vol15_pp115-133. 193KB Jun 04 2011 12:05:55 AM

Electronic Journal of Linear Algebra ISSN 1081-3810
A publication of the International Linear Algebra Society
Volume 15, pp. 115-133, April 2006

ELA

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EIGENVALUES AND EIGENVECTORS OF TRIDIAGONAL
MATRICES∗
SAID KOUACHI†
Abstract. This paper is continuation of previous work by the present author, where explicit
formulas for the eigenvalues associated with several tridiagonal matrices were given. In this paper
the associated eigenvectors are calculated explicitly. As a consequence, a result obtained by WenChyuan Yueh and independently by S. Kouachi, concerning the eigenvalues and in particular the
corresponding eigenvectors of tridiagonal matrices, is generalized. Expressions for the eigenvectors
are obtained that differ completely from those obtained by Yueh. The techniques used herein are
based on theory of recurrent sequences. The entries situated on each of the secondary diagonals are
not necessary equal as was the case considered by Yueh.
Key words. Eigenvectors, Tridiagonal matrices.
AMS subject classifications. 15A18.


1. Introduction. The subject of this paper is diagonalization of tridiagonal
matrices. We generalize a result obtained in [5] concerning the eigenvalues and the
corresponding eigenvectors of several tridiagonal matrices. We consider tridiagonal
matrices of the form


−α + b c1 0
0
...
0


b c2
0
...
0
a1





.
.
.
..
..
..


0
a
b
2


An = 
(1)
,
.
.

.
.
.
.


.
.
.
0
0
0




..
.. . .
..
..



.
.
.
.
c
.
n−1

0

n−1

...

...

n−1


0

an−1

−β + b



where {aj }j=1 and {cj }j=1 are two finite subsequences of the sequences {aj }j=1 and
{cj }∞
j=1 of the field of complex numbers C, respectively, and α, β and b are complex
numbers. We suppose that
 2
d1 , if j is odd
j = 1, 2, ...,
(2)
a j cj =
d22 , if j is even
where d 1 and d2 are complex numbers. We mention that matrices of the form (1)
are of circulant type in the special case when α = β = a1 = a2 = ... = 0 and all

the entries on the subdiagonal are equal. They are of Toeplitz type in the special
case when α = β = 0 and all the entries on the subdiagonal are equal and those
on the superdiagonal are also equal (see U. Grenander and G. Szego [4]). When the
∗ Received by the editors 9 January 2006. Accepted for publication 21 March 2006. Handling
Editor: Ludwig Elsner.
† Laboratoire de mathematiques, Universite de badji, Mokhtar, Annaba, 23200, Algeria
([email protected]).

115

Electronic Journal of Linear Algebra ISSN 1081-3810
A publication of the International Linear Algebra Society
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116


S. Kouachi

entries on the principal diagonal are not equal, the calculi of the eigenvalues and the
corresponding eigenvectors becomes very delicate (see S. Kouachi [6]).
When a1 = a2 = ... = c1 = c2 = ... = 1, b = −2 and α = β = 0, the eigenvalues of An
has been constructed by J. F. Elliott [2] and R. T. Gregory and D. Carney [3] to be
λk = −2 + 2 cos


, k = 1, 2, ..., n.
n+1

When a1 = a2 = ... = c1 = c2 = ... = 1, b = −2 and α = 1 and β = 0 or β = 1, the
eigenvalues has been reported to be
λk = −2 + 2 cos


, k = 1, 2, ..., n,
n


and
λk = −2 + 2 cos

2kπ
, k = 1, 2, ..., n,
2n + 1

respectively without proof.
W. Yueh[1] has generalized the results of J. F. Elliott [2] and R. T. Gregory and√D.
Carney [3] to the√case when a1 = a√
ac
2 = ... = a, c1 = c2 = ... = c and α = 0, β =
or α = 0,√β = − ac or α =√
−β = ac
α = β = ac or α = β = − ac. He has calculated, in this case, the eigenvalues and
their corresponding eigenvectors

λk = b + 2 ac cos θk , k = 1, .., n,
(2k−1)π kπ
2kπ

, (2k−1)π
, n and (k−1)π
, k = 1, .., n respectively.
where θk = 2n+1
2n+1 ,
2n
n
In S. Kouachi[5], we have generalized the results of W. Yueh [1] to more general
matrices of the form (1) for any complex constants satisfying condition

aj cj = d2 , j = 1, 2, ...,
where d is a complex number. We have proved that the eigenvalues remain the same as
in the case when the ai ’s and the ci ’s are equal but the components of the eigenvector
(k)
u(k) (σ) associated to the eigenvalue λk , which we denote by uj (σ) , j = 1, .., n , are
of the form
(k)

1−j


uj (σ) = (−d)

(k) d sin(n

aσ 1 ...aσ j−1 u1

− j + 1)θk − β sin(n − j)θ k
, j = 1, ..., n,
d sin nθk − β sin(n − 1)θ k

where θk is given by formula
d2 sin (n + 1) θ k − d (α + β) sin nθ k + αβ sin (n − 1) θ k = 0, k = 1, ..., n.
Recently in S. Kouachi [6], we generalized the above results concerning the eigenvalues
of tridiagonal matrices (1) satisfying condition (2), but we were unable to calculate
the corresponding eigenvectors, in view of the complexity of their expressions. The

