Planck and reionization history: a model selection view

TL;DR

This paper evaluates Planck's capability to differentiate reionization models in the cosmic microwave background polarization data using Bayesian model selection, highlighting limitations and future prospects.

Contribution

It applies Bayesian model selection to forecast Planck's ability to distinguish reionization models and explores implications for future surveys.

Findings

Planck cannot reliably distinguish between simple reionization models.

Bayesian model averaging is necessary for unbiased optical depth estimates.

Future cosmic variance limited surveys offer improved model discrimination.

Abstract

We use Bayesian model selection tools to forecast the Planck satellite's ability to distinguish between different models for the reionization history of the Universe, using the large angular scale signal in the cosmic microwave background polarization spectrum. We find that Planck is not expected to be able to distinguish between an instantaneous reionization model and a two-parameter smooth reionization model, except for extreme values of the additional reionization parameter. If it cannot, then it will be unable to distinguish between different two-parameter models either. However, Bayesian model averaging will be needed to obtain unbiased estimates of the optical depth to reionization. We also generalize our results to a hypothetical future cosmic variance limited microwave anisotropy survey, where the outlook is more optimistic.