Cosmic expansion history from SNe Ia data via information field theory -- the charm code

TL;DR

This paper introduces charm, a novel Bayesian inference algorithm based on information field theory, to reconstruct the cosmic expansion history from supernova data without assuming a specific parametric form.

Contribution

The paper presents a new non-parametric, Bayesian method using information field theory to reconstruct the cosmic expansion history from supernova data.

Findings

Reconstructed expansion history consistent with ΛCDM model.

Method effectively infers density evolution without assuming a specific form.

Compatible with Planck mission cosmological parameters.

Abstract

We present charm (cosmic history agnostic reconstruction method), a novel inference algorithm that reconstructs the cosmic expansion history as encoded in the Hubble parameter $H(z)$ from SNe Ia data. The novelty of the approach lies in the usage of information field theory, a statistical field theory that is very well suited for the construction of optimal signal recovery algorithms. The charm algorithm infers non-parametrically $s(a)=\ln(\rho(a)/\rho_{\mathrm{crit}0})$, the density evolution which determines $H(z)$, without assuming an analytical form of $\rho(a)$ but only its smoothness with the scale factor $a=(1+z)^{-1}$. The inference problem of recovering the signal $s(a)$ from the data is formulated in a fully Bayesian way. In detail, we have rewritten the signal as the sum of a background cosmology and a perturbation. This allows us to determine the maximum a posteriory estimate of the signal by an iterative Wiener filter method. Applying charm to the Union2.1 supernova compilation, we have recovered a cosmic expansion history that is fully compatible with the standard $\Lambda$CDM cosmological expansion history with parameter values consistent with the results of the Planck mission.