Electronic Journal of Linear Algebra ISSN 1081-3810
A publication of the International Linear Algebra Society
Volume 15, pp. 115-133, April 2006


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117

Eigenvalues and Eigenvectors of Tridiagonal Matrices

matrices studied by J. F. Elliott [2] and R. T. Gregory and D. Carney [3] are special
cases of those considered by W. Yueh[1] which are, at their tour, special cases with
regard to those that we have studied in S. Kouachi [5]. All the conditions imposed
in the above papers are very restrictive and the techniques used are complicated and
are not (in general) applicable to tridiagonal matrices considered in this paper even
tough for small n. For example, our techniques are applicable for all the 7×7 matrices



5−4 2 9
0
0
0
0
0


6
5
8
0
0
0
0




0
4
5
−3
0
0
0




0
0
−18
5
5
+
i
7
0
0
A7 = 





0
0
0
5−i 7
5
−27i
0



0
0
0
0
2i
5
−1√ 
0
0
0
0
0
−32 5 − 3 6

and







A′7 = 






5−4 2
−i
0
0
0
0
0

54i
0
5 −16
−2
5
0 −9i
0
0
0
0
0
0

0
0
6i
5√
2i 2
0
0

0
0
0
0
0
0
0√
0
0
−8i 2
0
0
5
−18i
0
3i
5
2 + 2i

0
8 − 8i 5 − 3 6







,





and guarantee that they possess the same eigenvalues and in addition they give their
exact expressions (formulas (15) lower) since condition (2) is satisfied:



2 √
2




3 6 + 4 2 + 2 3 6 4 2 cos
,
λ1 , λ4 = 5 ±
7



2 √
2




3 6 + 4 2 + 2 3 6 4 2 cos
λ2 , λ5 = 5 ±
,
7



2 √
2




3 6 + 4 2 + 2 3 6 4 2 cos
,
λ3 , λ6 = 5 ±
7



λ7 = 5 − 3 6 + 4 2 ,

whereas the recent techniques are restricted to the limited case when the entries on
the subdiagonal are equal and those on the superdiagonal are also equal and the direct
calculus give the following characteristic polynomial









P (λ) = λ7 + 4 2 + 3 6 − 35 λ6 + 24 3 − 120 2 − 90 6 + 267 λ5 +












684 2 − 600 3 + 447 6 + 2075 λ4 + 6320 2 + 1872 3 + 6060 6 − 23 893 λ3 +






31 920 3 − 47 124 2 − 33 891 6 − 24 105 λ2

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118

S. Kouachi






+ 369 185 − 98 568 3 − 114 090 6 − 44 760 2 λ






+ 365 828 2 − 239 160 3 + 142 833 6 + 80 825

for which the roots are very difficult to calculate (degree of P ≥ 5).
If σ is a mapping (not necessary a permutation) from the set of the integers from
1 to (n − 1) into the set of the integers different of zero N∗ , we denote by An (σ) the
n × n matrix


−α + b cσ1
0
0
...
0
 aσ 1

b
cσ 2 0
...
0




.
.
.
.
.
.


.
.
0
aσ 2
b
.


An (σ) = 
(1.1)

.
.
.
..
..
..


0
0
0




..
..
..
..
..

.
.
.
.
.
cσ n−1 
0
...
...
0 aσn−1 −β + b

and by ∆n (σ) = |∆n (σ) − λIn | its characteristic polynomial. If σ = i, where i is the
identity, then An (i) and its characteristic polynomial ∆n (i) will be denoted by An
and ∆n respectively. Our aim is to establish the eigenvalues and the corresponding
eigenvectors of the matrices An (σ).
2. The Eigenvalue Problem. Throughout this section we suppose d1 d2 = 0.In
the case when α = β = 0, the matrix An (σ) and its characteristic polynomial will
be denoted respectively by A0n (σ) and ∆0n (σ) and in the general case they will be
denoted by An and ∆n . We put
Y 2 = d21 + d22 + 2d1 d2 cos θ,

(3)

where
Y = b − λ.

(3.1)

In S. Kouachi [6], we have proved the following result
Theorem 2.1. When d1 d2 = 0, the eigenvalues of the class of matrices An (σ) on
the form (1.1) are independent of the entries (ai , ci , i = 1, .., n−1) and of the mapping
σ provided that condition (2) is satisfied and their characteristic determinants are
given by
∆n = (d1 d2 )

2
2
m−1 d1 d2 (Y −α−β) sin(m+1)θ+(αβY −αd1 −βd2 ) sin mθ
,
sin θ

(4.a)

when n = 2m + 1 is odd and
m−1

∆n = (d1 d2 )

when n = 2m is even.

d1 d2 sin(m+1)θ+[αβ+d22 −(α+β)Y ] sin mθ+αβ
sin θ

d1
d2

sin(m−1)θ

,

(4.b)

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Eigenvalues and Eigenvectors of Tridiagonal Matrices

119

Proof. When α = β = 0, formulas (4.a) and (4.b) become, respectively
m

∆0n = (d1 d2 ) Y

sin (m + 1) θ
,
sin θ

(4.a.0)

when n = 2m + 1 is odd and
m

sin(m + 1)θ +

∆0n = (d1 d2 )

d2
sin mθ
d1

sin θ

,

(4.b.0)

when n = 2m is even. Since the right hand sides of formulas (4.a.0) and (4.b.0) are
independent of σ, then to prove that the characteristic polynomial of A0n (σ), which
we denote by ∆0n , is also, it suffices to prove them for σ = i. Expanding ∆0n in terms
of it’s last column and using (2) and (3), we get
∆0n = Y ∆0n−1 − d22 ∆0n−2 , n = 3, ...,

