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The next decade of weak lensing science

The next decade of weak lensing science. Rachel Mandelbaum , CMU. Cosmology. A homogeneous and isotropic universe Spatially flat and expanding (accelerating!) General Relativity:. Function of the metric (defining space-time behavior).

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The next decade of weak lensing science

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  1. The next decade of weak lensing science Rachel Mandelbaum, CMU

  2. Cosmology • A homogeneous and isotropic universe • Spatially flat and expanding (accelerating!) • General Relativity: Function of the metric (defining space-time behavior) Stress-energy tensor describes matter/energy contents R. Mandelbaum

  3. ????? ?? Name for model: CDM Picture credits: NASA/WMAP science team R. Mandelbaum

  4. Quantum fluctuations seed small (/ ~10-5) inhomogeneities… …which are imprinted in CMB... Matter domination: growth through gravitational instability R. Mandelbaum Picture credits: NASA/WMAP science team

  5. Two classes of cosmological probes Geometric: SN1A, BAO Growth of structure R. Mandelbaum Picture credits: ESA/ESO (left), MPE/V. Springel (right)

  6. Summary: current status in cosmology ? • An observationally supported big picture • BUT… many fundamental uncertainties • nature of DM and DE, • nature of inflationary era, • GR confirmation on many scales. R. Mandelbaum

  7. A key problem: • The universe is dominated by dark contents. • But…we cannot directly observe those contents using a telescope. R. Mandelbaum

  8. Gravitational lensing Lensing deflection of light:

  9. Sensitive to all matter along line of sight, including dark matter! R. Mandelbaum

  10. Weak lensing Unlensed Lensed R. Mandelbaum

  11. Galaxies aren’t really round NASA, ESA, S. Beckwith (STScI) and the HUDF Team

  12. Cosmic shear Shape autocorrelation statistical map of large-scale structure R. Mandelbaum

  13. Galaxy-galaxy lensing • Stacked lens galaxy position – source galaxy shape cross-correlation • Revealstotalaverage matter distribution around lens galaxies or cluster (galaxy-mass correlation) R. Mandelbaum

  14. State of the field of weak lensing R. Mandelbaum

  15. Subaru telescope • 8.2 meter primary mirror • Mauna Kea • Excellent imaging conditions R. Mandelbaum

  16. Subaru telescope • Many instruments for optical and spectroscopic observations, e.g. Suprime-Cam R. Mandelbaum Miyatake, Takada, RM, et al (2012)

  17. Picture credit: S. Miyazaki R. Mandelbaum

  18. HSC is on the telescope! HSC blog at naoj.org R. Mandelbaum

  19. Looking good! R. Mandelbaum

  20. 3-layer HSC survey • Wide: ~1400 deg2, i<25.8 (grizy) • Weak lensing, z<1.5 galaxy populations • Deep: ~26 deg2, 1 mag deeper, 5 wide+3 NB filters • Ly-α emitters, quasars, deeper galaxy populations, lensingsystematics, … • Ultradeep: 3 deg2, 1 mag deeper, 5 wide+6 NB filters • Supernovae, galaxies to z<7 • Important synergies: CMB (ACT+ACTPol), redshifts (BOSS + assorted other), NIR, u band, … R. Mandelbaum

  21. What has driven this development? • ~8-10 years ago, people started to realize how very powerful cosmic shear is as a probe of dark energy! R. Mandelbaum (LSST science book)

  22. What has driven this development? • ~8-10 years ago, people started to realize how very powerful cosmic shear is as a probe of dark energy! R. Mandelbaum Zhan et al. (2006, 2008)

  23. A reminder • Cosmic shear measures the matter power spectrum • This is easily predicted from theory (modulo small-scale effects) • Contrast: the galaxy power spectrum from redshift surveys – galaxies are a biased tracer of matter Galaxies Density Dark matter halo Position R. Mandelbaum

  24. BUT R. Mandelbaum

  25. This is actually kind of difficult. Cosmic shear is an auto-correlation of shapes: Multiplicative biases are an issue! Coherent additive biases become an additional term! R. Mandelbaum

  26. That’s not the only problem, either. • Intrinsic alignments • Theoretical uncertainties on small scales (e.g. baryonic effects) • Photometric redshift uncertainties R. Mandelbaum

  27. Implications • As datasets grow, our control of systematics must get increasingly better • The past ~3 years have seen a change of perspective within the lensing community: • We should measure cosmic shear • But we should also identify combinations of lensing measurements with other measurements that allow us to calibrate out / marginalize over systematics directly • Use ALL the information available • Minimize the combination of statistical + systematic error! R. Mandelbaum

  28. What data will we have? • The lensing shear field: HSC • The 2d galaxy density field: HSC • (Sometimes) 3d galaxy density field and velocity field, with spectroscopy: BOSS • X-ray (galaxy clusters): XMM • SZ (galaxy clusters), CMB lensing: ACT • Lensing magnification field? (M. White) R. Mandelbaum

