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Weak Lensing Tomography

Weak Lensing Tomography. Sarah Bridle University College London. versus. 3d vs 2d (tomography) Non-Gaussian -> higher order statistics Low redshift -> dark energy. Weak Lensing Tomography. In principle (perfect zs) Hu 1999 astro-ph/9904153 Photometric redshifts

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Weak Lensing Tomography

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  1. Weak Lensing Tomography Sarah Bridle University College London

  2. versus • 3d vs 2d (tomography) • Non-Gaussian -> higher order statistics • Low redshift -> dark energy

  3. Weak Lensing Tomography • In principle (perfect zs) Hu 1999 astro-ph/9904153 • Photometric redshifts Csabai et al. astro-ph/0211080 • Effect of photometric redshift uncertainties Ma, Hu & Huterer astro-ph/0506614 • Intrinsic alignments • Shear calibration

  4. 1. In principle (perfect zs) • Qualitative overview • Lensing efficiency and power spectrum • Dependence on cosmology • Power spectrum uncertainties • Cosmological parameter constraints

  5. 1. In principle (perfect zs) Core reference • Hu 1999 astro-ph/9904153 See also • Refregier et al astro-ph/0304419 • Takada & Jain astro-ph/0310125

  6. Cosmic shear two point tomography  

  7. Cosmic shear two point tomography  

  8. Cosmic shear two point tomography q  

  9. Cosmic shear two point tomography q

  10. (Hu 1999)

  11. (Hu 1999)

  12. (Hu 1999) Lensing efficiency Equivalently: gi(zl) = ∫zl ni(zs) Dl Dls / Ds dzs i.e. g is just the weighted Dl Dls / Ds

  13. (Hu 1999) Can you sketch g1(z) and g2(z)? gi(z) = ∫ zs ni(zs) Dl Dls / Ds dzs

  14. Lensing efficiency for source plane?

  15. (Hu 1999)

  16. Sensitivity in each z bin

  17. NOT

  18. (Hu 1999) Why is g for bin 2 higher? • More structure along line of sight • Distances are larger gi(zd) = ∫ zs1 ni(zs) Dd Dds / Ds dzs

  19. * *

  20. (Hu 1999) Lensing power spectrum

  21. (Hu 1999) Lensing power spectrum Equivalently: Pii(l) = ∫ gi(zl)2 P(l/Dl,z) dDl/Dl2 i.e. matter power spectrum at each z, weighted by square of lensing efficiency

  22. (Hu 1999)

  23. (Hu 1999) Measurement uncertainties • <2int>1/2 = rms shear (intrinsic + photon noise) • ni = number of galaxies per steradian in bin i Cosmic Variance Observational noise

  24. (Hu 1999)

  25. Sensitivity in each z bin

  26. NOT

  27. (Hu 1999)

  28. Dependence on cosmology Refregier et al SNAP3 A. m = 0.35 w=-1 B. m = 0.30 w=-0.7 ? ?

  29. Approximate dependence • Increase 8→A. P↓ B. P↑ • Increase zs →A. P↓ B. P↑ • Increase m →A. P↓ B. P↑ • Increase DE (K=0) →A. P↓ B. P↑ • Increase w →A. P↓ B. P↑ Huterer et al

  30. Effect of increasing w on P • Distance to z • A. Decreases B. Increases

  31. Fainter Accelerating m =1, no DE Decelerating (m =1, DE=0) == (m = 0.3, DE = 0.7, wDE=0) Perlmutter et al.1998 Further away

  32. w=-1 Fainter, further EdS OR w=0 Brighter, closer Perlmutter et al.1998

  33. Effect of increasing w on P • Distance to z • A. Decreases B. Increases • When decrease distance, lensing effect decreases • Dark energy dominates • A. Earlier B. Later

  34. Effect of increasing w on P • Distance to z • A. Decreases B. Increases • When decrease distance, lensing decreases • Dark energy dominates • A. Earlier B. Later • Growth of structure • A. Suppressed B. Increased • Lensing A. Increases B. Decreases • Net effects: • Partial cancellation <-> decreased sensitivity • Distance wins

  35. Approximate dependence • Increase 8→A. P↓ B. P↑ • Increase zs →A. P↓ B. P↑ • Increase m →A. P↓ B. P↑ • Increase DE (K=0) →A. P↓ B. P↑ • Increase w →A. P↓ B. P↑ Huterer et al

  36. Approximate dependence • Increase 8→A. P↓ B. P↑ • Increase zs →A. P↓ B. P↑ • Increase m →A. P↓ B. P↑ • Increase DE (K=0) →A. P↓ B. P↑ • Increase w →A. P↓ B. P↑ Huterer et al Note modulus

  37. Which is more important?Distance or growth? Simpson & Bridle

  38. Dependence on cosmology Refregier et al SNAP3 A. m = 0.35 w=-1 B. m = 0.30 w=-0.7 ? ?

  39. (Hu 1999)

  40. (Hu 1999) See Heavens astro-ph/0304151 for full 3D treatment (~infinite # bins)

  41. (Hu 1999)

  42. (Hu 1999) Parameter estimation for z~2

  43. Predict the direction of degeneracy in w versus m plane

  44. Refregier et al SNAP3

  45. (Hu 1999)

  46. Takada & Jain

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