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Www.great08challenge.infowww.cosmocoffee.info 1/19 PASCAL Challenge PASCAL Workshop, Bled 28 Jan 2008 Sarah Bridle (UCL) on behalf of the GREAT08 Team.

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Presentation on theme: "Www.great08challenge.infowww.cosmocoffee.info 1/19 PASCAL Challenge PASCAL Workshop, Bled 28 Jan 2008 Sarah Bridle (UCL) on behalf of the GREAT08 Team."— Presentation transcript:

1 1/19 PASCAL Challenge PASCAL Workshop, Bled 28 Jan 2008 Sarah Bridle (UCL) on behalf of the GREAT08 Team

2 2/19 …tbc

3 3/19 Contents of our Universe 70% Dark Energy 25% Dark Matter 5% Baryonic Matter

4 4/19 Gravitational Lensing Light from a distant galaxy is bent around a mass

5 5/19 Gravitational Lensing Galaxies seen through dark matter distribution analogous to Streetlamps seen through your bathroom window

6 6/19

7 7/19 Cosmic Lensing Real data: g i ~0.03 g i ~0.2

8 8/19 Atmosphere and Telescope Convolution with kernel Real data: Kernel size ~ Galaxy size

9 9/19 Pixelisation Sum light in each square Real data: Pixel size ~ Kernel size /2

10 10/19 Noise Mostly Poisson. Some Gaussian and bad pixels. Uncertainty on total light ~ 5 per cent

11 11/19

12 12/19 Typical star Used for finding Convolution kernel Typical galaxy used for cosmic shear analysis

13 13/19

14 14/19 GREAT08 Data One galaxy per image Kernel is given One shear per set Noise is Poisson ~ images divided into ~10 sets ~ images Divided into ~1000 sets

15 15/19 GREAT08 Results You submit g 1, g 2 for each set of images

16 16/19 GREAT09 and Beyond Kernel is not given (just kernel images) Galaxies with more complicated shapes Kernel is more realistic Many objects in each image Correlated noise Poisson + Gaussian noise + bad pixels Shear is different for each galaxy Kernel is not the same for every galaxy Cosmic rays, satellite tracks, saturated stars Multiple exposures Pixels not exactly square or on a grid

17 17/19 GREAT08 Timeline ~8 Feb 2008 GREAT08 Handbook public Feb 2008 Produce simulations Mar 2008 Internal analysis of simulations ~ May 2008 Release simulations –Leaderboard starts containing best internal results ~ Nov 2008 Competition deadline ~ Dec 2008 Workshop; Release final report –Input shears public

18 18/19 GREAT08 Summary 100 million images 1 galaxy per image De-noise, de-convolve, average shear g i ~ 0.03 to accuracy Q~1000 Win!

19 19/19 cosmocoffee.info

20 20/19 GREAT08

21 21/19 Understanding Cosmology

22 22/19 GREAT08 Summary 100 million images 1 galaxy per image De-noise, de-convolve, average shear g i ~0.03 to accuracy Q~1000 Win! 18/18

23 23/19 Questions for you Is there too much astronomy to learn? –Yes –No Is timeline (~6 months) right? –Too short –Fine –Too long Is this potentially on your research agenda? –No –Maybe –Yes

24 24/19

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