(4.a.1)

when n = 2m + 1 is odd and
∆0n = Y ∆0n−1 − d21 ∆0n−2 , n = 3, ...,

(4.b.1)

when n = 2m is even. Then by writing the expressions of ∆0n for n = 2m + 1, 2m
and 2m − 1 respectively, multiplying ∆02m and ∆02m−1 by Y and d21 respectively and
adding the three resulting equations term to term, we get


∆02m+1 = Y 2 − d21 − d22 ∆02m−1 − d21 d22 ∆02m−3 ,
(4.a.2)
We will prove by induction in m that formula (4.a.0) is true.
If n = 2m + 1 is odd, for m = 0 and m = 1 formula (4.a.0) is satisfied. Suppose that
it is satisfied for all integers < m, then from (4.a.2) and using (3), we get
m

∆02m+1 = Y (d1 d2 )

2 sin mθ cos θ − sin (m − 1) θ
.
sin θ

Using the well known trigonometric formula
2 sin η cos ζ = sin (η + ζ) + sin (η − ζ) ,

(*)

for η = mθ and ζ = θ, we deduce formula (4.a.0).
When n = 2m is even, applying formula (4.a.1) for n = 2m + 1, we get
∆02m =

∆02m+1 + d22 ∆02m−1
.
Y

By direct application of (4.a.0) two times, for n = 2m + 1 and n = 2m − 1, to the
right hand side of the last expression, we deduce (4.b.0).
If we suppose that α = 0 or β = 0, then expanding ∆n in terms of the first
and last columns and using the linear property of the determinants with regard to its
columns, we get

Electronic Journal of Linear Algebra ISSN 1081-3810
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120

S. Kouachi












0
2
1
∆n = ∆n − α En−1  − β En−1  + αβ 






1
2
where En−1
and En−1

...
..
.

0
..
.

..

..

0

..

..

c2

a2
0
..
.

.

.

..

.
.
.
cn−2
0 ... 0 an−2
Y
are the (n − 1) square matrices of the form (1)



i
En−1

Y
..
.

0
..
.

Y





=




Y
..
.

0
..
.

...
..
.

0
..
.

..

.

..

.

0

..

..

.

..

.

cn+i−3
Y

Y

ci

ai
0
..
.

.
...

...

0

an+i−3








,












 , i = 1, 2.




Since all the entries ai ’s on the subdiagonal and ci ’s on the superdiagonal satisfy
condition (2), then using formulas (4.a.0) and (4.b.0) and taking in the account the
order of the entries ai ’s and ci ’s, we deduce the general formulas (4.a) and (4.b).
Before proceeding further, let us deduce from formula (4.b) a proposition for the
matrix Bn (σ) which is obtained from An (σ) by interchanging the numbers α and β.
Proposition 2.2. When n is even, the eigenvalues of Bn (σ) are the same as
An (σ).


Let us see what formula (4) says and what it does not say. It says that if ai , ci , i =
1, .., n − 1 are other constants satisfying condition (2) and


−α + b


a1



0


An = 


0

..


.
0





c1
b


a2
0
..
.
...

0

c2
b
..
..

.

.
...

0
0
..
.

...
...
..
.

..

.

..

.

..

..
0



0
0
..
.

.
.

an−1

0


cn−1
−β + b














then the matrices An , An and An (σ) possess the same characteristic polynomial and
hence the same eigenvalues. Therefore we have this immediate consequence of formula
(4)
Corollary 2.3. The class of matrices An (σ), where σ is a mapping from the
set of the integers from 1 to (n − 1) into N∗ are similar provided that all the entries
on the subdiagonal and on the superdiagonal satisfy condition (2).
The components of the eigenvector u(k) (σ) , k = 1, ..., n associated to the eigen(k)
value λk , k = 1, ..., n , which we denote by uj , j = 1, .., n , are solutions of the

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121

Eigenvalues and Eigenvectors of Tridiagonal Matrices

linear system of equations






(k)

(k)

(−α + ξ k )u1 + cσ 1 u2 = 0,
(k)
(k)
(k)
aσ 1 u1 + ξ k u2 + cσ2 u3 = 0,

...



(k)
(k)
aσ n−1 un−1 + (−β + ξ k )un = 0,

(5)

where ξ k = Y is given by formula (3) and θk , k = 1, ..., n are solutions of


d1 d2 (ξ k − α − β) sin (m + 1) θ k + αβξ k − αd21 − βd22 sin mθk = 0,

(6.a)

when n = 2m + 1 is odd and



d1
d1 d2 sin(m + 1)θk + αβ + d22 − (α + β) ξ k sin mθk + αβ sin(m − 1)θk = 0, (6.b)
d2

when n = 2m is even.
Since these n equations are linearly dependent, then by eliminating the first equation we obtain the following system of (n−1) equations and (n−1) unknowns, written
in a matrix form as

  (k)  
(k) 
ξ k cσ 2 0
...
0
u2
−aσ1 u1

..
  (k)  
..

0
 aσ 2 ξ k . . .
  u3  
.
.


 .  

..

