math.FA — Functional Analysis
The -Bures–Wasserstein distance via block matrices (with application to -Bures–Wasserstein barycenters)
We study the -Bures–Wasserstein distance on positive semidefinite matrices; it equals the Bures–Wasserstein distance for , and the Hilbert–Schmidt distance for . We prove that is a metric for every , by proving a stronger 2014 conjecture of Lin and van den Driessche on block matrices. Our main tool is a partition inequality for Schatten norms, proved by complex interpolation. We also characterize Fréchet means for by a fixed-point equation and prove geometric convergence of the associated iteration.
A mix of human-written and AI-generated textHuman understanding: all partsBures-Wasserstein distanceLin-van den Driessche conjectureSchatten normbarycenterscomplex interpolationpartition inequalitypositive semidefinite block matrices