A Combinatorial Proof of Ihara-Bass's Formula for the Zeta Function Of
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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. -
Interlacing Families I: Bipartite Ramanujan Graphs of All Degrees
Annals of Mathematics 182 (2015), 307{325 Interlacing families I: Bipartite Ramanujan graphs of all degrees By Adam W. Marcus, Daniel A. Spielman, and Nikhil Srivastava Abstract We prove that there exist infinite families of regular bipartite Ramanujan graphs of every degree bigger than 2. We do this by proving a variant of a conjecture of Bilu and Linial about the existence of good 2-lifts of every graph. We also establish the existence of infinite families of \irregular Ramanujan" graphs, whose eigenvalues are bounded by the spectral radius of their universal cover. Such families were conjectured to exist by Linial and others. In particular, we prove the existence of infinite families of (c; d)-biregular bipartite graphs with all nontrivial eigenvalues bounded by p p c − 1 + d − 1 for all c; d ≥ 3. Our proof exploits a new technique for controlling the eigenvalues of certain random matrices, which we call the \method of interlacing polynomials." 1. Introduction Ramanujan graphs have been the focus of substantial study in Theoret- ical Computer Science and Mathematics. They are graphs whose nontrivial adjacency matrix eigenvalues are as small as possible. Previous constructions of Ramanujan graphs have been sporadic, only producing infinite families of Ramanujan graphs of certain special degrees. In this paper, we prove a variant of a conjecture of Bilu and Linial [4] and use it to realize an approach they suggested for constructing bipartite Ramanujan graphs of every degree. Our main technical contribution is a novel existence argument. The con- jecture of Bilu and Linial requires us to prove that every graph has a signed adjacency matrix with all of its eigenvalues in a small range. -
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. -
Ramanujan Graphs of Every Degree
Ramanujan Graphs of Every Degree Adam Marcus (Crisply, Yale) Daniel Spielman (Yale) Nikhil Srivastava (MSR India) Expander Graphs Sparse, regular well-connected graphs with many properties of random graphs. Random walks mix quickly. Every set of vertices has many neighbors. Pseudo-random generators. Error-correcting codes. Sparse approximations of complete graphs. Spectral Expanders Let G be a graph and A be its adjacency matrix a 0 1 0 0 1 b 1 0 1 0 1 e 0 1 0 1 0 c 0 0 1 0 1 1 1 0 1 0 d Eigenvalues λ1 λ2 λn “trivial” ≥ ≥ ···≥ If d-regular (every vertex has d edges), λ1 = d Spectral Expanders If bipartite (all edges between two parts/colors) eigenvalues are symmetric about 0 If d-regular and bipartite, λ = d n − “trivial” a b 0 0 0 1 0 1 0 0 0 1 1 0 0 0 0 0 1 1 c d 1 1 0 0 0 0 0 1 1 0 0 0 e f 1 0 1 0 0 0 Spectral Expanders G is a good spectral expander if all non-trivial eigenvalues are small [ ] -d 0 d Bipartite Complete Graph Adjacency matrix has rank 2, so all non-trivial eigenvalues are 0 a b 0 0 0 1 1 1 0 0 0 1 1 1 0 0 0 1 1 1 c d 1 1 1 0 0 0 1 1 1 0 0 0 e f 1 1 1 0 0 0 Spectral Expanders G is a good spectral expander if all non-trivial eigenvalues are small [ ] -d 0 d Challenge: construct infinite families of fixed degree Spectral Expanders G is a good spectral expander if all non-trivial eigenvalues are small [ ] ( 0 ) -d 2pd 1 2pd 1 d − − − Challenge: construct infinite families of fixed degree Alon-Boppana ‘86: Cannot beat 2pd 1 − Ramanujan Graphs: 2pd 1 − G is a Ramanujan Graph if absolute value of non-trivial eigs 2pd 1 − [ -
Zeta Functions and Chaos Audrey Terras October 12, 2009 Abstract: the Zeta Functions of Riemann, Selberg and Ruelle Are Briefly Introduced Along with Some Others
Zeta Functions and Chaos Audrey Terras October 12, 2009 Abstract: The zeta functions of Riemann, Selberg and Ruelle are briefly introduced along with some others. The Ihara zeta function of a finite graph is our main topic. We consider two determinant formulas for the Ihara zeta, the Riemann hypothesis, and connections with random matrix theory and quantum chaos. 1 Introduction This paper is an expanded version of lectures given at M.S.R.I. in June of 2008. It provides an introduction to various zeta functions emphasizing zeta functions of a finite graph and connections with random matrix theory and quantum chaos. Section 2. Three Zeta Functions For the number theorist, most zeta functions are multiplicative generating functions for something like primes (or prime ideals). The Riemann zeta is the chief example. There are analogous functions arising in other fields such as Selberg’s zeta function of a Riemann surface, Ihara’s zeta function of a finite connected graph. We will consider the Riemann hypothesis for the Ihara zeta function and its connection with expander graphs. Section 3. Ruelle’s zeta function of a Dynamical System, A Determinant Formula, The Graph Prime Number Theorem. The first topic is the Ruelle zeta function which will be shown to be a generalization of the Ihara zeta. A determinant formula is proved for the Ihara zeta function. Then we prove the graph prime number theorem. Section 4. Edge and Path Zeta Functions and their Determinant Formulas, Connections with Quantum Chaos. We define two more zeta functions associated to a finite graph - the edge and path zetas. -
