Discovering a new well: Decaying dark matter with profile likelihoods

Understand

A large number of studies, all using Bayesian parameter inference from Markov Chain Monte Carlo methods, have constrained the presence of a decaying dark matter component.

• All such studies find a strong preference for either very long-lived or very short-lived dark matter.
• However, in this letter, we demonstrate that this preference is due to parameter volume effects that drive the model towards the standard $\Lambda$CDM model, which is known to provide a good fit to most observational data.
• Using profile likelihoods, which are free from volume effects, we instead find that the best-fitting parameters are associated with an intermediate regime where around $3 \%$ of cold dark matter decays just prior to recombination.