A Complete Decomposition of Stochastic Differential Equations
Fuente:
arXiv
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| Auteur principal: | |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866911370005446656 |
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| author | Duffield, Samuel |
| author_facet | Duffield, Samuel |
| contents | We show that any stochastic differential equation with prescribed time-dependent marginal distributions admits a decomposition into three components: a unique scalar field governing marginal evolution, a symmetric positive-semidefinite diffusion matrix field and a skew-symmetric matrix field. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_07834 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A Complete Decomposition of Stochastic Differential Equations Duffield, Samuel Probability Machine Learning Statistics Theory We show that any stochastic differential equation with prescribed time-dependent marginal distributions admits a decomposition into three components: a unique scalar field governing marginal evolution, a symmetric positive-semidefinite diffusion matrix field and a skew-symmetric matrix field. |
| title | A Complete Decomposition of Stochastic Differential Equations |
| topic | Probability Machine Learning Statistics Theory |
| url | https://arxiv.org/abs/2601.07834 |