5.1×1014 M

What causes this?
• Choice of cluster center
• Cluster galaxy
(de)contamina@on
• Shear calibra@on
• NFW concentra@on
• Source redshiF
distribu@on
• N-­‐body calibra@on
• …
20 D. E. Applegate et al.
Mean error: 0.77 Mean error: 0.88
My weak lensing mass
Mean error: 0.84 Mean error: 1.38
Your weak lensing mass
Applegate et al. (2012)
Figure 13. Comparison of our mass measurements to results in the literature. Panel a) shows the comparison to Okabe et al. (2010), panel b) to Mahdavi et al.
(2008), panel c) to Bardeau et al. (2007), and panel d) to Pedersen & Dahle (2007). For each comparison, we measure the mass within the overdensity radis r∆
of the respective work. The solid line indicates the one-to-one line, the long-dashed line shows the average of the mass ratios, and the dotted line the median.
For simplicity, the unweighted average is shown, since the measurements are correlated due to overlap in the source galaxy samples.

An observable that scales with mass
What causes this?
It’s not just weak lensing. Systema@c errors in X-­‐ray, SZ, and O/
IR mass-­‐observables propagate through the system to create
(or hide) discrepancies. Lesson: calibrate mass-­‐observables
jointly in fully self-­‐consistent way. If you do this, you find the
field is in a significantly worse state than stated systema9c
errors in previous published works would have you believe.
Planck Collaboration: Planck early results. XII.
Planck Early Results XII (2011)
Your mass calibrated to weak lensing My mass calibrated to weak lensing
. 2. Scaled SZ signal measurements, ˜Y500, binnedbyrichness,N200. Theleft-handpanelpresentstheresultsfortheJohnston et al. (20
00 − N200 relation, the right-hand panel for the Rozo et al. (2009) relation.Ineachcase,thereddiamondsshowthebin-average,redshift-sca
0 calculated as the weighted mean of all individual measurements (e.g., Fig. 1) inthebin,wheretheweightsaretakenfromtheestimatedfi
se. The thick error bars show the corresponding uncertainty on the bin-average SZ signal, while the lighter error bars indicate the uncertai
nd by bootstrap analysis; they are larger due to the presence of intrinsic scatter within the bins, most notable at high richness (see Fig. 4). T
e points represent the model prediction for each bin found by averaging, with the same weights as the data, the SZ signal expected from

Cluster-­‐abundance cosmology
234 G. Mark Voit: Tracing cosmic evolution with clusters of galaxies
• Cosmological parameters:
However, this problem is not as severe as one might
expect because the evolution in the mass function itself
is so dramatic, – Dark especially energyfor equa@on M1. This of state: part of w the =
review discusses P/

ARI 2 August 2011 10:40
Sample size
10 6
10 5
10 4
10 3
10 2
10 1
10 0
Cluster surveys
ACO
B50
EMSS
1990
RCS1
MaxBGC
BCS
REFLEX
400d
MACS
RDCS
ACT
2000
Year
SPT
2010
10 14 M ☉
10 15 M ☉
SPT 2500 deg 2
SPT 720 deg 2
(Reichardt et al., 2012)
Figure 1
Yields from modern surveys of clusters used for cosmological studies are shown, with symbol size
proportional to median redshift. Samples selected at optical ( gray filled circles), X-ray (red squares), and
millimeter (blue triangles) wavelengths are discussed in Section 3.2. Stars and horizontal lines (purple) show
full sky counts of halos expected in the reference CDM cosmology (see Section 2) with masses above 1015 Adapted from Allen, Evrard, & Mantz (2012)
14
MCXC
•

