Linear Algebra Problem Set 7 Solutions: Eigenvalues and Eigenvectors, Assignments of Linear Algebra

Solutions to problem set 7 of a linear algebra course, focusing on eigenvalues and eigenvectors. The solutions cover various problems, including proving that an eigenvector of a matrix t has the same eigenvalue when multiplied by a scalar a, finding the eigenvectors of a shift operator s, and proving that the eigenvalues of an upper triangular matrix are its diagonal entries. The document also includes an optional problem about the characteristic polynomial of a graph's adjacency matrix.

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Pre 2010

Uploaded on 10/01/2009

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Problem Set 7 Solutions
MATH 110: Linear Algebra
Each problem is worth 5 points.
PART 1
1. Curtis p. 192 3.
2. Curtis p. 192 5.
3. Curtis p. 215 1(a,b,c,d,e).
Solutions in book.
PART 2
Problem 1(10)
a) If T:VVhas an eigenvalue λ, prove that aT has the eigenvalue
.
Proof: Let xbe an eigenvector for the eigenvalue λ. (aT )(x) = a(T(x)) =
a(λx) = λ(ax) so ax is an eigenvector of aT with eigenvalue λ.
b) If xis an eigenvector for both T1and T2, prove that xis an eigenvector
for aT1+bT2and find the eigenvalues of aT1+bT2in terms of the eigenvalues
of T1and T2.
Proof: Let λbe the eigenvalue of xfor T1and let µbe the eigenvalue of
xfor T2. (aT1+bT2)(x) = (aT1)(x)+(bT2)(x) = (λa +µb)x.
c) Suppose that xis an eigenvector of Twith eigenvalue λ. Show that x
is an eigenvector of T2with eigenvalue λ2.
Proof:T2(x) = T(T(x)) = T(λx) = λ(T(x)) = λ(λx) = λ2x.
d) Let Pbe a polynomial. Show that if xis an eigenvector of Twith
eigenvalue λthen xis an eigenvector of P(T) with eigenvalue P(λ).
Proof: By induction on the degree of P(we will denote the degree with
the variable n). Suppose n= 0: the polynomial is a constant, and certainly
xis an eigenvector of P(T) (every vector actually is) with eigenvalue P(λ).
Now suppose the theorem is true for all polynomials of degree less than or
equal to n. Consider Pof degree n+ 1. If Phas no constant term, then
P(T) = T Q(T) where Qhas degree n. By induction xis an eigenvector of
Qwith eigenvalue Q(λ). Therefore, T Q(T)(x) = T(Q(λ)x) = Q(λ)T(x) =
Q(λ)(λx) = λQ(λ)x. Thus xis an eigenvector of Pwith eigenvalue λQ(λ) =
P(λ). Now, if Phas a constant term c, then Pcis a polynomial of degree
1
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Problem Set 7 Solutions MATH 110: Linear Algebra

