Strong Lensing by Clusters of Galaxies

1. Strong Lensing by Clusters of Galaxies Joseph F. Hennawi UC Berkeley Fermilab June 14, 2007

2. Outline • Cosmology with Cluster Lenses • Giant Arc Abundance • Suggestive Anomalies • SDSS Giant Arc Survey

3. Suspects Paul Bode (Princeton) Neal Dalal (IAS) Jeremiah Ostriker (Princeton) Ben Koester (Chicago) Priya Natarajan (Yale) Håkon Dahle (University of Oslo ) Masamune Oguri (Princeton) Mike Gladders (Chicago)

4. Cosmology with Cluster Lenses • Why is Strong Lensing by Clusters Interesting? • Natural Gravitational Telescopes magnify high-z galaxies • Measure Cosmological Parameters?? • Study the small scale distribution of dark matter in clusters. • Galaxies don’t get much bigger than 1013 M. So interior to the Einstein radii of the widest arcs, the M/L ratio is > 10: ;

5. N(>r) Number of Arcs r [arcsecs] 6,000,000 Question: Can we neglect dissipative physics? YES: For large angle arcs, observables predictable ab initio NO: Must simulate effects of dissipation on DM distribution. Can we Neglect the Baryons? • For giant arcs with  > 20”, the mass enclosed by the Einstein radius is dominated by dark matter. • Effect of Cooling and BCG formation on DM: • DM adiabatically contracts and density profile steepens (increase lensing) • DM halo becomes more circular (decrease lensing) • Recent work claims factor of ~ 2 increase (Rozo et al. 2006, Puchwein et al. 2006), but sims suffer from severe overcooling.

6. Cluster Lensing Statistics Giant Arc Abundance(talks by Horesh, Gilbank and Scarpine’s poster) • Count number of arcs per deg2. Compare to N-body sims. Absolute counts vulnerable to many systematics (next slide). • Need deep ground based images of clusters over > 1000 deg2 (there is about 1 arc per 40 deg2). • Measure relative distribution of lens mass, redshift, or arc angular separation. Much less vulnerable to systematics. Detailed Modeling(see talks by Sharon & Kneib) • Measure lens parameters (concentration, ellipticity, inner profile slope, subhalos). Compare to distributions from simulations. • Requires spaced based imaging. Thus far only handfuls studied. • Strongest constraints when combined with wide field WL. • Dramatic lenses represent atypical clusters. Must quantify this.

7. Giant Arc Abundance Theoretical Uncertainties • Source counts: Need to use real HST images as background source planes (factor ~ 2-3).(See talk by Horesh). • Ray tracing simulations disagree (factor ~ 2 ). • Have simulations converged for rarest objects? Largest sims correspond to area < 100 deg2, for 0 < z < 1 (factor ~ ??). • Baryons/Dissipation effect on DM? (factor ~ 2). • Cosmological parameters (m, 8): WMAP3 (0.24, 0.74) differs from concordance (0.3, 0.9) by factor ~ 6. Observational Uncertainties • Arc detection/Selection Function :“arcs by eye” breaks down near surface brightness limit (factor ~ ??). (See talks by McGinnis, Seidel, Horesh and poster by Scarpine). • Uncertainties in mass limit for snapshot surveys (factor ~ ??).

8. Ray Tracing Simulations • Identify massive cluster halos in cosmological N-body simulation Massive Cluster Lens Plane • Compute surface density. Solve lens equation for mapping from source plane to image plane • Place background sources at random positions in source plane Source Plane Image Plane • Map each source pixel to image plane and identify giant arcs

9. Lens Redshift Distribution • Sims predict ~ 5 z < 0.6 arcs in RCS-1. None found. • Prediction made with params: (m, , 8) = (0.3, 0.7, 0.95). Lower 8, would make high-z clusters much less common?? RCS-1 Are high redshift lenses over-represented? Simulated Hennawi, Dalal, Bode, Ostriker (2007) Comparison of RCS-1 to Simulation Predictions

10. Predicted Concentration Distribution All Clusters dP/dcNFW Lensing Clusters 3 best studied lenses cNFW = 13.7! cNFW Hennawi, Dalal, Bode, Ostriker (2007) Anomalous Concentrations? Abell 1689: ~ 100 images of ~ 30 lensed sources Broadhurst et al. (2005) • Two other high concentration clusters using same technique: • CL0024+1654, cNFW = 26.2! (Kneib et al. 2003) • MS2137-2353 cNFW =14.6 (Gavazzi et al. 2003). • But see Limousin et al. (2007) who found cNFW = 9.5 for Abell 1689. • Less than 2% of lenses should have concentrations this high. Why are the 3 best studied systems in the tail of the distribution?

11. SDSS Giant Arc Survey SDSS Cluster Catalog • ~ 10,000 clusters from RCS technique (Gladders et al. 2007) • Largest cluster catalog ever created. • Photo-z’s accurate to dz ~ 0.02 • 8000 deg2 over 0.1 < z < 0.6, ~ 2 (Gpc/h)3 SDSS Sized Hammer • But SDSS imaging is too shallow (g< 22 mag/) and seeing is too poor (FWHM ~ 1.4) to find substantial #’s of arcs. • Solution: Snapshot imaging survey of ~ 300 most massive clusters using 2-4m telescopes with good image quality. • Low redshift complement to high-z surveys such as RCS. • Probe ~ 40 times larger volume than any previous arc survey.