7
The thermal
Sunyaev-Zel’dovich
effect"
7

photon by roughly kBTe/mec 2 , causing a small (⇥1 mK) distortion in the CMB
spectrum. Figure 1 shows the SZE spectral distortion for a fictional cluster that is
over 1000 times more massive than a typical cluster to illustrate the small effect.
The SZE appears as a decrease in the intensity of the CMB at frequencies below
⇥218 GHz and as an increase at higher frequencies.
The derivation of the SZE can be found in the original papers of Sunyaev &
Zel’dovich (Sunyaev & Zel’dovich 1970, 1972), in several reviews (Sunyaev &
The Sunyaev-­‐Zel’dovich effect
Zel’dovich 1980a, Rephaeli 1995, Birkinshaw 1999), and in a number of more re-
cent contributions that include relativistic corrections (see below for references).
This review discusses the basic features of the SZE that make it a useful cosmological
tool.
Take-­‐home message #1
SZ signal is not an emissive process but a
spectral disor@on, so with beam well
matched to the size of clusters, it’s nearly
redshiF independent.
Figure 1 The cosmic microwave background (CMB) spectrum, undistorted (dashed
line) and distorted by the Sunyaev-Zel’dovich effect (SZE) (solid line). Following
Sunyaev & Zel’dovich (1980a) to illustrate the effect, the SZE distortion shown is for
a fictional cluster 1000 times more massive than a typical massive galaxy cluster. The
SZE causes a decrease in the CMB intensity at frequencies ⇥218 GHz and an increase
at higher frequencies.
Measured SZ spectrum
of A2163
Take-­‐home message #2
SZ signal is a direct probe of total thermal
energy, and so is a good proxy for cluster
mass.

South Pole Telescope
M500 (10 14 -1
Msun h70) detected clusters
10
SPT-720 deg 2
Planck-ESZ
ROSAT-All sky
Reichardt et al. (2012)
1
0.0 0.5 1.0 1.5
z

Calibra@ng mass-­‐observables with
weak lensing
NDRA CLUSTER COSMOLOGY PROJECT. II. 1047
that the scatter in
in Mtot for a given
X-ray analysis, as
al mass in simulated
robust X-ray mass
YX,isdefinedas
(10)
ng the cluster X-ray
ii 0.15 r500 − 1 r500,
phere r500, derived
otal thermal energy
atedlow-frequency
ich 1972). The total
nstobeaverygood
al. 2004;Motletal.
n the simplest selfes
with the cluster
• Hydrosta@c equilibrium
◌ Weak lensing
Vikhlinin et al. (2009)
Figure 11. Calibration of the Mtot–YX relation. Points with errorbars show
Chandra results from Vikhlinin et al. (2006) withsevenadditionalclusters
(Section 4). The dashed line shows a power law fit (excluding the lowest mass
cluster) with the free slope. The dotted line shows the fit with the slope fixed
at the self-similar value, 3/5 (parametersforbothcasesaregiveninTable3).
Open points show weak lensing measurements from Hoekstra (2007;thesedata

Weak lensing

Weak lensing
Williamson, Oluseyi, & Roe (2007)

SPT targeted weak lensing sample
o 33 clusters at 0.3 < z < 1.3
o Complete SZ, X-­‐ray coverage
o Spectroscopy, Spitzer NIR, and
mul@band OIR from the ground
Ground WL sample
• Magellan/Megacam camera
• 19 clusters at 0.3 < z < 0.6
• Imaging in (u)gri in 2011A+B
Space WL sample
• HST/ACS camera
• 14 clusters at 0.6 < z < 1.3
• Imaging in F606W and F814W
in Cycle 18 and Cycle 19
• Added deep imaging with VLT
• Observa@ons ongoing

SPT-­‐CL J0348-­‐4514, z = 0.39, M 500 = 5.2×10 14 M sun

SPT-­‐CL J0546-­‐5345, z = 1.07, M 500 = 8.0×10 14 M sun

Stellar locus photometric calibra@on
Magellan/IMACS stellar locus
SLR: Stellar Locus Regression
Allows for calibra@on of
colors and magnitudes
without the tradi@onal use
of standard star fields
Successfully used by
Weighing the Giants to
obtain photo-­‐z’s
Adapted from
High et al. (2009)
SLR gives dereddened colors to 0.01−0.03 mag (SDSS)
and magnitudes to 0.05 mag (2MASS).

− i
Stellar locus photometric calibra@on
Magellan/Megacam stellar locus
i − J
g − r r − i
SLR gives dereddened colors to 0.01−0.03 mag (SDSS)
and magnitudes to 0.05 mag (2MASS).