Each problem is worth 5 points. PART 1

  1. Curtis p. 192 3.
  2. Curtis p. 192 5.
  3. Curtis p. 215 1(a,b,c,d,e).

Solutions in book. PART 2 Problem 1(10) a) If T : V → V has an eigenvalue λ, prove that aT has the eigenvalue aλ. Proof: Let x be an eigenvector for the eigenvalue λ. (aT )(x) = a(T (x)) = a(λx) = λ(ax) so ax is an eigenvector of aT with eigenvalue λ. b) If x is an eigenvector for both T 1 and T 2 , prove that x is an eigenvector for aT 1 + bT 2 and find the eigenvalues of aT 1 + bT 2 in terms of the eigenvalues of T 1 and T 2. Proof: Let λ be the eigenvalue of x for T 1 and let μ be the eigenvalue of x for T 2. (aT 1 + bT 2 )(x) = (aT 1 )(x) + (bT 2 )(x) = (λa + μb)x. c) Suppose that x is an eigenvector of T with eigenvalue λ. Show that x is an eigenvector of T 2 with eigenvalue λ^2. Proof: T 2 (x) = T (T (x)) = T (λx) = λ(T (x)) = λ(λx) = λ^2 x. d) Let P be a polynomial. Show that if x is an eigenvector of T with eigenvalue λ then x is an eigenvector of P (T ) with eigenvalue P (λ). Proof: By induction on the degree of P (we will denote the degree with the variable n). Suppose n = 0: the polynomial is a constant, and certainly x is an eigenvector of P (T ) (every vector actually is) with eigenvalue P (λ). Now suppose the theorem is true for all polynomials of degree less than or equal to n. Consider P of degree n + 1. If P has no constant term, then P (T ) = T Q(T ) where Q has degree n. By induction x is an eigenvector of Q with eigenvalue Q(λ). Therefore, T Q(T )(x) = T (Q(λ)x) = Q(λ)T (x) = Q(λ)(λx) = λQ(λ)x. Thus x is an eigenvector of P with eigenvalue λQ(λ) = P (λ). Now, if P has a constant term c, then P − c is a polynomial of degree

n + 1 with no constant term. By the above argument x is an eigenvector of P − c with eigenvalue (P − c)(λ). Notice that x is also an eigenvector of c with eigenvalue c (proved for the base case). By part (b) x is an eigenvector of the polynomial P − c + c = P with eigenvalue (P − c)(λ) + c = P (λ). Problem 2(10) If T : V → V has the property that T 2 has a nonnegative eigenvalue λ^2 , prove that at least one of λ or −λ is an eigenvalue for T. (Hint: T 2 − λ^2 I = (T + λI)(T − λI)). Proof: Let x be an eigenvector of T 2 with the eigenvalue λ^2. (T 2 − λ^2 I)(x) = 0. Therefore, (T + λI)(T − λI)(x) = 0. If (T − λI)(x) = 0 then x is an eigenvector of T with eigenvalue λ. Otherwise, (T − λI)(x) = y where y is some nonzero vector. In this case, (T + λI)(y) = 0, which means that y is an eigenvector of T with eigenvalue −λ. Thus, either λ or −λ is an eigenvalue. Problem 3 (10) Let V be the linear space of all real convergent sequences {xn}. Define T : V → V as follows: if x = {xn} is a convergent sequence with limit a, let T (x) = {yn} where yn = a − xn for n ≥ 1. Prove that T has only two eigenvalues λ = 0 and λ = −1 and determine the eigenvectors belonging to each such λ. Solution: Let λ be an eigenvalue of T. Then a − xn = λxn for each n, which means that xn = (^) λ+1a (assuming that λ 6 = −1). Taking the limit, as n → ∞, we see that (^) λ+1a = a which implies that λ = 0. Thus λ is either 0 or −1. If λ = 0 this means that xn is a constant sequence, thus the eigenvectors corresponding to eigenvalue 0 are the constant sequences. If λ = −1 then we see that there is no restriction on xn, other than that a = 0. Thus, the sequences with limit 0 are the eigenvectors with eigenvalue −1. Problem 4 (20) Let V be the vector space of sequences {an} over the real numbers. The shift operator S : V → V is defined by

S((a 1 , a 2 ,.. .) = (a 2 , a 3 , a 4 ,.. .).

Find the eigenvectors of S, and show that the subspace W consisting of the sequences {xn} satisfying xn+2 = xn+1 + xn is a two dimensional, S-invariant subspace of V. Also, find an explicit basis for W. Using these results, find an explicit formula for the nth Fibonacci number fn where fn+2 = fn+1 + fn and f 1 = f 2 = 1.

Let f (x) = xn^ +c 1 xn−^1 +c 2 xn−^2 +.. .+cn be the characteristic polynomial of the adjacency matrix of a graph. Show that c 1 = 0, −c 2 is the number of edges in the graph, and −c 3 is twice the number of triangles in the graph.