Integrated Markov Chain Monte Carlo (MCMC) analysis of primordial non-Gaussianity (fNL) in the recent CMB data

Jaiseung Kim

Abstract

We have made a Markov Chain Monte Carlo (MCMC) analysis of primordial non-Gaussianity (fNL) using the WMAP bispectrum and power spectrum. In our analysis, we have simultaneously constrained fNL and cosmological parameters so that the uncertainties of cosmological parameters can properly propagate into the fNL estimation. Investigating the parameter likelihoods deduced from MCMC samples, we find slight deviation from Gaussian shape, which makes a Fisher matrix estimation less accurate. Therefore, we have estimated the confidence interval of fNL by exploring the parameter likelihood without using the Fisher matrix. We find that the best-fit values of our analysis make a good agreement with other results, but the confidence interval is slightly different.

OriginalsprogEngelsk
TidsskriftJournal of Cosmology and Astroparticle Physics
Vol/bind2011
Udgave nummer4
Sider (fra-til)018
ISSN1475-7516
DOI
StatusUdgivet - 14 apr. 2011

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