 .  
..
..
..
.
=
(7)
 0



.
.
.
.
.
0




 

.
.
 .



..
..
..
..

 ..
  ..  
.
.
.
cσn−1
(k)
0
un
0
...
0 aσn−1 (−β + ξ k )
The determinant of this system is given by formulas (4) for α = 0 and n replaced by
n − 1 and equal to
(k)
∆n−1

m−1

= (d1 d2 )



d1 d2 sin(m + 1)θ k + d21 − βξ k sin mθk
,
sin θ k

(8.a)

when n = 2m + 1 is odd and

(k)

∆n−1 = (d1 d2 )m−1

(ξ k − β) sin mθ k − β

d1
sin(m − 1)θ k
d2

sin θ k

,

(8.b)

when n = 2m is even, for all k = 1, ..., n.
(k)

(k)

uj (σ) =

Γj (σ)
(k)

∆n−1

, j, k = 1, ..., n,

(9)

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122

S. Kouachi

where












(k)
Γj (σ) = 











ξk

cσ 2

aσ 2
0

ξk
..
.

0
..
.
..
.
..
.

0
..
.
..
.
..
.

0

...

0
..
.
..

.

aσj−2
..
.
..

.

...
...

(k)

−aσ1 u1

0

...

0
..
.

...

cσj−2

0
..
.

ξk

0

0

aσj−1
..
.

0

cσ j

0
..
.

ξk

...
..
.
..
.
..
.

...
..
.

..

.
...

...

.
aσ j +1 . .
0

0













,





0



cσn−1

(−β + ξ k ) 
0
..
.
..
.
..
.
..
.

aσn−1

j = 2, ..., n, k = 1, ..., n. By permuting the j − 2 first columns with the (j − 1)-th
one and using the properties of the determinants, we get
(k)

(k)

j−2

uj (σ) = (−1)

Λj (σ)
, j = 2, ..., n,
∆n−1

(10)

(k)

where Λj (σ) is the determinant of the matrix


(k)
Tj−1 (σ)
0
(k)
,
Cj (σ) =
(k)
0
Sn−j (σ)
where







(k)
Tj−1 (σ) = 






(k)

−aσ1 u1
0
..
.
..
.
..
.
0

ξk

0

cσ 2
..
.
..
.
..
.

0
···

0
···

aσ 2
..
.

0
..
.

···
..
.
.. ..
.
.
.. ..
.
.
.. ..
.
.
··· 0

0
..
.
0
cσ j−2
ξk
aσ j−1













(k)

is the supertriangular matrix of order j − 1 with diagonal (−aσ1 u1 , aσ2 , ..., aσj−1 )
and


cσj+1 0
···
0
ξk
..


..
..
..

 aσj +1
.
.
.
.




(k)
.
.
.
..
..
..
Sn−j (σ) =  0
,
0




..
..
..
..


.
.
.
.
cσn−1
0
···
0 aσn−1 (−β + ξ k )

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123

Eigenvalues and Eigenvectors of Tridiagonal Matrices

is a tridiagonal matrix of order n − j belonging to the class of the form (1.1) and
satisfying condition (2). Thus

 


 (k)
  (k)
  (k)

(11)
Cj (σ) = Tj−1 (σ) Sn−j (σ)
(k)

(k)

= −aσ1 ...aσ j−1 u1 ∆n−j , j = 2, ..., n and k = 1, ..., n,

(k)

where ∆n−j (σ) is given by formulas (4) for α = 0 and n − 1 replaced by n − j
(k)

∆n−j =


n−j

−1

 (d1 d2 ) 2




(d1 d2 )

n−j
2 θ k , when

2
d1 d2 sin( n−j
2 +1)θ k +(d1 −βξ k ) sin
sin θk

n−j−1 (ξ −β) sin( n−j+1 )θ −β d2 sin( n−j−1 )θ
k
k
k
2
d1
2
2
,
sin θk

when n is odd and




n−j−1

 (d d ) 2
1 2
(k)
∆n−j =




 (d d ) n−j
2 −1
1 2

(ξ k −β) sin( n−j−1
)θ k −β
2
sin θk

d1
d2

j is odd,

when j is even,
(12.a)

)θ k
sin( n−j−1
2

, when j is odd,

2
d1 d2 sin( n−j
2 +1)θ k +(d2 −βξ k ) sin
sin θk

n−j
2 θk

, when j is even,
(12.b)
when n is even, for all j = 2, ..., n and k = 1, ..., n. Using formulas (9)-(12), we get
(k)
uj

j−1

(σ) = (−1)

(k)
(k) ∆n−j
,
aσ1 ...aσj−1 u1
(k)
∆n−1

j = 2, ..., n and k = 1, ..., n.