s, in
ation
and
nly a
The
ples,
cribe
and
laxy
stars
f the
hese
from
een
few
is more difficult for smaller or fainter galaxies, and the intrinsic morphology
distribution of galaxies varies as a function of magnitude
in images other than set B, ngals and σ γ are likely to be correlated
in a complicated fashion. Es@ma@ng Galaxy selectionshear effects and weighting
schemes are discussed in Sections 5.6 and 5.7.
4.3 Shear calibration bias and residual shear offset
Shear pipelines that we use:
• ground data: Henk Hoekstra (HH)
• space data: Tim Schrabback (TS)
As with STEP1, we assess the success of each method by comparing
the mean shear measured in each image with the known input shears
γ input
i . We quantify deviations from perfect shear recovery via a
linear fit that incorporates a multiplicative ‘calibration bias’ m and an
additive ‘residual shear offset’ c. With a perfect shear-measurement
method, both of these quantities would be zero. Since the input shear
is now applied in random directions, we measure two components
each of m and c, which correspond to the two components of shear:
Full pipelines blind-­‐tested by the Shear
TesHng Program (STEP: Heymans et al.
2006; Massey et al. 2007). Includes
realis@c point-­‐spread func@ons.
STEP bias sta@s@cs:
〈 ˜γ1〉−γ input
1
〈 ˜γ2〉−γ input
2
= m1γ input
1
= m2γ input
2
+ c1
+ c2.
(43)
Shear code recovers truth with no measurable
C○ 2007 The Authors. Journal compilation C○ 2007 RAS, MNRAS 376, 13–38
Massey et al. (2007)
Figure 6. Comparison of shear-measurement accuracy from different meth-
addi9ve bias (c) and with mul9plica9ve bias
ods, in terms of their mean residual shear offset 〈c〉 and mean shearcalibration
bias (m) 〈m〉. of 2% In the ortop beRer. panel, these parameters have been averaged
over both components of shear and all six sets of images; the bottom panel
includes only image sets A, B, C and F, to avoid the two highly elliptical
PSFs. Note that the entire region of these plots lie inside the grey band that
indicated good performance for methods in Fig. 3 of STEP1. The results
from methods C1, SP, MS1 and ES1 are not shown here.
age set
bias is
elliptic
Strang
pixelliz
betwee
not hav
indeed
succes
Pixe
about t
it may
conseq
able to
objects
high o
galaxie
if Nyqu
etry, bu
pixelliz
seeing,
seeing)
unders
worse
there.
We
lization
ential c
study o
(in pre
bration
pixels,
Becaus
of shea
tics. H
ual clu
The ne
pixel s
mean
promis
method

Magellan/Megacam PSF performance
PSF polariza9on residuals are 0.003 to 0.005 rms,
no appreciable residual in radial bins.
High et al. (2012)

Magellan/Megacam catalogs
Source redshiF distribu@on and
cluster-­‐galaxy decontamina@on
Procedure for ground sample:
o Cut out i > 25 24
o Cut out |z phot − z cluster| < 0.05 region in color-­‐color
space
o Es@mate mean and variance of β from reference
photo-­‐z catalogs using the same cuts
CFHTLS Deep field photo-­‐z catalogs
Coupon et al. 2009
Low contamina9on
near z cluster
High et al. (2012)

Magellan/Megacam catalogs
Source redshiF distribu@on and
cluster-­‐galaxy decontamina@on
Procedure for ground sample:
o Cut out i > 25 24
o Cut out |z phot − z cluster| < 0.05 region in color-­‐color
space
o Es@mate mean and variance of β from reference
photo-­‐z catalogs using the same cuts
Magellan/Megacam catalogs
High et al. (2012)

O/NIR: Magellan/Megacam
SZ: SPT S/N
κ: Kaiser Squires reconstruc@on
Color scale: SZ S/N Black contours: κ
The results
SPT-­‐CL J2145-­‐5644, z = 0.48, M 500 = 6.5×10 14 M sun
White contours: SZ S/N Cyan contours: κ

The results
SPT-­‐CL J2145-­‐5644, z = 0.48, M 500 = 6.5×10 14 M sun

O/NIR: Magellan/Megacam
SZ: SPT S/N
κ: Kaiser Squires reconstruc@on
Color scale: SZ S/N Black contours: κ
The results
SPT-­‐CL J0348-­‐4514, z = 0.39, M 500 = 5.2×10 14 M sun
White contours: SZ S/N Cyan contours: κ

The results
SPT-­‐CL J0348-­‐4514, z = 0.39, M 500 = 5.2×10 14 M sun

O/NIR: VLT/FORS2 & Spitzer
SZ: SPT S/N
κ: Kaiser Squires reconstruc@on
Color scale: SZ S/N Black contours: κ
The results
SPT-­‐CL J0546-­‐5345, z = 1.07, M 500 = 8.0×10 14 M sun
Cyan contours: κ

The results
SPT-­‐CL J0546-­‐5345, z = 1.07, M 500 = 8.0×10 14 M sun

O/NIR: VLT/FORS2
SZ: SPT S/N
κ: Kaiser Squires reconstruc@on
Color scale: SZ S/N Black contours: κ
The results
SPT-­‐CL J2331-­‐5051, z = 0.58, M 500 = 5.1×10 14 M sun
Cyan contours: κ

