Linear Algebra Exercises-n-Answers.pdf
Linear Algebra Exercises-n-Answers.pdf Linear Algebra Exercises-n-Answers.pdf
182 Linear Algebra, by Hefferon Restated more computationally, if T = P SP −1 then T 2 = (P SP −1 )(P SP −1 ) = P S 2 P −1 . Induction extends that to all powers. For the k ≤ 0 case, suppose that S is invertible and that T = P SP −1 . Note that T is invertible: T −1 = (P SP −1 ) −1 = P S −1 P −1 , and that same equation shows that T −1 is similar to S −1 . Other negative powers are now given by the first paragraph. Five.II.1.18 In conceptual terms, both represent p(t) for some transformation t. In computational terms, we have this. p(T ) = c n (P SP −1 ) n + · · · + c 1 (P SP −1 ) + c 0 I = c n P S n P −1 + · · · + c 1 P SP −1 + c 0 I = P c n S n P −1 + · · · + P c 1 SP −1 + P c 0 P −1 = P (c n S n + · · · + c 1 S + c 0 )P −1 Five.II.1.19 There are two equivalence classes, (i) the class of rank zero matrices, of which there is one: C 1 = {(0)}, and (2) the class of rank one matrices, of which there are infinitely many: C 2 = {(k) ∣ k ≠ 0}. Each 1 × 1 matrix is alone in its similarity class. That’s because any transformation of a onedimensional space is multiplication by a scalar t k : V → V given by ⃗v ↦→ k · ⃗v. Thus, for any basis B = 〈 β〉, ⃗ the matrix representing a transformation t k with respect to B, B is (Rep B (t k ( β))) ⃗ = (k). So, contained in the matrix equivalence class C 1 is (obviously) the single similarity class consisting of the matrix (0). And, contained in the matrix equivalence class C 2 are the infinitely many, onemember-each, similarity classes consisting of (k) for k ≠ 0. Five.II.1.20 No. Here is an example that has two pairs, each of two similar matrices: ( ) ( ) ( ) ( ) 1 −1 1 0 2/3 1/3 5/3 −2/3 = 1 2 0 3 −1/3 1/3 −4/3 7/3 and ( ) ( ) ( ) 1 −2 −1 0 −1 −2 −1 1 0 −3 −1 −1 = ( ) −5 −4 2 1 (this example is mostly arbitrary, but not entirely, because the the center matrices on the two left sides add to the zero matrix). Note that the sums of these similar matrices are not similar ( ) ( ) ( ) ( ) ( ) ( ) 1 0 −1 0 0 0 5/3 −2/3 −5 −4 0 0 + = + ≠ 0 3 0 −3 0 0 −4/3 7/3 2 1 0 0 since the zero matrix is similar only to itself. Five.II.1.21 If N = P (T −λI)P −1 then N = P T P −1 −P (λI)P −1 . The diagonal matrix λI commutes with anything, so P (λI)P −1 = P P −1 (λI) = λI. Thus N = P T P −1 − λI and consequently N + λI = P T P −1 . (So not only are they similar, in fact they are similar via the same P .) Subsection Five.II.2: Diagonalizability Five.II.2.6 Because the basis vectors are chosen arbitrarily, many different answers are possible. However, here is one way to go; to diagonalize ( ) 4 −2 T = 1 1 take it as the representation of a transformation with respect to the standard basis T = Rep E2 ,E 2 (t) and look for B = 〈 ⃗ β 1 , ⃗ β 2 〉 such that Rep B,B (t) = ( ) λ1 0 0 λ 2 that is, such that t( β ⃗ 1 ) = λ 1 and t( β ⃗ 2 ) = λ 2 . ( ) ( ) 4 −2 ⃗β 1 1 1 = λ 1 · ⃗β 4 −2 1 ⃗β 1 1 2 = λ 2 · ⃗β 2 We are looking for scalars x such that this equation ( ) ( ) ( ) 4 −2 b1 b1 = x · 1 1 b 2 b 2
