Exploring uncertainties in dark energy constraints using current observational data with Planck 2015 distance priors
Yun Wang, and Mi Dai

TL;DR
This study combines Planck 2015 data with supernovae and galaxy clustering observations to assess systematic uncertainties in dark energy constraints, finding flux-averaging of supernovae notably tightens constraints and suggests current measurements are systematics-limited.
Contribution
It introduces derived Planck distance priors and demonstrates how flux-averaging supernovae impacts dark energy constraints, highlighting the importance of systematic uncertainty reduction.
Findings
Flux-averaging supernovae significantly tightens dark energy constraints.
Systematic uncertainties in galaxy clustering are minimal with current methods.
Measured dark energy density function deviates from a cosmological constant at 95% confidence.
Abstract
We present the distance priors that we have derived from the 2015 Planck data, and use these in combination with the latest observational data from Type Ia Supernovae (SNe Ia) and galaxy clustering, to explore the systematic uncertainties in dark energy constraints. We use the Joint Lightcurve Analysis (JLA) set of 740 SNe Ia, galaxy clustering measurements of H(z)s and D_A(z)/s (where s is the sound horizon at the drag epoch) from the Sloan Digital Sky Survey (SDSS) at z=0.35 and z=0.57 (BOSS DR12). We find that the combined dark energy constraints are insensitive to the assumptions made in the galaxy clustering measurements (whether they are for BAO only or marginalized over RSD), which indicates that as the analysis of galaxy clustering data becomes more accurate and robust, the systematic uncertainties are reduced. On the other hand, we find that flux-averaging SNe Ia at z>= 0.5…
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