Positivstellensätze for polynomial matrices with universal quantifiers
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arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866918424076091392 |
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| author | Guo, Feng Wang, Jie |
| author_facet | Guo, Feng Wang, Jie |
| contents | This paper investigates Positivstellensätze for polynomial matrices subject to universally quantified polynomial matrix inequality constraints. We first establish a matrix-valued Positivstellensatz under the Archimedean condition, incorporating universal quantifiers. For scalar-valued polynomial objectives, we further develop a sparse Positivstellensatz that leverages correlative sparsity patterns within these quantified constraints. Moving beyond the Archimedean framework, we then derive two generalized Positivstellensätze under analogous settings. These results collectively unify and extend foundational theorems in three distinct contexts: classical polynomial Positivstellensätze, their universally quantified counterparts, and matrix polynomial formulations. Applications of the established Positivstellensätze to robust polynomial matrix inequality constrained optimization are also investigated. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_03470 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Positivstellensätze for polynomial matrices with universal quantifiers Guo, Feng Wang, Jie Optimization and Control 90C23, 15A54, 13J30, 14P10, 11E25, 12D15 This paper investigates Positivstellensätze for polynomial matrices subject to universally quantified polynomial matrix inequality constraints. We first establish a matrix-valued Positivstellensatz under the Archimedean condition, incorporating universal quantifiers. For scalar-valued polynomial objectives, we further develop a sparse Positivstellensatz that leverages correlative sparsity patterns within these quantified constraints. Moving beyond the Archimedean framework, we then derive two generalized Positivstellensätze under analogous settings. These results collectively unify and extend foundational theorems in three distinct contexts: classical polynomial Positivstellensätze, their universally quantified counterparts, and matrix polynomial formulations. Applications of the established Positivstellensätze to robust polynomial matrix inequality constrained optimization are also investigated. |
| title | Positivstellensätze for polynomial matrices with universal quantifiers |
| topic | Optimization and Control 90C23, 15A54, 13J30, 14P10, 11E25, 12D15 |
| url | https://arxiv.org/abs/2501.03470 |