LINEAR-
ALGEBRA
AND
ITS
23
APPLICATIONS
Reduction of a Matrix Using Properties of the Schur Complement* EMILIE
V. HAYNSWORTH
of Afathematics,
Department Auburn.
Auburn
University
Alabama
Communicated
by Alan
J. Hoffman
1. INTRODUCTION
Suppose A.
B is a nonsingular
The Schur complement
follows:
submatrix
of B in A, denoted
Let a be the matrix
tion of rows and columns leaving
principal
obtained
of an n x n matrix
by (A/B), is defined
from A by a simultaneous
which puts B into the upper left corner
the rows and columns
of B and G in increasing
as
permutaof A,
order.
Then (A/B) = G Schur proved that the determinant of any nonsingular
principal
DB-lC.
(1)
of A is the product of the determinants
submatrix
B with its Schur
complement,
IAl = IBII(W In
[l]
the following
“quotient
(2)
property”
was proved:
(A/B) = ((AIC)I(BIC)). * This work was done under contract DA-91-591-EUC-3686 of the U.S. Army with the Institute of Mathematics, University of Basel. The author wishes to thank Prof.
A. M. Ostrowski
for very helpful Linear
Copyright
0
discussions.
Algebra
1970 by American
and Its Applications Elsevier
Publishing
3(1970), Company,
23-29 Inc.
E. V.
24 In another
paper
[3] it was shown that
matrix can be determined together
the inertia
from that of any nonsingular
with that of its Schur complement.
and B is a nonsingular
principal
of a Hermitian
principal submatrix
That
submatrix
HAYNSWORTH
is, if A is Hermitian
of A, then
In A = In B + In(A/B).
(3)
In this paper we make use of the properties to compute
the eigenvalues
n, from those 2. APPLICATIONS
of related OF
THE
It is well known a matrix
of an arbitrary
matrices SCHUR
[2] that,
of the Schur complement
complex
matrix
of order m and n -
COMPLEMENT
TO
EIGENVALUE
if there is a commutator
A of order n to a matrix
A, of order
m, respectively. PROBLEMS
Y of rank m from
B of order llz,
AY=YB, then m, of the roots of A are the roots of B. we can obtain
a matrix
A by first constructing replaced
by those
the matrix Since
whose roots a matrix
In Theorem
are the remaining
A(Y)
in which
of Y, and then computing
Y, in A(Y).
(A(Y)
is defined
Y has rank m, we assume,
Y= where Y, is a nonsingular
m
x
the Schur
loss of generality,
For, if it is necessary
matrix
(PAP-l)(PY)
Linear
to permute
in the first m rows, we may since the equation
= (PY)B
(Fi), we partition
Y,
where A,,
that
to (4).
Now under the assumption with
of
(4
permute the rows and columns of A in the same manner,
is equivalent
complement
9
m matrix.
of
of A are
below.)
(~,Yl1
the rows of Y to obtain a nonsingular
m roots
m columns
precisely
without
1 we show that 12 -
is an m x 112 matrix.
Algebra
and Its
Applications
3(1970),
23-29
the matrix
A conformally
PROPERTIES
OF THE
We define
THEOREM
A(Y)
1.
m, respectively.
SCHUR
25
COMPLEMENT
to be the n x wz matrix
Suppose
A and B are square matrices of orders rz and
If there exists an n x m matrix
Y, of rank m, satisfying
(4) and (5), then m roots of A aye roots of B and the remaining n aye those of (A(Y)/Y,),
the Schw
complement
m roots
of Y, in the ma&ix
A(Y)
defined in (6). Proof.
From
(4) we have
A,,Y, + A,sY, = Y,B> (7)
A,,Y, + A,$‘, = Y,B. Now we let
Yl 0 y, I?&., i
1
s= Since
Y,
is nonsingular,
S is nonsingular. AS =(;:;
Then,
from
(7),
;;:).
If we let
then Y,B
sa= so that
S-lA.S
Y,B
Y,C
’
= a if and only if Y,C = A,,
which implies
Y,C D+
and
D + Y,C = A,,
that D = A,, Linear
Y,Y,-lA12,
Algebra
and Its Applications
3(1970),
23-29
26
E. V. HAYNSWORTH
the Schur complement
of Y, in the matrix
A(Y)
in (6).
Since the roots
of a are those of A, which are in turn those of the submatrices the theorem
B and D,
is proved.
COROLLARY. Suppose the matrix A has m linearly independent column to the roots, 2,, . . . , 1, (which are not
characteristic vectors corresponding necessarily
distinct).
Let X be the n x m matrix whose columns are these
vectors and assume, without loss of generality,
where X, is nonsingular.
Then the remaining
of the matrix
where A(X)
Proof.
(A(X)/X,),
Since
AX
= XA,
follows immediately
that
n -
where A = diag(il,, . . ., A,),
Often it is easier to use some linear combination
this reason
LEMMA
the corollary
from the theorem.
vectors corresponding in order to compute
m roots of A are those
is constructed as in the theorem.
of the characteristic
to certain roots, rather than the vectors themselves, the matrix
we prove
which contains
Lemma
1. If A E M,(C),
the remaining
roots.