O/NIR: HST/ACS
SZ: SPT S/N
κ: Kaiser Squires reconstruc@on
Color scale: SZ S/N Black contours: κ
The results
SPT-­‐CL J2331-­‐5051, z = 0.58, M 500 = 5.1×10 14 M sun
Cyan contours: κ

The results
SPT-­‐CL J2331-­‐5051, z = 0.58, M 500 = 5.1×10 14 M sun

O/NIR: HST/ACS & Spitzer
SZ: SPT S/N
κ: Kaiser Squires reconstruc@on
Color scale: SZ S/N Black contours: κ
The results
SPT-­‐CL J2106-­‐5844, z = 1.13, M 500 = 8.4×10 14 M sun
Cyan contours: κ

The results
SPT-­‐CL J2106-­‐5844, z = 1.13, M 500 = 8.4×10 14 M sun

Calibra@on to N-­‐body simula@ons
ArHcle NFW WL mass bias
Becker & Kravtsov
2012
-­‐5% to -­‐10%
Rasia et al. 2012 -­‐5% to -­‐10%
Bahe et al. 2012 -­‐5%
High et al. 2012 -­‐5% to -­‐10%
Our tests:
• Use two flavors of Dark Energy Survey mocks at 220
deg 2 and 5k deg 2 ; fake galaxies with realis@c color,
magnitude, and clustering proper@es (ADDGALS, R.
Wechsler et al.)
• Replicate our color and magnitude selec@on for all
massive 0.25 < z < 0.65 halos
• Also geared up on simula@ons from Becker &
Kravtsov (2012)
WL NFW masses recover truth with overall bias of -­‐5% to -­‐10%.

WL test of joint SZ/X-­‐ray masses
Mean calibraHon from ground
sample: 1.26 ± 0.16
Mean calibraHon from space
sample: 1.16 ± 0.26
High et al. (in prep.)

=0.655 ± 0.02 (1.16)
AWL = 4G
R2 BWL ↵Mpiv 1c2 Dpiv =0.0457 ⇥ (BWL0.13) (±BWL0.06) (1.17)
WL calibraHon of M – YSZ :
A first look at the SPT data
BWL = (1.18)
CWL =1± 0.01 (1.19)
YSZ measured with Rapid Gridded
Likelihood Es@mator (T. Montroy et al.
in prep.).
DWL =0± 0 (fixed) (1.20)
EWL =0± 0 (fixed) (1.21)
Assume self-­‐similar scaling with free
normaliza@on parameter,
Astrophysical scaling relations
M500
10 14 M
= eA
✓
YsphD2 2/3
AE(z) 10 5 Mpc 2
◆3/5
19 SPT-­‐detected clusters used here:
• 7 from space sample
• 12 from ground sample
Aghanim et al. (2012) and Applegate et
al. (2012) have also given evidence for
-­‐30% WL biases in LoCuSS results
(Okabe et al. 2010; Marrone et al.
2012).
(1.22)
These results are preliminary.
High et al. (in prep.)

