Optimal ISW detection and joint likelihood for cosmological parameter estimation
Mona Frommert, Torsten A. Ensslin, and Francisco S. Kitaura

TL;DR
This paper introduces an optimal method to detect the ISW effect by reducing local variance bias, improving detection significance, and providing a joint likelihood for cosmological parameters using CMB and LSS data.
Contribution
The paper presents a new optimal approach to ISW detection that minimizes local variance effects and derives a joint likelihood function for cosmological parameters.
Findings
Optimal method increases signal-to-noise ratio by about 7%.
Reduces bias in detection significance and parameter constraints.
Eliminates need for Monte Carlo covariance estimation.
Abstract
We analyse the local variance effect in the standard method for detecting the integrated Sachs-Wolfe effect (ISW) via cross-correlating the cosmic microwave background (CMB) with the large-scale structure (LSS). Local variance is defined as the systematic noise in the ISW detection that originates in the realisation of the matter distribution in the observed Universe. We show that the local variance contributes about 11 per cent to the total variance in the standard method, if a perfect and complete LSS survey up to z ~ 2 is assumed. Due to local variance, the estimated detection significance and cosmological parameter constraints in the standard method are biased. In this work, we present an optimal method of how to reduce the local variance effect in the ISW detection by working conditional on the LSS-data. The variance of the optimal method, and hence the signal-to-noise ratio,…
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