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Related papers: Transport equation driven by a stochastic measure

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In this Note, we study a transport-diffusion equation with rough coefficients and we prove that solutions are unique in a low-regularity class.

Analysis of PDEs · Mathematics 2016-05-16 Guillaume Lévy

A quantum finite multi-barrier system, with a periodic potential, is considered and exact expressions for its plane wave amplitudes are obtained using the Transfer Matrix method [10]. This quantum model is then associated with a stochastic…

Statistical Mechanics · Physics 2019-06-26 Emilio N. M. Cirillo , Matteo Colangeli , Lamberto Rondoni

The distribution of finite time observable averages and transport in low dimensional Hamiltonian systems is studied. Finite time observable average distributions are computed, from which an exponent $\alpha$ characteristic of how the…

Chaotic Dynamics · Physics 2015-10-28 Lydia Bouchara , Ouerdia Ourrad , Sandro Vaienti , Xavier Leoncini

Given a function $F$ transforming a probability measure $\mu$ into another one $F(\mu)$, we study the existence and regularity of a transport representation of it. That is, we ask whether we can represent the image $F(\mu)$ of the input…

Functional Analysis · Mathematics 2026-04-21 Hugo Lavenant , Giuseppe Savaré

In this paper, we study a connection between disintegration of measures and geometric properties of probability spaces. We prove a disintegration theorem, addressing disintegration from the perspective of an optimal transport problem. We…

Probability · Mathematics 2025-04-09 Renata Possobon , Christian S. Rodrigues

We propose a suitable analytical framework to perform numerical analysis of problems arising in compressible fluid models with uncertain data. We discuss both weak and strong stochastic approach, where the former is based on the knowledge…

Analysis of PDEs · Mathematics 2022-08-24 Eduard Feireisl

In quantum physics, recent investigations deal with the so-called "quantum trajectory" theory. Heuristic rules are usually used to give rise to "stochastic Schrodinger equations" which are stochastic differential equations of non-usual type…

Probability · Mathematics 2009-04-02 Clement Pellegrini

In this article, we introduce the notion of stochastic symmetry of a differential equation. It consists in a stochastic flow that acts over a solution of a differential equation and produces another solution of the same equation. In the…

Probability · Mathematics 2011-12-19 Pedro J. Catuogno , Luis R. Lucinger

The results established by Flandoli, Gubinelli and Priola ({\it Invent. Math.} {\bf 180} (2010) 1--53) for stochastic transport equation with bounded and H\"{o}lder continuous drift are generalized to bounded and Dini continuous drift. The…

Probability · Mathematics 2021-07-29 Jinlong Wei , Guangying Lv , Wei Wang

We consider a one dimensional transport model with nonlocal velocity given by the Hilbert transform and develop a global well-posedness theory of probability measure solutions. Both the viscous and non-viscous cases are analyzed. Both in…

Analysis of PDEs · Mathematics 2011-11-01 J. A. Carrillo , L. C. F. Ferreira , J. C. Precioso

In this paper, we prove a Talagrand's T2 transportation cost-information inequality for the law of a stochastic wave equation in spatial dimension d=3 driven by the Gaussian random field, white in time and correlated in space, on the…

Probability · Mathematics 2019-01-25 Yumeng Li , Xinyu Wang

We investigate the accuracy of the recently proposed nonclassical transport equation. This equation contains an extra independent variable compared to the classical transport equation (the path-length $s$), and models particle transport…

Nuclear Theory · Physics 2016-11-08 Richard Vasques , Kai Krycki , Rachel N. Slaybaugh

Coupling probability measures lies at the core of many problems in statistics and machine learning, from domain adaptation to transfer learning and causal inference. Yet, even when restricted to deterministic transports, such couplings are…

Machine Learning · Statistics 2025-09-22 Lucas De Lara , Luca Ganassali

We study the problem of estimating, in the sense of optimal transport metrics, a measure which is assumed supported on a manifold embedded in a Hilbert space. By establishing a precise connection between optimal transport metrics, optimal…

Machine Learning · Computer Science 2012-09-06 Guillermo D. Canas , Lorenzo Rosasco

Optimal transport has become part of the standard quantitative economics toolbox. It is the framework of choice to describe models of matching with transfers, but beyond that, it allows to: extend quantile regression; identify discrete…

General Economics · Economics 2021-07-13 Alfred Galichon

The mobility of an overdamped particle, in a periodic potential tilted by a constant external field and moving in a medium with periodic friction coefficient is examined. When the potential and the friction coefficient have the same…

Statistical Mechanics · Physics 2009-10-31 Debasis Dan , Mangal C. Mahato , A. M. Jayannavar

We relate transport-entropy inequalities to the study of critical points of functionals defined on the space of probability measures. This approach leads in particular to a new proof of a result by Otto and Villani [43] showing that the…

Probability · Mathematics 2016-04-27 Joaquin Fontbona , Nathael Gozlan , Jean-Francois Jabir

We study ergodic properties of a family of traffic maps acting in the space of bi-infinite sequences of real numbers. The corresponding dynamics mimics the motion of vehicles in a simple traffic flow, which explains the name. Using…

Dynamical Systems · Mathematics 2015-06-11 Michael Blank

We consider probability measures on $\mathbb{R}^{\infty}$ and study optimal transportation mappings for the case of infinite Kantorovich distance. Our examples include 1) quasi-product measures, 2) measures with certain symmetric…

Functional Analysis · Mathematics 2017-10-18 Alexander V. Kolesnikov , Danila A. Zaev

Given two probability measures on sequential data, we investigate the transport problem with time-inconsistent preferences in a discrete-time setting. Motivating examples are nonlinear objectives, state-dependent costs, and regularized…

Optimization and Control · Mathematics 2025-06-23 Erhan Bayraktar , Bingyan Han