Dark Energy from Cosmic Shear

1. Dark Energy from Cosmic Shear • Dark energy observables • Cosmic shear • Euclid Sarah Bridle, UCL P&A

2. Dark Energy from Cosmic Shear Dark energy observables Cosmic shear Euclid Sarah Bridle, UCL P&A

3. Concordance Model 70% Dark Energy 5% Baryonic Matter 25% Cold Dark Matter

4. The nature of dark energy • Cosmological constant? or • New type of material? • Most generally, describe by pressure: density ratio w = p / r

5. Observational perspective • Try to measure • amount, WDE • nature of dark energy, w • NB. w could be a function of time w(z)

6. Kowalski et al 2008

7. Probes of Dark Energy Cosmic Shear Evolution of dark matter perturbations Angular diameter distance Growth rate of structure Baryon Wiggles Standard ruler Angular diameter distance Supernovae Standard candle Luminosity distance Cluster counts Evolution of dark matter perturbations Angular diameter distance Growth rate of structure CMB Snapshot at ~400,000 yr, viewed from z=0 Angular diameter distance to z~1000 Growth rate of structure (from ISW)

8. Surveys to measure Dark Energy 2020 2005 2010 KIDS Imaging CFHTLS DES LSST Euclid SKA SDSS VISTA JDEM SUBARU Pan-STARRS Euclid Wiggles DES SKA WiggleZ SDSS ATLAS WFMOS FMOS VISTA Supernovae CSP ESSENCE DES LSST CFHTLS JDEM Pan-STARRS Xeus Clusters AMI APEX SPT DES XCS SZA AMIBA ACT JDEM CMB WMAP3 WMAP5 Planck 2005 2010 2020

9. Dark Energy Task Force report astro-ph/0609591

10. Dark Energy from Cosmic Shear Dark energy observables Cosmic shear Euclid Sarah Bridle, UCL P&A

11. Cosmic Shear Tyson et al 2002

13. Cosmic shear tomography  

14. Cosmic shear tomography  

15. Cosmic Shear: Potential systematics Shear measurement Measurement Photometric redshifts Astrophysical Intrinsic alignments Accuracy of predictions Theoretical

16. Cosmic Shear: Potential systematics Shear measurement Photometric redshifts Intrinsic alignments Accuracy of predictions

18. Typical galaxy used for cosmic shear analysis Typical star Used for finding Convolution kernel

19. Gravitational Lensing Galaxies seen through dark matter distribution analogous to Streetlamps seen through your bathroom window

21. Cosmic Lensing gi~0.2 Real data: gi~0.03

22. Atmosphere and Telescope Convolution with kernel Real data: Kernel size ~ Galaxy size

23. Pixelisation Sum light in each square Real data: Pixel size ~ Kernel size /2

24. Noise Mostly Poisson. Some Gaussian and bad pixels. Uncertainty on total light ~ 5 per cent

26. www.great08challenge.info www.great08challenge.info

28. GREAT08 Data 150 000 images divided into 15 sets One galaxy per image Kernel is given One shear per set Noise is Poisson 27 000 000 images Divided into 2700 sets

29. GREAT08 Data Released 4 days ago! 150 000 LowNoise images 3000 000 RealNoise images

30. GREAT08 Active Leaderboard You submit g1, g2 for each set of images

31. GREAT08 Summary • 30 million images • 1 galaxy per image • De-noise, de-convolve, average → shear • gi ~ 0.03 to accuracy 0.0003 → Q~1000 → Win!

32. Cosmic Shear: Potential systematics Shear measurement Photometric redshifts Intrinsic alignments Accuracy of predictions

33. Cosmic shear (2 point function)

34. Cosmic shear Face-on view Gravitationally sheared Gravitationally sheared Lensing by dark matter causes galaxies to appear aligned

35. Intrinsic alignments (II) Croft & Metzler 2000, Heavens et al 2000, Crittenden et al 2001, Catelan et al 2001, Mackey et al, Brown et al 2002, Jing 2002, Hui & Zhang 2002

36. Intrinsic alignments (II) Face-on view Intrinsically Aligned (I) Intrinsically Aligned (I) Tidal stretching causes galaxies to align Adds to cosmic shear signal

37. Intrinsic-shear correlation (GI) Hirata & Seljak 2004 See also Heymans et al 2006, Mandelbaum et al 2006, Hirata et al 2007

38. Intrinsic-shear correlation (GI) Face-on view Gravitationally sheared (G) Intrinsically aligned (I) Galaxies point in opposite directions Partially cancels cosmic shear signal

39. Cosmic shear two point tomography

40. Effect on cosmic shear of changing w by 1% Cosmic Shear Intrinsic Alignments (IA) Normalised to Super-COSMOS Heymans et al 2004

41. Effect on cosmic shear of changing w by 1% If consider only w then IA bias on w is ~10% If marginalise 6 cosmological parameters then IA bias on w is ~100% (+/- 1 !) Intrinsic Alignments (IA)

42. Removal of intrinsic alignmentsusing the redshift dependence

43. Removal of intrinsic alignmentsusing the redshift dependence

44. Removal of intrinsic alignmentsusing the redshift dependence

45. Removal of intrinsic alignments • Intrinsic – intrinsic (II) • Weight down close pairs (King & Schneider 2002, Heymans & Heavens 2003, Takada & White 2004) • Fit parameterized models (King & Schneider 2003) • Shear – intrinsic (GI) • Redshift weighting (Joachimi & Schneider 2008) • Fit parameterized models (King 2005, Bernstein DETF)

46. No Intrinsic Alignments FoM / FoM(specz) Relatively flat (e.g. Hu 1999, Ma, Hu, Huterer 2006, Jain et al 2007, Amara & Refregier 2007 ....) Photoz error σz / (1+z)

47. Reasonable model? (14 IA pars) Very flexible (100 IA pars) FoM / FoM(specz) Photoz error σz / (1+z)

48. A factor of ~3 better photozs required! 0.8 FoM / FoM(specz) 0.02 (1+z) 0.08 (1+z) Photoz error σz / (1+z)

49. Future work on intrinsic alignments • Analytic predictions • Identify physical origin of contributions • Provide fitting functions to compare with data • n-body and hydro simulations • Compare with analytic predictions • Test effectiveness of removal methods • Observational constraints • From other statistics and using spectra For more information see: http://zuserver2.star.ucl.ac.uk/~sarah/ia_ucl_apr08 http://docs.google.com/View?docid=dcrd4nqb_34d9st35cs

50. Dark Energy from Cosmic Shear Dark energy observables Cosmic shear Euclid Sarah Bridle, UCL P&A