Transcript Measuring the Growth Factor via Gravitational Lensing

Testing the Shear Ratio Test:
(More) Cosmology from
Lensing in the COSMOS
Field
James Taylor
University of Waterloo
(Waterloo, Ontario, Canada)
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DUEL
Summer Conference
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Edinburgh,
July 18-23 2010
The COSMOS Survey
P.I. Nick Scoville
The COSMOS Survey
 2 square degree ACS mosaic
 lensing results from
1.64 square degrees
(~600 pointings)
 2-3 million galaxies down to
F814WAB = 26.6 (0.6M to 26)
 30-band photometry,
photo-zs with dz ~ 0.012(1+z)
to z = 1.25 and IF814W = 24
 follow-up in X-ray, radio, IR, UV,
Sub-mm, …
WL Convergence Maps
(cf. Rhodes et al. 2007; Massey et al. 2007;
Leauthaud et al 2007)
 cut catalogue down to
40 galaxies/arcmin2 to remove bad zs
 correct for PSF variations, CTE
 Get lensing maps, low-resolution
3D maps, various measures of power
in 2D and restricted 3D
 results compare well with baryonic
distributions (e.g. galaxy distribution)
The Final
Result:
E-modes (left) versus B-modes (right)
The Final
Result:
3-D constraints on the amplitude of fluctuations:
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recent updates:
- improved photo-zs
- improved CTE correction in images
- new shear calibration underway
+ updated group catalog(s)
so expect stronger signal around peaks in lensing map,
and cleaner dependence on source and lens redshift
 time for some 2nd generation tests of the lensing signal
Massey et al 2007
Measuring Geometry: Shear Ratio Test
(Jain & Taylor 2003, Bernstein & Jain 2004, Taylor et al. 2007)
 Take ratio of shear of objects behind a particular cluster, as a function of
redshift
 Details of mass distribution & overall calibration cancel  clean
geometric test
 Can extend this to continuous result by fitting to all redshifts Z(z) 
DLS/DS
Relative
Lensing
Strength
Z(z)
Your cluster goes here
Bartelmann & Schneider 1999
But how big is the signal?
Use strength of signal behind cluster as a function of redshift to measure
DA(z):
Base:
h = 0.73, m = 0.27
( or X = 1 - m)
Variants (different curves):
m = 0.25,0.30,0.32
w0 = -1,-0.95,-0.9,-0.85,-0.8
w(z) = w0 + wa(1-a)
with w0 = -1, wa = 0.05, 0.1
h = 0.7, 0.75
How big is the signal?
Use strength of signal behind cluster as a function of redshift to measure
DA(z):
weak but distinctive signal; relative change (change in distance ratio) is
only 0.5%
Base:
Lens at z = 0.2
h = 0.73, m = 0.27
( or X = 1 - m)
Variants (different curves):
m = 0.25,0.30,0.32
w0 = -1,-0.95,-0.9,-0.85,-0.8
w(z) = w0 + wa(1-a)
with w0 = -1, wa = 0.05, 0.1
h = 0.7, 0.75
0.5% relative change
How big is the signal?
Use strength of signal behind cluster as a function of redshift to measure
DA(z):
weak but distinctive signal; relative change (change in distance ratio) is
only 0.5%
Base:
Lens at z = 0.3
h = 0.73, m = 0.27
( or X = 1 - m)
Variants (different curves):
m = 0.25,0.30,0.32
w0 = -1,-0.95,-0.9,-0.85,-0.8
w(z) = w0 + wa(1-a)
with w0 = -1, wa = 0.05, 0.1
h = 0.7, 0.75
0.5% relative change
How big is the signal?
Use strength of signal behind cluster as a function of redshift to measure
DA(z):
weak but distinctive signal; relative change (change in distance ratio) is
only 0.5%
Base:
Lens at z = 0.5
h = 0.73, m = 0.27
( or X = 1 - m)
Variants (different curves):
m = 0.25,0.30,0.32
w0 = -1,-0.95,-0.9,-0.85,-0.8
w(z) = w0 + wa(1-a)
with w0 = -1, wa = 0.05, 0.1
h = 0.7, 0.75
0.5% relative change
How big is the signal?