A SZ
jak 20
at ⇠ > 2. This maximization bias comes from having
maximized ⇠ across possible cluster positions and filters 2
explain
scales, e↵ectively adding three degrees of freedom to the
levels
fit with ⇠ analogous to a 0.5 0.6 0.7 0.8 0.9 1.0 1.1 verse,
at z =
8
Implica@on for cosmology
creasin
of CM
Fig. 5.— Assuming a wCDM cosmology, the two-dimensional
marginalized constraints on ASZ and 8. Contours show the a 95%
68% and 95% confidence regions for the SPTCL +H0+BBN (red) In F
and CMB+BAO+SNe+SPTCL (green) data sets. The horizontal and 8
black dashed line is the center of the theory prior on ASZ.
after13i the ma
that find some evidence for a sterile neutrino species. sumeIt
has been pointed out that these measurements areing most the
wCDM
consistent with two sterile neutrinos and ⌃m⌫& 1.7 ⌃m⌫< eV
SPTCL+H0+BBN (Kopp et al. 2011).
CDM+(m
0.6
Therefore, we >0)
consider the joint Ne↵= cos-
8
CMB+BAO+SNe mological constraints
CMB+H
on Ne↵ 0+BAO
and ⌃m⌫ to compare additio with
+SPT these terrestrial results. CMB+H0+BAO+SPTCL 8 by a
CL 0.5
With only threeCMB+H neutrino 0+SPT species, CL we would expect by a fa
Ne↵= 3.046, a value slightly larger than three because data d
6
0.4
of energy injection from electron-positron annihilation
ized on
at the end of neutrino freeze-out (Dicus et al.
maxim
1982;
Lopez
0.3
⌃m⌫=
et al. 1999; Mangano et al. 2005). As Ne↵ in-
As n
creases, the contribution to the gravitational potential
4
of 0.2
power
the additional neutrino perturbations boosts thevored early
growth of dark matter perturbations (Bashinsky & Seljak
0.1
the ne
2004), which also increases 8 (Hou et al. 2011). its phy As
2
explained in Section 5.2, adding neutrino mass at the
0.0
Ne↵ m
levels considered here only a↵ects the low-redshift theuni mo
0.5 0.6 0.7 0.8 0.9 1.0 1.1 verse, 0.65 suppressing 0.70 structure 0.75 0.80 formation, 0.85 and lowering Keisler 8
at z = 0. Therefore, increasing 8 Ne↵ will also allowthe an in- ex
8
creasing ⌃m⌫. Keisler et al. (2011) used a combination the mo
Fig. 6.— of Assuming CMB+H0+BAO a ⇤CDM cosmology data to withconstrain massive neutrinos, ⌃m⌫< 0.69also eV at w
the two-dimensional a 95% CL, marginalized
8 =0.803 constraints ± 0.056, and on Ne↵= ⌃m⌫ and 3.98 ± 0.43. genera
8. Contours show the 68% and 95% confidence regions for
the CMB+H0+BAO In Figure (gray, 7, dashed), we showCMB+H0+BAO+SPT the constraints on Ne↵, cosmo ⌃m⌫,
CL
(orange, solid), and and 8, usingtheCMB+H0+BAO CMB+H0+SPTCL (blue, dot-dashed) data data set, before8, and wh
sets. The SPT after CLincluding data improves the theSPTCL constraints data. on 8InandTable, ⌃m⌫, 5 we improv give
by factors of 1.8 and 1.4, respectively.
the marginalized constraints. When varying Ne↵ ⌃m⌫ we asc
sume consistency with BBN for our constraints. conser Us-
Recent ing measurements the CMB+H have+BAO+SPT shown a ⇠2 preference data set, for we constrain ical m
2 . Additionally, h⇠i relates to
⇠ by a Gaussian scatter of unit width. Simulations have
been used to verify that these approximations introduce
negligible bias or scatter compared to the Poisson noise
of the sample. For further details we refer the reader to
V10.
We assume a ⇣ M500 relation of the form
✓
M500
⇣ = ASZ
3 ⇥ 1014M h 1
◆BSZ ✓ cally spaced redshifts between 0

Summary
o Weak lensing quality data obtained for 33 clusters
o 19 clusters at 0.3 < z < 0.6 with Magellan/Megacam
o 14 clusters at 0.6 < z < 1.3 with HST/ACS
o full SZ, X-­‐ray, and spectroscopic overlap
o First look at 28 clusters
o provides 14% direct mass calibra@on
o shows weak evidence for low mass es@mates
o Analysis now undergoing refinement and scru@ny
o First
o WL detec@ons using Megacam at Magellan
o direct calibra@on of code used on real data to N-­‐body
simula@ons
o Matching the staHsHcal power of the SPT CL data set will
require a sub-­‐3% calibraHon of mass. SPT CL poised to
achieve δw = 0.035
o Ancillary science
SPT
Magellan
HST

