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## Euclidean Distance Matrices and Separations in Communication Complexity Theory

A Euclidean distance matrix D(α) is defined by D_ij=(α_i−α_j)^2, where α=(α_1,…,α_n) is a real vector. We prove that D(α) cannot be written as a sum of [2sqrt(n)−2] nonnegative rank-one matrices, provided that the coordinates of α are algebraically independent. As a corollary, we provide an asymptotically optimal separation between the complexities of quantum and classical communication protocols computing a given matrix in expectation.