Use strength of signal behind cluster as a function of redshift to measure
DA(z):
weak but distinctive signal; relative change (change in distance ratio) is
only 0.5%
Base:
Lens at z = 0.7
h = 0.73, m = 0.27
( or X = 1 - m)
Variants (different curves):
m = 0.25,0.30,0.32
w0 = -1,-0.95,-0.9,-0.85,-0.8
w(z) = w0 + wa(1-a)
with w0 = -1, wa = 0.05, 0.1
h = 0.7, 0.75
0.5% relative change
How big is the signal?
Use strength of signal behind cluster as a function of redshift to measure
DA(z):
weak but distinctive signal; relative change (change in distance ratio) is
only 0.5%
Base:
Lens at z = 1.0
h = 0.73, m = 0.27
( or X = 1 - m)
Variants (different curves):
m = 0.25,0.30,0.32
w0 = -1,-0.95,-0.9,-0.85,-0.8
w(z) = w0 + wa(1-a)
with w0 = -1, wa = 0.05, 0.1
h = 0.7, 0.75
0.5% relative change
Signal weak but distinctive
Previous detections with massive clusters
Signal has been seen previously behind a few clusters:
e.g. Wittman et al. 2001
~3e14 Mo cluster in DLS; detection, mass and redshift all from weak lensing
(source photo-zs from 4 bands)
Previous detections with massive clusters
Signal has been seen previously behind a few clusters:
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e.g. Gavazzi & Soucail (2008): cluster Cl-02 in CFHTLS-Deep
(cf. also Medezinski et al. submitted:
1.25 M galaxies behind 25 massive clusters, in a few bands)
So why try this in COSMOS ?
 Less signal (groups only, no truly massive clusters), but far better
photo-zs
 can push techniques down to group or galaxy scales
 nice test of systematics in catalogue selection, effect of photo-z
errors
 test/confirm error forecasts for future surveys
 Percival et al .2007: interesting indication of possible mismatch in distance
scales in BAO?
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The sample of COSMOS Groups and Clusters
(X-ray
derived
Mass)
Log(volume)
(plot from Leauthaud et al. 2009)
The sample of COSMOS Groups and Clusters
~67  in top
14 objects?
(X-ray
derived
Mass)
Log(volume)
(plot from Leauthaud et al. 2009)
The sample of COSMOS Groups and Clusters
could get
another
~60 
from less
massive groups?
(X-ray
derived
Mass)
Log(volume)
(plot from Leauthaud et al. 2009)
Shear vs. photo-z around peaks, along promising lines of
sight
Shear vs. photo-z around peaks, along promising lines of
sight
How to stack clusters?
Tangential shear goes as:
so redshift dependence enters via critical surface density:
Thus if we define
and
then
independent of cosmology
(assumes flat models)
We see the signal!
Stack of regions within 6’ of
~200+ x-ray groups
good fit in front of/behind
cluster
significance still unclear;
seems less than expected
effect of other structures
along the line of sight
decreases chi2, but hard to
quantify
A Caveat
In a field this small, a few
redshifts dominate the
distribution of structure 
systematics in shear ratio
Prospects
¶ Signal detected, well behaved, significance slightly lower than expected?
¶ Still studying noise versus radial weighting, catalogue cuts, path weighting
¶ Results roughly consistent with w0 ~ -1.0 +/- 1.0
¶ Future predictions for large surveys + CMB + BAO
w0 = 0.047, wa = 0.111 and 2%
measurement of dark energy at
z ~ 0.6
Or use CMB as an extra slice?
(cf. Hu, Holz & Vale 2007;
Das & Spergel 2009)
error forecasts from 20,000 deg2
survey (Taylor et al. 2007)
(Taylor et al. 2007):