Song and Percival, arXiv:0807.0810 Okumura et al., arXiv:0711.3640

More Related