Sensor placement via large deviations in the Eikonal equation
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866912902924992512 |
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| author | Ftouhi, Ilias Zuazua, Enrique |
| author_facet | Ftouhi, Ilias Zuazua, Enrique |
| contents | In this work, we address the problem of optimally placing a finite number of sensors within a given region so as to minimize the mean or maximal distance to the points of the domain. To tackle this natural geometric performance criterion, formulated in terms of distance functions, we combine tools from geometric analysis with a classical result of Varadhan, which provides an efficient approximation of the distance function via the solution of a simple elliptic PDE. The effectiveness of the proposed approach is demonstrated through illustrative numerical simulations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_21469 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Sensor placement via large deviations in the Eikonal equation Ftouhi, Ilias Zuazua, Enrique Optimization and Control In this work, we address the problem of optimally placing a finite number of sensors within a given region so as to minimize the mean or maximal distance to the points of the domain. To tackle this natural geometric performance criterion, formulated in terms of distance functions, we combine tools from geometric analysis with a classical result of Varadhan, which provides an efficient approximation of the distance function via the solution of a simple elliptic PDE. The effectiveness of the proposed approach is demonstrated through illustrative numerical simulations. |
| title | Sensor placement via large deviations in the Eikonal equation |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2508.21469 |