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Related papers: Quantum optimal transport with quantum channels

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We resolve a conjecture of De Palma and Trevisan by proving the triangle inequality for a quantum 2-Wasserstein distance. The proof relies on complex analysis methods to establish a new integral representation of the cost in the optimal…

Mathematical Physics · Physics 2025-11-26 Melchior Wirth

We compare bipartite (Euclidean) matching problems in classical and quantum mechanics. The quantum case is treated in terms of a quantum version of the Wasserstein distance introduced in [F. Golse, C. Mouhot, T. Paul, Commun. Math. Phys.…

Analysis of PDEs · Mathematics 2021-03-19 François Golse , Emanuele Caglioti , Thierry Paul

We set up a general theory for a quantum Wasserstein distance of order 1 in an operator algebraic framework, extending recent work in finite dimensions. In addition, this theory applies not only to states, but also to channels, giving a…

Quantum Physics · Physics 2023-10-05 Rocco Duvenhage , Mathumo Mapaya

We prove a new version of Egorov's theorem formulated in the Schr\"{o}dinger picture of quantum mechanics, using the $p$-Wasserstein metric applied to the Husimi functions of quantum states. The special case $p=1$ corresponds to a…

Quantum Physics · Physics 2025-09-10 Jordan Cotler , Felipe Hernández

We introduce a novel optimal transport framework for probabilistic circuits (PCs). While it has been shown recently that divergences between distributions represented as certain classes of PCs can be computed tractably, to the best of our…

Artificial Intelligence · Computer Science 2025-10-16 Adrian Ciotinga , YooJung Choi

We study the behavior of the Wasserstein-$2$ distance between discrete measures $\mu$ and $\nu$ in $\mathbb{R}^d$ when both measures are smoothed by small amounts of Gaussian noise. This procedure, known as Gaussian-smoothed optimal…

Statistics Theory · Mathematics 2022-06-15 Yunzi Ding , Jonathan Niles-Weed

We investigate quantum teleportation of ensembles of coherent states of light with a Gaussian distributed displacement in phase space. Recently, the following general question has been addressed in [P. Liuzzo-Scorpo et al.,…

Quantum Physics · Physics 2017-11-29 Pietro Liuzzo-Scorpo , Gerardo Adesso

Quadratic Wasserstein distances are obtained between dynamical systems (with states as special case), on $\mathbb{Z}_2$-graded von Neumann algebras. This is achieved through a systematic translation from non-graded to $\mathbb{Z}_2$-graded…

Mathematical Physics · Physics 2025-10-06 Rocco Duvenhage , Dylan van Zyl , Paola Zurlo

A generalization of the Wasserstein metric, the integrated transportation distance, establishes a novel distance between probability kernels of Markov systems. This metric serves as the foundation for an efficient approximation technique,…

Machine Learning · Computer Science 2023-12-07 Zhengqi Lin , Andrzej Ruszczynski

We determine the isometry group of the $n$-qubit state space with respect to the quantum Wasserstein distance induced by the so-called symmetric transport cost for all $n \in \mathbb{N}.$ It turns out that the isometries are precisely the…

Mathematical Physics · Physics 2026-02-10 Gergely Bunth , Eszter Szabó , Dániel Virosztek

There has been much work in the recent past in developing the idea of quantum geometry to characterize and understand the structure of many-particle states. For mean-field states, the quantum geometry has been defined and analysed in terms…

Strongly Correlated Electrons · Physics 2019-06-03 S. R. Hassan , Ankita Chakrabarti , R. Shankar

A quantum version of the Monge--Kantorovich optimal transport problem is analyzed. The transport cost is minimized over the set of all bipartite coupling states $\rho^{AB}$, such that both of its reduced density matrices $\rho^A$ and…

Quantum Physics · Physics 2022-09-21 Shmuel Friedland , Michał Eckstein , Sam Cole , Karol Życzkowski

We establish novel quantitative stability results for optimal transport problems with respect to perturbations in the target measure. We provide explicit bounds on the stability of optimal transport potentials and maps, which are relevant…

Functional Analysis · Mathematics 2026-05-12 Octave Mischler , Dario Trevisan

We consider several definitions of the quantum Wasserstein distance based on an optimization over general bipartite quantum states with given marginals. Then, we examine the quantities obtained after the optimization is carried out over…

Quantum Physics · Physics 2026-05-15 Géza Tóth , József Pitrik

We prove new concentration inequalities for quantum spin systems which apply to any local observable measured on any product state or on any state with exponentially decaying correlations. Our results do not require the spins to be arranged…

Mathematical Physics · Physics 2025-06-17 Giacomo De Palma , Davide Pastorello

Quantum teleportation of qudits is revisited. In particular, we analyze the case where the quantum channel corresponds to a non-maximally entangled state and show that the success of the protocol is directly related to the problem of…

Quantum Physics · Physics 2009-11-10 L. Roa , A. Delgado , I. Fuentes-Guridi

Let $\mathsf{H}$ be a separable Hilbert space. We prove that the Grassmannian $\mathsf{P}_c(\mathsf{H})$ of the finite dimensional subspaces of $\mathsf{H}$ is an Alexandrov space of nonnegative curvature and we employ its metric geometry…

Differential Geometry · Mathematics 2021-04-07 Paolo Antonini , Fabio Cavalletti

We study the Kimble-Braunstein continuous-variable quantum teleportation with the quantum channel physically realized in the turbulent atmosphere. In this context, we examine the applicability of different strategies preserving the Gaussian…

Quantum Physics · Physics 2019-09-27 K. Hofmann , A. A. Semenov , W. Vogel , Martin Bohmann

We develop a general approach to setting up and studying classes of quantum dynamical systems close to and structurally similar to systems having specified properties, in particular detailed balance. This is done in terms of transport plans…

Quantum Physics · Physics 2025-05-13 Rocco Duvenhage , Samuel Skosana , Machiel Snyman

The adapted Wasserstein distance is a metric for quantifying distributional uncertainty and assessing the sensitivity of stochastic optimization problems on time series data. A computationally efficient alternative to it, is provided by the…

Optimization and Control · Mathematics 2025-10-10 Beatrice Acciaio , Songyan Hou , Gudmund Pammer