12. Survey Telescopes UH 2.2m NOT 2.5m telescope • g < 25.7 in 10 mins • median seeing = 0.65” WIYN 3.5m Telescope • g < 25.7 in 10 mins • median seeing = 0.7” UH 88-inch telescope • V < 26.9 in 30 mins • median seeing = 0.6”

13. New Cluster Lenses Shallow SDSS gri composite Deep WIYN gri composite 30” Cluster photo - z = 0.50 Hennawi et al. (2006)

14. New Cluster Lenses Shallow SDSS gri composite Deep WIYN gri composite Counter Image? 30” Cluster z = 0.65 ; Arc z = 1.14 (spectra from Magellan) Hennawi et al. (2006)

15. New Cluster Lenses Hennawi, et al. (2006)

16. Survey Status • Nearly 300 clusters imaged thus far, of which ~ 160 have sub-arcsecond image quality. • About 30 new cluster lenses discovered, including several dramatic “poster child” systems. • Several high surface brightness cB58-ish arc candidates. • Survey about half complete. 17 nights scheduled next semester. • The bright arcs we discover are ideally suited for spectroscopic follow-up. • Arc spectroscopy from Magellan and (hopefully) Gemini. • Weak lensing underway at Subaru 8m and NOT 2.5m.

17. Conclusions/Future Work • Cluster lensing is a powerful probe of the dark matter distribution on ~ 100 kpc/h scales. • Currently, comparison of giant arc abundance to theory is probably only believable to factor ~ 10. • Large statistical samples of lenses required to address suggestive differences between observations and CDM. • Future Work: • Study effects of baryons on DM. • Improve accuracy of ray tracing simulations. • End to end simulation pipelines that look like the data. • Automate arc detection and quantify selection functions. • Detailed mass modeling of new lenses discovered. Will require follow-up with HST, WL, and spectroscopy.

18. Biases in Lensing Selected Samples With a sample of well studied lensing clusters we can measure distributions of cluster properties. However lenses are biased with respect to . . . . Concentration Mass [c/c(M)]1/2 = 1.18 M1/2 = 4.5  1014 Mvir c/c(M) Substructure Orientation [Msub]1/2 = 0.045 [Msub]1/2 = 0.041 q2  lower third q2  middle third q2 upper third |cos|1/2 = 0.50 |cos|1/2 = 0.67 Msub |cos|

19. Solid: EMSS Dashed: Simulations N(>r) Number of Arcs r [arcsecs] Comparison of Arc Surveys to Ray Trace Predictions Dalal, Holder, & Hennawi (2004) Giant Arc Abundance • EMSS: 8 of 38 clusters with LX > 2  1044 ergs/s show giant arcs. • Extrapolating gives ~ 900 over full sky. • Ray tracing sims + HDF galaxy counts predicts ~ 1000 • NO GIANT ARC PROBLEM! • Previous claim of order of magnitude discrepancy incorrectly extrapolated EMSS and used lower source density

20. Quasars Multiply Imaged by Clusters • Predict ~ 2 lenses with  > 10” in current (~ 4000 deg2) sample • Consistent with discovery of quad lens SDSS 1004 SDSS Spectroscopic Quasars SDSS Photometric Quasars • Predict ~ 8 lenses with  > 10” in current (~ 7000 deg2) sample • ~ 1 should have  > 30” • ~ 1 will have zs ~ 4 Hennawi et al. (2005) in prep

21. Analog Halos Simulated Spherical No Substructure Triaxial

22. Analog Halos Source plane: zs = 2.0; Lens Plane: zd = 0.41 • Replace each halo with analog halo. Ray trace and compare number of arcs to original simulated clusters • Substructure identified by FOF algorithm with b= 0.05 • Triaxiality boosts cross sections by factor 4-25 compared to spherical • Analytical models under predict arc abundance by • up to 50 for spherical models • up to 2 for triaxial models • Halo Triaxiality much more important than projections of substructure onto small radii N(>) Number of Arcs Hennawi et al. (2005) in prep

23. Cluster Lenses in the SDSS Multiply Imaged Quasars Giant Arcs ARC 3.5m WIYN 3.5m SDSS 2.5m UH 2.2m • SDSS quasar samples • Spectro: 50,000 quasars -- 4000 deg2 • Photo: 400,000 quasars -- 7000 deg2 • Search for companions around quasars with similar colors • Follow up spectroscopy (ARC 3.5m) required because of fiber collisions Jim Gunn Apache Point Observatory • SDSS cluster sample • Richness selected clusters out to z < 0.6 -- 7000 deg2 or ~ Gpc3 • Photo-z’s good to within dz = 0.02 • Deep imaging (g < 26) of richest clusters on 4m class imagers • Arc redshifts from Magellan and MMT • HST imaging of lenses discovered?

24. Counter Image? SDSS Arcs • Brightest arc (g ~ 22 )  = 11” • Discovered by visual inspection of SDSS southern coadd data (r < 24) • Magellan spectroscopy • BCG galaxy @ z = 0.65 • Arc A @ z = 1.14 • Preliminary models prefer the BCG to be off center? 30” Extreme example of minor axis cusp? Or instead, is BCG off-center? WIYN gri composite - seeing ~ 0.6” Lin et al. (2005) in preparation

25. SDSS Arcs A 30” B WIYN g + i composite - seeing ~ 1.2” • Arcs at  = 35” and  = 12” • Abell cluster @ z = 0.28. LX = 8.7  1044 (NORAS) • Models prefer high ellipticities (q < 0.5) for inner slopes typical of CDM halos (n ~ 0.5) Hennawi et al. (2005) in preparation

26. z=1.734 B A G1 D C The Widest Lensed Quasar Largest Splitting  = 14.6”! Fifth Image? ACS Original ACS Subtracted Inada et al. (2003) Oguri et al. (2004) Inada et al. (2005) HST ACS HST NICMOS