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2019

Primordial power spectrum and cosmology from black-box galaxy surveys

Leclercq, Florent, Enzi, Wolfgang, Jasche, Jens et al.

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We propose a new, likelihood-free approach to inferring the primordial matter power spectrum and cosmological parameters from arbitrarily complex forward models of galaxy surveys where all relevant statistics can be determined from numerical simulations, i.e.

black-boxes.
Our approach, which we call simulator expansion for likelihood-free inference (SELFI), builds upon approximate Bayesian computation using a novel effective likelihood, and upon the linearisation of black-box models around an expansion point.
Consequently, we obtain simple "filter equations" for an effective posterior of the primordial power spectrum, and a straightforward scheme for cosmological parameter inference.

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