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Cluster Lensing Modeling, Physics & Cosmology

Cluster Lensing Modeling, Physics & Cosmology. Jean-Paul KNEIB Laboratoire d’Astrophysique de Marseille, France. Outline. Cluster Lens Modeling Recent results Mass distribution - small to large scales Scaling relations Cosmology [Cosmic Telescope: Hi-z, SN] Prospects.

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Cluster Lensing Modeling, Physics & Cosmology

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  1. Cluster LensingModeling, Physics & Cosmology Jean-Paul KNEIB Laboratoire d’Astrophysique de Marseille, France

  2. Outline • Cluster Lens Modeling • Recent results • Mass distribution - small to large scales • Scaling relations • Cosmology • [Cosmic Telescope: Hi-z, SN] • Prospects

  3. More than 2 decades ago: 1st arc in cluster • 1987 the first giant luminous arc discovered • “Cluster are massive and dense enough to produce strong lensing - they must be filled with dark matter” • Every massive cluster is a lens !!! Abell 370 WFPC2- 1996 CFHT - 1985

  4. Lensing Back to Basics • Basics of lensing: • Large mass over-densities locally deform the Space-Time • A pure geometrical effect, no dependence with photon energy - depends on TOTAL MASS • Lensing by (massive) clusters • Deflection of ~10-50 arcsec • strongly lens many background sources => allow detailed mass reconstruction at different scales: cluster core, substructures, large scales • ~1 SL cluster-lens per ~10 sq. deg: potentially ~2000 to study, Probably only ~200 identified today, nearly 20 with “a good” (SL) mass model Ned Wright

  5. Halo Mass Function Cluster mass function evolves strongly with redshift => cosmological probe (growth factor) 1D WL Stacking 1D WL 2D SL+WL

  6. Massive X-ray selected Cluster Dt~2Gyr Dt~2Gyr Dt~2Gyr X-ray Luminosity LoCuss Hamilton-Morris talk z=0 z=0.2 z=0.5 z~1

  7. HST MACS survey • ~130 MACS clusters (z>0.3), HST, Subaru, Chandra, ground-based spectroscopy follow-up • Find many strong lensing clusters (>50% show SL) • Constrain cluster masses individually and in a statistical way with ultimately possible cosmological implications MACSJ1149.5+2233 Smith et al 2009 MACSJ1206.2-0847 [OII] @ Z=1.48 C B A Ebeling et al 2009

  8. Optically Selected Strong lensing Clusters RCS-1 (Rz survey ~90 deg2), 5 arcs (Gladders et al 2003) found by visual inspection CFHT-LS wide (150 deg2 provides a few arcs in clusters): Cabanac et al 2007 RCS-2 ~830 deg2 provide better stat a few tens SDSS Altogether more than 200 clusters identified with bright arcs (Gladders et al 2009, Oguri et al 2009)

  9. Modeling:Mass Distribution Measurement

  10. Mass Distribution Measurement • How do we measure mass ? • Central mass profile ? => learn about DM and baryon interactions • Large scale mass profile and substructures ? => structure formation paradigm, halo models • Case of mergers => probe nature of DM • Comparison of the distribution of the different components => scaling relations, cluster thermodynamics

  11. SL Cluster Modeling and Errors Constraints: • Multiple images (position, redshift, flux, shape) • Single images with known redshift • Light/X-ray gas distribution Model parameterization • Need to include small scales: galaxy halos (parametric form scaled with light) • Large scale: DM/X-ray gas (parametric form or multi-scale grid) Model optimization • e.g. Bayesian approach (robust errors) • Not a unique solution: “most likely model and errors” • Predict amplification value and errors => cluster as telescopes Jullo et al 2007, Jullo & Kneib 2009 LENSTOOL public software http://www.oamp.fr/cosmology/lenstool

  12. Where is the Matter in A2218? BAD FIT GOOD FIT • Strong Lensingconstraints in Abell 2218: • Mass distribution proportional to the stellar mass produce a BAD FIT to the lensing data • Require large scale mass distribution (cluster DM) • Important difference between DM , Galaxy distribution and X-ray gas (different physics) • But, scaling relation should exists Mass scales with stellar mass MATTER vs GAL. LIGHT MATTER vs. X-Ray Gas Eliasdottir et al. 2009

  13. Deep = Many • Deep HST/ACS multi-band imaging of massive clusters provides MANY multiple images: • A1689 ~40 systems • A1703 ~20 systems • Standard parametric modeling have the RMS image position fit proportional to number of constraints = model too rigid! • Need a change of paradigm in strong lensing mass modeling • Grid approach: Jullo & Kneib 2009 • LensPerfect approach: Coe et al 2008 Limousin et al 2008. Richard et al 2009

  14. The most massive cluster: Abell 1689 • Mass models form different groups w. or w/o weak lensing • Massive spectroscopic surveys (2003-2006) • 41 multiple image systems, 24 with spectro-z with 1.1 < z < 4.9 Broadhurst et al 2005Halkola et al 2007Limousin, et al. 2007 Richard et al. 2007Frye et al 2007Leonard et al 2007Jullo & Kneib 2009 … X KECK/LRIS X VLT/FORS XCFHT/MOS X MAGELLAN /LDSS2 X Littérature