(13)

Finally

(k)
uj

(σ) =

(k)
µj (σ) u1

when n is odd and

(k)

(k)

uj (σ) = µj (σ) u1







2
d1 d2 sin( n−j
2 +1)θ k +(d1 −βξ k ) sin

n−j
2 θk

n−1
2
d1 d2 sin( n+1
2 )θ k +(d1 −βξ k ) sin( 2 )θ k

, when j is odd,


d


(ξ −β) sin( n−j+1
)θk −β d2 sin( n−j−1
)θk

2
2
1
 d1 d2 k
, when j is even,
n+1
2
d1 d2 sin( 2 )θ k +(d1 −βξ k ) sin( n−1
2 )θ k
(13.a)






















)θk −β
(ξ k −β) sin( n−j−1
2
(ξ k −β) sin

n
2 θ k −β

d1
d2

d1
d2

)θk
sin( n−j−1
2

, when j is odd,

sin( n
2 −1)θ k

n−j
2
d1 d2 sin( n−j
2 +1)θ k +(d2 −βξ k ) sin 2 θ k
√ 1
,
d1 d2
d1
n
(ξ k −β) sin n
θ
−β
−1)θ
sin(
k
2 k
2
d2

when j is even,
(13.b)

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for all j = 2, ..., n and k = 1, ..., n, when n is even, where

1−j

aσ 1 ...aσ j−1 , j = 2, ..., n,
µj (σ) = − d1 d2

(†)

ξ k = Y and θ k are given respectively by (3) and formulas (6).
3. Special Cases. From now on, we put



n−1
ρj (σ) = − d1 d2
µj (σ) , j = 1, ..., n,

(‡)

where µj (σ) is given by (†).

3.1. Case when n is odd. If α = β = 0, we have
Theorem 3.1. If α = β = 0,the eigenvalues λk (σ) , k = 1, ..., n of the class of
matrices An (σ) on the form (1.1)are independent of the entries (ai , ci , i = 1, .., n−1)
and of σ provided that condition (2) is satisfied and they are given by


b + d21 + d22 + 2d1 d2 cos θk , k = 1, ..., m,






λk =
(14)
b − d21 + d22 + 2d1 d2 cos θk , k = m + 1, ..., 2m,





b, k = n.


t

(k)
(k)
The corresponding eigenvectors u(k) (σ) = u1 (σ) , ..., un (σ) , k = 1, .., n − 1 are
given by

n−j
n−j
 d1 d2 sin( 2 + 1)θk + d21 sin 2 θk , when is j odd,
(k)
uj (σ) = ρj (σ)
(14.a)



,
when
is
j
even,
d1 d2 (b − λk ) sin( n−j+1
k
2

and

(k)

uj (σ) =


 n−j


 aσ 1 ...aσ j−1 −d22 2 , when j is odd,



(14.b)

0, when j is even,

j = 1, ...n, where ρj (σ) is given by (‡) and

θk =





2kπ
n+1 ,

k = 1, ..., m,
.

2(k−m)π
n+1 ,

k = m + 1, ..., 2m.

Proof, We take aσ0 = a0 = 1. The eigenvalues λk , k = 1, ..., 2m are trivial
consequence of (4) by putting (m + 1)θ = kπ, k = 1, ..., m and using (3). The

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Eigenvalues and Eigenvectors of Tridiagonal Matrices

125

eigenvalue λn is a consequence of (4) and (3.1) by putting Y = 0. Formula (14.a) is
a trivial consequence of (13.a) by taking β = 0 and choosing



n−1 

n−1
n+1
(k)
2
u1 = − d1 d2
)θk + d1 sin
d1 d2 sin(
θ k , k = 1, ..., n − 1.
2
2
Concerning the n−th eigenvector, we solve directly system (7) and choose
(n)

u1

 n−1

= −d22 2 .

If α = d2 and β = d1 or β = −d1 and α = −d2 , then using the trigonometric
θk
formula (*) for η = ( 2m+1
2 )θ k and ζ = 2 , formula (6.a) becomes
(ξ k ± (d1 + d2 )) sin

(2m + 1)
θk
θk cos
= 0,
2
2

(6.a.1)

then we get
Theorem 3.2. If α = d2 and β = d1 or β = −d1 and α = −d2 ,the eigenvalues
λk (σ) , k = 1, ..., n of the class of matrices An (σ) on the form (1.1)are independent
of the entries (ai , ci , i = 1, .., n − 1) and of σ provided that condition (2) is satisfied
and they are given by


b + d21 + d22 + 2d1 d2 cos θk , k = 1, ..., m,






(15)
λk =
b − d21 + d22 + 2d1 d2 cos θk , k = m + 1, ..., 2m,





b − (α + β), k = n.


t
(k)
(k)
The corresponding eigenvectors u(k) (σ) = u1 (σ) , ..., un (σ) , k = 1, .., n are
given by

n−j
d2 sin( n−j


2 + 1)θ k + [d1 − b + λk ] sin 2 θ k , j is odd,
(k)
uj (σ) = ρj (σ)


− d2 (d1 − b + λk ) sin( n−j+1 )θk + d2 sin( n−j−1 )θk  j, is even,
d1
2
2
(15.a)
k = 1, ..n − 1 and

1, when j is odd,


(n)
uj (σ) = ρj (σ)


d2

d1 , when j is even,
j = 1, .., n, when α = d2 and β = d1 and

n−j
d2 sin( n−j


2 + 1)θ k + [d1 + b − λk ] sin 2 θ k , j is odd,
(k)
uj (σ) = ρj (σ)  

 d2 (d1 + b − λk ) sin( n−j+1 )θ k + d2 sin( n−j−1 )θ k  j, is even,
d1

2

2

(15.b)

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126

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k = 1, ..n − 1 and
(n)
uj

(σ) = ρj (σ)





1, when j is odd,


 −



d2
d1 ,

when j is even,

j = 1, .., n, when β = −d1 and α = −d2 , j = 1, .., n, where ρj (σ) is given by (‡)
and

2kπ

n , k = 1, ..., m,
.
θk =
 2(k−m)π
, k = m + 1, ..., 2m.
n

Proof. Formula (15) is a simple consequence of (6.a.1). Using (13.a), the expressions (15.a) and (15.b) are trivial by choosing



n−1 

n−1
n+1
(k)
)θk + [d1 − b + λk ] sin
u1 = − d1 d2
d2 sin(
θk ,
2
2
if α = d2 and β = d1 and



n−1 

n+1
n−1
(k)
)θk + [d1 + b − λk ] sin
d2 sin(
u1 = − d1 d2
θk ,
2
2
when β = −d1 and α = −d2 .The last eigenvector is obtained by choosing

n−1

(n)
u1 (σ) = − d1 d2
aσ1 ...aσj−1 .

