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arXiv 2602.20769math.APmath-phmath.MP
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对半线性抛物型方程的连续数据同化:通过演化方程提出的一种通用方法

Continuous Data Assimilation for Semilinear Parabolic Equations: A General Approach by Evolution Equations

Technische Universität Darmstadt(达姆施塔特工业大学);Università degli Studi della Campania L. Vanvitelli(坎帕尼亚路易吉范维泰利大学)

Gianmarco Del Sarto, Matthias Hieber, Filippo Palma, Tarek Zöchling

AI总结:

本文提出通过演化方程对半线性抛物型方程进行连续数据同化的通用方法,证明了近似解的指数收敛性,并首次应用于多个复杂系统。

摘要:

本文通过演化方程发展了一种针对半线性抛物型方程的连续确定性数据同化通用框架。引入一个由部分观测驱动的修正模型,建立了参考系统和近似系统的全局well-posed性,基于自然假设。此外,证明在观测分辨率和修正参数适当选择的情况下,近似解以指数形式收敛到参考系统的解。该方法使我们能够首次考虑许多系统,如Allen-Cahn、Cahn-Hilliard、Sellers型能量平衡、双域系统。

英文摘要:

This article develops a general framework for continuous deterministic data assimilation for semilinear parabolic equations by means of evolution equations. Introducing a nudged model driven by partial observations, the global well-posedness of the reference and the approximating systems is established under natural assumptions. In addition, it is shown that the approximating solution converges exponentially to the solution of the reference system, provided the observational resolution and the nudging parameter are suitably chosen. The approach allows us to consider many systems, such as the Allen-Cahn, Cahn-Hilliard, Sellers-type energy balance, and bidomain systems, for the first time.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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