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We introduce a novel quantum algorithm for the lattice Boltzmann method (LBM) based on the one-step simplified LBM. The structure of the algorithm allows for more flexibility in modelling different physics in contrast to earlier quantum…

In this paper, a regularization of Wasserstein barycenters for random measures supported on $\mathbb{R}^{d}$ is introduced via convex penalization. The existence and uniqueness of such barycenters is first proved for a large class of…

Statistics Theory · Mathematics 2019-03-20 Jérémie Bigot , Elsa Cazelles , Nicolas Papadakis

The lattice Boltzmann method (LBM) has gained increasing popularity in incompressible viscous flow simulations, but it uses many more variables than necessary. This defect was overcome by a recent approach that solves the more actual…

Fluid Dynamics · Physics 2021-06-02 Jun-Jie Huang

We propose a novel probabilistic approach to multilevel clustering problems based on composite transportation distance, which is a variant of transportation distance where the underlying metric is Kullback-Leibler divergence. Our method…

Machine Learning · Computer Science 2018-10-30 Nhat Ho , Viet Huynh , Dinh Phung , Michael I. Jordan

We derive the partial differential equation (PDE) to which the pseudo-potential lattice Boltzmann method (P-LBM) converges under diffusive scaling, providing a rigorous basis for its consistency analysis. By establishing a direct link…

In [Q. Liao et al., Commun. Math. Sci., 20(2022)], a linear-time Sinkhorn algorithm is developed based on dynamic programming, which significantly reduces the computational complexity involved in solving optimal transport problems. However,…

Optimization and Control · Mathematics 2025-03-25 Ziyuan Lyu , Zihao Wang , Hao Wu , Shuai Yang

Variational problems that involve Wasserstein distances and more generally optimal transport (OT) theory are playing an increasingly important role in data sciences. Such problems can be used to form an examplar measure out of various…

Machine Learning · Computer Science 2018-11-15 Marco Cuturi , Gabriel Peyré

In this paper, we study the problem of sampling from a given probability density function that is known to be smooth and strongly log-concave. We analyze several methods of approximate sampling based on discretizations of the (highly…

Statistics Theory · Mathematics 2024-02-26 Arnak S. Dalalyan , Avetik G. Karagulyan

We consider the rate-limited quantum-to-classical optimal transport in terms of output-constrained rate-distortion coding for both finite-dimensional and continuous-variable quantum-to-classical systems with limited classical common…

Quantum Physics · Physics 2023-11-30 Hafez M. Garmaroudi , S. Sandeep Pradhan , Jun Chen

An efficient method for computing solutions to the Optimal Transportation (OT) problem with a wide class of cost functions is presented. The standard linear programming (LP) discretization of the continuous problem becomes intractible for…

Numerical Analysis · Mathematics 2015-09-15 Adam M. Oberman , Yuanlong Ruan

We define a metric in the space of positive finite positive measures that extends the 2-Wasserstein metric, i.e. its restriction to the set of probability measures is the 2-Wasserstein metric. We prove a dual and a dynamic formulation and…

Metric Geometry · Mathematics 2023-03-07 Hugo Leblanc , Thibaut Le Gouic , Jacques Liandrat , Magali Tournus

Bipartite graphs are ubiquitous across various scientific and engineering fields. Simultaneously grouping the two types of nodes in a bipartite graph via biclustering represents a fundamental challenge in network analysis for such graphs.…

Machine Learning · Statistics 2024-06-07 Yunpeng Zhao , Ning Hao , Ji Zhu

We show that the variance of a probability measure $\mu$ on a compact subset $X$ of a complete metric space $M$ is bounded by the square of the circumradius $R$ of the canonical embedding of $X$ into the space $P(M)$ of probability measures…

Probability · Mathematics 2020-06-05 Brendan Pass

The lattice Boltzmann method (LBM) is emerging as a powerful engineering tool for aeroacoustic computations. However, the LBM has been shown to present accuracy and stability issues in the medium-low Mach number range, that is of interest…

Fluid Dynamics · Physics 2017-11-22 Federico Brogi , Orestis Malaspinas , Bastien Chopard , Costanza Bonadonna

This work outlines a Lattice Boltzmann Method (LBM) for geometrically and constitutively nonlinear solid mechanics to simulate large deformations under dynamic loading conditions. The method utilizes the moment chain approach, where the…

Computational Engineering, Finance, and Science · Computer Science 2025-07-02 Henning Müller , Erik Faust , Alexander Schlüter , Ralf Müller

The optimal transport barycenter (a.k.a. Wasserstein barycenter) is a fundamental notion of averaging that extends from the Euclidean space to the Wasserstein space of probability distributions. Computation of the unregularized barycenter…

Machine Learning · Statistics 2025-05-27 Kaheon Kim , Rentian Yao , Changbo Zhu , Xiaohui Chen

The aim of this article is to propose a new reduced-order modelling approach for parametric eigenvalue problems arising in electronic structure calculations. Namely, we develop nonlinear reduced basis techniques for the approximation of…

Numerical Analysis · Mathematics 2025-11-19 Maxime Dalery , Genevieve Dusson , Virginie Ehrlacher , Alexei Lozinski

The simplified lattice Boltzmann method (SLBM) is a recent development in the lattice Boltzmann method (LBM) community, addressing the intrinsic limitations of the traditional LBM by directly evolving macroscopic quantities and maintaining…

Fluid Dynamics · Physics 2026-05-29 Zhengwei He , Zhen Chen

Due to its invariance to rigid transformations such as rotations and reflections, Procrustes-Wasserstein (PW) was introduced in the literature as an optimal transport (OT) distance, alternative to Wasserstein and more suited to tasks such…

Machine Learning · Statistics 2025-07-02 Davide Adamo , Marco Corneli , Manon Vuillien , Emmanuelle Vila

We propose a variational technique to optimize for generalized barycentric coordinates that offers additional control compared to existing models. Prior work represents barycentric coordinates using meshes or closed-form formulae, in…

Graphics · Computer Science 2023-10-09 Ana Dodik , Oded Stein , Vincent Sitzmann , Justin Solomon