  We derive central limit theorems for the Wasserstein distance between the
empirical distributions of Gaussian samples. The cases are distinguished
whether the underlying laws are the same or different. Results are based on the
(quadratic) Frechet differentiability of the Wasserstein distance in the
Gaussian case. Extensions to elliptically symmetric distributions are discussed
as well as several applications such as bootstrap and statistical testing.
