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 $\mathrm{\Lambda }$ cold dark matter. Exposing this model to cosmic microwave background, baryon acoustic oscillations, 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.

• Received 25 August 2023
• Accepted 9 October 2023

DOI:https://doi.org/10.1103/PhysRevD.108.103527