Cosmological parameter inference from galaxy clustering: the effect of the posterior distribution of the power spectrum - Kalus, B.; Percival, W. J.; Samushia, Lado (My University, 2016)
We consider the shape of the posterior distribution to be used when fitting cosmological models to power spectra measured from galaxy surveys. At very large scales, Gaussian posterior distributions in the power do not approximate the posterior distribution P-R we expect for a Gaussian density field delta(k), even if we vary the covariance matrix according to the model to be tested. We compare alternative posterior distributions with P-R, both mode-by-mode and in terms of expected measurements of primordial non-Gaussianity parametrized by f(NL). Marginalising over a Gaussian posterior distribution P-f with fixed covariance matrix yields a posterior mean value of f(NL) which, for a data set with the characteristics of Euclid, will be underestimated by Delta f(NL) = 0.4, while for the data release 9 of the Sloan Digital Sky Survey-III Baryon Oscillation Spectroscopic Survey (BOSS DR9; Ahn et al.) it will be underestimated by Delta f(NL) = 19.1. Adopting a different form of the posterior function means that we do not necessarily require a different covariance matrix for each model to be tested: this dependence is absorbed into the functional form of the posterior. Thus, the computational burden of analysis is significantly reduced.
Citation: Kalus, B., Percival, W. J., & Samushia, L. (2016). YCosmological parameter inference from galaxy clustering: the effect of the posterior distribution of the power spectrum. Monthly Notices of the Royal Astronomical Society, 455(3), 2573-2581. doi:10.1093/mnras/stv2307
Keywords: Methods: Statistical; Inflation; Large-Scale Structure Of Universe; Primordial Non-Gaussianity; Oscillation Spectroscopic Survey; Sdss-Iii