Principal components of dark energy with SNLS supernovae: the effects of systematic errors

TL;DR

This paper assesses how systematic errors in Type Ia supernova measurements impact dark energy constraints, finding that systematics significantly degrade the constraints but overall remain robust across multiple parameters.

Contribution

It provides a detailed analysis of the effects of systematic errors on dark energy constraints using principal components, with a focus on SNLS supernova data.

Findings

Systematic errors degrade the figure of merit by a factor of two to three.

Constraints on more than five principal components remain strong despite systematics.

Current constraints are robust to the finite detection significance of BAO features.

Abstract

We study the effects of current systematic errors in Type Ia supernova (SN Ia) measurements on dark energy (DE) constraints using current data from the Supernova Legacy Survey (SNLS). We consider how SN systematic errors affect constraints from combined SN Ia, baryon acoustic oscillations (BAO), and cosmic microwave background (CMB) data, given that SNe Ia still provide the strongest constraints on DE but are arguably subject to more significant systematics than the latter two probes. We focus our attention on the temporal evolution of DE described in terms of principal components (PCs) of the equation of state, though we examine a few of the more common, simpler parametrizations as well. We find that the SN Ia systematics degrade the total generalized figure of merit (FoM), which characterizes constraints in multi-dimensional DE parameter space, by a factor of two to three. Nevertheless, overall constraints obtained on more than five PCs are very good even with current data and systematics. We further show that current constraints are robust to allowing for the finite detection significance of the BAO feature in galaxy surveys.