Quantitative equidistribution of eigenvalues of Random Normal Matrices in the Wasserstein distance

The object of study in this paper is the expected $2$-Wasserstein distance between the empirical measures of several point processes and their respective limit. For this, the main tool developed is a smoothing procedure in Euclidean spaces using the heat equation with Neumann boundary conditions. It is applied to the spectrum of Random Normal Matrices with $\mathit{\text{reasonable}}$ assumptions, as well as to several families of Homogeneous Point Processes such as the infinite Ginibre ensemble, the Bessel ensemble, and the zero set of the planar Gaussian Analytic Function.