{"title":"A Highly Efficient and Accurate Divergence-Free Spectral Method for the Curl-Curl Equation in Two and Three Dimensions","authors":"Lechang Qin, Changtao Sheng, Zhiguo Yang","doi":"10.1137/23m1587038","DOIUrl":null,"url":null,"abstract":"SIAM Journal on Scientific Computing, Volume 46, Issue 4, Page A2150-A2177, August 2024. <br/> Abstract. In this paper, we present a fast divergence-free spectral algorithm for the curl-curl problem. Divergence-free bases in two and three dimensions are constructed by using the generalized Jacobi polynomials. An accurate spectral method with exact preservation of the divergence-free constraint pointwisely is then proposed, and its corresponding error estimate is established. We then present a highly efficient solution algorithm based on a combination of the matrix-free preconditioned Krylov subspace iterative method and a fully diagonalizable auxiliary problem, which is derived from the spectral discretizations of generalized eigenvalue problems of Laplace and biharmonic operators. We rigorously prove that the dimensions of the invariant subspace of the preconditioned linear system resulting from the divergence-free spectral method with respect to the dominant eigenvalue 1 are [math] and [math] for two- and three-dimensional problems with [math] and [math] unknowns, respectively. Thus, the proposed method usually takes only several iterations to converge, and, astonishingly, as the problem size (polynomial order) increases, the number of iterations will decrease, even for highly indefinite system and oscillatory solutions. As a result, the computational cost of the solution algorithm is only a small multiple of [math] and [math] floating number operations for two- and three-dimensional problems, respectively. Plenty of numerical examples for solving the curl-curl problem with both constant and variable coefficients in two and three dimensions are presented to demonstrate the accuracy and efficiency of the proposed method.","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1137/23m1587038","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
SIAM Journal on Scientific Computing, Volume 46, Issue 4, Page A2150-A2177, August 2024. Abstract. In this paper, we present a fast divergence-free spectral algorithm for the curl-curl problem. Divergence-free bases in two and three dimensions are constructed by using the generalized Jacobi polynomials. An accurate spectral method with exact preservation of the divergence-free constraint pointwisely is then proposed, and its corresponding error estimate is established. We then present a highly efficient solution algorithm based on a combination of the matrix-free preconditioned Krylov subspace iterative method and a fully diagonalizable auxiliary problem, which is derived from the spectral discretizations of generalized eigenvalue problems of Laplace and biharmonic operators. We rigorously prove that the dimensions of the invariant subspace of the preconditioned linear system resulting from the divergence-free spectral method with respect to the dominant eigenvalue 1 are [math] and [math] for two- and three-dimensional problems with [math] and [math] unknowns, respectively. Thus, the proposed method usually takes only several iterations to converge, and, astonishingly, as the problem size (polynomial order) increases, the number of iterations will decrease, even for highly indefinite system and oscillatory solutions. As a result, the computational cost of the solution algorithm is only a small multiple of [math] and [math] floating number operations for two- and three-dimensional problems, respectively. Plenty of numerical examples for solving the curl-curl problem with both constant and variable coefficients in two and three dimensions are presented to demonstrate the accuracy and efficiency of the proposed method.