C O M P L E X FACTORIZATIONS O F T H E F I B O N A C C I AND LUCAS NUMBERS

Similar documents
A Note on the Determinant of Five-Diagonal Matrices with Fibonacci Numbers

COMPLEX FACTORIZATION BY CHEBYSEV POLYNOMIALS

-P" -p. and V n = a n + ft\ (1.2)

On the Pell Polynomials

GOLDEN SEQUENCES OF MATRICES WITH APPLICATIONS TO FIBONACCI ALGEBRA

ADVANCED PROBLEMS AND SOLUTIONS

Z J7 TT I?2 17 n r n+l''' r n+4m+l (1 A \

A Probabilistic View of Certain Weighted Fibonacci Sums

F A M I L I E S OF IDENTITIES INVOLVING SUMS OF POWERS OF THE FIBONACCI AND LUCAS NUMBERS

Background on Linear Algebra - Lecture 2

DYNAMICS OF THE ZEROS OF FIBONACCI POLYNOMIALS M. X. He Nova Southeastern University, Fort Lauderdale, FL. D, Simon

CHOLESKY ALGORITHM MATRICES OF FIBONACCI TYPE AND PROPERTIES OF GENERALIZED SEQUENCES*

L U C A S SEQUENCES AND FUNCTIONS O F A 3-BY-3 M A T R I X

SOME FORMULAE FOR THE FIBONACCI NUMBERS

GENERATING FUNCTIONS OF CENTRAL VALUES IN GENERALIZED PASCAL TRIANGLES. CLAUDIA SMITH and VERNER E. HOGGATT, JR.

FORMULAS FOR P + 3^ + + n p

SOME PROPERTIES OF THIRD-ORDER RECURRENCE RELATIONS

EXPANSION OF ANALYTIC FUNCTIONS IN TERMS INVOLVING LUCAS NUMBERS OR SIMILAR NUMBER SEQUENCES

Discrete Math, Spring Solutions to Problems V

arxiv: v1 [math.na] 30 Jun 2011

ON QUADRAPELL NUMBERS AND QUADRAPELL POLYNOMIALS

Lecture 2 INF-MAT : A boundary value problem and an eigenvalue problem; Block Multiplication; Tridiagonal Systems

Chapter 2 Spectra of Finite Graphs

LINEAR RECURRENCES AND CHEBYSHEV POLYNOMIALS

INTEGER POWERS OF ANTI-BIDIAGONAL HANKEL MATRICES

Lucas Polynomials and Power Sums

ON SOME RECIPROCAL SUMS OF BROUSSEAU: AN ALTERNATIVE APPROACH TO THAT OF CARLITZ

M.A. Botchev. September 5, 2014

VAROL'S PERMUTATION AND ITS GENERALIZATION. Bolian Liu South China Normal University, Guangzhou, P. R. of China {Submitted June 1994)

Boolean Inner-Product Spaces and Boolean Matrices

arxiv: v1 [math.nt] 17 Nov 2011

X(^+(2^i) = i + X02^r + i.

ELA

Research Article The Adjacency Matrix of One Type of Directed Graph and the Jacobsthal Numbers and Their Determinantal Representation

1. Introduction Definition 1.1. Let r 1 be an integer. The r-generalized Fibonacci sequence {G n } is defined as

ASYMPTOTIC DISTRIBUTION OF THE MAXIMUM CUMULATIVE SUM OF INDEPENDENT RANDOM VARIABLES

MATH 341 MIDTERM 2. (a) [5 pts] Demonstrate that A and B are row equivalent by providing a sequence of row operations leading from A to B.

ELEMENTARY PROBLEMS AND SOLUTIONS. Edited by Russ Euler and Jawad Sadek

SOME SUMMATION IDENTITIES USING GENERALIZED g-matrices

FIFTH ROOTS OF FIBONACCI FRACTIONS. Christopher P. French Grinnell College, Grinnell, IA (Submitted June 2004-Final Revision September 2004)

Discrete Mathematics

Summation of certain infinite Fibonacci related series

AND RELATED NUMBERS. GERHARD ROSENBERGER Dortmund, Federal Republic of Germany (Submitted April 1982)

On the (s,t)-pell and (s,t)-pell-lucas numbers by matrix methods

The generalized order-k Fibonacci Pell sequence by matrix methods

Rational Trigonometry. Rational Trigonometry

Divisibility in the Fibonacci Numbers. Stefan Erickson Colorado College January 27, 2006

On the generating matrices of the k-fibonacci numbers

SQUARE ROOTS OF 2x2 MATRICES 1. Sam Northshield SUNY-Plattsburgh

An Efficient Algorithm for Deriving Summation Identities from Mutual Recurrences

COMPOSITIONS AND FIBONACCI NUMBERS

The inverse of a tridiagonal matrix

MATH 423 Linear Algebra II Lecture 33: Diagonalization of normal operators.

