Inverse problems for stochastic partial differential equations

Fuente: arXiv
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Autores principales: Lü, Qi, Wang, Yu
Formato: Preprint
Publicado: 2024
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author Lü, Qi
Wang, Yu
author_facet Lü, Qi
Wang, Yu
contents This book aims to provide a brief overview of recent advancements in the theory of inverse problems for stochastic partial differential equations. In order to keep the content concise, we will only discuss the inverse problems of two typical classes of stochastic partial differential equations: second-order stochastic parabolic equations and secondorder stochastic hyperbolic equations. The main tool for studying these inverse problem is Carleman estimate. We do not intend to pursue any general treatment of the Carleman estimates themselves and choose direct arguments based on basic stochastic calculus, rather than more general sophisticated methods. As this field is still developing and there are many challenging issues to be addressed, the purpose of this book is not to serve as a comprehensive summary, but rather to spark interest and encourage further exploration in this area among readers. We prefer to present results that, from our perspective, include fresh and promising ideas. In cases where a complete mathematical theory is lacking, we only provide the available results. We do not intend for the current book to be encyclopedic in any sense, and the references are limited.
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id arxiv_https___arxiv_org_abs_2411_05534
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Inverse problems for stochastic partial differential equations
Lü, Qi
Wang, Yu
Probability
Analysis of PDEs
Optimization and Control
This book aims to provide a brief overview of recent advancements in the theory of inverse problems for stochastic partial differential equations. In order to keep the content concise, we will only discuss the inverse problems of two typical classes of stochastic partial differential equations: second-order stochastic parabolic equations and secondorder stochastic hyperbolic equations. The main tool for studying these inverse problem is Carleman estimate. We do not intend to pursue any general treatment of the Carleman estimates themselves and choose direct arguments based on basic stochastic calculus, rather than more general sophisticated methods. As this field is still developing and there are many challenging issues to be addressed, the purpose of this book is not to serve as a comprehensive summary, but rather to spark interest and encourage further exploration in this area among readers. We prefer to present results that, from our perspective, include fresh and promising ideas. In cases where a complete mathematical theory is lacking, we only provide the available results. We do not intend for the current book to be encyclopedic in any sense, and the references are limited.
title Inverse problems for stochastic partial differential equations
topic Probability
Analysis of PDEs
Optimization and Control
url https://arxiv.org/abs/2411.05534