Generalized locally Toeplitz sequences : a review and an extension

We review the theory of Generalized Locally Toeplitz (GLT) sequences, hereinafter called ‘the GLT theory’, which goes back to the pioneering work by Tilli on Locally Toeplitz (LT) sequences and was developed by the second author during the last decade: every GLT sequence has a measurable symbol; the singular value distrbution of any GLT sequence is identified by the symbol (also the eigenvalue distribution if the sequence is made by Hermitian matrices); the GLT sequences form an algebra, closed under linear combinations, (pseudo)inverse if the symbol vanishes in a set of zero measure, product and the symbol obeys to the same algebraic manipulations. As already proved in several contexts, this theory is a powerful tool for computing/analyzing the asymptotic spectral distribution of the discretization matrices arising from the numerical approximation of continuous problems, such as Integral Equations and, especially, Partial Differential Equations, including variable coefficients, irregular domains, different approximation schemes such as Finite Differences, Finite Elements, Collocation/Galerkin Isogeometric Analysis etc. However, in this review we are not concerned with the applicative interest of the GLT theory, for which we limit to refer the reader to the numerous applications available in the literature. On the contrary, we focus on the theoretical foundations. We propose slight (but relevant) modifications of the original definitions, which allow us to enlarge the applicability of the GLT theory. In particular, we remove a certain ‘technical’ hypothesis concerning the Riemann-integrability of the so-called ‘weight functions’, which appeared in the statement of many spectral distribution and algebraic results for GLT sequences. With the new definitions, we introduce new technical and useful results and we provide a formal proof of the fact that sequences formed by multilevel diagonal sampling matrices, as well as multilevel Toeplitz sequences, fall in the class of LT sequences; the latter results were mentioned in previous papers, but no direct proof was given especially regarding the case of multilevel diagonal sampling matrix-sequences. As a final step, we extend the GLT theory: we first prove an approximation result, which is particularly useful to show that a given sequence of matrices is a GLT sequence; by using this result, we provide a new and easier proof of the fact that {A−1 n }n is a GLT sequence with symbol κ−1 whenever {An}n is a GLT sequence of invertible matrices with symbol κ and κ 6= 0 almost everywhere; finally, using again the approximation result, we prove that {f(An)}n is a GLT sequence with symbol f(κ), as long as f : R → R is continuous and {An}n is a GLT sequence of Hermitian matrices with symbol κ. This latter theoretical property has important implications, e.g. in proving that the geometric means of GLT sequences are still GLT, so obtaining for free that the spectral distribution of the mean is just the geometric mean of the symbols.

[1]  Hendrik Speleers,et al.  Robust and optimal multi-iterative techniques for IgA Galerkin linear systems This is a preprint of a paper published in Comput. Methods Appl. Mech. Engrg. 284 (2015) 230264. , 2015 .

[2]  Paolo Tilli,et al.  Locally Toeplitz sequences: spectral properties and applications , 1998 .

[3]  Stefano Serra Capizzano,et al.  Spectral Analysis and Spectral Symbol of d-variate $\mathbb Q_{\boldsymbol p}$ Lagrangian FEM Stiffness Matrices , 2015, SIAM J. Matrix Anal. Appl..

[4]  Hendrik Speleers,et al.  On the spectrum of stiffness matrices arising from isogeometric analysis , 2014, Numerische Mathematik.

[5]  Stefano Serra-Capizzano More Inequalities and Asymptotics for Matrix Valued Linear Positive Operators: the Noncommutative Case , 2002 .

[6]  Hendrik Speleers,et al.  Lusin theorem, GLT sequences and matrix computations: An application to the spectral analysis of PDE discretization matrices , 2017 .

[7]  A. Brandt Guide to multigrid development , 1982 .

[8]  Stefano Serra Capizzano,et al.  On the Regularizing Power of Multigrid-type Algorithms , 2005, SIAM J. Sci. Comput..

[9]  Marco Donatelli,et al.  A V-cycle Multigrid for multilevel matrix algebras: proof of optimality , 2007, Numerische Mathematik.

[10]  J. Strikwerda Finite Difference Schemes and Partial Differential Equations, Second Edition , 2004 .

[11]  Gene H. Golub,et al.  Matrix computations , 1983 .

[12]  T. Hughes,et al.  Isogeometric analysis : CAD, finite elements, NURBS, exact geometry and mesh refinement , 2005 .

[13]  Stefano Serra-Capizzano,et al.  Eigenvalue-eigenvector structure of Schoenmakers–Coffey matrices via Toeplitz technology and applications , 2016 .

[14]  Stefano Serra Capizzano,et al.  Spectral and structural analysis of high precision finite difference matrices for elliptic operators , 1999 .

[15]  Paolo Tilli,et al.  A note on the spectral distribution of toeplitz matrices , 1998 .

[16]  A. Böttcher,et al.  Introduction to Large Truncated Toeplitz Matrices , 1998 .

[17]  Stefano Serra-Capizzano,et al.  The GLT class as a generalized Fourier analysis and applications , 2006 .

[18]  Hendrik Speleers,et al.  Spectral analysis and spectral symbol of matrices in isogeometric collocation methods , 2015, Math. Comput..

[19]  Stefano Serra Capizzano,et al.  Preconditioned HSS method for large multilevel block Toeplitz linear systems via the notion of matrix‐valued symbol , 2016, Numer. Linear Algebra Appl..

[20]  Uwe Fink Finite Element Solution Of Boundary Value Problems Theory And Computation , 2016 .

