{"title":"Bures–Wasserstein Minimizing Geodesics between Covariance Matrices of Different Ranks","authors":"Yann Thanwerdas, Xavier Pennec","doi":"10.1137/22m149168x","DOIUrl":null,"url":null,"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 semidefinite matrices of fixed rank endowed with the Bures–Wasserstein Riemannian metric. In this work, we study the geodesics of the Bures–Wasserstein distance. First, we complete the literature on geodesics in each stratum by clarifying the set of preimages of the exponential map and by specifying the injectivity domain. We also give explicit formulae of the horizontal lift, the exponential map, and the Riemannian logarithms that were kept implicit in previous works. Second, 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 and is parametrized by the closed unit ball of for the spectral norm, where are the respective ranks of . In particular, the minimizing geodesic is unique if and only if . Otherwise, there are infinitely many. As a secondary contribution, we provide a review of the definitions related to geodesics in metric spaces, affine connection manifolds, and Riemannian manifolds, which is helpful for the study of other spaces.","PeriodicalId":49538,"journal":{"name":"SIAM Journal on Matrix Analysis and Applications","volume":"22 1","pages":"0"},"PeriodicalIF":1.5000,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIAM Journal on Matrix Analysis and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1137/22m149168x","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 1
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 semidefinite matrices of fixed rank endowed with the Bures–Wasserstein Riemannian metric. In this work, we study the geodesics of the Bures–Wasserstein distance. First, we complete the literature on geodesics in each stratum by clarifying the set of preimages of the exponential map and by specifying the injectivity domain. We also give explicit formulae of the horizontal lift, the exponential map, and the Riemannian logarithms that were kept implicit in previous works. Second, 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 and is parametrized by the closed unit ball of for the spectral norm, where are the respective ranks of . In particular, the minimizing geodesic is unique if and only if . Otherwise, there are infinitely many. As a secondary contribution, we provide a review of the definitions related to geodesics in metric spaces, affine connection manifolds, and Riemannian manifolds, which is helpful for the study of other spaces.
期刊介绍:
The SIAM Journal on Matrix Analysis and Applications contains research articles in matrix analysis and its applications and papers of interest to the numerical linear algebra community. Applications include such areas as signal processing, systems and control theory, statistics, Markov chains, and mathematical biology. Also contains papers that are of a theoretical nature but have a possible impact on applications.