Advances in Linear Algebra & Matrix Theory
Vol.04 No.04(2014), Article ID:52891,5 pages
10.4236/alamt.2014.44019
Estimated Bounds for Zeros of Polynomials from Traces of Graeffe Matrices
Ousmane Moussa Tessa1, Maimouna Salou1, Morou Amidou2
1Département de Mathématiques et d’informatique, Université A. Moumouni de Niamey, Niamey, Niger
2Institut de Recherche sur l’Enseignement des Mathématiques, Université A. Moumouni de Niamey, Niamey, Niger
Email: ousmane@musatesa.net, maimouna_idi@yahoo.fr, moorou_a@yahoo.fr
Copyright © 2014 by authors and Scientific Research Publishing Inc.
This work is licensed under the Creative Commons Attribution International License (CC BY).
http://creativecommons.org/licenses/by/4.0/



Received 28 November 2014; revised 20 December 2014; accepted 26 December 2014
ABSTRACT
In this paper, we combine Graeffe matrices with the classical numerical method of Dandelin-Graeffe to estimate bounds for the moduli of the zeros of polynomials. Furthermore, we give some examples showing significant gain for the convergence towards the polynomials dominant zeros moduli.
Keywords:
Graeffe Matrices, Numerical Approximation of Eigenvalues, Dandelin-Graeffe’s Method, Bounds of Zeros of Polynomial

1. Introduction
Deriving zero bounds for polynomials is a classical problem that has been proven essential in various disciplines such as controling engineering problems, eigenvalue problems in mathematical physics, and digital audio signal processing problems―to name just a few [1] . Specially, a large number of research papers have given bounds of their moduli, e.g., well-known and classical bounds named after Cauchy, Montel and Kojima [2] [3] ; more advanced results can be found in [4] - [8] and references therein. Furthermore, bounds for the zeros of poly- nomials were needed in achieving some numerical computation methods, as providing information on the location of the zeros can be used to find initial guesses for iterative computation algorithms.
An estimated value of the largest moduli of the roots of a polynomial can be obtained as a limit of a sum of power of these roots using resultants [9] . However, it is well-known that computation of polynomials resultants is tedious and expensive; for this, we proceed by determining the trace of the Graffe matrix of order m of the polynomial P, which is exactly the sum of the m-th powers of the eigenvalues of the companion matrix of P. So we get our main result relying on Dandelin-Graeffe method to estimate the largest moduli bounds of the roots of P. This seems to be a significant progress compared to the use of resultants; moreover, it reveals a substantial convergence gain, teaming up with an approach used in [7] . This finding is rather significant in the large available methods used to improve the location of the zeros of polynomials.
The rest of the paper is organized as follows. In Section 2, we introduce the Graeffe matrix of a complex polynomial P and derive its trace from the classical Jordan normal form. In Section 3, we extend the Dandelin- Graeffe’s method to find the maximum moduli of the zeros of P, relying on the limit of Graeffe matrix’s trace of P. Through some examples, Section 3 illustrates that a few iterations of Graeffe’s matrix trace can give very tight bounds for the absolute value of the zeros of polynomials, with comparatively fast convergence.
2. Graeffe Polynomials and Graeffe Matrix’s Trace
For an n-dimensional matrix A, we call the spectrum of A the set of all its eigenvalues, denoted by
. Its spectral radius
is defined by
as the largest magnitude attained by any eigenvalue of A. Setting up the elements of
with their geometric and algebraic multiplicities, determines the eigenstructure of A. It’s well-known that all matrices similar to A have the same eigenstructure, specially we have the useful classical lemma [10] :
Lemma 1. A square complex matrix A of order n is similar to a block diagonal matrix

for
, each block
is a square matrix of order
of the form

For
,
is called a “Jordan block” of
and
the Jordan normal form of
.
Remark: The spectrum of a matrix
is identical with the spectrum of its Jordan normal form.
Lemma 2. If
is a Jordan block of order 

