An Informational Approach to Cosmological Parameter Estimation
  We introduce a new approach for cosmological parameter estimation based on
the information-theoretical Jensen-Shannon divergence (${\cal D}_{\rm JS}$),
calculating it for models in the restricted parameter space $\{H_0, w_0,
w_a\}$, where $H_0$ is the value of the Hubble constant today, and $w_0$ and
$w_a$ are dark energy parameters, with the other parameters held fixed at their
best-fit values from the Planck 2018 data. As an application, we investigate
the $H_0$ tension between the Planck temperature power spectrum data (TT) and
the local astronomical data by comparing the $\Lambda$CDM model with the $w$CDM
and the $w_0w_a$CDM dynamic dark energy models. We find agreement with other
works using the standard Bayesian inference for parameter estimation; in
addition, we show that while the ${\cal D}_{\rm JS}$ is equally minimized for
both values of $H_0$ along the $(w_0,w_a)$ plane, the lines of degeneracy are
different for each value of $H_0$. This allows for distinguishing between the
two, once the value of either $w_0$ or $w_a$ is known.
