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arXiv 2205.05024math.NAcs.NA
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弥合差距:Runge-Kutta共振格式中的辛性与低正则性

Bridging the gap: symplecticity and low regularity in Runge-Kutta resonance-based schemes

Georg Maierhofer, Katharina Schratz

AI总结:

本文提出Runge-Kutta共振方法框架,在保持低正则性收敛优势的同时,为KdV和NLSE方程刻画辛共振格式,弥合低正则性与几何结构保持之间的差距。

摘要:

近年来,针对色散非线性偏微分方程的所谓共振方法的研究日益增多。在许多情况下,这类新方法允许在比经典分裂法或指数积分器方法更一般的设定(例如粗糙数据)下进行近似。然而,它们缺乏一个重要性质:保持流的几何性质。这在Korteweg-de Vries(KdV)方程和非线性薛定谔方程(NLSE)的情况下尤为严重,这两个方程是色散无限维哈密顿系统广泛领域中的基本模型,拥有无穷多个守恒量,这是我们希望在离散层面至少在一定程度上捕捉的重要性质。如今,已有多种保持结构的哈密顿系统积分器可用,然而,这些现有算法通常只能高效地近似高正则解。另一方面,最先进的低正则性积分器对底层偏微分方程的几何结构保持较差。在这项工作中,我们针对一大类色散非线性方程引入了一种新颖的框架,即所谓的Runge-Kutta共振方法,该方法比先前的共振格式包含了多得多的自由度,同时具有类似有利的低正则性收敛性质。特别是,对于KdV和NLSE情形,我们通过刻画两类方程的辛(在哈密顿图像中)共振方法的大类,弥合了低正则性与结构保持之间的差距,这些方法允许对解进行低正则性近似,同时在离散层面保持连续问题的底层几何结构。

英文摘要:

Recent years have seen an increasing amount of research devoted to the development of so-called resonance-based methods for dispersive nonlinear partial differential equations. In many situations, this new class of methods allows for approximations in a much more general setting (e.g. for rough data) than, for instance, classical splitting or exponential integrator methods. However, they lack one important property: the preservation of geometric properties of the flow. This is particularly drastic in the case of the Korteweg-de Vries (KdV) equation and the nonlinear Schrödinger equation (NLSE) which are fundamental models in the broad field of dispersive infinite-dimensional Hamiltonian systems, possessing infinitely many conserved quantities, an important property which we wish to capture - at least up to some degree - also on the discrete level. Nowadays, a wide range of structure preserving integrators for Hamiltonian systems are available, however, typically these existing algorithms can only approximate highly regular solutions efficiently. State-of-the-art low-regularity integrators, on the other hand, poorly preserve the geometric structure of the underlying PDE. In this work we introduce a novel framework, so-called Runge-Kutta resonance-based methods, for a large class of dispersive nonlinear equations which incorporate a much larger amount of degrees of freedom than prior resonance-based schemes while featuring similarly favourable low-regularity convergence properties. In particular, for the KdV and NLSE case, we are able to bridge the gap between low regularity and structure preservation by characterising a large class of symplectic (in the Hamiltonian picture) resonance-based methods for both equations that allow for low-regularity approximations to the solution while preserving the underlying geometric structure of the continuous problem on the discrete level.

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