Algorithms for Classical Orthogonal Polynomials
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Chebyshev Polynomials of the Second, Third and Fourth Kinds in Approximation, Indefinite Integration, and Integral Transforms *
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Journal of Computational and Applied Mathematics 49 (1993) 169-178 169 North-Holland CAM 1429 Chebyshev polynomials of the second, third and fourth kinds in approximation, indefinite integration, and integral transforms * J.C. Mason Applied and Computational Mathematics Group, Royal Military College of Science, Shrivenham, Swindon, Wiltshire, United Kingdom Dedicated to Dr. D.F. Mayers on the occasion of his 60th birthday Received 18 February 1992 Revised 31 March 1992 Abstract Mason, J.C., Chebyshev polynomials of the second, third and fourth kinds in approximation, indefinite integration, and integral transforms, Journal of Computational and Applied Mathematics 49 (1993) 169-178. Chebyshev polynomials of the third and fourth kinds, orthogonal with respect to (l+ x)‘/‘(l- x)-‘I* and (l- x)‘/*(l+ x)-‘/~, respectively, on [ - 1, 11, are less well known than traditional first- and second-kind polynomials. We therefore summarise basic properties of all four polynomials, and then show how some well-known properties of first-kind polynomials extend to cover second-, third- and fourth-kind polynomials. Specifically, we summarise a recent set of first-, second-, third- and fourth-kind results for near-minimax constrained approximation by series and interpolation criteria, then we give new uniform convergence results for the indefinite integration of functions weighted by (1 + x)-i/* or (1 - x)-l/* using third- or fourth-kind polynomial expansions, and finally we establish a set of logarithmically singular integral transforms for which weighted first-, second-, third- and fourth-kind polynomials are eigenfunctions. -
Generalizations of Chebyshev Polynomials and Polynomial Mappings
TRANSACTIONS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 359, Number 10, October 2007, Pages 4787–4828 S 0002-9947(07)04022-6 Article electronically published on May 17, 2007 GENERALIZATIONS OF CHEBYSHEV POLYNOMIALS AND POLYNOMIAL MAPPINGS YANG CHEN, JAMES GRIFFIN, AND MOURAD E.H. ISMAIL Abstract. In this paper we show how polynomial mappings of degree K from a union of disjoint intervals onto [−1, 1] generate a countable number of spe- cial cases of generalizations of Chebyshev polynomials. We also derive a new expression for these generalized Chebyshev polynomials for any genus g, from which the coefficients of xn can be found explicitly in terms of the branch points and the recurrence coefficients. We find that this representation is use- ful for specializing to polynomial mapping cases for small K where we will have explicit expressions for the recurrence coefficients in terms of the branch points. We study in detail certain special cases of the polynomials for small degree mappings and prove a theorem concerning the location of the zeroes of the polynomials. We also derive an explicit expression for the discrimi- nant for the genus 1 case of our Chebyshev polynomials that is valid for any configuration of the branch point. 1. Introduction and preliminaries Akhiezer [2], [1] and, Akhiezer and Tomˇcuk [3] introduced orthogonal polynomi- als on two intervals which generalize the Chebyshev polynomials. He observed that the study of properties of these polynomials requires the use of elliptic functions. In thecaseofmorethantwointervals,Tomˇcuk [17], investigated their Bernstein-Szeg˝o asymptotics, with the theory of Hyperelliptic integrals, and found expressions in terms of a certain Abelian integral of the third kind. -
Chebyshev and Fourier Spectral Methods 2000
