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L. Perivolaropoulos leandros.physics.uoi.gr Department of Physics University of Ioannina

Open page. ΛCDM: Triumphs, Puzzles and Remedies. L. Perivolaropoulos http://leandros.physics.uoi.gr Department of Physics University of Ioannina. Main Points. The consistency level of LCDM with geometrical data probes has been increasing with time during the last decade.

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L. Perivolaropoulos leandros.physics.uoi.gr Department of Physics University of Ioannina

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  1. Open page ΛCDM: Triumphs, Puzzles and Remedies L. Perivolaropouloshttp://leandros.physics.uoi.gr Department of Physics University of Ioannina

  2. Main Points The consistency level of LCDM with geometrical data probes has been increasing with time during the last decade. There are some puzzling conflicts between ΛCDM predictions and dynamical data probes (bulk flows, alignment and magnitude of low CMB multipoles, alignment of quasar optical polarization vectors, cluster halo profiles) Most of these puzzles are related to the existence of preferred anisotropy axes which appear to be surprisingly close to each other! The axis of maximum anisotropy of the Union2 SnIa dataset is also located close to the other anisotropy directions. The probability for such a coincidence is less than 1%. The amplified dark energy clustering properties that emerge in Scalar-Tensor cosmology may help resolve the puzzles related to amplified bulk flows and cluster halo profiles.

  3. SnIa Obs GRB Direct Probes of the Cosmic Metric: Geometric Observational Probes Direct Probes of H(z): Luminosity Distance (standard candles: SnIa,GRB): flat Significantly less accurate probesS. Basilakos, LP, MBRAS ,391, 411, 2008arXiv:0805.0875 Angular Diameter Distance (standard rulers: CMB sound horizon, clusters):

  4. Geometric Constraints Parametrize H(z): Chevallier, Pollarski, Linder Minimize: WMAP3+SDSS(2007) data ESSENCE (+SNLS+HST) data Standard Candles (SnIa) Lazkoz, Nesseris, LPJCAP 0807:012,2008.arxiv: 0712.1232 Standard Rulers (CMB+BAO)

  5. Geometric Probes: Recent SnIa Datasets Q1: What is the Figure of Merit of each dataset? Q2: What is the consistency of each dataset with ΛCDM? Q3: What is the consistency of each dataset with Standard Rulers? J. C. Bueno Sanchez, S. Nesseris, LP, JCAP 0911:029,2009, 0908.2636

  6. Figures of Merit The Figure of Merit:Inverse area of the 2σ CPL parameter contour.A measure of the effectiveness of the dataset in constraining the given parameters. GOLD06 SNLS ESSENCE UNION CONSTITUTION UNION2 WMAP5+SDSS7 WMAP5+SDSS5

  7. Figures of Merit The Figure of Merit:Inverse area of the 2σ CPL parameter contour.A measure of the effectiveness of the dataset in constraining the given parameters. U2 C SDSS MLCS2k2 U1 G06 SDSS SALTII E SNLS SDSS5 Percival et. al. SDSS7 Percival et. al.

  8. Consistency with ΛCDM Trajectories of Best Fit Parameter Point ESSENCE+SNLS+HST data Ω0m=0.24 SNLS 1yr data The trajectories of SNLS, Union2 and Constitution are clearly closer to ΛCDM for most values of Ω0m Gold06 is the furthest from ΛCDM for most values of Ω0m Q: What about the σ-distance (dσ) from ΛCDM?

  9. The σ-distance to ΛCDM ESSENCE+SNLS+HST data Trajectories of Best Fit Parameter Point Consistency with ΛCDM Ranking:

  10. The σ-distance to Standard Rulers ESSENCE+SNLS+HST Trajectories of Best Fit Parameter Point Consistency with Standard Rulers Ranking:

  11. From LP, 0811.4684,I. Antoniou, LP 1007.4347 Puzzles for ΛCDM Large Scale Velocity Flows - Predicted: On scale larger than 50 h-1Mpc Dipole Flows of 110km/sec or less. - Observed: Dipole Flows of more than 400km/sec on scales 50 h-1Mpc or larger. - Probability of Consistency:1% R. Watkins et. al. , 0809.4041 Alignment of Low CMB Spectrum Multipoles - Predicted: Orientations of coordinate systems that maximize of CMB maps should be independent of the multipole l . - Observed: Orientations of l=2 and l=3 systems are unlikely close to each other. - Probability of Consistency:1% M. Tegmark et. al., PRD 68, 123523 (2003), astro-ph/0302496 Large Scale Alignment of QSO Optical Polarization Data - Predicted: Optical Polarization of QSOs should be randomly oriented - Observed: Optical polarization vectors are aligned over 1Gpc scale along a preferred axis. - Probability of Consistency:1% D. Hutsemekers et. al.. AAS, 441,915 (2005), astro-ph/0507274 Cluster and Galaxy Halo Profiles: - Predicted: Shallow, low-concentration mass profiles - Observed: Highly concentrated, dense halos - Probability of Consistency:3-5% Broadhurst et. al. ,ApJ 685, L5, 2008, 0805.2617, S. Basilakos, J.C. Bueno Sanchez, LP., 0908.1333, PRD, 80, 043530, 2009.

