How accurate do we need to be?

1. How accurate do we need to be?

2. The Forward Process During observation, a galaxy image is convolved with a PSF: making it bigger and changing its ellipticity The process of shear measurement The Inverse… During data analysis, shear measurement methods seek to undo these changes to recover the true shape …problem An imperfect shear measurement method may not measure (any of) these quantities well. It instead obtains an inaccurate measurement, denoted by a hat.

3. STEP Obtain imperfect shear measurements where Previous figures of merit GREAT10 galaxy challenge GREAT10 star challenge Generically expect things to be easier for large galaxies G08 But can’t compare true against measured shear from images containing a spatially varying signal, and still average over intrinsic galaxy shapes.

4. From imperfect shear measurements with constant m and c form 2-point correlation function Quantifying shear measurement accuracy from a power spectrum Multiplicative systematics Fourier transform into power spectrum where Additive systematics But if systematics vary spatially, where

5. To ensure bias/error<1 (Kitching et al. 2010) Requirement on multiplicative systematics Multiplicative systematics Can break this down into separate requirements on accuracy of PSF modelling (G10star) and galaxy shape measurement (G10galaxy). Constraints on dark energy parameter w

6. From imperfect shear measurements with constant m and c form 2-point correlation function Quantifying shear measurement accuracy from a power spectrum Fourier transform into power spectrum where Additive scatter systematics But if systematics vary spatially, where G10 “ ”

7. To ensure bias/error<1 (Amara & Refregier 2009) But this depends strongly on l-range, z-binning. Req’mt on additive scatter systematics Can break this down into separate requirements on accuracy of PSF modelling (G10star) and galaxy shape measurement (G10galaxy).

8. STEP Simple & direct to useful quantities Cannot be used with variable shear field where Single number Bigger is better Only really sensitive to c Cannot be used with variable shear field G08 Possible figures of merit G10 Single number sensitive to both m and c A(l) and M(l) can vary with scale Systematics prob’ly positive definite anyway Ugly absolute value not really a variance Normalisation depends on assumed l-range denominator better? and similar

9. What bias/error is enough?

10. What bias/error is enough?