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

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