  12. Preferred Axes Three of the four puzzles for ΛCDM are related to the existence of a preferred axis QSO optical polarization angle along the diretction l=267o, b=69o D. Hutsemekers et. al.. AAS, 441,915 (2005), astro-ph/0507274

  13. Preferred Axes Quasar Align. CMB Octopole Q1: Are there other cosmological data with hints towards a preferred axis? Q2: What is the probability that these independent axes lie so close in the sky? CMB Dipole I. Antoniou, LP 1007.4347 CMB Quadrup. Velocity Flows Octopole component of CMB map Dipole component of CMB map Quadrupole component of CMB map M. Tegmark et. al., PRD 68, 123523 (2003), astro-ph/0302496

  14. Union2 SnIa Data Z=1.4 Z=0 South Galactic Hemisphere North Galactic Hemisphere

  15. Hemisphere Comparison Method 2. Evaluate Best Fit Ωm in each Hemisphere Z=1.4 1. Select Random Axis Z=0 3.Evaluate Union2 DataGalactic Coordinates (view of sphere from opposite directions 4. Repeat with several random axes and find

  16. Anisotropies for Random Axes Union2 Data North-South Galactic Coordinates ΔΩ/Ω=0.43 ΔΩ/Ω= -0.43 Direction of Maximum Acceleration: (l,b)=(306o,15o)

  17. Anisotropies for Random Axes (Union2 Data) View from above Maximum Asymmetry Axis Galactic Coordinates Minimum Acceleration: (l,b)=(126o,-15o) ΔΩ/Ω=0.43 ΔΩ/Ω= -0.43 Maximum Acceleration Direction: (l,b)=(306o,15o)

  18. Consistency with Statistical Isotropy Construct Simulated Isotropic Dataset: 2. Keep same directions, redshifts and σμi as real Union2 data 3. Replace real distance modulus μobs(zi) by gaussian random distance moduli with mean and standard deviation σμi . 1. Find best fit parameter and zero point ofcet ΔΩ/Ω=0.43 ΔΩ/Ω=-0.43 Anisotropies for Random Axes (Isotropic Simulated Data)View from above Maximum Asymmetry Axis (Galactic Coordinates)

  19. Statistical Isotropy Test 1. Compare a simulated isotropic dataset with the real Union2 dataset by splitting each dataset into hemisphere pairs using 10 random directions. 2. Find the maximum levels of anisotropy (Union2) and (Isotropic) and compare them. 3. Repeat this comparison experiment 40 times with different simulated isotropic data and axes each time.

  20. Distribution of Isotropic Data can Reproduce the Asymmetry Level of Union2 Data Maximum after 10 trial axes Frequencies Max

  21. Statistical Isotropy Test: Results In about 1/3 of the numerical experiments (14 times out of 40) i.e. the anisotropy level was larger in the isotropic simulated data. There is a direction of maximum anisotropy in the Union2 data (l,b)=(306o,15o). The level of this anisotropy is larger than the corresponding level of about 70% of isotropic simulated datasets but it is consistent with statistical isotropy. Simulated Data Test Axes Real Data Test Axes ΔΩ/Ω=0.43 ΔΩ/Ω=0.43 ΔΩ/Ω=-0.43 ΔΩ/Ω=-0.43

  22. Comparison with other Axes Q: What is the probability that these independent axes lie so close in the sky? Calculate: Compare 6 real directions with 6 random directions

  23. Comparison with other Axes Q: What is the probability that these independent axes lie so close in the sky? Simulated 6 Random Directions: Calculate: 6 Real Directions (3σ away from mean value): Compare 6 real directions with 6 random directions

  24. Distribution of Mean Inner Product of Six Preferred Directions (CMB included) The observed coincidence of the axes is a statistically very unlikely event. 8/1000 larger than real data Frequencies < |cosθij|>=0.72 (observations) <cosθij>

  25. Distribution of Mean Inner Product of Three Preferred Directions (CMB excluded) Even if we ignore CMB data the coincidence remains relatively improbable 71/1000 larger than real data Frequencies < |cosθij|>=0.76(observations) <cosθij>

