A First Course in Linear Algebra, 2017a

368 Spectral Theory
Then also
whichyoumaywishtoverify.
Then,
P −1 AP =
=
⎡
⎣
⎡
⎣
= D
⎡
P −1 = ⎣
1 1 1
0 1 0
−1 −1 0
1 0 0
0 1 0
0 0 2
⎤
⎦
1 1 1
0 1 0
−1 −1 0
⎤⎡
⎦⎣
Now it follows by rearranging the equation that
⎡
0 −1
⎤⎡
−1
A = PDP −1 = ⎣ 0 1 0 ⎦⎣
1 0 1
Therefore,
A 50 = PD 50 P −1
⎡
⎤⎡
0 −1 −1
= ⎣ 0 1 0 ⎦⎣
1 0 1
⎤
⎦
2 1 0
0 1 0
−1 −1 1
1 0 0
0 1 0
0 0 2
1 0 0
0 1 0
0 0 2
⎤
⎦
⎤⎡
⎦⎣
⎤⎡
⎦⎣
50 ⎡
⎣
0 −1 −1
0 1 0
1 0 1
1 1 1
0 1 0
−1 −1 0
1 1 1
0 1 0
−1 −1 0
⎤
⎦
⎤
⎦
⎤
⎦
By our discussion above, D 50 is found as follows.
⎡
1 0
⎤50
0
⎡
⎣ 0 1 0 ⎦ = ⎣
0 0 2
1 50 ⎤
0 0
0 1 50 0 ⎦
0 0 2 50
It follows that
A 50 =
=
⎡
⎣
⎡
⎣
0 −1 −1
0 1 0
1 0 1
⎤⎡
⎦⎣
2 50 −1 + 2 50 0
0 1 0
1 − 2 50 1 − 2 50 1
1 50 ⎤
0 0
0 1 50 0 ⎦
0 0 2 50
⎤
⎦
⎡
⎣
1 1 1
0 1 0
−1 −1 0
⎤
⎦
Through diagonalization, we can efficiently compute a high power of A. Without this, we would be
forced to multiply this by hand!
The next section explores another interesting application of diagonalization.
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