Fibonacci and k Lucas Sequences as Series of Fractions

ON A KIND OF GENERALIZED ARITHMETIC-GEOMETRIC PROGRESSION

F. T. HOWARD AND CURTIS COOPER

Yi Wang Department of Applied Mathematics, Dalian University of Technology, Dalian , China (Submitted June 2002)

DIFFERENTIAL PROPERTIES OF A GENERAL CLASS OF POLYNOMIALS. Richard Andre-Jeannin IUT GEA, Route de Romain, Longwy, France (Submitted April 1994)

Eigenvectors and Reconstruction

arxiv: v1 [math.co] 20 Aug 2015

1. INTRODUCTION. Figure 1: An ellipse with b < 0. are the image of the n th roots of unity under the mapping. n,j ) + (a n + b n ) (2) j=0

Numerical Linear Algebra

^ ) = ^ : g ' f ^4(x)=a(xr + /xxr,

w = X ^ = ^ ^, (i*i < ix

Numerical Linear Algebra Homework Assignment - Week 2

Counting k-marked Durfee Symbols

ALTERNATING SUMS OF FIBONACCI PRODUCTS

DIOPHANTINE EQUATIONS, FIBONACCI HYPERBOLAS, AND QUADRATIC FORMS. Keith Brandt and John Koelzer

Bidiagonal decompositions, minors and applications

Frame Diagonalization of Matrices

RANDOM FIBONACCI-TYPE SEQUENCES

1. I N T R O D U C T I O N. DeMoivre (1718) used the generating function (found by employing the recurrence) for the

Links Between Sums Over Paths in Bernoulli s Triangles and the Fibonacci Numbers

Supplementary Information

f = 0 (n < 0), fj = 1, f = J2 f. (n > 1).

q-counting hypercubes in Lucas cubes

Transformations Preserving the Hankel Transform

Polynomial Formula for Sums of Powers of Integers

Phased Tilings and Generalized Fibonacci Identities

GENERAL SOLUTION OF A FIBONACCI-LIKE RECURSION RELATION AND APPLICATIONS

REPRESENTATION GRIDS FOR CERTAIN MORGAN-VOYCE NUMBERS A. F. Horadam The University of New England, Annidale, 2351, Australia (Submitted February 1998)

The Fibonacci Identities of Orthogonality

G E N E R A L I Z E D C O N V O L U T I O N A R R A Y S

Remember. Passover: A Time. The to

ON LINEAR COMBINATIONS OF CHEBYSHEV POLYNOMIALS arxiv: v1 [math.nt] 9 Nov 2013

Orthogonal diagonalization for complex skew-persymmetric anti-tridiagonal Hankel matrices

Properties of Linear Transformations from R n to R m

arxiv: v1 [math.nt] 6 Apr 2018

Discrete Orthogonal Polynomials on Equidistant Nodes

Linear algebra II Homework #1 due Thursday, Feb A =

On the positivity of linear weights in WENO approximations. Abstract

= W z1 + W z2 and W z1 z 2

EQUATIONS WHOSE ROOTS ARE T I E nth POWERS OF T I E ROOTS OF A GIVEN CUBIC EQUATION

Generalized Burgers equations and Miura Map in nonabelian ring. nonabelian rings as integrable systems.

