pkann – II. A non-linear matter power spectrum interpolator developed using artificial neural networks

This is the published version. Copyright © 2014 The Authors Published by Oxford University Press on behalf of the Royal Astronomical SocietyIn this paper we introduce pkann, a freely available software package for interpolating the non-linear matter power spectrum, constructed using artificial neural networks (ANNs). Previously, using halofit to calculate matter power spectrum, we demonstrated that ANNs can make extremely quick and accurate predictions of the power spectrum. Now, using a suite of 6380 N-body simulations spanning 580 cosmologies, we train ANNs to predict the power spectrum over the cosmological parameter space spanning 3σ confidence level around the concordance cosmology. When presented with a set of cosmological parameters (Ωmh2, Ωbh2, ns, w, σ8, ∑mν and redshift z), the trained ANN interpolates the power spectrum for z ≤ 2 at sub-per cent accuracy for modes up to k≤ 0.9 h Mpc−1. pkann is faster than computationally expensive N-body simulations, yet provides a worst-case error 0.5 eV, predictions are expected to be at 5 (10) per cent level for redshifts z > 1 (z ≤ 1). The pkann interpolator may be freely downloaded from http://zuserver2.star.ucl.ac.uk/∼fba/PkANN