Tom Kitching Tom Kitching
Coordination Team: THOMAS KITCHING, ADAM AMARA, SARAH BRIDLE, MANDEEP GILL, CATHERINE HEYMANS, RICHARD MASSEY, BARNABY ROWE, LISA VOIGT Advisory Team: SREE BALAN, GARY BERNSTEIN, MATTHIAS BETHGE, FREDERIC COURBIN, MARC GENTILE, STEFAN HARMELING, ALAN HEAVENS, MICHAEL HIRSCH, RESHAD HOSSEINI, DONNACHA KIRK, KONRAD KUIJKEN, RACHEL MANDELBAUM, BABACK MOGHADDAM, GULDARIYA NURBAEVA, STEPHANE PAULIN-HENRIKSSON, ANAIS RASSAT, JASON RHODES, BERNHARD SCHOLKOPF, TIM SCHRABBACK, JOHN SHAWE-TAYLOR, MARINA SHMAKOVA, ANDY TAYLOR, MALIN VELANDER, LUDOVIC VAN WAERBEKE, DUGAN WITHERICK, DAVID WITTMAN
The Challenge of Measuring Shapes
Typical galaxy used for cosmic shear analysis Typical star Used for finding Convolution kernel Slide from S. Bridle
Cosmic Lensing gi~0.2 Real data: gi~0.03 5/19 Slide from S. Bridle 5
Atmosphere and Telescope Convolution with kernel Real data: Kernel size ~ Galaxy size 6/19 Slide from S. Bridle 6
Sum light in each square Pixelisation Sum light in each square Real data: Pixel size ~ Kernel size /2 7/19 Slide from S. Bridle 7
Mostly Poisson. Some Gaussian and bad pixels. Noise Mostly Poisson. Some Gaussian and bad pixels. Uncertainty on total light ~ 5 per cent 8/19 Slide from S. Bridle 8
Need to measure shear to 10-3
Current Methods
STEP : Shear Testing Programme
Heymans et al., 2006; Massey et al., 2007 & Kitching et al., 2008 KSB
Quality Factor Kitching et al., 2008 (form filling functions); Amara & Refregier (2007)
7 non-lensing participants Q~1000 in some regimes
GREAT08 : Stacking Procedure is Important Average Data Individual Object Statistic Ensemble Statistic Average Estimators Winning Methods (Q=1000) Stacked the Data
STEP 2006 2010 2008
Massey et al. 2008 Fu et al. 2008 Excplitily challenge the winning methods
Bonus Star Challenge: Reconstruct the PSF at non-star positions
Get Ready !
http://www.greatchallenges.info/ GREAT10 Handbook, Kitching et al., 2010
http://www.greatchallenges.info/ “Every time the amount of data increases by a factor of ten we should totally rethink the way we analyze it” Jerome Freidman, Data Mining and Statistics, 1997