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Transport information geometry I: Riemannian calculus on probability simplex (1803.06360v2)

Published 16 Mar 2018 in math.DG, cs.IT, and math.IT

Abstract: We formulate the Riemannian calculus of the probability set embedded with $L2$-Wasserstein metric. This is an initial work of transport information geometry. Our investigation starts with the probability simplex (probability manifold) supported on vertices of a finite graph. The main idea is to embed the probability manifold as a submanifold of the positive measure space with a nonlinear metric tensor. Here the nonlinearity comes from the linear weighted Laplacian operator. By this viewpoint, we establish torsion-free Christoffel symbols, Levi-Civita connections, curvature tensors and volume forms in the probability manifold by Euclidean coordinates. As a consequence, the Jacobi equation, Laplace-Beltrami and Hessian operators on the probability manifold are derived. These geometric computations are also provided in the infinite-dimensional density space (density manifold) supported on a finite-dimensional manifold. In particular, an identity is given connecting the Baker-{\'E}mery $\Gamma_2$ operator (carr{\'e} du champ it{\'e}r{\'e}) by connecting Fisher-Rao information metric and optimal transport metric. Several examples are demonstrated.

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