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!