Answers to Exercises 183 has solutions b 1 and b 2 , which are not both zero. Rewrite that as a linear system (4 − x) · b 1 + −2 · b 2 = 0 1 · b 1 + (1 − x) · b 2 = 0 If x = 4 then the first equation gives that b 2 = 0, and then the second equation gives that b 1 = 0. The case where both b’s are zero is disallowed so we can assume that x ≠ 4. (−1/(4−x))ρ 1 +ρ 2 (4 − x) · b −→ 1 + −2 · b 2 = 0 ((x 2 − 5x + 6)/(4 − x)) · b 2 = 0 Consider the bottom equation. If b 2 = 0 then the first equation gives b 1 = 0 or x = 4. The b 1 = b 2 = 0 case is disallowed. The other possibility for the bottom equation is that the numerator of the fraction x 2 − 5x + 6 = (x − 2)(x − 3) is zero. The x = 2 case gives a first equation of 2b 1 − 2b 2 = 0, and so associated with x = 2 we have vectors whose first and second components are equal: ( ( ) ( ( 1 4 −2 1 1 ⃗β 1 = (so = 2 · , and λ 1) 1 1 1) 1) 1 = 2). If x = 3 then the first equation is b 1 − 2b 2 = 0 and so the associated vectors are those whose first component is twice their second: ( ( ) ( ( 2 4 −2 2 2 ⃗β 2 = (so = 3 · , and so λ 1) 1 1 1) 1) 2 = 3). This picture R 2 t w.r.t. E 2 −−−−→ R 2 w.r.t. E T 2 ⏐ ⏐ id↓ id↓ shows how to get the diagonalization. ( ) 2 0 = 0 3 R 2 w.r.t. B ( 1 2 1 1 t −−−−→ D R 2 w.r.t. B ) −1 ( 4 −2 1 1 ) ( 1 2 1 1 Comment. This equation matches the T = P SP −1 definition under this renaming. ( ) ( ) −1 ( ) ( ) 2 0 1 2 T = P = p −1 1 2 4 −2 = S = 0 3 1 1 1 1 1 1 Five.II.2.7 (a) Setting up ( ) ( ) ( ) −2 1 b1 b1 (−2 − x) · b = x · =⇒ 1 + b 2 = 0 0 2 b 2 b 2 (2 − x) · b 2 = 0 gives the two possibilities that b 2 = 0 and x = 2. Following the b 2 = 0 possibility leads to the first equation (−2 − x)b 1 = 0 with the two cases that b 1 = 0 and that x = −2. Thus, under this first possibility, we find x = −2 and the associated vectors whose second component is zero, and whose first component is free. ( ( ) ( ) ( −2 1 b1 b1 1 = −2 · ⃗β 0 2) 0 0 1 = 0) Following the other possibility leads to a first equation of −4b 1 +b 2 = 0 and so the vectors associated with this solution have a second component that is four times their first component. ( ) ( ) ( ) ( −2 1 b1 b1 1 = 2 · ⃗β 0 2 4b 1 4b 2 = 1 4) The diagonalization is this. ( ) −1 ( ) ( ) −1 ( ) 1 1 −2 1 1 1 −2 0 0 4 0 2 0 4 0 2 (b) The calculations are like those in the prior part. ( ) ( ) ( ) 5 4 b1 b1 (5 − x) · b = x · =⇒ 1 + 4 · b 2 = 0 0 1 b 2 b 2 (1 − x) · b 2 = 0 The bottom equation gives the two possibilities that b 2 = 0 and x = 1. Following the b 2 = 0 possibility, and discarding the case where both b 2 and b 1 are zero, gives that x = 5, associated with vectors whose second component is zero and whose first component is free. ( 1 ⃗β 1 = 0) )
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<strong>Answers</strong> to <strong>Exercises</strong> 183<br />
has solutions b 1 and b 2 , which are not both zero. Rewrite that as a linear system<br />
(4 − x) · b 1 + −2 · b 2 = 0<br />
1 · b 1 + (1 − x) · b 2 = 0<br />
If x = 4 then the first equation gives that b 2 = 0, and then the second equation gives that b 1 = 0. The<br />
