1. Probing dark matter halos at redshifts z=[1,3] with lensing magnification L. Van Waerbeke With H. Hildebrandt (Leiden) J. Ford (UBC) M. Milkeraitis (UBC) CIfAR Lake Louise Feb 18-21 2010

2. Why are high redshift DM halos interesting? -N(M,z) is a strong probe of cosmology/DE (cf Gill’s talk) -DM halo shape/profile can provide a test of CDM -make an observational connection between galaxy/cluster formation and DM environment

4. Lensing studies are exclusively interested in shear     )

5. Limitations/difficulties with the shear: -requires very accurate Point Spread Function correction to measure the Shape of distant galaxies -this limits how small source galaxies can be, i.e. how far they can be. In practice there is little hope to precise measurement above z source ~1 -this limits the maximum redshift one can probe the dark matter distribution, i.e. z lens ~0.5-1.

6. What is cosmic magnification?

7. magnification depends on shear and convergence: The number of lensed objects at magnitude m: Where  is the number count slope.

8. 2D number density contrast at sky position  :   d 

9. Convergence profile of A1689 (Taylor et al 1998) Magnification profile in A1689 (Taylor et al 1998) Two sources of noise: -Statistical (Poisson) -Clustering of bck sources

10. Advantages of magnification: -does NOT requires Point Spread Function correction to measure the photometry. -there is NO limits how small source galaxies can be, i.e. how far they can be. -there is NO limits on the maximum redshift one can probe the dark matter distribution as long you can find enough sources behind. Can we probe redshift z=[1,3] dark matter halos with optical data?

11. We looked at LBGs in CFHTLS deep data with the dropout technique (cf Ellis’s talk). Redshift z=3 LBG Spectral energy distribution

12. LBG counts in CFHTLS Deep (4 sq.deg. Deep MEGACAM) is used to calibrate the slope  Hildebrandt et al. 2009

13. ug dropout with z=[0.5,1] foregrounds Hildebrandt et al 2009 Magnification correlation fct

14. DM halo magnification: proof of concept on 15 SpARCS high-z clusters (PI: Wilson)

15. Expected cumulative number density n(>z) of halos for a250 sq. deg. Survey, CFHTLS depth (i<24.5) (taken from MS,  8 adjusted): (for a 250 sq.deg. FOV)

16. 1-5 10 13 Mo >3 10 14 Mo 1-2 10 14 Mo Stacked signal for Halos at z>1 Full error from CFHTLSW LBGs

17. Conclusions: - new window on DM studies: magnification can probe dark matter halos in a redsfhit range inaccessible by shear measurements. -complementarity: combined with shear measurement for redshift z<1 clusters it can constrain intrinsic alignment. -can be used to get the average mass from baryonic proxy (SZ, Xray, 21cm) -much easier technically than shear: we already know it can be done from ground based and balloon observatories.

18. Caveats: -loss in SNR is ~5, but gain in sources number density is ~2. Net SNR loss is ~2-3. -dust absorption. Small effect but detectable at the percent level (Menard 2009). Multiwavelength data can actually measure both! -Eddington bias -need to find targets (need a cluster proxy, not necessarily mass). Easy for low mass and high mass DM halos. Not easy for low cluster mass/groups.