Proof. For arbitrary indices i and j, it is direct to verify the claim by using a proof by induction.
From the previous result, we deduce the two following corollaries:
Corollary 1. The m-th power of an n-dimensional matrix A is similar to the m-th power of its Jordan normal form as a direct sum of upper triangular matrices. Besides, each triangular block will consist of m-th power of its associate eigenvalue on the main diagonal.
Corollary 2. The trace of the m-th power of A is the sum of the m-th powers of the eigenvalues of A.
Definition 1. For 

Let 



Definition 2. The characteristic polynomial of 

Remarks:
1) It can be computed also using resultants, as quoted in the following lemma ( [9] , Thàreme 3.1): assuming that P be a polynomial of degree d and

2) Relying on Proposition 1, it follows that for all


Table 1. Computing time for


Proposition 1. Let P be a polynomial of degree d with complex coefficients, then the trace of 
Proof. It is well-known that the eigenvalues are the zeros of the polynomial P; therefore, the result follows immediately from Corollary 2.
3. Estimation Method of Dandelin-Graeffe
Proposition 2. Let P be a polynomial of degree d with complex coefficients and 
There exists a sequence of polynomials 
the zeros of 


Proof. The basic technique to write down the proclaimed sequence of polynomials is done through an iteration refered to as the Dandelin-Graeffe method (see [6] ).
Starting with 

a polynomial of degree

For the induction process, one performs the following iteration
which transforms 

of the zeros of



Lemma 3.
Let 


Proof. One can refer to [9] (Thèorème 1.4).
As a special case of Lemma 3, we can consider sequences of traces of

Proposition 3. Let 

where 


Remark: It is important to note that the existence of an unique dominant zero is essential to the validity of the previous result, as shown in ( [9] , p. 8). However, there is a more general result which doesn’t rely on neither the existence of a single dominant absolute value of the polynomial’s zero, nor the obligation to browse only terms whose indices are powers of 2. Such generalization, due to Mignotte and Ştefǎnescu [7] includes Lemma 3 as a special case; it can be stated as the following lemma:
Lemma 4. Let 


Remark: Bearing in mind that there is no need to check the unicity of the largest modulus of the zero of a given ploynomial, a few iterations of d consecutive values of the traces 


Proposition 4.
Let 

where 


4. Numerical Results
1) We consider the polynomial
with an unique absolute value of dominant zero, namely 5. The application of the Graeffe’s zero-squaring method (Proposition 3) to the Graeffe’s polynomial of order 

Table 2. Unique dominant bound via Graeffe’s zero-squaring method.
The previous result turns out as a considerably better bound, comparing with some classical explicit bounds gathered from Dehmer ( [4] , p. 1, 2), as shown in Table 3.
Table 3. Classical explicit bounds for 
2) Let 
By Proposition 4, few iterations of sequences of the maximum of 

yield some sharp estimations of the real modulus of this double zero, for small values of m (Table 4).
Table 4. Computation of the largest (double) bound of
Moreover, the method leads to better results when locating explicit bounds for zeros of polynomials as shown in Table 5.
Table 5. Classical explicit bounds for 
3) Let’s now consider the polynomial 


Table 6. Estimation of the largest (triple) bound of
It’s important to notice that the convergence seems to become a bit slower than that in the previous case of the existence of a double dominant zero.
Moreover, the method leads to better results when locating explicit bounds for the zeros of polynomials (see Table 7).
Table 7. Classical explicit bounds for 
Acknowledgements
We would like to thank Professor Maurice Mignotte for his valuable suggestions and comments. We thank also the Editor and the anonymous referees for their comments.
References
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Appendix: Maple Codes
Graeffegen := proc (

local
if 
else G := sort(resultant
end if
end proc:
GraeffeMatrix := proc (

local




sort(CharacteristicPolynomial
end proc:
・ In Graeffegen, P is a polynomial in
・ In GraeffeMatrix, B = CompanionMatrix(P, X) stands for the CompanionMatrix of the polynomial 
