[21]  Carlo Garoni Structured matrices coming from PDE approximation theory: spectral analysis, spectral symbol and design of fast iterative solvers. , 2015 .

[22]  TONY F. CHAN,et al.  Fourier Analysis of Iterative Methods for Elliptic pr , 1989, SIAM Rev..

[23]  Burton Wendroff,et al.  On the stability of difference schemes , 1962 .

[24]  W. Rudin Real and complex analysis , 1968 .

[25]  Philippe G. Ciarlet,et al.  The finite element method for elliptic problems , 2002, Classics in applied mathematics.

[26]  S. Serra Capizzano,et al.  Distribution results on the algebra generated by Toeplitz sequences: a finite-dimensional approach , 2001 .

[27]  J. Strikwerda Finite Difference Schemes and Partial Differential Equations , 1989 .

[28]  Stefano Serra-Capizzano,et al.  Multigrid Methods for Multilevel Circulant Matrices , 2005 .

[29]  Stefano Serra Capizzano,et al.  Spectral behavior of preconditioned non-Hermitian multilevel block Toeplitz matrices with matrix-valued symbol , 2014, Appl. Math. Comput..

[30]  E. E. Tyrtyshnikov A unifying approach to some old and new theorems on distribution and clustering , 1996 .

[31]  Seymour V. Parter,et al.  On the eigenvalues of certain generalisations of Toeplitz matrices , 1962 .

[32]  Stefano Serra Capizzano,et al.  On the Asymptotic Spectrum of Finite Element Matrix Sequences , 2007, SIAM J. Numer. Anal..

[33]  Stefano Serra Capizzano,et al.  Singular‐value (and eigenvalue) distribution and Krylov preconditioning of sequences of sampling matrices approximating integral operators , 2014, Numer. Linear Algebra Appl..

[34]  U. Grenander,et al.  Toeplitz Forms And Their Applications , 1958 .

[35]  Maya Neytcheva,et al.  Spectral analysis of coupled PDEs and of their Schur complements via the notion of generalized locally Toeplitz sequences , 2015 .

[36]  Hendrik Speleers,et al.  Robust and optimal multi-iterative techniques for IgA Galerkin linear systems , 2015 .

[37]  Stefano Serra Capizzano,et al.  A note on the asymptotic spectra of finite difference discretizations of second order elliptic partial differential equations , 2000 .

[38]  Peter D. Lax,et al.  On the stability of difference approximations to solutions of hyperbolic equations with variable coefficients , 1961 .

[39]  S. Serra Capizzano,et al.  Generalized locally Toeplitz sequences: spectral analysis and applications to discretized partial differential equations , 2003 .

[40]  Carlo Garoni,et al.  Spectral Analysis and Spectral Symbol of d-variate $\mathbb Q_{\boldsymbol p}$ Lagrangian FEM Stiffness Matrices , 2015, SIAM J. Matrix Anal. Appl..

[41]  Stefano Serra Capizzano,et al.  Analysis of preconditioning strategies for collocation linear systems , 2003 .

[42]  S. Serra-Capizzano,et al.  Approximating classes of sequences: The Hermitian case , 2011 .

[43]  Paolo Tilli,et al.  Some Results on Complex Toeplitz Eigenvalues , 1999 .

[44]  Thomas J. R. Hughes,et al.  Isogeometric Analysis: Toward Integration of CAD and FEA , 2009 .

[45]  Carlo Garoni,et al.  A general tool for determining the asymptotic spectral distribution of Hermitian matrix-sequences , 2015 .

[46]  L. Hörmander,et al.  Pseudo-differential Operators and Non-elliptic Boundary Problems , 1966 .

[47]  Carlo Garoni,et al.  Tools for Determining the Asymptotic Spectral Distribution of non-Hermitian Perturbations of Hermitian Matrix-Sequences and Applications , 2015 .

[48]  Stefano Serra Capizzano,et al.  V-cycle Optimal Convergence for Certain (Multilevel) Structured Linear Systems , 2004, SIAM J. Matrix Anal. Appl..

[49]  STEFANO SERRA CAPIZZANO,et al.  Locally X Matrices, Spectral Distributions, Preconditioning, and Applications , 2000, SIAM J. Matrix Anal. Appl..

[50]  Michel Fortin,et al.  Mixed and Hybrid Finite Element Methods , 2011, Springer Series in Computational Mathematics.

[51]  Debora Sesana Spectral distributions of structured matrix-sequences: tools and applications. , 2011 .

[52]  Stefano Serra Capizzano,et al.  Numerische Mathematik Convergence analysis of two-grid methods for elliptic Toeplitz and PDEs Matrix-sequences , 2002 .

[53]  Hendrik Speleers,et al.  Spectral analysis and spectral symbol of matrices in isogeometric Galerkin methods , 2017, Math. Comput..

[54]  Marco Donatelli,et al.  Canonical Eigenvalue Distribution of Multilevel Block Toeplitz Sequences with Non-Hermitian Symbols , 2012 .

[55]  Leonid Golinskii,et al.  The asymptotic properties of the spectrum of nonsymmetrically perturbed Jacobi matrix sequences , 2007, J. Approx. Theory.

[56]  R. Bhatia Matrix Analysis , 1996 .

[57]  Gene H. Golub,et al.  Matrix Computations, Third Edition , 1996 .

[58]  M. Donatelli,et al.  Spectral filtering for trend estimation , 2012 .

[59]  S. Capizzano Spectral behavior of matrix sequences and discretized boundary value problems , 2001 .