Linear Algebra Assignment 8: Eigenvalues, Eigenvectors, Diagonalizability, Assignments of Mathematics

Instructions and solutions for math 324 assignment 8, which involves representing a linear operator as a matrix, finding its eigenvalues and eigenvectors, diagonalizing it, and calculating its characteristic polynomial.

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Pre 2010

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Math 324: Assignment 8
Instructions. On this assignment, you may use MathCAD for things like evaluating deter-
minants, or rref, multiplying matrices and finding inverses. Do not use its built-in commands
for finding eigenvalues or eigenvectors. This assignment is a group assignment. The entire
class must agree upon and turn-in one assignment. It is worth 30 homework points and due
Monday, November 8.
1. (10 pts) Consider the linear operator T(x, y, z ) = (7x4y+10z , 4x3y+8z, 2x+y2z).
(a) Represent Tas a matrix with respect to the standard basis on IR3.
(b) Find the characteristic polynomial of T, then find the eigenvalues and eigenvectors for the
matrix you found in (a).
(c) Find a basis βon IR3for which D= [T]βis a diagonal matrix.
(d) Evaluate T(2,3,1) using the formula given above.
(e) Find the coordinate vector [v]βwhere v= (2,3,1) and βis the basis in (c).
(f) Evaluate [T v]β= [T]β[v]βby performing the matrix multiplication on the right hand side.
Convert the coordinate [T v]βback to standard form. Does this agree with your answer in (d)?
(g) Find a formula for Anwhere Ais the matrix representation of Tyou found in (a). Check
your formula with n= 5.
(h) Use (g) to find a formula for Tn(x, y, z).
(i) Evaluate p(A) where pis the characteristic polynomial of Tand Ais the matrix represen-
tation of Tfound in (a).
(j) Find the characteristic polynomial of Dthe diagonal matrix you found in (c). Is it the
same as the characteristic polynomial of A?
Answer. Done on MathCAD.
2. (3 pts) Show that if Aand Bare similar matrices, then Aand Bhave the same characteristic
polynomial.
Proof. Because Aand Bare similar, there is a matrix Csuch that A=C1BC . Therefore,
fA(t) = |AtI|=|C1B C tI|
=|C1BC tI (C1C)|
=|C1BC C1(tI )C|=|C1(BtI)C|
=|C1||BtI ||C|=1
|C||BtI||C|
=|BtI|=fB(t)
That is, Aand Bhave the same characteristic polynomial.
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Math 324: Assignment 8

Instructions. On this assignment, you may use MathCAD for things like evaluating deter- minants, or rref, multiplying matrices and finding inverses. Do not use its built-in commands for finding eigenvalues or eigenvectors. This assignment is a group assignment. The entire class must agree upon and turn-in one assignment. It is worth 30 homework points and due Monday, November 8.

  1. (10 pts) Consider the linear operator T (x, y, z) = (7x − 4 y + 10z, 4 x − 3 y + 8z, − 2 x + y − 2 z).

(a) Represent T as a matrix with respect to the standard basis on IR^3.

(b) Find the characteristic polynomial of T , then find the eigenvalues and eigenvectors for the matrix you found in (a).

(c) Find a basis β on IR^3 for which D = [T ]β is a diagonal matrix.

(d) Evaluate T (2, − 3 , 1) using the formula given above.

(e) Find the coordinate vector [v]β where v = (2, − 3 , 1) and β is the basis in (c).

(f) Evaluate [T v]β = [T ]β [v]β by performing the matrix multiplication on the right hand side. Convert the coordinate [T v]β back to standard form. Does this agree with your answer in (d)?

(g) Find a formula for An^ where A is the matrix representation of T you found in (a). Check your formula with n = 5.

(h) Use (g) to find a formula for T n(x, y, z).

(i) Evaluate p(A) where p is the characteristic polynomial of T and A is the matrix represen- tation of T found in (a).

(j) Find the characteristic polynomial of D the diagonal matrix you found in (c). Is it the same as the characteristic polynomial of A?

Answer. Done on MathCAD.

  1. (3 pts) Show that if A and B are similar matrices, then A and B have the same characteristic polynomial.

Proof. Because A and B are similar, there is a matrix C such that A = C−^1 BC. Therefore,

fA(t) = |A − tI| = |C−^1 BC − tI| = |C−^1 BC − tI(C−^1 C)| = |C−^1 BC − C−^1 (tI)C| = |C−^1 (B − tI)C|

= |C−^1 | |B − tI| |C| =

|C|

|B − tI||C|

= |B − tI| = fB (t)

That is, A and B have the same characteristic polynomial.

Note, also, that question 2 implies that similar matrices have the same eigenvalues since the characteristic polynomials have the same zeros.

  1. (4 pts) (a) Find bases for the eigenspaces of A =

(b) Is A diagonalizable? Justify your answer.

Answer. (a) The eigenvalues of A are λ 1 = 1 and λ 2 = 2. Note, Eλ 1 = {v ∈ IR^4 : (A−1I) = 0}. A basis for Eλ 1 is a basis for the homogeneous system of equations (A − I)v = 0 which is {(1, 0 , 0 , 0)}. Similarly, for λ 2 = 2, Eλ 2 = {v ∈ IR^4 : (A − 2I) = 0. You should check that a basis for Eλ 2 = {(1, 1 , 0 , 0), (1, 0 , 1 , 0)}.

(b) A is not diagonalizable because dim(Eλ 1 ) + dim(Eλ 2 ) = 1 + 2 = 3 < 4.

  1. (6 pts) (a) The Fibonacci sequence is defined by the difference equation

an = an− 1 + an− 2

where a 1 = 1, and a 2 = 1. Find a formula for an.

(b) Determine the exact value lim n→∞

an an− 1

. (This limit is called the golden ratio.)

Answer. MathCAD did not do this question very cleanly. Here is another approach. Let bn = an− 1 , then an = an− 1 + bn− 1 and bn = an− 1. Therefore, in matrix form, [ an bn

]

[

] [

an− 1 bn− 1

]

hence,

[ a 3 b 3

]

[

] [

] [

a 4 b 4

]

[

] [

a 3 b 3

]

[

] 2 [

]

And in general (see notes from class on solving difference equations),

[ an an− 1

]

[

]n− 2 [ 1 1

]

Now let A =

[

]

. Then the eigevalues of A are λ 1 =

and λ 2 =

. One can

check that

[

λ 1 1

]

and

[

λ 2 1

]

are eigenvectors corresponding to these eigenvalues. Therefore,

using diaglonalization techniques,

An−^2 = B

[

λn 1 −^20 0 λn 2 −^2

]

B−^1 where B =

[

λ 1 λ 2 1 1

]

(b) Describe the eigenvalues of A and justify your answer.

(c) Is the matrix A =

 diagonalizable? Why?

Answer. (a) The chracteristic polynomial is

fA(t) = |A − tI| = (a 11 − t)(a 22 − t) · · · (ann − t)

(b) The eigenvalues of A are λk = akk for k = 1, 2 ,... , n, because these are the zeros of the characteristic polynomial in (a).

(c) Yes, because it is a 4 by 4 matrix with 4 distinct eigenvalues 1, 2 , 3 , 4. (It is interesting to compare this with the matrix in question 3 which is the same except for the values on the diagonal. The matrix in question 3 is not diagonalizable, but the matrix in this question is.)