LARGE SAMPLE THEORY FOR BURES-WASSERSTEIN BARYCENTRES

We establish a strong law of large numbers and a central limit theorem in the Bures-Wasserstein space of covariance operators-or equivalently centred Gaussian measures-over a general separable Hilbert space. Specifically, we show that empirical barycentre sequences indexed by sample size are almost certainly relatively compact, with accumulation points comprising population barycentres. We give a sufficient regularity condition for the limit to be unique. When the limit is unique, we also establish a central limit theorem under a refined pair of moment and regularity conditions. Finally, we prove strong operator convergence of the empirical optimal transport maps to their population counterparts. Though our results naturally extend finite-dimensional counterparts, including associated regularity conditions, our techniques are distinctly different owing to the functional nature of the problem in the general setting. A key element is the characterisation of compact sets in the Bures-Wasserstein topology that reflects an ordered Heine-Borel property of the Bures-Wasserstein space.