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The theory of optimal transport of probability measures has wide-ranging applications across a number of different fields, including concentration of measure, machine learning, Markov chains, and economics. The generalisation of optimal…

Quantum Physics · Physics 2026-04-21 Emily Beatty

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

We study a class of quadratic Wasserstein distances on spaces consisting of generalized dynamical systems on a von Neumann algebra. We emphasize how symmetry of such a Wasserstein distance arises, but also study the asymmetric case. This…

Operator Algebras · Mathematics 2024-11-05 Rocco Duvenhage

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 define the quantum Wasserstein distance such that the optimization of the coupling is carried out over bipartite separable states rather than bipartite quantum states in general, and examine its properties. Surprisingly, we find that the…

Quantum Physics · Physics 2023-10-17 Géza Tóth , József Pitrik

Distinguishing quantum states with minimal sampling overhead is of fundamental importance to teach quantum data to an algorithm. Recently, the quantum Wasserstein distance emerged from the theory of quantum optimal transport as a promising…

Quantum Physics · Physics 2025-12-02 Gonzalo Camacho , Benedikt Fauseweh

In this work we build a theoretical framework for the transport of information in quantum systems. This is a framework aimed at describing how out of equilibrium open quantum systems move information around their state space, using an…

Quantum Physics · Physics 2021-07-23 F. Anza

These notes are based on the lectures given by the second author at the School on Optimal Transport on Quantum Structures at Erd\"os Center in September 2022. The focus of the exposition is on two recently introduced approaches on quantum…

Mathematical Physics · Physics 2025-01-07 Giacomo De Palma , Dario Trevisan

To study discrete dynamical systems of different types --- deterministic, statistical and quantum --- we develop various approaches. We introduce the concept of a system of discrete relations on an abstract simplicial complex and develop…

Mathematical Physics · Physics 2010-11-10 Vladimir V. Kornyak

We study a connection between quantum detailed balance, which is a concept of importance in statistical mechanics, and entanglement. We also explore how this connection fits into thermofield dynamics.

Quantum Physics · Physics 2015-03-30 Rocco Duvenhage , Machiel Snyman

Topological Data Analysis methods can be useful for classification and clustering tasks in many different fields as they can provide two dimensional persistence diagrams that summarize important information about the shape of potentially…

Quantum Physics · Physics 2024-09-02 Bernardo Ameneyro , Rebekah Herrman , George Siopsis , Vasileios Maroulas

We propose a new generalization to quantum states of the Wasserstein distance, which is a fundamental distance between probability distributions given by the minimization of a transport cost. Our proposal is the first where the transport…

Mathematical Physics · Physics 2021-09-21 Giacomo De Palma , Dario Trevisan

Optimal transport provides a powerful mathematical framework with applications spanning numerous fields. A cornerstone within this domain is the $p$-Wasserstein distance, which serves to quantify the cost of transporting one probability…

Quantum Physics · Physics 2025-03-13 Emily Beatty , Daniel Stilck França

We present a toolkit of directed distances between quantile functions. By employing this, we solve some new optimal transport (OT) problems which e.g. considerably flexibilize some prominent OTs expressed through Wasserstein distances.

Information Theory · Computer Science 2021-07-02 Wolfgang Stummer

The late-time dynamics of quantum many-body systems is organized in distinct dynamical universality classes, characterized by their conservation laws and thus by their emergent hydrodynamic transport. Here, we study transport in the…

Quantum Gases · Physics 2022-08-30 Philip Zechmann , Alvise Bastianello , Michael Knap

We introduce quantum association schemes. This allows to define distance regular and strongly regular quantum graphs. We bring examples thereof. In addition, we formulate the duality for translation quantum association schemes corresponding…

Quantum Algebra · Mathematics 2026-02-10 Daniel Gromada

Optimal transport between classical probability distributions has been proven useful in areas such as machine learning and random combinatorial optimization. Quantum optimal transport, and the quantum Wasserstein distance as the minimal…

We discuss recent findings about properties of quantum nonequilibrium steady states. In particular we focus on transport properties. It is shown that the time dependent density matrix renormalization method can be used successfully to find…

Quantum Physics · Physics 2011-11-15 Marko Znidaric

Recent years have seen tremendous progress in the theoretical understanding of quantum systems driven dissipatively by coupling them to different baths at their edges. This was possible because of the concurrent advances in the models used…

Quantum Physics · Physics 2022-12-15 Gabriel T. Landi , Dario Poletti , Gernot Schaller

We study the discretization of generalized Wasserstein distances with nonlinear mobilities on the real line via suitable discrete metrics on the cone of N ordered particles, a setting which naturally appears in the framework of…

Analysis of PDEs · Mathematics 2022-09-01 Simone Di Marino , Lorenzo Portinale , Emanuela Radici
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