Hubble distancing: Focusing on distance measurements in cosmology

TL;DR

This paper emphasizes the importance of accurate distance measurements in cosmology, arguing that focusing solely on the Hubble constant $H_0$ can lead to misleading conclusions about new physics, and advocates for broader sharing of distance data.

Contribution

It introduces the `distanceladder` likelihood package that integrates local distance measurements into cosmological analyses, highlighting the need to prioritize distance data over $H_0$ values.

Findings

Focusing only on $H_0$ can cause spurious detection of new physics.

Accurate distance measurements are crucial for testing cosmological models.

Sharing distance data broadly can improve model constraints.

Abstract

The Hubble-Lemaitre tension is currently one of the most important questions in cosmology. Most of the focus so far has been on reconciling the Hubble constant value inferred from detailed cosmic microwave background measurement with that from the local distance ladder. This emphasis on one number -- namely $H_0$ -- misses the fact that the tension fundamentally arises from disagreements of distance measurements. To be successful, a proposed cosmological model must accurately fit these distances rather than simply infer a given value of $H_0$. Using the newly developed likelihood package `distanceladder', which integrates the local distance ladder into MontePython, we show that focusing on $H_0$ at the expense of distances can lead to the spurious detection of new physics in models which change late-time cosmology. As such, we encourage the observational cosmology community to make their actual distance measurements broadly available to model builders instead of simply quoting their derived Hubble constant values.