1. L. Perivolaropoulos http://leandros.physics.uoi.gr Department of Physics University of Ioannina Open page

2. 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. 3 Luminosity Distance (standard candles: SnIa,GRB): Angular Diameter Distance (standard rulers: CMB sound horizon, clusters): SnIa Obs GRB flat Direct Probes of H(z): Significantly less accurate probes S. Basilakos, LP, MBRAS,391, 411, 2008 arXiv:0805.0875

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

5. 5 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 Q1: What is the Figure of Merit of each dataset?

6. 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. SNLS ESSENCE GOLD06 UNION CONSTITUTION WMAP5+SDSS5 WMAP5+SDSS7 UNION2

7. 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. SDSS5 SDSS7 Percival et. al. SNLS G06 E SDSS MLCS2k2 U1 C U2 SDSS SALTII

8. 8 ESSENCE+SNLS+HST data SNLS 1yr data Trajectories of Best Fit Parameter Point The trajectories of SNLS, Union2 and Constitution are clearly closer to ΛCDM for most values of Ω 0m Gold06 is the furthest from ΛCDM for most values of Ω 0m Q: What about the σ-distance (d σ ) from ΛCDM? Ω 0m =0.24

9. 9 ESSENCE+SNLS+HST data Trajectories of Best Fit Parameter Point Consistency with ΛCDM Ranking:

10. 10 Consistency with Standard Rulers Ranking: ESSENCE+SNLS+HST Trajectories of Best Fit Parameter Point

11. Large Scale Velocity Flows - Predicted: On scale larger than 50 h -1 Mpc Dipole Flows of 110km/sec or less. - Observed: Dipole Flows of more than 400km/sec on scales 50 h -1 Mpc or larger. - Probability of Consistency: 1% Cluster and Galaxy Halo Profiles: - Predicted: Shallow, low-concentration mass profiles - Observed: Highly concentrated, dense halos - Probability of Consistency: 3-5% From LP, 0811.4684, I. Antoniou, LP 1007.4347 R. Watkins et. al., 0809.4041 Broadhurst et. al.,ApJ 685, L5, 2008, 0805.2617, S. Basilakos, J.C. Bueno Sanchez, LP., 0908.1333, PRD, 80, 043530, 2009. 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% 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 M. Tegmark et. al., PRD 68, 123523 (2003), astro-ph/0302496

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

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

14. Z=0 Z=1.4 North Galactic Hemisphere South Galactic Hemisphere

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

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)=(306 o,15 o )

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

18. Construct Simulated Isotropic Dataset: 2. Keep same directions, redshifts and σ μi as real Union2 data 3. Replace real distance modulus μ obs (z i ) by gaussian random distance moduli with mean and standard deviation σ μi. 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. 1. Compare a simulated isotropic dataset with the real Union2 dataset by splitting each dataset into hemisphere pairs using 10 random directions. 3. Repeat this comparison experiment 40 times with different simulated isotropic data and axes each time. 2. Find the maximum levels of anisotropy (Union2) and (Isotropic) and compare them.

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

21. There is a direction of maximum anisotropy in the Union2 data (l,b)=(306 o,15 o ). 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. 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. ΔΩ/Ω=0.43 ΔΩ/Ω=-0.43 ΔΩ/Ω=0.43 ΔΩ/Ω=-0.43 Real Data Test Axes Simulated Data Test Axes

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

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

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

26. 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. 27 NFW profile: ΛCDM prediction: The predicted concentration parameter c vir is significantly smaller than the observed. From S. Basilakos, J.C. Bueno-Sanchez and LP, PRD, 80, 043530, 2009, 0908.1333. Data from: Navarro, Frenk, White, Ap.J., 463, 563, 1996

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

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 ΦUnits: General Relativity:

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

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 (w eff <-1) Amplified Dark Energy Perturbations Constraints: Solar System Cosmology

33. Oscillations (due to coupling to ρ m ) and non-trivial evolution

34. Effective Equation of State: Scalar-Tensor (λ f =5) Minimal Coupling (λ f =0) w eff z

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

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

37. Scale Dependence of Dark Energy/Dark Matter Perturbations Minimal Coupling (F=1)Non-Minimal Coupling (F=1-λ f Φ 2 ) Dramatic (10 5 ) Amplification on sub-Hubble scales!

38. 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-λ f Φ 2 ) 10 % Amplification of matter perturbations on sub-Hubble scales!