X-Ramanujan-Graphs.Pdf
X-Ramanujan graphs Sidhanth Mohanty* Ryan O’Donnell† April 4, 2019 Abstract Let X be an infinite graph of bounded degree; e.g., the Cayley graph of a free product of finite groups. If G is a finite graph covered by X, it is said to be X-Ramanujan if its second- largest eigenvalue l2(G) is at most the spectral radius r(X) of X, and more generally k-quasi- X-Ramanujan if lk(G) is at most r(X). In case X is the infinite D-regular tree, this reduces to the well known notion of a finite D-regular graph being Ramanujan. Inspired by the Interlacing Polynomials method of Marcus, Spielman, and Srivastava, we show the existence of infinitely many k-quasi-X-Ramanujan graphs for a variety of infinite X. In particular, X need not be a tree; our analysis is applicable whenever X is what we call an additive product graph. This additive product is a new construction of an infinite graph A1 + ··· + Ac from finite “atom” graphs A1,..., Ac over a common vertex set. It generalizes the notion of the free product graph A1 ∗ · · · ∗ Ac when the atoms Aj are vertex-transitive, and it generalizes the notion of the uni- versal covering tree when the atoms Aj are single-edge graphs. Key to our analysis is a new graph polynomial a(A1,..., Ac; x) that we call the additive characteristic polynomial. It general- izes the well known matching polynomial m(G; x) in case the atoms Aj are the single edges of G, and it generalizes the r-characteristic polynomial introduced in [Rav16, LR18]. -
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. -
Zeta Functions of Finite Graphs and Coverings, III
Graph Zeta Functions 1 INTRODUCTION Zeta Functions of Finite Graphs and Coverings, III A. A. Terras Math. Dept., U.C.S.D., La Jolla, CA 92093-0112 E-mail: [email protected] and H. M. Stark Math. Dept., U.C.S.D., La Jolla, CA 92093-0112 Version: March 13, 2006 A graph theoretical analog of Brauer-Siegel theory for zeta functions of number …elds is developed using the theory of Artin L-functions for Galois coverings of graphs from parts I and II. In the process, we discuss possible versions of the Riemann hypothesis for the Ihara zeta function of an irregular graph. 1. INTRODUCTION In our previous two papers [12], [13] we developed the theory of zeta and L-functions of graphs and covering graphs. Here zeta and L-functions are reciprocals of polynomials which means these functions have poles not zeros. Just as number theorists are interested in the locations of the zeros of number theoretic zeta and L-functions, thanks to applications to the distribution of primes, we are interested in knowing the locations of the poles of graph-theoretic zeta and L-functions. We study an analog of Brauer-Siegel theory for the zeta functions of number …elds (see Stark [11] or Lang [6]). As explained below, this is a necessary step in the discussion of the distribution of primes. We will always assume that our graphs X are …nite, connected, rank 1 with no danglers (i.e., degree 1 vertices). Let us recall some of the de…nitions basic to Stark and Terras [12], [13]. -
Algorithms for Classical Orthogonal Polynomials
Konrad-Zuse-Zentrum für Informationstechnik Berlin Takustr. 7, D-14195 Berlin - Dahlem Wolfram Ko epf Dieter Schmersau Algorithms for Classical Orthogonal Polynomials at Berlin Fachb ereich Mathematik und Informatik der Freien Universit Preprint SC Septemb er Algorithms for Classical Orthogonal Polynomials Wolfram Ko epf Dieter Schmersau koepfzibde Abstract In this article explicit formulas for the recurrence equation p x A x B p x C p x n+1 n n n n n1 and the derivative rules 0 x p x p x p x p x n n+1 n n n n1 n and 0 p x p x x p x x n n n n1 n n resp ectively which are valid for the orthogonal p olynomial solutions p x of the dierential n equation 00 0 x y x x y x y x n of hyp ergeometric typ e are develop ed that dep end only on the co ecients x and x which themselves are p olynomials wrt x of degrees not larger than and resp ectively Partial solutions of this problem had b een previously published by Tricomi and recently by Yanez Dehesa and Nikiforov Our formulas yield an algorithm with which it can b e decided whether a given holonomic recur rence equation ie one with p olynomial co ecients generates a family of classical orthogonal p olynomials and returns the corresp onding data density function interval including the stan dardization data in the armative case In a similar way explicit formulas for the co ecients of the recurrence equation and the dierence rule x rp x p x p x p x n n n+1 n n n n1 of the classical orthogonal p olynomials of a discrete variable are given that dep end only