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We develop a quantitative contraction framework for Schrodinger and Sinkhorn bridges based on transportation-cost inequalities and Riccati matrix difference equations. Our approach combines logarithmic Sobolev and Talagrand-type…

Optimization and Control · Mathematics 2026-01-21 Pierre Del Moral

The paper considers a linear system of Boltzmann transport equations modelling the evolution of three species of particles, photons, electrons and positrons. The system is coupled because of the collision term (an integral operator). The…

Optimization and Control · Mathematics 2017-02-02 Jouko Tervo , Petri Kokkonen

We study quantum transport properties of an open Heisenberg XXZ spin 1/2 chain driven by a pair of Lindblad jump operators satisfying a global `microcanonical' constraint, i.e. conserving the total magnetization. We will show that this…

Quantum Physics · Physics 2012-08-10 Berislav Buca , Tomaz Prosen

The contribution of this work is twofold. The first part deals with a Hilbert-space version of McCann's celebrated result on the existence and uniqueness of monotone measure-preserving maps: given two probability measures $\rm P$ and $\rm…

Probability · Mathematics 2023-05-23 Alberto González-Sanz , Marc Hallin , Bodhisattva Sen

We consider the multi-marginal optimal transport of aligning several compactly supported marginals on the Heisenberg group to minimize the total cost, which we take to be the sum of the squared Carnot-Carath\'eodory distances from the…

Optimization and Control · Mathematics 2020-06-22 Brendan Pass , Andrea Pinamonti , Mattia Vedovato

A perturbative quantum theory of the two Killing vector reduction of Einstein gravity is constructed. Although the reduced theory inherits from the full one the lack of standard perturbative renormalizability, we show that strict cutoff…

High Energy Physics - Theory · Physics 2007-05-23 P. Forgacs , M. Niedermaier

We consider network routing under random link failures with a desired final distribution. We provide a mathematical formulation of a relaxed transport problem where the final distribution only needs to be close to the desired one. The…

Optimization and Control · Mathematics 2018-01-25 Yongxin Chen , Tryphon Georgiou , Michele Pavon , Allen Tannenbaum

We propose a new geometric framework to address the stability of the Kerr solution to gravitational perturbations in the full sub-extremal range $|a|<M$. Central to our framework is a new formulation of nonlinear gravitational perturbations…

General Relativity and Quantum Cosmology · Physics 2022-11-02 Gabriele Benomio

The dynamical formulation of the optimal transport can be extended through various choices of the underlying geometry (kinetic energy), and the regularization of density paths (potential energy). These combinations yield different…

Machine Learning · Computer Science 2024-07-04 Kirill Neklyudov , Rob Brekelmans , Alexander Tong , Lazar Atanackovic , Qiang Liu , Alireza Makhzani

We propose a greedy mixture reduction algorithm which is capable of pruning mixture components as well as merging them based on the Kullback-Leibler divergence (KLD). The algorithm is distinct from the well-known Runnalls' KLD based method…

Machine Learning · Statistics 2015-08-25 Tohid Ardeshiri , Umut Orguner , Emre Özkan

Entropy regularized optimal transport and its multi-marginal generalization have attracted increasing attention in various applications, in particular due to efficient Sinkhorn-like algorithms for computing optimal transport plans. However,…

Optimization and Control · Mathematics 2023-01-25 Florian Beier , Johannes von Lindheim , Sebastian Neumayer , Gabriele Steidl

In this note, we study an optimal transportation problem arising in density functional theory. We derive an upper bound on the semi-classical Hohenberg-Kohn functional derived by Cotar, Friesecke and Kl\"{u}ppelberg (2012) which can be…

Optimization and Control · Mathematics 2015-06-12 Brendan Pass

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

Kullback-Leibler (KL) divergence is a fundamental concept in information theory that quantifies the discrepancy between two probability distributions. In the context of Variational Autoencoders (VAEs), it serves as a central regularization…

Machine Learning · Computer Science 2026-04-14 Andrés Muñoz , Rodrigo Ramele

Motivated by applications in deep learning, where the global Lipschitz continuity condition is often not satisfied, we examine the problem of sampling from distributions with super-linearly growing log-gradients. We propose a novel tamed…

Statistics Theory · Mathematics 2025-06-06 Iosif Lytras , Sotirios Sabanis , Ying Zhang

In this paper we prove that, within the framework of $RCD^*(K,N)$ spaces with $N < \infty$, the entropic cost (i.e. the minimal value of the Schr\"odinger problem) admits: - a threefold dynamical variational representation, in the spirit of…

Analysis of PDEs · Mathematics 2018-05-17 Nicola Gigli , Luca Tamanini

We present a novel method for mixed-integer optimization problems with multivariate and Lipschitz continuous nonlinearities. In particular, we do not assume that the nonlinear constraints are explicitly given but that we can only evaluate…

Optimization and Control · Mathematics 2023-03-22 Julia Grübel , Richard Krug , Martin Schmidt , Winnifried Wollner

We develop a formalism to treat higher order (nonlinear) metric perturbations of the Kerr spacetime in a Teukolsky framework. We first show that solutions to the linearized Einstein equation with nonvanishing stress tensor can be decomposed…

General Relativity and Quantum Cosmology · Physics 2020-09-15 Stephen R. Green , Stefan Hollands , Peter Zimmerman

Classical optimal transport problem seeks a transportation map that preserves the total mass betwenn two probability distributions, requiring their mass to be the same. This may be too restrictive in certain applications such as color or…

Machine Learning · Statistics 2020-06-15 Laetitia Chapel , Mokhtar Z. Alaya , Gilles Gasso

The quadratically regularized optimal transport problem is empirically known to have sparse solutions: its optimal coupling $\pi_{\varepsilon}$ has sparse support for small regularization parameter $\varepsilon$, in contrast to entropic…

Optimization and Control · Mathematics 2026-02-25 Alberto González-Sanz , Marcel Nutz
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