EXTRA SLIDES

asic imaging information for the five
of which has already been transformed to the SDSS
hose be slopes a population are equal to thethat color-term coefficients,
this is not an exhaustive test.
The mean tangential shear as a fun
the plane of the sky at the cluster re
projected surface density, Σ(R), as (M
where c is the speed of light, G is the gravitational constant, and
er the source redshift β ≡ Dls/Ds is the lensing efficiency. Quantities D are angular-
ure ometric is availableerror, in the online δi, journal.) by diameter distances, and l indicates the lens (the cluster) while s
iCFHT > 24 − δi and indicates
Weak
sources.
lensing
photometric accuracy The observable quantity is not the shear but the reduced shear,
basic WL-SZ imaging massinformation ratios at for the g, whichrelatestotheshearas
five
ly stimated subdominant from the to median the magnitude of
-to-noise ematic uncertainties.
ratio is five. Seeing is estimated
Observable quan@ty: reduced shear, g. γ = (1 − κ)g (8)
of photometric zero-point errors on the
ios. Systematic errors in photometry 5 enter
is through theShear estimation relates oftothe mass critical via:
ch cluster (Section 4.2). We estimate this
ly available photometric redshift catalogs
which we apply the same photometric
o the Megacam catalogs. If there is an
i ′ this is the shear component oriented at 45
-band zero point relative to that of the
n we effectively probe a population that
from which we infer the source redshift
the effect of photometric error, δi, by
hoto-z catalogs at iCFHT > 24 − δi and
lysis. The level of photometric accuracy
auses changes in the WL-SZ mass ratios at
which is significantly subdominant to the
and the largest systematic uncertainties.
◦ with respect to γ+.
The azimuthally averaged cross shear 〈γ×〉 as a function of
radius provides a diagnostic for residual systematics, because no
astrophysical effects, including lensing, produce such a signal.
As a consequence, a non-zero 〈γ×〉 indicates the presence of
some types of residual systematic error, though we note that
this is not an exhaustive test.
The mean tangential shear as a function of radial distance in
the plane of the sky at the cluster redshift, R, dependsonthe
projected surface density, Σ(R), as (Miralda-Escude 1995)
〈Σ〉(< R) − Σ(R)
〈γ+〉(R) = . (6)
Σcrit
This depends on the critical surface density,
Σcrit = c2
s the shear component oriented at 45
The signal is a func@on of lens and source redshiFs through: 1
, (7)
4πG Dlβ
where c is the speed of light, G is the gravitational constant, and
β ≡ Dls/Ds is the lensing efficiency. Quantities D are angulardiameter
distances, and l indicates the lens (the cluster) while s
indicates sources.
The observable quantity is not the shear but the reduced shear,
g, whichrelatestotheshearas
γ = (1 − κ)g (8)
5
◦ with respect to γ+.
azimuthally averaged cross shear 〈γ×〉 as a function of
s provides a diagnostic for residual systematics, because no
physical effects, including lensing, produce such a signal.
consequence, a non-zero 〈γ×〉 indicates the presence of
types of residual systematic error, though we note that
s not an exhaustive test.
e mean tangential shear as a function of radial distance in
lane of the sky at the cluster redshift, R, dependsonthe
cted surface density, Σ(R), as (Miralda-Escude 1995)
〈Σ〉(< R) − Σ(R)
〈γ+〉(R) = . (6)
Σcrit
depends on the critical surface density,
Σcrit = c2
estimated from the median magnitude of
l-to-noise ratio is five. Seeing is estimated
t of photometric zero-point errors on the
tios. Systematic errors in photometry enter
sis through the estimation of the critical
ach cluster (Section 4.2). We estimate this
cly available photometric redshift catalogs
o which we apply the same photometric
to the Megacam catalogs. If there is an
m i
1
, (7)
4πG Dlβ
e c is the speed of light, G is the gravitational constant, and
A model for the project mass density,

Advantages
1. Extremely simple theore@cal
rela@onship between total
mass and observables
– A key piece of evidence for
the existence of dark maver
– Independent of maver’s
dynamical state or history
2. Rela@vely straighworward to
realis@cally simulate in the
same N-­‐body simula@ons that
cosmological fixng func@ons
are tuned to
– Ray tracing
– Source selec@on
Weak lensing
Challenges
1. Accurately es@ma@ng
reduced shear
– Correct for the smearing and
shearing by anisotropic point-­‐
spread func@ons
– Cluster galaxies contaminate
shear profiles
2. Accurately es@ma@ng source
redshiF distribu@on
– Photo-­‐z’s are hard!
– Availability of photo-­‐z’s at very
faint magnitudes or very high
redshiF is scant

South Pole Telescope
• (Sub)millimeter wavelength
telescope:
– 10 meter aperture
– 1’ FWHM beam at 150 GHz
– Off-­‐axis Gregorian op@cs design
– 20 micron RMS surface accuracy
– 1 arc-­‐second poin@ng
– Fast scanning, up to 4 deg/sec in
azimuth
• SZ receiver:
– 1 sq. deg FOV
– ~960 background limited pixels
– Observe in 3+ bands between 95-­‐220
GHz simultaneously
– Modular focal plane
• Polarimeters are currently deployed
for CMB polariza@on and deep-­‐SZ
studies (SPTpol)