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Hauptverfasser: Benko, Matej, Chlebicka, Iwona, Endal, Jørgen, Miasojedow, Błażej
Format: Preprint
Veröffentlicht: 2024
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2405.18034
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author Benko, Matej
Chlebicka, Iwona
Endal, Jørgen
Miasojedow, Błażej
author_facet Benko, Matej
Chlebicka, Iwona
Endal, Jørgen
Miasojedow, Błażej
contents We study the spatially homogeneous granular medium equation \[\partial_tμ=\rm{div}(μ\nabla V)+\rm{div}(μ(\nabla W \ast μ))+Δμ\,,\] within a large and natural class of the confinement potentials $V$ and interaction potentials $W$. The considered problem do not need to assume that $\nabla V$ or $\nabla W$ are globally Lipschitz. With the aim of providing particle approximation of solutions, we design efficient forward-backward splitting algorithms. Sharp convergence rates in terms of the Wasserstein distance are provided.
format Preprint
id arxiv_https___arxiv_org_abs_2405_18034
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Convergence rates of particle approximation of forward-backward splitting algorithm for granular medium equations
Benko, Matej
Chlebicka, Iwona
Endal, Jørgen
Miasojedow, Błażej
Numerical Analysis
Computation
We study the spatially homogeneous granular medium equation \[\partial_tμ=\rm{div}(μ\nabla V)+\rm{div}(μ(\nabla W \ast μ))+Δμ\,,\] within a large and natural class of the confinement potentials $V$ and interaction potentials $W$. The considered problem do not need to assume that $\nabla V$ or $\nabla W$ are globally Lipschitz. With the aim of providing particle approximation of solutions, we design efficient forward-backward splitting algorithms. Sharp convergence rates in terms of the Wasserstein distance are provided.
title Convergence rates of particle approximation of forward-backward splitting algorithm for granular medium equations
topic Numerical Analysis
Computation
url https://arxiv.org/abs/2405.18034