Semi-discrete optimal transport techniques for the compressible semi-geostrophic equations

Mathematics > Analysis of PDEs [Submitted on 29 Apr 2025 (v1), last revised 16 Jun 2026 (this version, v2)] Title:Semi-discrete optimal transport techniques for the compressible semi-geostrophic equations View PDF HTML (experimental)Abstract:We prove existence of weak solutions of the 3D compressible semi-geostrophic (SG) equations with compactly supported measure-valued initial data. These equations model large-scale atmospheric flows. Our proof uses a particle discretisation and semi-discrete optimal transport techniques. We show that, if the initial data is a discrete measure, then the compressible SG equations admit a unique, twice continuously differentiable, energy-conserving and global-in-time solution. In general, by discretising the initial measure by particles and sending the number of particles to infinity, we show that for any compactly supported initial measure there exists a global-in-time solution of the compressible SG equations that is Lipschitz in time. This significantly generalises the original results due to Cullen and Maroofi (2003), and it provides the theoretical foundation for the design of numerical schemes using semi-discrete optimal transport to solve the 3D compressible SG equations. Submission history From: Théo Lavier [view email][v1] Tue, 29 Apr 2025 14:21:04 UTC (3,489 KB) [v2] Tue, 16 Jun 2026 07:18:38 UTC (3,499 KB) References & Citations Loading... Bibliographic and Citation Tools Bibliographic Explorer (What is the Explorer?) Connected Papers (What is Connected Papers?) Litmaps (What is Litmaps?) scite Smart Citations (What are Smart Citations?) Code, Data and Media Associated with this Article alphaXiv (What is alphaXiv?) CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub (What is DagsHub?) Gotit.pub (What is GotitPub?) Hugging Face (What is Huggingface?) ScienceCast (What is ScienceCast?) Demos Recommenders and Search Tools Influence Flower (What are Influence Flowers?) CORE Recommender (What is CORE?) arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.