When α = d2 and β = −d1 or α = −d2 and β = d1 , then using the trigonometric

formula
2 cos η sin ζ = sin(η + ζ) − sin(η − ζ),
for η = ( 2m+1
2 )θ k and ζ =

θk
2 ,

(**)

formula (4.a) becomes

(ξ k ± (d2 − d1 )) cos

θk
(2m + 1)
θ k sin
= 0,
2
2

(6.a.2)

then we get
Theorem 3.3. If α = −d2 and β = d1 or β = −d1 and α = d2 ,the eigenvalues
λk (σ) , k = 1, ..., n of the class of matrices An (σ) on the form (1.1)are independent
of the entries (ai , ci , i = 1, .., n − 1) and of σ provided that condition (2) is satisfied
and they are given by


b + d21 + d22 + 2d1 d2 cos θk , k = 1, ..., m,






λk =
(16)
b − d21 + d22 + 2d1 d2 cos θk , k = m + 1, ..., 2m,





b − (α + β), k = n.

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Eigenvalues and Eigenvectors of Tridiagonal Matrices

The corresponding eigenvectors u(k) (σ) =
given by (15.a) and
(n)
uj




127



t
(k)
(k)
u1 (σ) , ..., un (σ) , k = 1, .., n are

j−1

2
 (−1) j+2, when j is odd,
(σ) = ρj (σ)
d2
2

, when j is even,
d1 (−1)

when α = −d2 and β = d1 and (15.b) and

j−1

(−1) 2 , when j is odd,
(n)

j
uj (σ) = ρj (σ)
d2
2

d (−1) , when j is even,

j = 1, .., n,

j = 1, .., n,

1

when β = −d1 and α = d2 ,where ρj (σ) is given by (‡) and
θk =



(2k−1)π
, k = 1, ..., m,
n
(2(k−m)−1)π
,
k = m + 1, ..., 2m.
n

.

Proof. Formula (16) is trivial by solving (6.a.2). Concerning the eigenvectors,
following the same reasoning as in the case when α = d2 and β = d1 or β = −d1 and
α = −d2 and since we use formula (13.a) to find the components of the eigenvectors
which depend only of β, we deduce the same results. The last eigenvector is obtained
by passage to the limit in formula (13.a) when θk tends to π and choosing the first
component as in the previous case.
3.2. Case when n is even. If αβ = d22 , then using (*) for η = mθk and ζ = θk ,
formula (6.b) becomes

Using (3), we get

which gives




2d1 d2 cos θ k + αβ + d22 − (α + β) ξ k sin mθk = 0.
 2

ξ k − (α + β) ξ k + d22 − d21 sin mθk = 0,

(6.b.1)

sin mθk = 0
and
ξ 2k − (α + β) ξ k + d22 − d21 = 0,

(3.2)

then we get
Theorem 3.4. If αb = d22 ,the eigenvalues λk (σ) , k = 1, ..., n of the class of
matrices An (σ) on the form (1.1)are independent of the entries (ai , ci , i = 1, .., n−1)

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128

S. Kouachi

and of σ provided that condition (2) is satisfied and they are given by



b + d21 + d22 + 2d1 d2 cos θk , k = 1, ..., m − 1,









d21 + d22 + 2d1 d2 cos θk , k = m, ..., 2m − 2,
b








2
λk =
(17)
(α + β) + (α − β) + 4d21


b+
, k = n − 1,


2









(α + β) − (α − β)2 + 4d21



, k = n.
b+
2


t
(k)
(k)
The corresponding eigenvectors u(k) (σ) = u1 (σ) , ..., un (σ) , k = 1, .., n − 2 are
given by

d1


(b − λk − β) sin( n−j−1
)θ k − β sin( n−j−1
)θk , j is odd,

2
2
d
(k)
2
uj (σ) = ρj (σ)


 √ 1 d d sin( n−j +1)θ +
d2 − β (b − λ ) sin n−j θ  , jeven
d1 d2

1 2

k

2

2

k

2

k

(17.a)

where ρj (σ) , j = 1, ..., n is given by (‡) and

θk =





2kπ
n ,

k = 1, ..., m − 1,

2(k−m+1)π
,
n

.

k = m, ..., 2m − 2.

