Geometric linearisation for optimal transport with strongly p-convex cost
Fuente:
arXiv
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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866916193723482112 |
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| author | Koch, Lukas |
| author_facet | Koch, Lukas |
| contents | We prove a geometric linearisation result for minimisers of optimal transport problems where the cost-function is strongly p-convex and of p-growth. Initial and target measures are allowed to be rough, but are assumed to be close to Lebesgue measure. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2303_10760 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Geometric linearisation for optimal transport with strongly p-convex cost Koch, Lukas Analysis of PDEs We prove a geometric linearisation result for minimisers of optimal transport problems where the cost-function is strongly p-convex and of p-growth. Initial and target measures are allowed to be rough, but are assumed to be close to Lebesgue measure. |
| title | Geometric linearisation for optimal transport with strongly p-convex cost |
| topic | Analysis of PDEs |
| url | https://arxiv.org/abs/2303.10760 |