A Divide-and-Conquer Algorithm for Functions of Triangular Matrices

±i-iy (j)^> = P"±(-iy (j)#> (2)

M _ J 1, 0 ] - - ^ + 2 [ 1, 0 ],

Sparse polynomial interpolation in Chebyshev bases

Some Determinantal Identities Involving Pell Polynomials

Legendre s Equation. PHYS Southern Illinois University. October 18, 2016

Transcription:

C O M P L E X FACTORIZATIONS O F T H E F I B O N A C C I AND LUCAS NUMBERS Nathan D. Cahill, John R. D'Errico, and John P* Spence Eastman Kodak Company, 343 State Street, Rochester, NY 4650 {natfaan. cahill, john.derrico, john.spence]@kodak.com (Submitted November 2000). INTRODUCTION It is always fascinating to see what'results when seemingly different areas of mathematics overlap. This article reveals one such result; number theory and linear algebra (with the help of orthogonal polynomials) are intertwined to yield complex factorizations of the Fibonacci and Lucas numbers. In Sections 2 and 3 3 respectively, we derive these complex factorizations: and n-l F. = W-V k=l FCOS ṉk n{k-\) i\\ z =ni-2/ COS' k=l\ Along the way, we also establish the general forms: and w>2, n>\. ^sinjheo^-i)) r -i r- ( _ u.^, n>l, sin(cos X-i)) L = 2i" cos(n cos _ (- )), n >. A simple proof of (.) can be obtained by considering the roots of Fibonacci polynomials (see Webb and Parberry [7] and Hoggatt and Long [3]). This paper proves (.) by considering how the Fibonacci numbers can be connected to Chebyshev polynomials by determinants of a sequence of matrices, and then illustrates a connection between the Lucas numbers and Chebyshev polynomials (and hence proves (.2)) by using a slightly different sequence of matrices. (.3) and (.4) are not new developments (see Morgado [4] and Rivlin [5]); however, they are of interest here because they fall out of the derivations of (.) and (.2) quite naturally. In order to simplify the derivations of (.) and (.2), we present the following lemma (the proof is included for completeness). Lemma : Let {H(H), n =,2,...} be a sequence of tridiagonal matrices of the form: (.) (.2) (.3) (.4) "2, ^2,2 "2,3 H(«) = A,.2 Ki *. (.5) n.n l Then the successive determinants of H(/i) are given by the recursive formula: K 2003] 3

H() =/* U, \m)\=hihi-hihi> m n )\=h JlI(n-\)\-h _ l Ji n, - i mn-2)l Proof: We prove Lemma by the second principle of finite induction, computing all deter minants by cofactor expansion. For the basis step, we have: H(l)M(/> U )l=\i, (.6) H(2) = \&\ h X2)\ -",^2,2 "l,2"2,b Then H(3) = (hi hi o "I "2, "2,2 "2,3 [ hi hi) tive step, we assume H(* + ) = =h + i M Mk)\-h Ml = ^ 3 ^ ( 2 ) - ^ 3 (h i h»\ ", # *,2 l hi) = \ 3 H ( 2 ) - / I 2 J 3 \Jl(k)\=h kk \ll{k-x)\-h k _^kh kk _^K(k-2) (hi hi ] "2, *ha "2,3 "3,2 ^3,3 %-2,fc-l "k-l,k-2 K-\,k-l "k-l,k \,k-\ \ f c \Ml V ''k+l.k "k+l,k+lj 'h,, \i h l2 hi hi "2,3 "3,2 "3,3 = h + imi\ ll ( k )\-hk + i h Mj l (k-l)\. D n k-l,k-l h-l,k-2 "k-l,k-l "k-l,k 0 h k + l,k 2. COMPLEX FACTORIZATION OF THE FIBONACCI NUMBERS In order to derive (.), we introduce the sequence of matrices {M(ri),n = l, 2,...}, where M(n) is the» x» tridiagonal matrix with entries m kk = \, \<k<n, and m k _^k = m kk _ x -i, 2 < k<n. That is, '\ i i i M(«) = i (2.). / i 4 [FEB.

