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Journal Articles SIAM Journal on Matrix Analysis and Applications Year : 2023

Bures-Wasserstein minimizing geodesics between covariance matrices of different ranks

Abstract

The set of covariance matrices equipped with the Bures-Wasserstein distance is the orbit space of the smooth, proper and isometric action of the orthogonal group on the Euclidean space of square matrices. This construction induces a natural orbit stratification on covariance matrices, which is exactly the stratification by the rank. Thus, the strata are the manifolds of symmetric positive semi-definite (PSD) matrices of fixed rank endowed with the Bures-Wasserstein Riemannian metric. In this work, we study the geodesics of the Bures-Wasserstein distance. Firstly, we complete the literature on geodesics in each stratum by clarifying the set of preimages of the exponential map and by specifying the injection domain. We also give explicit formulae of the horizontal lift, the exponential map and the Riemannian logarithms that were kept implicit in previous works. Secondly, we give the expression of all the minimizing geodesic segments joining two covariance matrices of any rank. More precisely, we show that the set of all minimizing geodesics between two covariance matrices Σ and Λ is parametrized by the closed unit ball of R^(k−r)×(l−r) for the spectral norm, where k, l, r are the respective ranks of Σ, Λ, ΣΛ. In particular, the minimizing geodesic is unique if and only if r = min(k, l). Otherwise, there are infinitely many.
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Dates and versions

hal-03647321 , version 1 (20-04-2022)

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Yann Thanwerdas, Xavier Pennec. Bures-Wasserstein minimizing geodesics between covariance matrices of different ranks. SIAM Journal on Matrix Analysis and Applications, 2023, 44 (3), pp.1447-1476. ⟨10.1137/22M149168X⟩. ⟨hal-03647321⟩
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