Solutions Problem Set 8 Math 240, Fall

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1 Solutions Problem Set 8 Math 240, Fall T/F.2. True. If A is upper or lower diagonal, to make det(a λi) 0, we need product of the main diagonal elements of A λi to be 0, which means λ is one of the main diagonal elements of A. T/F.4. False. For example and T/F.8. True. The characteristic polynomial has degree n, which has n complex solutions taking into account of multiplicity. Prob.8. The transformation T projects any vector onto its y component. From its geometrical meaning, T i T k 0 and T j j. Therefore we have two eigenvalues 0 and 1. Eigenvalue 0 has two eigenvectors ri and sk. Eigenvalue 1 has eigenvector tj. Here r, s, t are arbitrary nonzero real numbers λ 0 0 Prob.16. A 0 2 1, A λi 0 2 λ 1, λ det(a λi) (3 λ)(2 λ) 2 1. The characteristic has two real solution λ 3 and λ 1. λ 3 s eigenvector satisfies (A 3I)v v

2 There is one linearly independent solution to this equation, which can be taken to be v 3 r(0, 1, 1). For λ 1 we have (A I)v v We can solve its eigenvector to be v 1 s(0, 1, 1). Here r, s are arbitrary nonzero numbers. Prob.32. First we want to solve v c 1 v 1 + c 2 v 2 + c 3 v 3 for c 1, c 2, c 3. equivalent to c 1 c 2 c We do a series of row operation on augmented matrix as follows A 12(1),A 13 ( 1) P A 23 ( 3) M 23( 1/11) Therefore c 3 1, c 2 2 3c 3 1 and c 1 5 2c 2 + c 3 2. Therefore It follows that v 2v 1 + v 2 v 3. Av 2Av 1 + Av 2 Av 3 4v 1 2v 2 3v 3 (3, 3, 8). This is Prob.38. Since det(m) det(m T ) for any square matrix M, we have det(a λi) det((a λi) T ) det(a T λi).

3 This means A and A T have the same characteristic equation, hence they have the same eigenvalues. 5.8 T/F.2. True. If S 1 AS diag(λ 1,, λ n ) and A is invertible, then none of the λ i s is zero. We have S 1 A 1 S diag(λ 1 1,, λ 1 n ). T/F.6. True. If S 1 AS diag(λ 1,, λ n ) then S 1 A 2 S diag(λ 2 1,, λ 2 n). Prob.8. Since A has rank 1, it only has one non-zero eigenvalue. We can also see this from direct calculation as follows. A, 2 λ 1 4 A λi 2 1 λ 4, λ 2 λ λ 1 4 det(a λi) det λ λ 0 det 0 λ 0 (3 λ)λ 2. λ 0 λ 0 0 λ The characteristic has two real solutions λ 3 and λ 0. λ 3 s eigenvector satisfies (A 3I)v v

4 There is one linearly independent solution to this equation, which can be taken to be v 3 (1, 1, 1). For λ 0 we have Av v 0. We can solve its eigenvectors to be v 1 (0, 4, 1) and v 2 (2, 0, 1). Now we take We have S v 1, v 2, v AS S diag(0, 0, 3), or S 1 AS diag(0, 0, 3). Remark. In solving the eigenvectors, you might end up getting something totally different from my answer, that s completely normal. As long as your answer and mine are linearly dependent on each other, it s fine. Prob.10. We do this problem using the standard procedure just as in the last one λ 0 0 A 3 1 1, A λi 3 1 λ 1, λ det(a λi) (4 λ)( 1 λ)(1 λ) + 2 (4 λ)(λ 2 + 1). The characteristic has one real solution λ 4 and two imaginary solutions λ ±i. λ 4 s eigenvector satisfies (A 4I)v v

5 We can solve its eigenvector to be v 1 (17, 9, 6). For λ i we have 4 i 0 0 (A ii)v 3 1 i 1 v i We can solve its eigenvector to be v 2 (0, 1, 1 i). And for λ i we have 4 + i 0 0 (A ii)v i 1 v i We can solve its eigenvector to be v 3 (0, 1, 1 + i). Now we take We have S v 1, v 2, v i 1 + i AS S diag(4, i, i), or S 1 AS diag(4, i, i). Prob.22. If A SDS 1, And for any positive integer k, A 2 SDS 1 SDS 1 SDDS 1 SD 2 S 1. A k SDS 1 SDS 1 SDS 1 SDD DS 1 SD k S 1. The equality holds since all the S 1 and S in between D s cancel each other λ 4 Prob.24. We need to diagonalize A first. A λi λ det(a λi) ( 7 λ)(11 λ) + 72 (λ + 1)(λ 5). A has two eigenvalues 1 and 5. When λ 1, 6 4 (A λi)v v

6 has eigenvector solution v 1 (2, 3). When λ 5, 12 4 (A λi)v v has eigenvector solution v 2 (1, 3). Therefore we can take 2 1 S v 1, v 2, 3 3 and D diag( 1, 5). It follows from the prob 22, 23 that A 3 S diag(( 1) 3, 5 3 ) S / (1+53 ) /3 3( ) , A 5 S diag(( 1) 5, 5 5 ) S / (1+55 ) /3 3( )

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