According to Lemma, successive determinants of M(w) are given by the recursive formula: M() =, M(2) = l 2 - i 2 = 2, (2.2) M(^) = l M(^-l) -i 2 M(/i-2) = M(^i-l) -h Clearly, this is also the Fibonacci sequence, starting with F 2. Hence, F n = \M(n-l)\,n>2. (2.3) There are a variety of ways to compute the matrix determinant (see Golub and Van Loan [2] for more details). In addition to the method of cofactor expansion, the determinant of a matrix can be found by taking the product of its eigenvalues. Therefore, we will compute the spectrum of M(/i) in order to find an alternate formulation for M(n)\. We now introduce another sequence of matrices {G(w)? n =,2,...}, where G(w) is the n x n tridiagonal matrix with entries g k k = 0,l<k <n, and g k _ t k - g^-i =, 2<k<n. That is, G(«): 0 0 0.' 0 (2.4) Note that M(w) = l+ig(n). Let A k, k =,2,...,n, be the eigenvalues of G(ri) (with associated eigenvectors x k ). Then, for eachy, M(ri)\j = [I+iG(ri)]Xj = lxj +ig(«)x / = x y +iaj*j = (+M,)*,.. Therefore, fi k = +il k, k =,2,..., n, are the eigenvalues of M(/i). Hence, \M(n)\ = fl(l+a k Xn>L k=l In order to determine the X k 's, we recall that each X k is a zero of the characteristic polynomial p (X) - G(») - XI. Since G(«) - I I is a tridiagonal matrix, i.e., (2.5) G(n)-XY = f-x -X -X (2.6) we use Lemma to establish a recursive formula for the characteristic polynomials of (G(»), «=,2,...}: Pi{X) = -X, p 2 (X) = X 2 -l, (2.7) This family of characteristic polynomials can be transformed into another family {U (x), n > } by the transformation X = -2x: 2003] 5

U i (x) = 2x, U 2 (x) = 4x 2 -\, (2.8) U {x) = 2xU n _ (x)-u n. 2 (x). The family {U (x), n > } is the set of Chebyshev polynomials of the second kind. It is a wellknown fact (see Rivlin [5]) that defining x = cos# allows the Chebyshev polynomials of the second kind to be written as: u(x)=srn[(n + l)0] sm0 From (2.9), we can see that the roots of U n (x) = 0 are given by 0 k = -~f, k =,2,..., n, or x k = cos0 = cos j-, k -,2,...,n. Applying the transformation X = -2x, we now have the eigenvalues of G(n): -2 cos- nk k, * = l,2,...,/i. (2.0) ~ w + Combining (2.3), (2.5), and (2.0), we have ^fi = M(/i) = n ( l - 2 i c o s ^ n>\ (2.) which is identical to the complex factorization (.). From (2.6), we can think of Chebyshev polynomials of the second kind as being generated by determinants of successive matrices of the form A(w, x) = 2x 2x 2x 2x (2.2) where A(w, x) is n x n. If we note that M(ri) = /A(w, - -0, then we have: \M(ri)\=f Combining (2.3), (2.9), and (2.3) yields Since it is also true that n+ A M)k<-0 sin((» + l)cos-'(-i)) sin(cos _ (- )) (2.3) (2.4) (.3) holds. J7 = = f-o sin ( cos " (-^)) sin(cos _ (-^))' 3. COMPLEX FACTORIZATION OF THE LUCAS NUMMEMS The process by which we derive (.2) is similar to that of the derivation of (.), but it has its owe intricacies. Consider the sequence of matrices {S(TI), n =,2,...}, where S(w) is the n x n tridiagonal matrix with entries \ x = y, $ kfk =, 2<k<n, and % u = s k^ml = i, 2 < k < n. That is, 6 [FEB.

S(») = 2 ' i i i. i i According to Lemma, successive determinants-of S(/i) are given by the recursive formula: S() = ±, (3.) S(2) = ± - / 2 = f, (3.2) S(«) = S(«-) -/ 2 S(»-2) = S(«-) + S(»-2). Clearly, each number in this sequence is half of the corresponding Lucas number. We have L n = 2\S(n)l n>h (3.3) Unlike the derivation in the previous section, we will not compute the spectrum of S(w) directly. Instead, we will first note the following: S(«) =i (l+e i e f)s(»), (3.4) where tj is the j * column of the identity matrix. (This is true because + e^j" = 2.) Furthermore, we can express the right-hand side of (3.4) in the following way: i (l + e i ens(«) =i l+/(g(/i) + e ^), (3.5) where G(«) is the matrix given in (2.4). Let y k, k = l,2,...,n be the eigenvalues of G(n) + e x ej (with associated eigenvectors j k ). Then, for eachj, Therefore, ( l + i t G ^ + e^))^- = Iy y +i(g(«) + e e )y / = y, +i> y y y = (l+iy y )y y. i\l + i(g(n) + t^)\^^u( l+i r k ) (3.6) J f c = l In order to determine the y ^ss, we recall that each y k is a zero of the characteristic polynomial q (y) = G(«) + CjcJ -yl\. Since ( I - jepj) = j, we can alternately represent the characteristic polynomial as ^ ( r ) = 2 (l-le e?')(g(») + e ^ - r l ). (3.7) Since q n (y) is twice the determinant of a tridiagonal matrix, i.e., q (r) = 2\(l-}e ej)(g( n ) + e^-ri)\=2 (-*- 2 i -r I I - r i - Y, (3.8) we can use Lemma to establish a recursive formula for q (y): 2003J 7