  15. Multi-Scale Grid Based Modeling Jullo & Kneib 2009 More flexible ”multi-scale” model: • hexagonal/triangle padding- to match the natural shape of clusters • Multi-scale: split triangles according to a mass density threshold • Circular mass clump at each grid point: • Truncated isothermal profile with a core • size of the mass clump depends on the grid: r_core =grid-size • Truncation also depends on the grid: r_cut/r_core = 3 • one free parameter for each clump • Add galaxy-scale mass clumps • MCMC optimized • Easy extension to WL regime ACS field of A1689

  16. Application to Abell 1689 Jullo & Kneib 2009 • Mass map similar to Limousin et al 2007 • mean RMS = 0.22” • RMS min = 0.09” max = 0.48” (sys6)‏ Mass distribution and S/N map (300,200,100,10)

  17. LensPerfect - not yet perfect ! • IDEA: Solve lensing equation perfectly using curl-free basis of function • However for a multiple image system, there is an infinity of solution depending on the source position • What is the most likely “perfect model” ??? • Perfect model only converge if an infinity of constraints … Coe et al 2008, Coe 2009

  18. Mass Profile of Clusters (SL+Dynamics) MS2137 • DM simulation predicts a universal profile; what is observed in the inner core? • Combination of strong lensing (radial and tangential arcs) + dynamical estimates from the cD galaxies • Some degeneracies, but indication of a flatter profile than canonical NFW: -0.5<beta<-1 • “Flat” core found in other clusters (RCS0224, Cl0024) • Possibly probe DM & Baryon coupling? New detailed modeling Abell 383 Sand, et al. 2007

  19. Log(shear) Log(radius) Mass Profile of Clusters (SL+WL) • background source selection is critical to accurately measure WL • Improved lensing constraints, revised concentration from c~15 to c~8 • Better agreement. • See also: Smith/Hoekstra talks HST/WFPC2 mosaic SUBARU CFHT Abell 1689 Limousin, et al. 2007, Dahle et al 2009

  20. « Bullet Cluster » unusually strong mergers Clowe et al 2006, Bradac et al 2006 1E0657 Encounter of 2 massive clusters Significant offset between X-ray gas and lensing mass peaks probably best evidence for « collision-less dark matter » put constraints on DM/baryon interactions

  21. Other « Baby Bullet» and Nature of DM Combining the Chandra data with lensing mass maps -> place an upper bound on the dark matter self-interaction cross section: Baby bullet: σ/m < 4 cm2g−1 = 8 barn/GeV. Bullet cluster: σ/m < 0.7 cm2g−1 = 1.3barn/GeV (Randall et al.2008) MACSJ0025-1222 Bradac et al 2008

  22. Physics:Cluster/Group Lensing in the Field, Scaling Relations

  23. Cluster/groups in COSMOS ~200 XMM cluster candidates: 64 clusters: 0.5<z<1.0 50 clusters: z> 1 (Finoguenov et al 2007, 2008) Photo-z concentration Massey et al. 2007 X-ray clusters WL mass calibration for X-ray clusters 23

  24. Photoz z=0.8 z=0.6 z=0.4 z=0.2 IAB<25 1.4M galaxies X-ray contours

  25. Clusters/Groups in COSMOS probed by WL • Weak Lensing in COSMOS not only allows tomography (Massey 3D map) but makes possible a direct measurement of mass of structures down to galaxy sizes Leauthaud et al 2009 mass profile 0.4 keV 0.8 keV 1.6 keV radius

  26. Leauthaud et al 2009 • M ~ L 0.6 over 3 decades in X-ray luminosity! (slope inconsistent with self-similar prediction) • But redshift evolution: consistent with self-similar model X-ray Luminosity vs Lensing Mass Results: Lensing mass as a function of X-ray luminosity Possibility to use other mass proxy like richness (used for SDSS measurement)

  27. Cosmological World Model

  28. Cosmography with SL clusters Lensing depends on cosmology via the angular distance. Probing different source planes, one probes different distances! => Clusters with many (>>3) multiple image systems at different redshift can constrain cosmology Abell 2218 • Early work on A2218: with 4 multiple image systems at z=0.7, 1.03, 2.55, 5.56 favors Lambda-CDM • Need of deep imaging and deep spectroscopy … Omega_lambda Golse et al 2002, Soucail et al 2004 Omega_matter

  29. Cosmography with Abell 1689 Mass model with 12 multiple image systems with spectroscopic redshifts. Optimizing cosmography (M , wX ) for a flat Universe Jullo et al 2009

  30. Cosmography with Abell 1689 Mass model with 12 multiple image systems with spectroscopic redshifts. Optimizing cosmography (M , wX ) for a flat Universe Combination with other cosmological probes (WMAP5, SDSS-BAO, SNLS) => mild improvement Evidence for a non Lambda cosmology ?? More cluster cosmography constraints needed! Easier than Cosmic shear? Jullo et al 2009

  31. Future Prospects • Lensing images better from space => true for cluster lensing too (both SL and WL), multicolor very helpful • Mass reconstruction techniques are limited by quality/quantity of data => results will improve with better, larger dataset … and faster computers! • Slope of DM and substructure are measurable quantities => need to improve datasets • Cluster cosmography is a promising new (geometrical) cosmological probe - Simple? Competitive? • New serviced HST and JWST, as well as wide-field/spectroscopy ground-based 8-10m telescope are unique tools to conduct cluster lensing science.

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