Constraining Dark Energy with ClusterStrong Lensing
Priyamvada Natarajan
Yale University
Collaborators: Eric Jullo (JPL), Jean-Paul Kneib (OAMP), Anson D’Aloiso*(Yale),
Marceau Limousin (Toulouse), Johann Richard (DARK), Carlo Schimd (OAMP)
HST’s high resolution
•Post COSTAR, Hubble has provided a unique view of multiply imagedgalaxies: better identification, fainter images, morphologies
1996
HST
Cl2244
1986
CFHT
Einstein radii at multiple source redshifts
Ratio of the position of multiple images,depends on mass
distribution and cosmological parameters
Ratio of the position of multiple images,depends on mass
distribution and cosmological parameters
Allows constraining dark energy out tozsource!
How does this work?
ISOTHERMAL SPHERE LENS lens at z = zL; sources at zS1 & zS2
•EXTENDING TO MORE COMPLICATED MASS PROFILESAND MORE MULTIPLY IMAGED SOURCES…………
Obtained from data
Solve for cosmological parameters
Broadhurst+ 05, Benitez+ 06; Halkola+ 06; Limousin, PN+ 07; Jullo+ 2010(Science)
34 multiply imaged systems, 24 with measured redshifts
Cluster arcs and dark energy: Abell1689
Strong lensingmultiple image geometries for an elliptical lens
Source plane
caustics
Image plane
critical curves
Multiple image families and sensitivity to darkenergy
notation denotes the position
of the ith image of family f
For multiple images of the same source
Taking the ratio of 2 distinct
families of multiple images
Gilmore & PN 08; D’Aloisio & PN 10
Dependence on the
mass distribution
Mass profile of Abell 1689
First results for A1689
Limousin+ 07
Degeneracies….
First results for A1689
D’Aloisio & PN 09; Jullo & Kneib 09: Jullo+ 10 (Science, August 2010, 329,924)
Mass model with 3 PIEMD potentials; 58 cluster galaxies
Bayesian optimization: 32 constraints, 21 free parameters;
RMS = 0.6 arcsec; 28 multiple images from 12 sources with
spec z, flat Universe prior
Requirements for cluster strong lensing
•Need complement of ground based spectroscopy
•Mass modeling positional accuracy
•Need spectroscopic redshifts for all sources (no photo-z’s)
•Structure along the line of sight behind the lens plane (environments of lensesneeds to be modeled Momcheva et al. 06, Oguri, Keeton& Dalal 05)
structure behind 0024
perturbations in the
positions of multiple images
Area under caustic likely
to produce multiple images
Contribution of structure behind the lensplane
D’Aloisio & PN 10
KEY SYSTEMATICS
L.O.S. SUBSTRUCTURE IN LENS PLANE & ALONG L.O.S
Scaling Relations (relation between mass & light)
Correlated LOS (infalling subclusters, filaments)
Uncorrelated LOS (primary contribution to the errors)
BIASES: choice of density profile, bimodality?
Not particularly sensitive to the inner slope/outer slope of the densityprofile
No bias from choice of profile NFW vs. PIEMD or bi-modality
10 clusters, 20 families!Flat prior, input w = -1; evolving wa
Chevallier, Polarski & Linder 01
Current constraints including CSL
Combining X-ray clusters, WMAP5, stronglensing competitive with WMAP5 + SNe+ BAO
Jullo, Kneib, PN+ 10
The SDSS Giant-Arc Survey & MCTClusters….
Hennawi+ 07, 08; Oguri+ 09; Gladders+ 10;Postman+
Parameter degeneracies
For each clump: ellipticity, core radius, clump vel disp, Omegam
wx