Examining the cosmic acceleration with the latest Union2 supernova data

TL;DR

This study analyzes the cosmic expansion history using the latest supernova, BAO, and CMB data, revealing tensions between low and high redshift observations and highlighting the impact of systematic errors on conclusions about cosmic acceleration.

Contribution

It reconstructs the cosmic expansion history with updated data and examines the effects of systematic errors and data subsamples on the acceleration trend.

Findings

Union2+BAO favors decreasing acceleration at low z

Adding CMB data suggests ongoing acceleration, causing tension

Systematic errors significantly influence the interpretation of acceleration trends

Abstract

In this Letter, by reconstructing the $Om$ diagnostic and the deceleration parameter $q$ from the latest Union2 Type Ia supernova sample with and without the systematic error along with the baryon acoustic oscillation (BAO) and the cosmic microwave background (CMB), we study the cosmic expanding history, using the Chevallier-Polarski-Linder (CPL) parametrization. We obtain that Union2+BAO favor an expansion with a decreasing of the acceleration at $z<0.3$. However, once the CMB data is added in the analysis, the cosmic acceleration is found to be still increasing, indicating a tension between low redshift data and high redshift one. In order to reduce this tension significantly, two different methods are considered and thus two different subsamples of Union2 are selected. We then find that two different subsamples+BAO+CMB give completely different results on the cosmic expanding history when the systematic error is ignored, with one suggesting a decreasing cosmic acceleration, the other just the opposite, although both of them alone with BAO support that the cosmic acceleration is slowing down. However, once the systematic error is considered, two different subsamples of Union2 along with BAO and CMB all favor an increasing of the present cosmic acceleration. Therefore a clear-cut answer on whether the cosmic acceleration is slowing down calls for more consistent data and more reliable methods to analyze them.