A Fourier-Legendre spectral method for approximating the minimizers of 𝜎_{2,𝑝}-energy

IF 0.9 4区 数学 Q3 MATHEMATICS, APPLIED
M. Taghavi, M. Shahrokhi-Dehkordi
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Let <inline-formula content-type=\"math/mathml\">\n<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" alttext=\"double-struck upper X subset-of double-struck upper R Superscript n\">\n <mml:semantics>\n <mml:mrow>\n <mml:mrow class=\"MJX-TeXAtom-ORD\">\n <mml:mrow class=\"MJX-TeXAtom-ORD\">\n <mml:mi mathvariant=\"double-struck\">X</mml:mi>\n </mml:mrow>\n </mml:mrow>\n <mml:mo>⊂<!-- ⊂ --></mml:mo>\n <mml:msup>\n <mml:mrow class=\"MJX-TeXAtom-ORD\">\n <mml:mi mathvariant=\"double-struck\">R</mml:mi>\n </mml:mrow>\n <mml:mi>n</mml:mi>\n </mml:msup>\n </mml:mrow>\n <mml:annotation encoding=\"application/x-tex\">{\\mathbb {X}}\\subset \\mathbb {R}^n</mml:annotation>\n </mml:semantics>\n</mml:math>\n</inline-formula> be a bounded Lipschitz domain and consider the energy functional <inline-formula content-type=\"math/mathml\">\n<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" alttext=\"left-parenthesis 1.1 right-parenthesis\">\n <mml:semantics>\n <mml:mrow>\n <mml:mo stretchy=\"false\">(</mml:mo>\n <mml:mn>1.1</mml:mn>\n <mml:mo stretchy=\"false\">)</mml:mo>\n </mml:mrow>\n <mml:annotation encoding=\"application/x-tex\">(1.1)</mml:annotation>\n </mml:semantics>\n</mml:math>\n</inline-formula> whose integrand is defined by <inline-formula content-type=\"math/mathml\">\n<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" alttext=\"bold upper W left-parenthesis nabla u left-parenthesis x right-parenthesis right-parenthesis colon-equal left-parenthesis sigma 2 left-parenthesis u right-parenthesis right-parenthesis Superscript StartFraction p Over 2 EndFraction Baseline plus normal upper Phi left-parenthesis det nabla u right-parenthesis\">\n <mml:semantics>\n <mml:mrow>\n <mml:mrow class=\"MJX-TeXAtom-ORD\">\n <mml:mrow class=\"MJX-TeXAtom-ORD\">\n <mml:mi mathvariant=\"bold\">W</mml:mi>\n </mml:mrow>\n </mml:mrow>\n <mml:mo stretchy=\"false\">(</mml:mo>\n <mml:mi mathvariant=\"normal\">∇<!-- ∇ --></mml:mi>\n <mml:mi>u</mml:mi>\n <mml:mo stretchy=\"false\">(</mml:mo>\n <mml:mi>x</mml:mi>\n <mml:mo stretchy=\"false\">)</mml:mo>\n <mml:mo stretchy=\"false\">)</mml:mo>\n <mml:mo>≔</mml:mo>\n <mml:mo stretchy=\"false\">(</mml:mo>\n <mml:msub>\n <mml:mi>σ<!-- σ --></mml:mi>\n <mml:mn>2</mml:mn>\n </mml:msub>\n <mml:mo stretchy=\"false\">(</mml:mo>\n <mml:mi>u</mml:mi>\n <mml:mo stretchy=\"false\">)</mml:mo>\n <mml:msup>\n <mml:mo stretchy=\"false\">)</mml:mo>\n <mml:mrow class=\"MJX-TeXAtom-ORD\">\n <mml:mfrac>\n <mml:mi>p</mml:mi>\n <mml:mn>2</mml:mn>\n </mml:mfrac>\n </mml:mrow>\n </mml:msup>\n <mml:mo>+</mml:mo>\n <mml:mi mathvariant=\"normal\">Φ<!-- Φ --></mml:mi>\n <mml:mo stretchy=\"false\">(</mml:mo>\n <mml:mo movablelimits=\"true\" form=\"prefix\">det</mml:mo>\n <mml:mi mathvariant=\"normal\">∇<!-- ∇ --></mml:mi>\n <mml:mi>u</mml:mi>\n <mml:mo stretchy=\"false\">)</mml:mo>\n </mml:mrow>\n <mml:annotation encoding=\"application/x-tex\">{\\mathbf {W}}(\\nabla u(x))≔(\\sigma _2(u))^{\\frac {p}{2}}+\\Phi (\\det \\nabla u)</mml:annotation>\n </mml:semantics>\n</mml:math>\n</inline-formula> over an appropriate space of admissible maps, <inline-formula content-type=\"math/mathml\">\n<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" alttext=\"script upper A Subscript p Baseline left-parenthesis double-struck upper X right-parenthesis\">\n <mml:semantics>\n <mml:mrow>\n <mml:msub>\n <mml:mrow class=\"MJX-TeXAtom-ORD\">\n <mml:mi class=\"MJX-tex-caligraphic\" mathvariant=\"script\">A</mml:mi>\n </mml:mrow>\n <mml:mi>p</mml:mi>\n </mml:msub>\n <mml:mo stretchy=\"false\">(</mml:mo>\n <mml:mrow class=\"MJX-TeXAtom-ORD\">\n <mml:mrow class=\"MJX-TeXAtom-ORD\">\n <mml:mi mathvariant=\"double-struck\">X</mml:mi>\n </mml:mrow>\n </mml:mrow>\n <mml:mo stretchy=\"false\">)</mml:mo>\n </mml:mrow>\n <mml:annotation encoding=\"application/x-tex\">\\mathcal {A}_p({\\mathbb {X}})</mml:annotation>\n </mml:semantics>\n</mml:math>\n</inline-formula>. Using Fourier and Legendre interpolation errors, we obtain an error estimate for the energy functional and prove a convergence theorem for the proposed method. Furthermore, we apply the gradient descent method to solve a nonlinear algebraic system which is obtained by discretizing the Euler-Lagrange equations. The numerical experiments are performed to demonstrate the accuracy and effectiveness of our method.</p>","PeriodicalId":20964,"journal":{"name":"Quarterly of Applied Mathematics","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quarterly of Applied Mathematics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1090/qam/1674","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0

