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arxiv: 2512.01722 · v4 · pith:6HIHITNAnew · submitted 2025-12-01 · 🧮 math.FA · math-ph· math.MP· quant-ph

Folded optimal transport and its application to separable quantum optimal transport

classification 🧮 math.FA math-phmath.MPquant-ph
keywords optimaltransportfoldedconvexcostquantumdistanceseparable
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We introduce folded optimal transport, as a method to extend a cost or distance defined on the extreme boundary of a convex to the whole convex, related to convex extension. This construction broadens the framework of standard optimal transport, found to be the particular case of the convex being a simplex. Relying on Choquet's theory and standard optimal transport, we introduce the folded Kantorovich cost and folded Wasserstein distances, and study their induced metric properties. We then apply the construction to the quantum setting, and obtain an actual separable quantum Wasserstein distance on the set of density matrices from a distance on the set of pure states, closely related to the semi-distance of Beatty and Stilck-Franca [4], and of which we obtain a variety of properties. We also find that the semiclassical Golse-Paul [16] cost writes as a folded Kantorovich cost. Folded optimal transport therefore provides a unified framework for classical, semiclassical and separable quantum optimal transport.

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  1. Relations between different definitions of the quantum Wasserstein distance for qubits

    quant-ph 2026-05 unverdicted novelty 5.0

    Two quantum Wasserstein distance definitions coincide for qubits with single-operator cost functions, implying the self-distance equals the Wigner-Yanase skew information.