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Page 1: Finding eigenvalues, char poly

Announcements

Ï Quiz 4 will be on Thurs Feb 18 on sec 3.3, 5.1 and 5.2.

Ï "Curved" quiz grades (3 point curve as I mentioned in theemail) will be posted by today evening.

Ï I have updated the homework set (again!!). I decided to skip5.5 and start chap 6 after 5.3.

Page 2: Finding eigenvalues, char poly

Last Week

1. De�ned eigenvalues and eigenvectors of a square matrix

2. How to test whether a given vector is an eigenvector of a givenmatrix (multiply and check whether we get a scalar multiple ofthe original vector)

3. How to test whether a given number λ is an eigenvalue (checkwhether the matrix A−λI has linearly dependent columns)

4. How to �nd the eigenvectors of a given eigenvalue (row reduceA−λI and solve for basic in terms of free variables).

5. Eigenvalues of any triangular matrix are the entries of themain diagonal

6. Zero is an eigenvalue of A if and only if A is not invertible.

7. We did not see how to �nd eigenvalues of a general squarematrix.

Page 3: Finding eigenvalues, char poly

Last Week

1. De�ned eigenvalues and eigenvectors of a square matrix

2. How to test whether a given vector is an eigenvector of a givenmatrix (multiply and check whether we get a scalar multiple ofthe original vector)

3. How to test whether a given number λ is an eigenvalue (checkwhether the matrix A−λI has linearly dependent columns)

4. How to �nd the eigenvectors of a given eigenvalue (row reduceA−λI and solve for basic in terms of free variables).

5. Eigenvalues of any triangular matrix are the entries of themain diagonal

6. Zero is an eigenvalue of A if and only if A is not invertible.

7. We did not see how to �nd eigenvalues of a general squarematrix.

Page 4: Finding eigenvalues, char poly

Last Week

1. De�ned eigenvalues and eigenvectors of a square matrix

2. How to test whether a given vector is an eigenvector of a givenmatrix (multiply and check whether we get a scalar multiple ofthe original vector)

3. How to test whether a given number λ is an eigenvalue (checkwhether the matrix A−λI has linearly dependent columns)

4. How to �nd the eigenvectors of a given eigenvalue (row reduceA−λI and solve for basic in terms of free variables).

5. Eigenvalues of any triangular matrix are the entries of themain diagonal

6. Zero is an eigenvalue of A if and only if A is not invertible.

7. We did not see how to �nd eigenvalues of a general squarematrix.

Page 5: Finding eigenvalues, char poly

Last Week

1. De�ned eigenvalues and eigenvectors of a square matrix

2. How to test whether a given vector is an eigenvector of a givenmatrix (multiply and check whether we get a scalar multiple ofthe original vector)

3. How to test whether a given number λ is an eigenvalue (checkwhether the matrix A−λI has linearly dependent columns)

4. How to �nd the eigenvectors of a given eigenvalue (row reduceA−λI and solve for basic in terms of free variables).

5. Eigenvalues of any triangular matrix are the entries of themain diagonal

6. Zero is an eigenvalue of A if and only if A is not invertible.

7. We did not see how to �nd eigenvalues of a general squarematrix.

Page 6: Finding eigenvalues, char poly

Last Week

1. De�ned eigenvalues and eigenvectors of a square matrix

2. How to test whether a given vector is an eigenvector of a givenmatrix (multiply and check whether we get a scalar multiple ofthe original vector)

3. How to test whether a given number λ is an eigenvalue (checkwhether the matrix A−λI has linearly dependent columns)

4. How to �nd the eigenvectors of a given eigenvalue (row reduceA−λI and solve for basic in terms of free variables).

5. Eigenvalues of any triangular matrix are the entries of themain diagonal

6. Zero is an eigenvalue of A if and only if A is not invertible.

7. We did not see how to �nd eigenvalues of a general squarematrix.

Page 7: Finding eigenvalues, char poly

Last Week

1. De�ned eigenvalues and eigenvectors of a square matrix

2. How to test whether a given vector is an eigenvector of a givenmatrix (multiply and check whether we get a scalar multiple ofthe original vector)

3. How to test whether a given number λ is an eigenvalue (checkwhether the matrix A−λI has linearly dependent columns)

4. How to �nd the eigenvectors of a given eigenvalue (row reduceA−λI and solve for basic in terms of free variables).

5. Eigenvalues of any triangular matrix are the entries of themain diagonal

6. Zero is an eigenvalue of A if and only if A is not invertible.

7. We did not see how to �nd eigenvalues of a general squarematrix.

Page 8: Finding eigenvalues, char poly

Last Week

1. De�ned eigenvalues and eigenvectors of a square matrix

2. How to test whether a given vector is an eigenvector of a givenmatrix (multiply and check whether we get a scalar multiple ofthe original vector)

