{"title":"正反向进化方程的PinT预条件","authors":"Shu-Lin Wu, Zhiyong Wang, Tao Zhou","doi":"10.1137/22m1516476","DOIUrl":null,"url":null,"abstract":"SIAM Journal on Matrix Analysis and Applications, Volume 44, Issue 4, Page 1771-1798, December 2023. <br/> Abstract. Solving the linear system [math] is often the major computational burden when a forward-backward evolutionary equation must be solved in a problem, where [math] is the so-called all-at-once matrix of the forward subproblem after space-time discretization. An efficient solver requires a good preconditioner for [math]. Inspired by the structure of [math], we precondition [math] by [math] with [math] being a block [math]-circulant matrix constructed by replacing the Toeplitz matrices in [math] by the [math]-circulant matrices. By a block Fourier diagonalization of [math], the computation of the preconditioning step [math] is parallelizable for all the time steps. We give a spectral analysis for the preconditioned matrix [math] and prove that for any one-step stable time-integrator the eigenvalues of [math] spread in a mesh-independent interval [math] if the parameter [math] weakly scales in terms of the number of time steps [math] as [math], where [math] is a free constant. Two applications of the proposed preconditioner are illustrated: PDE-constrained optimal control problems and parabolic source identification problems. Numerical results for both problems indicate that spectral analysis predicts the convergence rate of the preconditioned conjugate gradient method very well.","PeriodicalId":49538,"journal":{"name":"SIAM Journal on Matrix Analysis and Applications","volume":"1 3","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"PinT Preconditioner for Forward-Backward Evolutionary Equations\",\"authors\":\"Shu-Lin Wu, Zhiyong Wang, Tao Zhou\",\"doi\":\"10.1137/22m1516476\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"SIAM Journal on Matrix Analysis and Applications, Volume 44, Issue 4, Page 1771-1798, December 2023. <br/> Abstract. Solving the linear system [math] is often the major computational burden when a forward-backward evolutionary equation must be solved in a problem, where [math] is the so-called all-at-once matrix of the forward subproblem after space-time discretization. An efficient solver requires a good preconditioner for [math]. Inspired by the structure of [math], we precondition [math] by [math] with [math] being a block [math]-circulant matrix constructed by replacing the Toeplitz matrices in [math] by the [math]-circulant matrices. By a block Fourier diagonalization of [math], the computation of the preconditioning step [math] is parallelizable for all the time steps. We give a spectral analysis for the preconditioned matrix [math] and prove that for any one-step stable time-integrator the eigenvalues of [math] spread in a mesh-independent interval [math] if the parameter [math] weakly scales in terms of the number of time steps [math] as [math], where [math] is a free constant. Two applications of the proposed preconditioner are illustrated: PDE-constrained optimal control problems and parabolic source identification problems. Numerical results for both problems indicate that spectral analysis predicts the convergence rate of the preconditioned conjugate gradient method very well.\",\"PeriodicalId\":49538,\"journal\":{\"name\":\"SIAM Journal on Matrix Analysis and Applications\",\"volume\":\"1 3\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2023-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SIAM Journal on Matrix Analysis and Applications\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1137/22m1516476\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIAM Journal on Matrix Analysis and Applications","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1137/22m1516476","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
PinT Preconditioner for Forward-Backward Evolutionary Equations
SIAM Journal on Matrix Analysis and Applications, Volume 44, Issue 4, Page 1771-1798, December 2023. Abstract. Solving the linear system [math] is often the major computational burden when a forward-backward evolutionary equation must be solved in a problem, where [math] is the so-called all-at-once matrix of the forward subproblem after space-time discretization. An efficient solver requires a good preconditioner for [math]. Inspired by the structure of [math], we precondition [math] by [math] with [math] being a block [math]-circulant matrix constructed by replacing the Toeplitz matrices in [math] by the [math]-circulant matrices. By a block Fourier diagonalization of [math], the computation of the preconditioning step [math] is parallelizable for all the time steps. We give a spectral analysis for the preconditioned matrix [math] and prove that for any one-step stable time-integrator the eigenvalues of [math] spread in a mesh-independent interval [math] if the parameter [math] weakly scales in terms of the number of time steps [math] as [math], where [math] is a free constant. Two applications of the proposed preconditioner are illustrated: PDE-constrained optimal control problems and parabolic source identification problems. Numerical results for both problems indicate that spectral analysis predicts the convergence rate of the preconditioned conjugate gradient method very well.
期刊介绍:
The SIAM Journal on Matrix Analysis and Applications contains research articles in matrix analysis and its applications and papers of interest to the numerical linear algebra community. Applications include such areas as signal processing, systems and control theory, statistics, Markov chains, and mathematical biology. Also contains papers that are of a theoretical nature but have a possible impact on applications.