Non-Gaussian inference from non-linear and non-Poisson biased distributed data
Metin Ata, Francisco-Shu Kitaura, Volker Ulrich Müller · arXiv (Cornell University) · 2014
We study the statistical inference of the cosmological dark matter density field from non-Gaussian, non-linear and non-Poisson biased distributed tracers. We have implemented a Bayesian posterior sampling computer-code solving this problem and tested it with mock data based on N-body simulations.