  29. Summary of approach to future data: Cross-correlate everything with everything = more information = less sensitivity to observational uncertainties specific to one particular method R. Mandelbaum

  30. What about galaxy-galaxy lensing? • Typically undervalued for cosmology, because it measures gm correlations, not mm • Observationally easier: • Coherent additive shear errors do not contribute at all! (cross-correlation) • Intrinsic alignments: • Don’t enter at all, with robust lens-source separation • If sources are not well behind lenses, they contribute, but in a different way from cosmic shear R. Mandelbaum

  31. Observational quantities • ξgg from galaxy clustering • ρξgm from g-g weak lensing • Infer matter clustering (schematically): Constrain nonlinear matter power spectrum on large scales R. Mandelbaum

  32. Let’s include cosmic shear • Use cosmic shear (mm), galaxy-galaxy lensing (gm), and galaxy clustering (gg) • Dependence on intrinsic alignments, shear systematics: • Different for the two lensing measurements • Joachimi & Bridle 2011, Kirk et al. (2011), Laszlo et al. (2011) showed that the cosmological power is = that of cosmic shear, even when marginalizing over extensive models for systematics! R. Mandelbaum

  33. A concrete example: Lensing + clustering in SDSS DR7 (RM, AnzeSlosar, Tobias Baldauf, UrosSeljak, Christopher Hirata, Reiko Nakajima, Reinabelle Reyes, 2012) R. Mandelbaum

  34. Observational quantities • ξgg from galaxy clustering • ρξgm from g-g weak lensing • Infer matter clustering (schematically): Constrain nonlinear matter power spectrum Cross-correlation coefficient between galaxies, matter R. Mandelbaum

  35. Integration lower limit is the problem Problem: small scales Theoretical uncertainties in Σ (surface density): • Baryonic effects • Cross-correlation ≠ 1 • Cannot remove by avoiding small scale ΔΣ R. Mandelbaum

  36. Solution to small-scale issues • Define “Annular differential surface density” (ADSD): NO dependence on signal below R0! →0 at R0 →ΔΣ at R>>R0 T. Baldauf, R. E. Smith, U. Seljak, RM, 2010, Phys. Rev. D, 81, 3531 RM, U. Seljak, T. Baldauf, R. E. Smith, 2010, MNRAS, 405, 2078 R. Mandelbaum

  37. Example from simulations Using ΔΣ Reconstruction Cross-correlation coeff(rcc) ϒmm Usingϒ, R0=3 Mpc/h R. Mandelbaum

  38. Sensitivity to cosmology Fiducial cosmology: Ωm=0.25 σ8=0.8 ns=1.0 R. Mandelbaum

  39. Results • Lenses: SDSS-I spectroscopic samples: • LRGs, z~0.3, typically 3L*, ~105 • Main, z~0.1, typically L*, 6 × 105 • Sources: 6 × 107 fainter galaxies • Treat samples separately, for sanity checks • Updated treatment of lensingsystematics (RM et al. 2011, Reyes et al. 2011) R. Mandelbaum

  40. Example of current data Stacked data: ~105LRGs (lenses), 70M sources Lensing signal Transverse separation R (Mpc/h) R. Mandelbaum

  41. Lensing data R. Mandelbaum

  42. Clustering data R. Mandelbaum

  43. Actual procedure • Direct fitting: • Nonlinear power spectrum • PT-motivated parametrization of non-linear bias • With these data alone, fitting for σ8, Ωm, and bias, marginalizing over bias and lensing calibration: • σ8 (Ωm/0.25)0.57 = 0.80±0.05 R. Mandelbaum

  44. Non-flat, free wde R. Mandelbaum

  45. Comparison to cosmic shear results • COSMOS (Schrabback et al. 2010), 11% σ8 constraint • CFHTLenS(Kilbinger et al. 2012), 4% σ8 constraint • Typical z~1, 0.8 vs. 0.25 for SDSS • SDSS gives better control of redshiftsystematics Results shown here establish SDSS among the most competitive extant surveys for weak lensing cosmology! R. Mandelbaum

  46. Near future improvements BOSS + HSC: Less dominated by lensing statistical errors R. Mandelbaum

  47. But that’s not all… Small-scale lensing profiles reveal galaxy DM halos Transverse separation R (Mpc/h) R. Mandelbaum

  48. Example of how we can use this: FoG • Small-scale effect due to velocity dispersion within halos • Cannot simply eliminate by using only individual halos, unless chosen “center” is really at center White et al. (2011): contours of 3d correlation function R. Mandelbaum

  49. Idea for how to calibrate out FoG • Hikage, Takada, Spergel (2011) • Rely on spectroscopic / photometric survey synergy • Select halos, then compare several measurements for different choices of halo centers: • Redshift-space power spectra • Galaxy-galaxy lensing (matter distribution) • Photometric galaxy cross-correlation R. Mandelbaum

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