case where both b’s are zero is disallowed so we can assume that x ≠ 4.<br />
(−1/(4−x))ρ 1 +ρ 2 (4 − x) · b −→ 1 + −2 · b 2 = 0<br />
((x 2 − 5x + 6)/(4 − x)) · b 2 = 0<br />
Consider the bottom equation. If b 2 = 0 then the first equation gives b 1 = 0 or x = 4. The b 1 = b 2 = 0<br />
case is disallowed. The other possibility for the bottom equation is that the numerator of the fraction<br />
x 2 − 5x + 6 = (x − 2)(x − 3) is zero. The x = 2 case gives a first equation of 2b 1 − 2b 2 = 0, and so<br />
associated with x = 2 we have vectors whose first and second components are equal:<br />
( ( ) ( ( 1 4 −2 1 1 ⃗β 1 = (so<br />
= 2 · , and λ<br />
1)<br />
1 1 1)<br />
1)<br />
1 = 2).<br />
If x = 3 then the first equation is b 1 − 2b 2 = 0 and so the associated vectors are those whose first<br />
component is twice their second:<br />
( ( ) ( (<br />
2 4 −2 2 2 ⃗β 2 = (so<br />
= 3 · , and so λ<br />
1)<br />
1 1 1)<br />
1)<br />
2 = 3).<br />
This picture<br />
R 2 t<br />
w.r.t. E 2<br />
−−−−→ R 2 w.r.t. E T 2<br />
⏐<br />
⏐<br />
id↓<br />
id↓<br />
shows how to get the diagonalization.<br />
( )<br />
2 0<br />
=<br />
0 3<br />
R 2 w.r.t. B<br />
(<br />
1 2<br />
1 1<br />
t<br />
−−−−→<br />
D<br />
R 2 w.r.t. B<br />
) −1 (<br />
4 −2<br />
1 1<br />
) (<br />
1 2<br />
1 1<br />
Comment. This equation matches the T = P SP −1 definition under this renaming.<br />
( ) ( ) −1 ( ) ( )<br />
2 0 1 2<br />
T = P =<br />
p −1 1 2 4 −2<br />
= S =<br />
0 3 1 1<br />
1 1 1 1<br />
Five.II.2.7 (a) Setting up<br />
( ) ( ) ( )<br />
−2 1 b1 b1<br />
(−2 − x) · b<br />
= x · =⇒<br />
1 + b 2 = 0<br />
0 2 b 2 b 2 (2 − x) · b 2 = 0<br />
gives the two possibilities that b 2 = 0 and x = 2. Following the b 2 = 0 possibility leads to the first<br />
equation (−2 − x)b 1 = 0 with the two cases that b 1 = 0 and that x = −2. Thus, under this first<br />
possibility, we find x = −2 and the associated vectors whose second component is zero, and whose<br />
first component is free. ( ( ) ( ) (<br />
−2 1 b1 b1 1<br />
= −2 · ⃗β<br />
0 2)<br />
0<br />
0 1 =<br />
0)<br />
Following the other possibility leads to a first equation of −4b 1 +b 2 = 0 and so the vectors associated<br />
with this solution have a second component that is four times their first component.<br />
( ) ( ) ( ) (<br />
−2 1 b1 b1<br />
1<br />
= 2 ·<br />
⃗β<br />
0 2 4b 1 4b 2 =<br />
1 4)<br />
The diagonalization is this.<br />
( ) −1 ( ) ( ) −1 ( )<br />
1 1 −2 1 1 1 −2 0<br />
0 4 0 2 0 4 0 2<br />
(b) The calculations are like those in the prior part.<br />
( ) ( ) ( )<br />
5 4 b1 b1<br />
(5 − x) · b<br />
= x · =⇒<br />
1 + 4 · b 2 = 0<br />
0 1 b 2 b 2 (1 − x) · b 2 = 0<br />
The bottom equation gives the two possibilities that b 2 = 0 and x = 1. Following the b 2 = 0<br />
possibility, and discarding the case where both b 2 and b 1 are zero, gives that x = 5, associated with<br />
vectors whose second component is zero and whose first component is free.<br />
(<br />
1 ⃗β 1 =<br />
0)<br />
)