Chebyshev and Fourier Spectral Methods Second Edition John P. Boyd University of Michigan Ann Arbor, Michigan 48109-2143 email: [email protected] http://www-personal.engin.umich.edu/jpboyd/ 2000 DOVER Publications, Inc. 31 East 2nd Street Mineola, New York 11501 1 Dedication To Marilyn, Ian, and Emma “A computation is a temptation that should be resisted as long as possible.” — J. P. Boyd, paraphrasing T. S. Eliot i Contents PREFACE x Acknowledgments xiv Errata and Extended-Bibliography xvi 1 Introduction 1 1.1 Series expansions .................................. 1 1.2 First Example .................................... 2 1.3 Comparison with finite element methods .................... 4 1.4 Comparisons with Finite Differences ....................... 6 1.5 Parallel Computers ................................. 9 1.6 Choice of basis functions .............................. 9 1.7 Boundary conditions ................................ 10 1.8 Non-Interpolating and Pseudospectral ...................... 12 1.9 Nonlinearity ..................................... 13 1.10 Time-dependent problems ............................. 15 1.11 FAQ: Frequently Asked Questions ........................ 16 1.12 The Chrysalis .................................... 17 2 Chebyshev & Fourier Series 19 2.1 Introduction ..................................... 19 2.2 Fourier series .................................... 20 2.3 Orders of Convergence ............................... 25 2.4 Convergence Order ................................. 27 2.5 Assumption of Equal Errors ........................... -
Dymore User's Manual Chebyshev Polynomials
Dymore User's Manual Chebyshev polynomials Olivier A. Bauchau August 27, 2019 Contents 1 Definition 1 1.1 Zeros and extrema....................................2 1.2 Orthogonality relationships................................3 1.3 Derivatives of Chebyshev polynomials..........................5 1.4 Integral of Chebyshev polynomials............................5 1.5 Products of Chebyshev polynomials...........................5 2 Chebyshev approximation of functions of a single variable6 2.1 Expansion of a function in Chebyshev polynomials...................6 2.2 Evaluation of Chebyshev expansions: Clenshaw's recurrence.............7 2.3 Derivatives and integrals of Chebyshev expansions...................7 2.4 Products of Chebyshev expansions...........................8 2.5 Examples.........................................9 2.6 Clenshaw-Curtis quadrature............................... 10 3 Chebyshev approximation of functions of two variables 12 3.1 Expansion of a function in Chebyshev polynomials................... 12 3.2 Evaluation of Chebyshev expansions: Clenshaw's recurrence............. 13 3.3 Derivatives of Chebyshev expansions.......................... 14 4 Chebychev polynomials 15 4.1 Examples......................................... 16 1 Definition Chebyshev polynomials [1,2] form a series of orthogonal polynomials, which play an important role in the theory of approximation. The lowest polynomials are 2 3 4 2 T0(x) = 1;T1(x) = x; T2(x) = 2x − 1;T3(x) = 4x − 3x; T4(x) = 8x − 8x + 1;::: (1) 1 and are depicted in fig.1. The polynomials can be generated from the following recurrence rela- tionship Tn+1 = 2xTn − Tn−1; n ≥ 1: (2) 1 0.8 0.6 0.4 0.2 0 −0.2 −0.4 CHEBYSHEV POLYNOMIALS −0.6 −0.8 −1 −1 −0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8 1 XX Figure 1: The seven lowest order Chebyshev polynomials It is possible to give an explicit expression of Chebyshev polynomials as Tn(x) = cos(n arccos x): (3) This equation can be verified by using elementary trigonometric identities. -
Approximation Atkinson Chapter 4, Dahlquist & Bjork Section 4.5
Approximation Atkinson Chapter 4, Dahlquist & Bjork Section 4.5, Trefethen's book Topics marked with ∗ are not on the exam 1 In approximation theory we want to find a function p(x) that is `close' to another function f(x). We can define closeness using any metric or norm, e.g. Z 2 2 kf(x) − p(x)k2 = (f(x) − p(x)) dx or kf(x) − p(x)k1 = sup jf(x) − p(x)j or Z kf(x) − p(x)k1 = jf(x) − p(x)jdx: In order for these norms to make sense we need to restrict the functions f and p to suitable function spaces. The polynomial approximation problem takes the form: Find a polynomial of degree at most n that minimizes the norm of the error. Naturally we will consider (i) whether a solution exists and is unique, (ii) whether the approximation converges as n ! 1. In our section on approximation (loosely following Atkinson, Chapter 4), we will first focus on approximation in the infinity norm, then in the 2 norm and related norms. 2 Existence for optimal polynomial approximation. Theorem (no reference): For every n ≥ 0 and f 2 C([a; b]) there is a polynomial of degree ≤ n that minimizes kf(x) − p(x)k where k · k is some norm on C([a; b]). Proof: To show that a minimum/minimizer exists, we want to find some compact subset of the set of polynomials of degree ≤ n (which is a finite-dimensional space) and show that the inf over this subset is less than the inf over everything else. -
