6.4. SCHUR’S THEOREM 161

where A1 is an n − 1 × n − 1 matrix. The above matrix B has the same eigenvalues as A.Also note in case of an eigenvalue µ for B,

µ

(a

x

)= B

(a

x

)=

(∗

A1x

)so x is an eigenvector for A1 with the same eigenvalue µ. Now by induction there exists an(n− 1)× (n− 1) unitary matrix Ũ1 such that

Ũ∗1A1Ũ1 = Tn−1,

an upper triangular matrix. Consider

U1 ≡

(1 0

0 Ũ1

)This is a unitary matrix and

U∗1U

∗0AU0U1 =

(1 0

0 Ũ∗1

)(λ1 ∗0 A1

)(1 0

0 Ũ1

)=

(λ1 ∗0 Tn−1

)≡ T

where T is upper triangular. Then let U = U0U1. Since (U0U1)∗= U∗

1U∗0 , it follows A

is similar to T and that U0U1 is unitary. Hence A and T have the same characteristicpolynomials and since the eigenvalues of T are the diagonal entries listed according toalgebraic multiplicity, these are also the eigenvalues of A listed according to multiplicity. ■

Corollary 6.4.5 Let A be a real n × n matrix having only real eigenvalues. Then thereexists a real orthogonal matrix Q and an upper triangular matrix T such that

QTAQ = T

and furthermore, if the eigenvalues of A are listed in decreasing order,

λ1 ≥ λ2 ≥ · · · ≥ λn

Q can be chosen such that T is of the formλ1 ∗ · · · ∗

0 λ2. . .

......

. . .. . . ∗

0 · · · 0 λn

Proof: Repeat the above argument but pick a real eigenvector for the first step which

corresponds to λ1 as just described. Then use induction as above. Simply replace the word“unitary” with the word “orthogonal”. ■

As a simple consequence of the above theorem, here is an interesting lemma.

Lemma 6.4.6 Let A be of the form

A =

P1 · · · ∗...

. . ....

0 · · · Ps



6.4. SCHUR’S THEOREM 161where A, is ann —1Xn-—1 matrix. The above matrix B has the same eigenvalues as A.Also note in case of an eigenvalue y for B,a a *= B =so x is an eigenvector for A; with the same eigenvalue y. Now by induction there exists an(n — 1) x (n—1) unitary matrix U; such thatUF AU, = Ty-1,an upper triangular matrix. ConsiderThis is a unitary matrix and1 1U*UX AUoU = 0 AL * O\_( xs * \epot }\o 4, )\o & 0 Trwhere T is upper triangular. Then let U = UpU;. Since (UpU1)" = U7U%, it follows Ais similar to T and that UpU, is unitary. Hence A and T have the same characteristicpolynomials and since the eigenvalues of T’ are the diagonal entries listed according toalgebraic multiplicity, these are also the eigenvalues of A listed according to multiplicity. HiCorollary 6.4.5 Let A be a realn x n matrix having only real eigenvalues. Then thereexists a real orthogonal matrix Q and an upper triangular matrix T such thatQT AQ=Tand furthermore, if the eigenvalues of A are listed in decreasing order,Ay 2 A22°°° 2AnQ can be chosen such that T is of the formMOOK Ott0 dro0 - 0 AyProof: Repeat the above argument but pick a real eigenvector for the first step whichcorresponds to A; as just described. Then use induction as above. Simply replace the word“unitary” with the word “orthogonal”. HfAs a simple consequence of the above theorem, here is an interesting lemma.Lemma 6.4.6 Let A be of the form