Crossing Statistic: Reconstructing the Expansion History of the Universe

TL;DR

This paper introduces a novel method combining Crossing Statistic and Smoothing techniques to accurately reconstruct the universe's expansion history without relying on prior assumptions, applicable to various dark energy models.

Contribution

The paper presents a new non-parametric reconstruction method that performs well across different dark energy models and data sets, improving over previous methods.

Findings

Reconstructed expansion history aligns with flat LCDM model.

Supernovae and BAO data are consistent with each other.

Method is model-independent and highly precise.

Abstract

We present that by combining Crossing Statistic and Smoothing method one can reconstruct the expansion history of the universe with a very high precision without considering any prior on the cosmological quantities such as the equation of state of dark energy. We show that the presented method performs very well in reconstruction of the expansion history of the universe independent of the underlying models and it works well even for non-trivial dark energy models with fast or slow changes in the equation of state of dark energy. Accuracy of the reconstructed quantities along with independence of the method to any prior or assumption gives the proposed method advantages to the other non-parametric methods proposed before in the literature. Applying on the Union 2.1 supernovae combined with WiggleZ BAO data we present the reconstructed results and test the consistency of the two data sets in a model independent manner. Results show that latest available supernovae and BAO data are in good agreement with each other and spatially flat LCDM model is in concordance with the current data.