For
1. BE M,(C),
X is a commutator of rank m
from A to B, and Y is an31matrix whose columns are also a basis for the space generated by the columns of X, then Y is a commutator from A to a matrix
2 which is similar to B.
Proof.
Y is a basis for the column
space of X if and only if
Y=XC, where
C is a nonsingular
matrix.
AY = AXC
Then
= XBC
= XC8
=
yB,
where E? = C-lBC. In particular,
if A has its elements
in a given field F, but the roots
of A do not lie in this fieId, then in certain cases, by using a linear combinaLinear Algebra and Its Applications
3(1970), 23-29
PROPERTIES
OF
THE
tion of the vectors, done entirely in F. of degree
2
SCHUR
COMPLEMENT
the computation
27
of the Schur complement
can be
The case in which the roots lie in an extension
over F is proved in Theorem
we need also the result of Lemma
2.
field
For the proof of Theorem
2, which is undoubtedly
2,
well known,
but as its proof is so simple it is included here for the sake of completeness. 2. Su$$ose A is an n x n matrix over a field F having as
LEMMA
a characteristic root il = a + bvd, zwheye a, b, and d belong to F but VZdoes not.
Then (i) the characteristic vector corresponding
X + VdY,
where X and Y aye linearly
(ii) x = a -
to il can be written as
independent
vectors ove7 F, and
b d is a root of A which has the corresponding
vector, X -
characteristic
Vii.
Proof.
Statement
(i) follows
R lies in the extension
field ~(j/d),
must also lie in this field.
A(X + which implies
immediately
from the fact that, since
th e corresponding
characteristic
vector
Then
@Y) =
(a + bva)(X
+ VZY),
that AX=aX+bdY
AY=bX+aY.
and
Thus A(X which
-
VZy) = aX + bdY -
proves
statement
vd(bX
+ aY) = (a -
(ii).
2. Suppose A is an 1z x n matrix
THEOREM
the distinct roots & = ai + b,v& but jldi does not belong to F. any pair i, j.
bVd)(X -VY),
over a field F having
i = 1, . . . , k, where ai, bi, d, belong to F,
Suppose also that iii # xj = aj -
b,Vd, for
Then.
(i) A has the 2k distinct roots, ai -+ b,Vdi, with corresponding Xifvd;Yi,i=l,..., independent (ii)
vectors
k, where the 2k vectors Xi, Yi belong to F and a7e over F.
If we let Z be the n x 2k matrix having the vectors Xi, Yi as its
coluvnns, the other n -
2k roots of A can be found as roots of the Schur Linear
Algebra
and Its Applications
3(1970), 23-29
E. V. HAYNSWORTH
28 complement of the matrix 2, in A(Z),
where A(Z)
is constructed as in the
theorem. Statement
Proo/.
roots
are distinct.
(i) follows immediately Then,
from Lemma
2 since the
if we let Wi be the n x 2 matrix,
wi =
viiiYi, xi
(Xi +
- vi&Yi)
and let W be the n x 2k matrix, W = (W,, w,, . . . >W,),
we have
4 W = WA,
where
A = diag(ii,,
I,, . . ., A,, I,).
Now we let
Ci be the 2 x 2 matrix
Then
WiCi = 2Z,, where Zi = (Xi, YJ.
Thus,
if we let C =
~~=I
* Ci,
having
the
we have WC = 22. and, by Lemma 2k roots of A. Theorem of 2,
1, Z is a commutator Then, using the columns
1 will have its elements
in A(Z)
from A to a matrix of Z, the matrix
in F, and thus the Schur complement
will also have its elements
This application field of rationals,
A(Z) defined in
is particularly
useful,
in F. of course,
where Vii is not rational,
if the field F is the
or the field of reals, where
v-.d, IS not real. Example.
Consider
the matrix
which has the roots 5 and (5 + roots Linear
we have the vectors Algebra
and
Its
1/5)/2. Corresponding
X 4
Apfhations
1/5 Y, where 3(1970), 23-29
to the two irrational
PROPERTIES
OF THE
SCHUR
29
COMPLEMENT
Then
and (/4(2)/Z,)
0 1) i 4
= 4 + $(l
Iii
1 1
1 o = 5.
REFERENCES 1 D. Crabtree and Emilie Haynsworth, a matrix,
Proc.
Amev.
Math.
Sot.
An identity
for the Schur complement
of
(to appear).
2 L. S. Goddard and H. Schneider, Pairs of matrices with a non-zero commutator, Proc.
Phil. SIX. 61(1955), 551-553. Haynsworth, Determination of the inertia
Camb.
3 Emilie
matrix, Linear Received
May
Algebra l(1968). 9,
of a partitioned
Hermitian
73-81.
7969
Linear
Algebra
and
Its
Applications
3(1970), 23-29