Abstract

In this work we show the results obtained applying a Unified Dark Matter (UDM) model with a fast transition to a set of cosmological data. Two different functions to model the transition are tested, and the feasibility of both models is explored using CMB shift data from Planck [1], Galaxy Clustering data from [2] and [3], and Union2.1 SNe Ia[4]. These new models are also statistically compared with the ACDM and quiessencemodels using Bayes factor through evidence. Bayesian inference does not discard the UDM models in favor of ACDM.

Highlights

  • In Unified Dark Matter (UDM) models the role of the dark energy and dark matter are played by a single fluid

  • Fast transition UDM models with scalar fields are compatible with observational data [9]

  • The Galaxy Clustering (GC) data we use are the measurements of H(z)rs(zd)/c and DA(z)/rs(zd) from the two dimensional two-point correlation function measured at z = 0.35 by [2] using a SDSS DR7 Luminous Red Galaxies sample, and at z = 0.57 by [3] using the CMASS galaxy sample from BOSS

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Summary

Introduction

In Unified Dark Matter (UDM) models the role of the dark energy and dark matter are played by a single fluid. Among the different UDM models, the ones with fast transitions are very interesting. In principle these models can be clearly distinguished from a standard ΛCDM without being ruled out by observational data. Whereas this is not the case for the generalized Chaplygin gas [7]. UDM models with fast transitions can provide an alternative explanation of the accelerated expansion of the universe [8], as they can fit the experimental data quite well, while they provide interesting and different new features.

UDM Models
GC data
SNe Ia data
Discussion
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