  In this paper we bring together some of the key ideas and methods of two
disparate fields of mathematical research, frame theory and optimal transport,
using the methods of the second to answer questions posed in the first. In
particular, we construct gradient flows in the Wasserstein space
$P_2(\mathbb{R}^d)$ for a new potential, the tightness potential, which is a
modification of the probabilistic frame potential. It is shown that the
potential is suited for the application of a gradient descent scheme from
optimal transport that can be used as the basis of an algorithm to evolve an
existing frame toward a tight probabilistic frame.

Functional Analysis