Abstract

This paper proposes a Fourier-Legendre spectral method to find the minimizers of a variational problem, called σ 2 , p \sigma _{2,p} -energy, in polar coordinates. Let X R n {\mathbb {X}}\subset \mathbb {R}^n be a bounded Lipschitz domain and consider the energy functional ( 1.1 ) (1.1) whose integrand is defined by W ( u ( x ) ) ( σ 2 ( u ) ) p 2 + Φ ( det u ) {\mathbf {W}}(\nabla u(x))≔(\sigma _2(u))^{\frac {p}{2}}+\Phi (\det \nabla u) over an appropriate space of admissible maps, A p ( X ) \mathcal {A}_p({\mathbb {X}}) . Using Fourier and Legendre interpolation errors, we obtain an error estimate for the energy functional and prove a convergence theorem for the proposed method. Furthermore, we apply the gradient descent method to solve a nonlinear algebraic system which is obtained by discretizing the Euler-Lagrange equations. The numerical experiments are performed to demonstrate the accuracy and effectiveness of our method.

近似𝜎_{2,𝑝}能量最小值的Fourier-Legendre谱方法
本文提出了一种Fourier-Legendre谱法来求极坐标下变分问题σ 2,p \sigma _2,p{ -能量的最小值。设X∧R n }{\mathbb X{}}\subset\mathbb R{^n是一个有界的Lipschitz域,并且考虑其被积量为W(∇u (X))的能量泛函数(1.1)(1.1),其定义为W(∇u (X))是(σ 2 (u))p2+ Φ (det∇u) }{\mathbf W{(}}\nabla u(x))是(\sigma _2(u))^ {\frac p2{+ }{}}\Phi (\det\nabla u)在一个适当空间上的可接受映射,A p(x) \mathcal A_p{(}{\mathbb x){。}}利用傅里叶插值误差和勒让德插值误差,得到了能量泛函的误差估计,并证明了该方法的收敛性定理。在此基础上,应用梯度下降法求解由欧拉-拉格朗日方程离散得到的非线性代数方程组。数值实验验证了该方法的准确性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Quarterly of Applied Mathematics
Quarterly of Applied Mathematics 数学-应用数学
CiteScore
1.90
自引率
12.50%
发文量
31
审稿时长
>12 weeks
期刊介绍: The Quarterly of Applied Mathematics contains original papers in applied mathematics which have a close connection with applications. An author index appears in the last issue of each volume. This journal, published quarterly by Brown University with articles electronically published individually before appearing in an issue, is distributed by the American Mathematical Society (AMS). In order to take advantage of some features offered for this journal, users will occasionally be linked to pages on the AMS website.
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