ft00 = -2-> q n (r) = -r<i -i(r)-<i -2(r)- This family of polynomials can be transformed into another family {T (x), n>\} by the transformation y = -2x: T l (x) = x, T 2 (x) = 2x 2 -l, (3.0) r w (x) = 2xr w _ (x)-r w. 2 (x). The family {T n {x\ n>\) is the set of Chebyshev polynomials of the first kind. Rivlin [5] shows that defining x = cos0 allows the Chebyshev polynomials of the first kind to be written as From (3.), we can see that the roots of T n {x) (3.9) ^(x) = cos«$. (3.) = 0 are given by ^ " ^ i ^ - i o ^ *. - s fl fe = c o s ^ ~"*', k=\2,...,n. 0 k = -, k = l,2,...,w, or X = cos?i * * n Applying the transformation y = -2x and considering that the roots of (3.7) are also roots of we now have the eigenvalues of G(n) + e^j'. y k =-2 cos- A*-\) -, * =,2,...,«. (3.2) Combining (3.3)-(3.6) and (3.2), we have 4=Il l-2'cos^-^>l,/i^l, (3.3) which is identical to the complex factorization (.2). From (3.8), we can think of Chebyshev polynomials of the first kind as being generated by determinants of successive matrices of the form B(n,x) = (x 2x k 2x.' 2x (3.4) where B(«, x) is n x n. If we note that S(») = ib(n, - j), then we have S(*) =i" Combining (3.3), (3.), and (3.5) yields»h)i " <- ) (3.5) which is exactly (.4). L = 2 / n c o s ^ c o s - ^ - ^ j,»>, (3.6) 8 [FEB.

4 CONCLUSION This method of exploiting special properties of the Chebyshev polynomials allows us to find other interesting factorizations as well. For instance, the factorizations ^ + 2 = n ( 3-2 c o s ^ y, «>, (4.) n = f t ( 2-2 c o s ^, n>2, (4.2) and 2 -«= nh- ^F%>^l> («) can be derived with judicious choices of entries in tridiagonal matrices (Strang [6] presents a family of tridiagonal matrices that can be used to derive (4.)). It is also possible to compare these factorizations with the Binet-like general formulas (see Burton []) for second-order linear recurrence relations in order to determine which products converge to zero, converge to a nonzero number, or diverge as n approaches infinity. One final note: an interesting (but fairly straightforward) problem for students of complex variables is to prove that (.3) is equivalent to Binet's formula for the Fibonacci Numbers. REFERENCES. D. M. Burton. Elementary Number Theory. 4th ed., pp. 259-74. New York: McGraw-Hill, 998. 2. G. Golub & C. Van Loan. Matrix Computations. 3rd ed., pp. 50-5, 30. Baltimore: Johns Hopkins University Press, 996. 3. V. Hoggatt, Jr., & C. Long. "Divisibility Properties of Generalized Fibonacci Polynomials." The Fibonacci Quarterly 2*2 (974): 3-20. 4. J. Morgado. "Note on the Chebyshev Polynomials and Applications to the Fibonacci Numbers." Poriugaliae Mathematica 52 (995):363-78. 5. T. Rivlin. Chebyshev Polynomials: From Approximation Theory to Algebra and Number Theory. 2nd ed. New York: Wiley & Sons, 990. 6. G. Strang & K. Borre. Linear Algebra, Geodesy and GPS, pp. 555-57. Wellesley, MA: Wellesley-Cambridge, 997. 7. W. A. Webb & E. A. Parberry. "Divisibility Properties of Fibonacci Polynomials." The Fibonacci Quarterly 75 (969):457-63. AMS Classification Numbers: B39, C20,33C52 2003] 9