{"title":"存在低随机性的分散性多变量方程的近似值","authors":"Yvonne Alama Bronsard, Yvain Bruned, Katharina Schratz","doi":"10.1007/s10208-023-09625-8","DOIUrl":null,"url":null,"abstract":"<p>We introduce a new class of numerical schemes which allow for low-regularity approximations to the expectation <span>\\( \\mathbb {E}(|u_{k}(t, v^{\\eta })|^2)\\)</span>, where <span>\\(u_k\\)</span> denotes the <i>k</i>-th Fourier coefficient of the solution <i>u</i> of the dispersive equation and <span>\\( v^{\\eta }(x) \\)</span> the associated random initial data. This quantity plays an important role in physics, in particular in the study of wave turbulence where one needs to adopt a statistical approach in order to obtain deep insight into the <i>generic</i> long-time behaviour of solutions to dispersive equations. Our new class of schemes is based on Wick’s theorem and Feynman diagrams together with a resonance-based discretisation (Bruned and Schratz in Forum Math Pi 10:E2, 2022) set in a more general context: we introduce a novel combinatorial structure called paired decorated forests which are two decorated trees whose decorations on the leaves come in pair. The character of the scheme draws its inspiration from the treatment of singular stochastic partial differential equations via regularity structures. In contrast to classical approaches, we do not discretise the PDE itself, but rather its expectation. This allows us to heavily exploit the optimal resonance structure and underlying gain in regularity on the finite dimensional (discrete) level.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Approximations of Dispersive PDEs in the Presence of Low-Regularity Randomness\",\"authors\":\"Yvonne Alama Bronsard, Yvain Bruned, Katharina Schratz\",\"doi\":\"10.1007/s10208-023-09625-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>We introduce a new class of numerical schemes which allow for low-regularity approximations to the expectation <span>\\\\( \\\\mathbb {E}(|u_{k}(t, v^{\\\\eta })|^2)\\\\)</span>, where <span>\\\\(u_k\\\\)</span> denotes the <i>k</i>-th Fourier coefficient of the solution <i>u</i> of the dispersive equation and <span>\\\\( v^{\\\\eta }(x) \\\\)</span> the associated random initial data. This quantity plays an important role in physics, in particular in the study of wave turbulence where one needs to adopt a statistical approach in order to obtain deep insight into the <i>generic</i> long-time behaviour of solutions to dispersive equations. Our new class of schemes is based on Wick’s theorem and Feynman diagrams together with a resonance-based discretisation (Bruned and Schratz in Forum Math Pi 10:E2, 2022) set in a more general context: we introduce a novel combinatorial structure called paired decorated forests which are two decorated trees whose decorations on the leaves come in pair. The character of the scheme draws its inspiration from the treatment of singular stochastic partial differential equations via regularity structures. In contrast to classical approaches, we do not discretise the PDE itself, but rather its expectation. This allows us to heavily exploit the optimal resonance structure and underlying gain in regularity on the finite dimensional (discrete) level.</p>\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-08-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1007/s10208-023-09625-8\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s10208-023-09625-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
摘要
我们引入了一类新的数值方案,它允许对期望值\( \mathbb {E}(|u_{k}(t, v^{\eta })|^2)\) 进行低规则性近似,其中\(u_k\) 表示分散方程解 u 的第 k 个傅里叶系数,\( v^{\eta }(x) \) 表示相关的随机初始数据。这个量在物理学中发挥着重要作用,尤其是在波湍流研究中,人们需要采用统计方法来深入了解分散方程解的一般长期行为。我们的新方案基于威克定理和费曼图,以及基于共振的离散化(Bruned 和 Schratz 在 Forum Math Pi 10:E2, 2022 上发表),其背景更为宽泛:我们引入了一种新颖的组合结构,称为配对装饰林,即两棵叶子上的装饰成对的装饰树。该方案的特点源自通过正则结构处理奇异随机偏微分方程。与经典方法不同的是,我们并不对 PDE 本身进行离散化,而是对其期望进行离散化。这样,我们就能在有限维(离散)水平上大量利用最优共振结构和正则性的潜在增益。
Approximations of Dispersive PDEs in the Presence of Low-Regularity Randomness
We introduce a new class of numerical schemes which allow for low-regularity approximations to the expectation \( \mathbb {E}(|u_{k}(t, v^{\eta })|^2)\), where \(u_k\) denotes the k-th Fourier coefficient of the solution u of the dispersive equation and \( v^{\eta }(x) \) the associated random initial data. This quantity plays an important role in physics, in particular in the study of wave turbulence where one needs to adopt a statistical approach in order to obtain deep insight into the generic long-time behaviour of solutions to dispersive equations. Our new class of schemes is based on Wick’s theorem and Feynman diagrams together with a resonance-based discretisation (Bruned and Schratz in Forum Math Pi 10:E2, 2022) set in a more general context: we introduce a novel combinatorial structure called paired decorated forests which are two decorated trees whose decorations on the leaves come in pair. The character of the scheme draws its inspiration from the treatment of singular stochastic partial differential equations via regularity structures. In contrast to classical approaches, we do not discretise the PDE itself, but rather its expectation. This allows us to heavily exploit the optimal resonance structure and underlying gain in regularity on the finite dimensional (discrete) level.