Exploration of the Pre-recombination Universe with a High-Dimensional Model of an Additional Dark Fluid

TL;DR

This paper explores a high-dimensional dark fluid model extending DM, demonstrating its potential to alleviate the Hubble tension and highlighting the importance of careful statistical analysis.

Contribution

It introduces a generalized high-dimensional dark matter model with an arbitrary redshift-dependent equation of state and discusses strategies to avoid misleading conclusions in data analysis.

Findings

HDGDM model can ease the Hubble tension

Marginalized posteriors may mislead model viability assessments

Best-fitting equations of state reveal features for future model development

Abstract

We implement and explore high-dimensional generalized dark matter (HDGDM) with an arbitrary equation of state as a function of redshift as an extension to {\Lambda}CDM.. Exposing this model to CMB, BAO, and supernova data, we demonstrate that the use of marginalized posterior distributions can easily lead to misleading conclusions on the viability of a high-dimensional model such as this one. We discuss such pitfalls and corresponding mitigation strategies, which can be used to search for an observationally favored region of the parameter space. We further show that the HDGDM model in particular does show promise in terms of its ability to ease the Hubble tension once such techniques are employed, and we find interesting features in the best-fitting equation of state that can serve as an inspiration for future model building.