  26. Models Predicting a Preferred Axis • Anisotropic dark energy equation of state (eg vector fields)(T. Koivisto and D. Mota (2006), R. Battye and A. Moss (2009)) • Horizon Scale Dark Matter or Dark Energy Perturbations (eg 1 Gpc void)(J. Garcia-Bellido and T. Haugboelle (2008), P. Dunsby, N. Goheer, B. Osano and J. P. Uzan (2010), T. Biswas, A. Notari and W. Valkenburg (2010)) • Fundamentaly Modified Cosmic Topology or Geometry (rotating universe, horizon scale compact dimension, non-commutative geometry etc)(J. P. Luminet (2008), P. Bielewicz and A. Riazuelo (2008), E. Akofor, A. P. Balachandran, S. G. Jo, A. Joseph,B. A. Qureshi (2008), T. S. Koivisto, D. F. Mota, M. Quartin and T. G. Zlosnik (2010)) • Statistically Anisotropic Primordial Perturbations (eg vector field inflation)(A. R. Pullen and M. Kamionkowski (2007), L. Ackerman, S. M. Carroll and M. B. Wise (2007), K. Dimopoulos, M. Karciauskas, D. H. Lyth and Y. Ro-driguez (2009)) • Horizon Scale Primordial Magnetic Field.(T. Kahniashvili, G. Lavrelashvili and B. Ratra (2008), L. Campanelli (2009))

  27. Cluster Halo Profiles Navarro, Frenk, White, Ap.J., 463, 563, 1996 NFW profile: From S. Basilakos, J.C. Bueno-Sanchez and LP, PRD, 80, 043530, 2009, 0908.1333. ΛCDM prediction: The predicted concentration parameter cvir is significantly smaller than the observed. Data from:

  28. Cluster Halo Profiles Navarro, Frenk, White, Ap.J., 463, 563, 1996 From S. Basilakos, J.C. Bueno-Sanchez and LP, PRD, 80, 043530, 2009, 0908.1333. NFW profile: clustered dark energy Clustered Dark Energy can produce more concentrated halo profiles Data from:

  29. ________ ___ ______ ____________ Q: Is there a model with a similar expansion rate as ΛCDM but with significant clustering of dark energy? A: Yes. This naturally occurs in Scalar-Tensor cosmologies due to the direct coupling of the scalar field perturbations to matter induced curvature perturbations J. C. Bueno-Sanchez, LP, Phys.Rev.D81:103505,2010, (arxiv: 1002.2042)

  30. _____ _____ _______ Rescale Φ Units: General Relativity:

  31. _________ ___________ ________ Flat FRW metric: Generalized Friedman equations: These terms allow for superacceleration(phantom divide crossing) Curvature (matter) drives evolution of Φ (dark energy) and of its perturbations.

  32. _________ ___ __________ • Advantages: • Natural generalizations of GR (superstring dilaton, Kaluza-Klein theories) • General theories (f(R) and Brans-Dicke theories consist a special case of ST) • Potential for Resolution of Coincidence Problem • Natural Super-acceleration (weff<-1) • Amplified Dark Energy Perturbations Constraints: Solar System Cosmology

  33. __ _______ _______ Oscillations (due to coupling to ρm ) and non-trivial evolution

  34. ________ _______ __ ____ Effective Equation of State: Scalar-Tensor (λf=5) weff Minimal Coupling (λf=0) z

  35. ____________ __ _____ ______ Perturbed FRW metric (Newtonian gauge): J. C. Bueno-Sanchez, LP, Phys.Rev.D81:103505,2010, (arxiv: 1002.2042) Anticorrelation No suppression on small scales!

  36. ____________ __ _____ ______ Sub-Hubble GR scales Suppressed fluctuations on small scales! (as in minimally coupled quintessence)

  37. ________ ________ Scale Dependence of Dark Energy/Dark Matter Perturbations Minimal Coupling (F=1) Non-Minimal Coupling (F=1-λfΦ2) Dramatic (105) Amplification on sub-Hubble scales!

  38. Summary Early hints for deviation from the cosmological principle and statistical isotropy are being accumulated. This appears to be one of the most likely directions which may lead to new fundamental physics in the coming years. The amplified dark energy clustering properties that emerge in Scalar-Tensor cosmology may help resolve the puzzles related to amplified bulk flows and cluster halo profiles.

  39. ________ ________ Scale Dependence of Dark Matter Perturbations Minimal Coupling (F=1) Non-Minimal Coupling (F=1-λfΦ2) 10 % Amplification of matter perturbations on sub-Hubble scales!

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