APJ 2010 & new result

2011/3/21 YITP workshopIntroduction
CMB anisotropy from super-structures
ISW signals in LSS-WMAP data
Origin of the Cold Spot (if time is available)
Summary

Alignment between l=2 and l=3 (Tegmark et al. 2003)
A unusually cold spot (Cruz et al. 2003)
Asymmetry in two hemispheres (Erikesen et al. 2004)
Correlation with the ecliptic plane (Schwarz et al.2004)

z～0Shapley
concentration

z~1(Inoue & Silk, 2007&2008)“the Cold Spot”

(Inoue & Silk, 2007&2008)“the Cold Spot”

z～0Shapley
concentration

z<1(Inoue & Silk, 2007&2008)“the Cold Spot”

2MASS

Local ISW
0.0<z<0.1

0.1<z<0.2

0.2<z<0.3(Francis &Peacock, 2009)

SDSS LRG
voids &clusrters

compensating filter

stacking(Granett et al.
2008)

0.45<z<0.75

TheoryThin-shell approx. (Inoue & Silk 2007&2008)
2nd order perturbations (Tomita & Inoue 2008)
LTB solutions (Sakai & Inoue 2008)

Observation


SDSS LRGs (Granett et al. 2008)
2MASS photo-z (Francis & Peacock 2009)

temperature fluctuation due to time-evolving
gravitational potential
LSS

Gravitational potential

accelerated
expansion-DEspace→low temperature for CMB photons that passthrough a void

temperature fluctuation due to time-evolving
gravitational potential
LSS

Gravitational potential

accelerated
expansion

DEspace→high temperature for CMB photons that passthrough a cluster

Gravitational potential

accelerated
expansion

+

space

peculiar
velocity

LSS

Gravitational potential

accelerated
expansion+

peculiar
velocity

DE

space

clustervoid



Stacked images enhances S/N for 3D images
Analytic formula suitable in quasi-linear regime
Sensitive to initial non-Gaussianity





Top-hat spherical void/cluster with a thin-shell
Homogeneous collapse without a shell
One-to-one correspondence between linear
and non-linear density fluctuations
Parameters:
comoving
Hubblecontrast
r radiusHmdensity contrast

N

Number of voids/clustersTemperature fluctuations
due to a thin shell void/cluster  arH

Time evolution of
Homogeneous FRW patch

Time evolution oflinear density perturbation

(0 ,  , b , h,  8 , n)  (0.26,0.74,0.044,0.72,0.80,0.90)

metric & equation

discretization in radial coordinates

SDSS：(Granett et al. 2008)
LTB,linear (compensating)z=0.5 ：(IST 2010)

compensating top-hat-filter
cuncompensating top-hat-filter

Smoothing scale

σ
ILC map

Q+V+W map

Smoothing scale Sample number~observed area/size of filtering At=5 degree , significance is 0.7-1 %(~2σ)
at =12 degree, significance is 0.01-0.2%(~3σ)

 Suppose 18 μK ISW contribution (1σ ) from asupervoid, the significance is 0.001% (~4.4σ)
in standard ΛCDM (preliminary).

δ_L as a function of z for θ0=12(blue), 15(red), 18(brown) degreeISW signal from SDSS –WMAP stacked images
is inconsistent with the prediction for aconcordant LCDM model at >3σ level.

ISW signals in photo-z 2MASS data (z<0.3) areseveral times larger than the LCDM prediction.

Non-linear effects (hot-ring around cold spot& dip at the center of hot spot) seem to bepresent in the SDSS data.

However, it seems difficult to make prominent
non-linear signals as in observations.

Suggesting non-compensating mass profiles
or deviation in the growth factor?

Suggesting non-Gaussianity or f(R)?