The eigenvectors u(n−1) (σ) and u(n) (σ) associated respectively with the eigenvalues
λn−1 and λn are given by formula (13.b), where θk is given by (3), (3.1) and (3.2).
Proof. Formula (17) is a consequence of (6.b.1). The eigenvectors are a consequence of formula (13.b) by choosing


n−1

(k)
u1 = − d1 d2


d1


(b − λk − β) sin n2 θk − β sin( n2 − 1)θ k , when j is odd,


d
2



d

(b − λk − β) sin n θ k − β 1 sin( n − 1)θ k , when j is even.
2
2
d2

When α = −β = ±d2 , then, using (**), formula (6.b) gives
2d1 d2 cos mθ = 0,

(6.b.2)

then we have
Theorem 3.5. If α = −β = ±d2 ,the eigenvalues λk (σ) , k = 1, ..., n of the
class of matrices An (σ) on the form (1.1)are independent of the entries (ai , ci , i =

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Eigenvalues and Eigenvectors of Tridiagonal Matrices

1, .., n − 1) and of σ provided that condition (2) is satisfied and they are given by
λk =





b+
b−


d21 + d22 + 2d1 d2 cos θk , k = 1, ..., m,

(18)


d21 + d22 + 2d1 d2 cos θ k , k = m + 1, ..., n,


t

(k)
(k)
The corresponding eigenvectors u(k) (σ) = u1 (σ) , ..., un (σ) , k = 1, .., n are
given by

)θk − d1 sin( n−j−1
)θ k , j is odd,
(b − λk − d2 ) sin( n−j−1

2
2
(k)
uj (σ) = ρj (σ)
 2


n−j
d1 d2 sin( n−j
2 + 1)θ k + d2 − d2 (b − λk ) sin 2 θ k , j is even,
(18.a)
when α = −β = −d2 and

)θk + d1 sin( n−j−1
)θ k , j is odd,
(b − λk + d2 ) sin( n−j−1

2
2
(k)
uj (σ) = ρj (σ)
 2


n−j
d1 d2 sin( n−j
2 + 1)θ k + d2 + d2 (b − λk ) sin 2 θ k , j is even,
(18.b)
when α = −β = d2 where ρj (σ) , j = 1, ..., n is given by (‡) and
θk =





(2k−1)π
,
n
(2k−2m−1)π
,
n

k = 1, ..., m,
k = m + 1, ..., n.

Proof. Formula (18) is a consequence of (6.b.2).The eigenvectors are a consequence of formula (13.b) by choosing

n
n

n−1 (b − λk − d2 ) sin 2 θ k − d1 sin( 2 − 1)θ k , when j = 2l + 1

(k)
u1 = − d1 d2


√
d1 d2 (b − λk − d2 ) sin n2 θ k − d1 sin( n2 − 1)θ k , when j = 2l

when α = −β = −d2
(k)

u1



n−1 (b − λk + d2 ) sin n2 θ k + d1 sin( n2 − 1)θ k , when j = 2l + 1

= − d1 d2


√
d1 d2 (b − λk + d2 ) sin n2 θ k + d1 sin( n2 − 1)θ k , when j = 2l

when α = −β = d2 .

4. Case when d1 d2 = 0. In this case, we have proved in S. Kouachi [6], the
following.
Proposition 4.1. When d1 d2 = 0,the eigenvalues λk (σ) , k = 1, ..., n of the
class of matrices An (σ) on the form (1.1) are independent of the entries (ai , ci , i =

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130
1, .., n − 1) and
polynomials are



∆n =



S. Kouachi

of σ provided that condition (2) is satisfied and their characteristic
given by
2


 n−1 −1
ξ − d22 2
(ξ − α) ξ 2 − βξ − d22 , when n is odd;

(19.a)

2
 n −1
2

ξ − d22 2
ξ − (α + β) ξ + αβ , when n is even,

when d1 = 0 and


 n−1 −1

2


(ξ − β) ξ 2 − αξ − d21 , when n is odd;
ξ − d21 2
∆n =



 n −2
2

2
ξ − αξ − d21 ξ 2 − βξ − d21 , when n is even,
ξ − d21 2

(19.b)

when d2 = 0, where ξ = Y is given by (3)
An immediate consequence of this proposition is
Proposition 4.2. If d1 d2 = 0,the eigenvalues λk (σ) , k = 1, ..., n of the class of
matrices An (σ) on the form (1.1)are independent of the entries (ai , ci , i = 1, .., n−1)
and of σ provided that condition (2) is satisfied:
1) When α = β = 0, they are reduced to three eigenvalues
{ b ± d2 , b}
when d1 = 0 or when n is odd and d2 = 0
{ b ± d1 , b}
and only two eigenvalues
{ b ± d1 }
when n is even and d2 = 0.
2) When α = 0 or β = 0, they are reduced to five eigenvalues



1
1
2
2
β + 4d2
: b ± d2 , b − α, b − β ±
2
2
when n is odd and d1 = 0, five also



1
1
2
2
b ± d1 , b − β, b − α ±
α + 4d1
2
2
when n is odd and d2 = 0, four
{b ± d2 , b − α, b − β}
when n is even and d1 = 0 and six eigenvalues




1
1
1
1
b ± d1 , b − α ±
α2 + 4d21 , b − β ±
β 2 + 4d21
2
2
2
2

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Eigenvalues and Eigenvectors of Tridiagonal Matrices

131

when n is even and d2 = 0.



t
(k)
(k)
3) All the corresponding eigenvectors u(k) (σ) = u1 (σ) , ..., un (σ) , k = 1, .., n
are are simple and given by
3.1)When λk is simple
 

 n−j
2
2

2

 
, when j is odd,
(b

λ
)

d

k

2





, n is odd,




 n−j−1




2

2
2


(b − λk ) , when j is even,
(b − λk ) − d2


(k)
,
uj (σ) = ν j (σ)



