230 CHAPTER 8. LINEAR TRANSFORMATIONS

8.5 Exercises

1. If A,B, and C are each n× n matrices and ABC is invertible, why are each of A,B,and C invertible?

2. Give an example of a 3 × 2 matrix with the property that the linear transformationdetermined by this matrix is one to one but not onto.

3. Explain why Ax = 0 always has a solution whenever A is a linear transformation.

4. Review problem: Suppose det (A− λI) = 0. Show using Theorem 3.1.15 there existsx ̸= 0 such that (A− λI)x = 0.

5. How does the minimal polynomial of an algebraic number relate to the minimal poly-nomial of a linear transformation? Can an algebraic number be thought of as a lineartransformation? How?

6. Recall the fact from algebra that if p (λ) and q (λ) are polynomials, then there existsl (λ) , a polynomial such that

q (λ) = p (λ) l (λ) + r (λ)

where the degree of r (λ) is less than the degree of p (λ) or else r (λ) = 0. With this inmind, why must the minimal polynomial always divide the characteristic polynomial?That is, why does there always exist a polynomial l (λ) such that p (λ) l (λ) = q (λ)?Can you give conditions which imply the minimal polynomial equals the characteristicpolynomial? Go ahead and use the Cayley Hamilton theorem.

7. In the following examples, a linear transformation, T is given by specifying its actionon a basis β. Find its matrix with respect to this basis.

(a) T

(1

2

)= 2

(1

2

)+ 1

(−1

1

), T

(−1

1

)=

(−1

1

)

(b) T

(0

1

)= 2

(0

1

)+ 1

(−1

1

), T

(−1

1

)=

(0

1

)

(c) T

(1

0

)= 2

(1

2

)+ 1

(1

0

), T

(1

2

)= 1

(1

0

)−

(1

2

)

8. Let β = {u1, · · · ,un} be a basis for Fn and let T : Fn → Fn be defined as follows.

T

(n∑

k=1

akuk

)=

n∑k=1

akbkuk

First show that T is a linear transformation. Next show that the matrix of T withrespect to this basis, [T ]β is 

b1. . .

bn

Show that the above definition is equivalent to simply specifying T on the basis vectorsof β by

T (uk) = bkuk.

230CHAPTER 8. LINEAR TRANSFORMATIONS8.5 Exercises1.If A, B, and C are each n x n matrices and ABC is invertible, why are each of A, B,and C' invertible?Give an example of a 3 x 2 matrix with the property that the linear transformationdetermined by this matrix is one to one but not onto.Explain why Ax = 0 always has a solution whenever A is a linear transformation.Review problem: Suppose det (A — AJ) = 0. Show using Theorem 3.1.15 there existsx #0 such that (A —AI)x = 0.How does the minimal polynomial of an algebraic number relate to the minimal poly-nomial of a linear transformation? Can an algebraic number be thought of as a lineartransformation? How?Recall the fact from algebra that if p(A) and q (A) are polynomials, then there exists1(A), a polynomial such thatq(A) = pA)LA) +r)where the degree of r (A) is less than the degree of p (A) or else r (A) = 0. With this inmind, why must the minimal polynomial always divide the characteristic polynomial?That is, why does there always exist a polynomial / (A) such that p(A) 1 (A) = q (A)?Can you give conditions which imply the minimal polynomial equals the characteristicpolynomial? Go ahead and use the Cayley Hamilton theorem.In the following examples, a linear transformation, T is given by specifying its actionon a basis @. Find its matrix with respect to this basis.er )a()()eG)-G)er)G)e (eG )-G)or) )eG)GQ)aG)-(). Let 6 = {uj,--- ,u,} be a basis for F” and let T : F” > F” be defined as follows.T (>: vt) = S- a,nbpuRk=1 k=1First show that JT is a linear transformation. Next show that the matrix of T withrespect to this basis, [7], isbybnShow that the above definition is equivalent to simply specifying T on the basis vectorsof 6 byT (uz) = bp Up.