32 FA15 Abstracts
32 FA15 Abstracts IP1 metric simple exclusion process and the KPZ equation. In Vector-Valued Nonsymmetric and Symmetric Jack addition, the experiments of Takeuchi and Sano will be and Macdonald Polynomials briefly discussed. For each partition τ of N there are irreducible representa- Craig A. Tracy tions of the symmetric group SN and the associated Hecke University of California, Davis algebra HN (q) on a real vector space Vτ whose basis is [email protected] indexed by the set of reverse standard Young tableaux of shape τ. The talk concerns orthogonal bases of Vτ -valued polynomials of x ∈ RN . The bases consist of polyno- IP6 mials which are simultaneous eigenfunctions of commuta- Limits of Orthogonal Polynomials and Contrac- tive algebras of differential-difference operators, which are tions of Lie Algebras parametrized by κ and (q, t) respectively. These polynomi- als reduce to the ordinary Jack and Macdonald polynomials In this talk, I will discuss the connection between superin- when the partition has just one part (N). The polynomi- tegrable systems and classical systems of orthogonal poly- als are constructed by means of the Yang-Baxter graph. nomials in particular in the expansion coefficients between There is a natural bilinear form, which is positive-definite separable coordinate systems, related to representations of for certain ranges of parameter values depending on τ,and the (quadratic) symmetry algebras. This connection al- there are integral kernels related to the bilinear form for lows us to extend the Askey scheme of classical orthogonal the group case, of Gaussian and of torus type. The mate- polynomials and the limiting processes within the scheme. -
Orthogonal Functions: the Legendre, Laguerre, and Hermite Polynomials
ORTHOGONAL FUNCTIONS: THE LEGENDRE, LAGUERRE, AND HERMITE POLYNOMIALS THOMAS COVERSON, SAVARNIK DIXIT, ALYSHA HARBOUR, AND TYLER OTTO Abstract. The Legendre, Laguerre, and Hermite equations are all homogeneous second order Sturm-Liouville equations. Using the Sturm-Liouville Theory we will be able to show that polynomial solutions to these equations are orthogonal. In a more general context, finding that these solutions are orthogonal allows us to write a function as a Fourier series with respect to these solutions. 1. Introduction The Legendre, Laguerre, and Hermite equations have many real world practical uses which we will not discuss here. We will only focus on the methods of solution and use in a mathematical sense. In solving these equations explicit solutions cannot be found. That is solutions in in terms of elementary functions cannot be found. In many cases it is easier to find a numerical or series solution. There is a generalized Fourier series theory which allows one to write a function f(x) as a linear combination of an orthogonal system of functions φ1(x),φ2(x),...,φn(x),... on [a; b]. The series produced is called the Fourier series with respect to the orthogonal system. While the R b a f(x)φn(x)dx coefficients ,which can be determined by the formula cn = R b 2 , a φn(x)dx are called the Fourier coefficients with respect to the orthogonal system. We are concerned only with showing that the Legendre, Laguerre, and Hermite polynomial solutions are orthogonal and can thus be used to form a Fourier series. In order to proceed we must define an inner product and define what it means for a linear operator to be self- adjoint. -
Orthogonal Polynomials on the Unit Circle Associated with the Laguerre Polynomials
PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 129, Number 3, Pages 873{879 S 0002-9939(00)05821-4 Article electronically published on October 11, 2000 ORTHOGONAL POLYNOMIALS ON THE UNIT CIRCLE ASSOCIATED WITH THE LAGUERRE POLYNOMIALS LI-CHIEN SHEN (Communicated by Hal L. Smith) Abstract. Using the well-known fact that the Fourier transform is unitary, we obtain a class of orthogonal polynomials on the unit circle from the Fourier transform of the Laguerre polynomials (with suitable weights attached). Some related extremal problems which arise naturally in this setting are investigated. 1. Introduction This paper deals with a class of orthogonal polynomials which arise from an application of the Fourier transform on the Laguerre polynomials. We shall briefly describe the essence of our method. Let Π+ denote the upper half plane fz : z = x + iy; y > 0g and let Z 1 H(Π+)=ff : f is analytic in Π+ and sup jf(x + yi)j2 dx < 1g: 0<y<1 −∞ It is well known that, from the Paley-Wiener Theorem [4, p. 368], the Fourier transform provides a unitary isometry between the spaces L2(0; 1)andH(Π+): Since the Laguerre polynomials form a complete orthogonal basis for L2([0; 1);xαe−x dx); the application of Fourier transform to the Laguerre polynomials (with suitable weight attached) generates a class of orthogonal rational functions which are com- plete in H(Π+); and by composition of which with the fractional linear transfor- mation (which maps Π+ conformally to the unit disc) z =(2t − i)=(2t + i); we obtain a family of polynomials which are orthogonal with respect to the weight α t j j sin 2 dt on the boundary z = 1 of the unit disc. -
Generalizations and Specializations of Generating Functions for Jacobi, Gegenbauer, Chebyshev and Legendre Polynomials with Definite Integrals
Journal of Classical Analysis Volume 3, Number 1 (2013), 17–33 doi:10.7153/jca-03-02 GENERALIZATIONS AND SPECIALIZATIONS OF GENERATING FUNCTIONS FOR JACOBI, GEGENBAUER, CHEBYSHEV AND LEGENDRE POLYNOMIALS WITH DEFINITE INTEGRALS HOWARD S. COHL AND CONNOR MACKENZIE Abstract. In this paper we generalize and specialize generating functions for classical orthogo- nal polynomials, namely Jacobi, Gegenbauer, Chebyshev and Legendre polynomials. We derive a generalization of the generating function for Gegenbauer polynomials through extension a two element sequence of generating functions for Jacobi polynomials. Specializations of generat- ing functions are accomplished through the re-expression of Gauss hypergeometric functions in terms of less general functions. Definite integrals which correspond to the presented orthogonal polynomial series expansions are also given. 1. Introduction This paper concerns itself with analysis of generating functions for Jacobi, Gegen- bauer, Chebyshev and Legendre polynomials involving generalization and specializa- tion by re-expression of Gauss hypergeometric generating functions for these orthog- onal polynomials. The generalizations that we present here are for two of the most important generating functions for Jacobi polynomials, namely [4, (4.3.1–2)].1 In fact, these are the first two generating functions which appear in Section 4.3 of [4]. As we will show, these two generating functions, traditionally expressed in terms of Gauss hy- pergeometric functions, can be re-expressed in terms of associated Legendre functions (and also in terms of Ferrers functions, associated Legendre functions on the real seg- ment ( 1,1)). Our Jacobi polynomial generating function generalizations, Theorem 1, Corollary− 1 and Corollary 2, generalize the generating function for Gegenbauer polyno- mials. -
Arxiv:1903.11395V3 [Math.NA] 1 Dec 2020 M
Noname manuscript No. (will be inserted by the editor) The Gauss quadrature for general linear functionals, Lanczos algorithm, and minimal partial realization Stefano Pozza · Miroslav Prani´c Received: date / Accepted: date Abstract The concept of Gauss quadrature can be generalized to approx- imate linear functionals with complex moments. Following the existing lit- erature, this survey will revisit such generalization. It is well known that the (classical) Gauss quadrature for positive definite linear functionals is connected with orthogonal polynomials, and with the (Hermitian) Lanczos algorithm. Analogously, the Gauss quadrature for linear functionals is connected with for- mal orthogonal polynomials, and with the non-Hermitian Lanczos algorithm with look-ahead strategy; moreover, it is related to the minimal partial realiza- tion problem. We will review these connections pointing out the relationships between several results established independently in related contexts. Original proofs of the Mismatch Theorem and of the Matching Moment Property are given by using the properties of formal orthogonal polynomials and the Gauss quadrature for linear functionals. Keywords Linear functionals · Matching moments · Gauss quadrature · Formal orthogonal polynomials · Minimal realization · Look-ahead Lanczos algorithm · Mismatch Theorem. 