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Cross-correlation of WMAP 3 rd year and SDSS DR4: new evidence for dark energy

Cross-correlation of WMAP 3 rd year and SDSS DR4: new evidence for dark energy. Anna Cabre, Enrique Gaztañaga, Pablo Fosalba, Marc Manera, Francisco Castander astro-ph/0603690. Motivation : Obtain dark energy from the ISW effect crosscorrelating CMB and LSS Summary

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Cross-correlation of WMAP 3 rd year and SDSS DR4: new evidence for dark energy

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  1. Cross-correlation of WMAP 3rd year and SDSS DR4: new evidence for dark energy Anna Cabre, Enrique Gaztañaga, Pablo Fosalba, Marc Manera, Francisco Castander astro-ph/0603690

  2. Motivation: Obtain dark energy from the ISW effect crosscorrelating CMB and LSS Summary Integrated Sachs Wolfe effect background Large scale structure data and CMB data Analysis, errors... Results Conclusions and Future

  3. t1 t2 t3 Integrated Sachs Wolfe effect ISW is the gravitational redshift that photons coming from CMB undergo when they fall in a deep potential and come out from a smoother one. This change in potential can be created by curvature or by dark energy. Assuming that the universe is flat (from WMAP results), ISW indicates the existence of dark energy.

  4. How to detect ISW? Temperature fluctuations created by ISW are difficult to see in power spectrum, and the results seem to supress that Alternative: Cross correlating CMB temperature with potential traced by LSS (Crittenden & Turok 1996) Wayne Hu

  5. CMB data LSS data SDSS DR4 WMAP 3rd year -5200 sq deg (13% sky) -Selection of subsamples with different redshift distribution -3 magnitude subsamples with r=18-19, r=19-20 and r=20-21 with 106 – 107 galaxies -high redshift Luminous Red Galaxy (Eisentein et al. 2001) -Mask avoids holes, trails, bleeding, bright stars and seeing>1.8 V-band (61 Hz) HEALPix tessellation Kp0 mask

  6. ISW in equations... Limber approximation

  7. wGG(q) ab2s82f(Wm) wTG(q) ab s82g(Wm) bs8from GG x s8from WMAP TG factor b s82 fix

  8. Autocorrelation results (galaxy-galaxy) Slices with more S/N bs8 20-21 0.90-0.96 LRG 1.02-1.12 + bias +deep +magnitude

  9. GG fitting for slice 20-21 GG fitting for slice high redshift

  10. Covariance matrix Redshift selection function Jack-knife errors LRG 20-21 Singular Value Decomposition (SVD) c2distribution r=20-21 zc=0 z0=0.2 zm=0.3 LRG zc=0.37 z0=0.45 zm=0.5

  11. r=20-21 S/N=3.6 LRG S/N=3. S/N total=4.7

  12. signal to noise picture... Covariance for MC Covariance for JK Covarianca matriu per DR4 2021 o 8888 Covarianca matriu simulacions MC

  13. For a flat universe, with bias, sigma8 and w=-1 fix.... dark energy must be... 68% 0.80-0.85 95% 0.77-0.86

  14. Can we obtain information about w? Contour: 1, 2 sigma 1 dof

  15. Errors JK, reliable?? CORRELACIÓ GG CORRELACIÓ TG 76 JK 38 JK 76 JK 38 JK

  16. 1000 simulations of galaxies and temperature fluctuations with ISW

  17. Conclusions: ·There is no change of the ISW detection from WMAP1 to WMAP3 ·To improve we need to sample a larger area (SDSS DR5) or larger volume (DES) and more slices...

  18. Dark Energy Survey predictions... ·GG prefers higher omega matter than TG, signal TG too high.. why? ·We can not break the degeneracy between WL and w with ISW and fsky=0.13

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