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Squeezing the CMB
Astro448 Final Presentation -Alan Zablocki
Outline
u Introduce the CMB u What can we squeeze out of the data u Standard techniques – MCMC u We want cosmological parameters u Linear data transform u Results and comparison to MCMC
The way forward
Usually we go from a sky map
The way forward
Express anisotropy as power spectrum
Cosmological Parameters
u Compare data to theory (Bayesian) u MCMC is the work horse standard u Set of marginalized estimates
{ }τ,,,,, 22ssbc
LCDM Anhh ΛΩΩ=Θ
MCMC
Instead… Let us apply a matrix to the data, the Cls. Carry this operation such that locally the Fisher Matrix is unchanged.
arXiv:astro-ph/9603021v2
2^
121
lml al
Cx+
==
x=µ
Fisher Matrix
∑ ∑ ∂
∂
∂
∂= −
l YYXX j
YYl
iji
XXlCMB
ijCCovCF
,
1)(θθ
Key components:Covariance
Key components:Derivatives
How well can we recover the Fisher Matrix?
Let’s use these on some data
We need some data: Mocks!
( )ibaglm +=21
)(21 idchlm +=)(
21 ibaglm +=
How well can we recover a single parameter?
Chalk Talk
2D Results
This is the End…for now!
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