1 Introduction Let A be an N × N Hermitian positive definite matrix and v a vector so that v∗v = 1, where v∗ is the conjugate transpose of v. Consider the specific linear S. Pozza Faculty of Mathematics and Physics, Charles University, Sokolovsk´a83, 186 75 Praha 8, Czech Republic. Associated member of ISTI-CNR, Pisa, Italy, and member of INdAM- GNCS group, Italy. E-mail: [email protected]ff.cuni.cz arXiv:1903.11395v3 [math.NA] 1 Dec 2020 M. -
Arxiv:2008.08079V2 [Math.FA] 29 Dec 2020 Hypergroups Is Not Required)
HARMONIC ANALYSIS OF LITTLE q-LEGENDRE POLYNOMIALS STEFAN KAHLER Abstract. Many classes of orthogonal polynomials satisfy a specific linearization prop- erty giving rise to a polynomial hypergroup structure, which offers an elegant and fruitful link to harmonic and functional analysis. From the opposite point of view, this allows regarding certain Banach algebras as L1-algebras, associated with underlying orthogonal polynomials or with the corresponding orthogonalization measures. The individual be- havior strongly depends on these underlying polynomials. We study the little q-Legendre polynomials, which are orthogonal with respect to a discrete measure. Their L1-algebras have been known to be not amenable but to satisfy some weaker properties like right character amenability. We will show that the L1-algebras associated with the little q- Legendre polynomials share the property that every element can be approximated by linear combinations of idempotents. This particularly implies that these L1-algebras are weakly amenable (i. e., every bounded derivation into the dual module is an inner deriva- tion), which is known to be shared by any L1-algebra of a locally compact group. As a crucial tool, we establish certain uniform boundedness properties of the characters. Our strategy relies on continued fractions, character estimations and asymptotic behavior. 1. Introduction 1.1. Motivation. One of the most famous results of mathematics, the ‘Banach–Tarski paradox’, states that any ball in d ≥ 3 dimensions can be split into a finite number of pieces in such a way that these pieces can be reassembled into two balls of the original size. It is also well-known that there is no analogue for d 2 f1; 2g, and the Banach–Tarski paradox heavily relies on the axiom of choice [37]. -
8.3 - Chebyshev Polynomials
8.3 - Chebyshev Polynomials 8.3 - Chebyshev Polynomials Chebyshev polynomials Definition Chebyshev polynomial of degree n ≥= 0 is defined as Tn(x) = cos (n arccos x) ; x 2 [−1; 1]; or, in a more instructive form, Tn(x) = cos nθ ; x = cos θ ; θ 2 [0; π] : Recursive relation of Chebyshev polynomials T0(x) = 1 ;T1(x) = x ; Tn+1(x) = 2xTn(x) − Tn−1(x) ; n ≥ 1 : Thus 2 3 4 2 T2(x) = 2x − 1 ;T3(x) = 4x − 3x ; T4(x) = 8x − 8x + 1 ··· n−1 Tn(x) is a polynomial of degree n with leading coefficient 2 for n ≥ 1. 8.3 - Chebyshev Polynomials Orthogonality Chebyshev polynomials are orthogonal w.r.t. weight function w(x) = p 1 . 1−x2 Namely, Z 1 T (x)T (x) 0 if m 6= n np m dx = (1) 2 π −1 1 − x 2 if n = m for each n ≥ 1 Theorem (Roots of Chebyshev polynomials) The roots of Tn(x) of degree n ≥ 1 has n simple zeros in [−1; 1] at 2k−1 x¯k = cos 2n π ; for each k = 1; 2 ··· n : Moreover, Tn(x) assumes its absolute extrema at 0 kπ 0 k x¯k = cos n ; with Tn(¯xk) = (−1) ; for each k = 0; 1; ··· n : 0 −1 k For k = 0; ··· n, Tn(¯xk) = cos n cos (cos(kπ=n)) = cos(kπ) = (−1) : 8.3 - Chebyshev Polynomials Definition A monic polynomial is a polynomial with leading coefficient 1. The monic Chebyshev polynomial T~n(x) is defined by dividing Tn(x) by 2n−1; n ≥ 1.