 1+n−j


2

2



(b − λk ) − d22
, when j is odd,







, n is even,


 
 n−j



2
2
 

2
(b − λk ) − d2
(b − λk ) , when j is even,
(20.a)
when d1 = 0 and
 
 n−j

2

2

2


(b

λ
, when j is odd,
)
(b

λ
)

d

k
k

1





, n is odd,




 n−j−1


+1

2


2
2


(b − λk ) − d1
, when j is even,


(k)
uj (σ) = ν j (σ)


 n−1−j



2

2

2


(b

λ
, when j is odd,
)
(b

λ
)

d

k
k

1





, n is even,


 n−j

 


2
2
 

2
(b − λk ) − d1
, when j is even,
(20.b)
when d2 = 0, j = 2, ..., n and k = 1, ..., n,where
n−j

ν j (σ) = (−1)

aσ1 ...aσj−1 , j = 2, ..., n.

3.2) When λk is multiple, then all the components are zero except the last four ones
at most and which we calculate directly.
Proof. The expressions of the eigenvalues are trivial by annulling the corresponding characteristic determinants. Following the same reasoning as the case d1 d2 = 0,
by solving system (7), we get the expressions of the eigenvectors by formulas (13)
!!
(k)
∆n−j
(k)
(k)
n−1
, j = 2, ..., n and k = 1, ..., n,
ν j (σ) u1
uj (σ) = (−1)
(k)
∆n−1
where [[ .]] denote the reduced fraction.



m−2
2
2

ξ k − d22 ξ 2k − βξ k − d22 , when n = 2m + 1 is odd,
 ξ k − d22
(k)
,
∆n−1 =
2


2


2
2 m−2
ξ k − d2
(ξ k − β) ξ k − d2 , when n = 2m is even,

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132

S. Kouachi

when d1 = 0 and

m−1
2


ξ 2k − d21
ξ k − βξ k , when n = 2m + 1 is odd,

(k)
∆n−1 =

m−2
2


2
ξ k − d21
ξ k ξ k − βξ k − d21 , when n = 2m is even,

when d2 = 0.
 


 n−j −2
2



ξ k − d22 ξ 2k − βξ k − d22 , when j is odd,
ξ 2k − d22 2





n is odd,

 
n−j−1




2

−1

2
2

ξ k − d22
ξ k ξ k − βξ k − d22 , when j is even

(k)
∆n−j =




 n−j−1

−1
2
2
 
2

ξ
(ξ k − β) ξ 2k − d22 , when j is odd,

d


k
2



n is even,



2

2
 n−j

 
2 −1
2
ξ k − d2
ξ k − βξ k , when j is even,

when d1 = 0 and

(k)

∆n−j =




























2
 n−j −1
2
ξ k − βξ k , when j is odd,
ξ k − d21 2








n is odd;


 n−j−1



2
−1
2
(ξ k − β) ξ 2k − d21 , when j is even
ξ k − d21






2
 n−j−1
−1
2
ξ k − d21
ξ k ξ 2k − βξ k − d21 , when j is odd,

ξ 2k



d21

n is even,


2
 n−j
2
2 −2
2
2
ξ k − d1 ξ k − βξ k − d1 , when j is even

when d2 = 0. Then, when d1 = 0, we have
 
 1−j

 
ξ 2k − d22 2 , when j is odd,





n is odd,




 −j


2
2 2

ξ k − d2
ξ k , when j is even

(k)
n−1
uj (σ) = (−1)
ν j (σ)
,


 1−j

2

2
2
 ξ k − d2

, when j is odd,
 



n is even.



 −j

2
 
2 2
ξ k − d2
ξ k , when j is even,
(k)

j = 2, ..., n and k = 1, ..., n. By putting j = n, calculating u1
and choosing
un(k) (σ) = aσ 1 ...aσ n−1 ,

(k)

according to un (σ)

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Eigenvalues and Eigenvectors of Tridiagonal Matrices

133

we get (20.a).
Following the same reasoning as in the case when d1 = 0, we deduce (20.b).
Acknowledgment. The author thanks the superior education ministry and the
national agency of development and scientific research (ANDRU) for their financial
support.
REFERENCES
[1] Wen-Chyuan Yueh. Eigenvalues of several tridiagonal matrices. Applied Mathematics E-Notes,
5:66–74, 2005.
[2] J. F. Elliott. The characteristic roots of certain real symmetric matrices. Master’s thesis, Univ.
of Tennessee, 1953.
[3] R. T. Gregory and D. Carney. A Collection of Matrices for Testing Computational Algorithm.
Wiley-Interscience, New York, 1969.
[4] U. Grenander and G. Szego. Toeplitz Forms and Their Applications. University of California.
Press, Berkeley and Los Angeles, 1958.
[5] S. Kouachi. Eigenvalues and eigenvectors of several tridiagonal matrices. Submitted to the Bulletin of the Belgian Mathematical Society.
[6] S. Kouachi. Eigenvalues and eigenvectors of tridiagonal matrices with non equal diagonal entries.
In preparation.
[7] S. Kouachi. Explicit Eigenvalues of tridiagonal matrices. To appear in Applied Mathematics
E-Notes.

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