Robust constraints on tensor perturbations from cosmological data: a comparative analysis from Bayesian and frequentist perspectives

Understand

We analyze primordial tensor perturbations using the latest cosmic microwave background and gravitational waves data, focusing on the tensor-to-scalar ratio, $r$, and the tensor spectral tilt, $n_t$.

• Utilizing data from Planck PR4, BICEP/Keck, and LIGO-Virgo-KAGRA, we employ both Bayesian and frequentist methods to provide robust constraints on these parameters.
• Our results indicate more conservative upper limits for $r$ with profile likelihoods compared to Bayesian credible intervals, highlighting the influence of prior selection and volume effects.
• The profile likelihood for $n_t$ shows that the current data do not provide sufficient information to derive quantitative bounds, unless extra assumptions on $r$ are used.