3. How to test whether a given number λ is an eigenvalue (checkwhether the matrix A−λI has linearly dependent columns)

4. How to �nd the eigenvectors of a given eigenvalue (row reduceA−λI and solve for basic in terms of free variables).

5. Eigenvalues of any triangular matrix are the entries of themain diagonal

6. Zero is an eigenvalue of A if and only if A is not invertible.

7. We did not see how to �nd eigenvalues of a general squarematrix.

Page 9: Finding eigenvalues, char poly

How to �nd eigenvalues of any square matrix A?

Idea: An eigenvalue λ is a scalar such that the equation(A−λI )x= 0 has free variables. This means

1. The matrix A−λI is not invertible or

2. The determinant of the matrix A−λI is zero3. Solve the equation det(A−λI )= 0 for λ

4. For a 2×2 matrix it is easy, we get a quadratic equation, sofactorize and �nd λ.

5. For a 3×3 matrix, it is not always easy to solve for λ (exceptin some carefully constructed matrices)

6. For a 4×4 and larger matrices, use ofcalculator/software/approximate numerical schemes areprefered.

Page 10: Finding eigenvalues, char poly

How to �nd eigenvalues of any square matrix A?

Idea: An eigenvalue λ is a scalar such that the equation(A−λI )x= 0 has free variables. This means

1. The matrix A−λI is not invertible or2. The determinant of the matrix A−λI is zero

3. Solve the equation det(A−λI )= 0 for λ

4. For a 2×2 matrix it is easy, we get a quadratic equation, sofactorize and �nd λ.

5. For a 3×3 matrix, it is not always easy to solve for λ (exceptin some carefully constructed matrices)

6. For a 4×4 and larger matrices, use ofcalculator/software/approximate numerical schemes areprefered.

Page 11: Finding eigenvalues, char poly

How to �nd eigenvalues of any square matrix A?

Idea: An eigenvalue λ is a scalar such that the equation(A−λI )x= 0 has free variables. This means

1. The matrix A−λI is not invertible or2. The determinant of the matrix A−λI is zero3. Solve the equation det(A−λI )= 0 for λ

4. For a 2×2 matrix it is easy, we get a quadratic equation, sofactorize and �nd λ.

5. For a 3×3 matrix, it is not always easy to solve for λ (exceptin some carefully constructed matrices)

6. For a 4×4 and larger matrices, use ofcalculator/software/approximate numerical schemes areprefered.

Page 12: Finding eigenvalues, char poly

How to �nd eigenvalues of any square matrix A?

Idea: An eigenvalue λ is a scalar such that the equation(A−λI )x= 0 has free variables. This means

1. The matrix A−λI is not invertible or2. The determinant of the matrix A−λI is zero3. Solve the equation det(A−λI )= 0 for λ

4. For a 2×2 matrix it is easy, we get a quadratic equation, sofactorize and �nd λ.

5. For a 3×3 matrix, it is not always easy to solve for λ (exceptin some carefully constructed matrices)

6. For a 4×4 and larger matrices, use ofcalculator/software/approximate numerical schemes areprefered.

Page 13: Finding eigenvalues, char poly

How to �nd eigenvalues of any square matrix A?

Idea: An eigenvalue λ is a scalar such that the equation(A−λI )x= 0 has free variables. This means

1. The matrix A−λI is not invertible or2. The determinant of the matrix A−λI is zero3. Solve the equation det(A−λI )= 0 for λ

4. For a 2×2 matrix it is easy, we get a quadratic equation, sofactorize and �nd λ.

5. For a 3×3 matrix, it is not always easy to solve for λ (exceptin some carefully constructed matrices)

6. For a 4×4 and larger matrices, use ofcalculator/software/approximate numerical schemes areprefered.

Page 14: Finding eigenvalues, char poly

How to �nd eigenvalues of any square matrix A?

Idea: An eigenvalue λ is a scalar such that the equation(A−λI )x= 0 has free variables. This means

1. The matrix A−λI is not invertible or2. The determinant of the matrix A−λI is zero3. Solve the equation det(A−λI )= 0 for λ

4. For a 2×2 matrix it is easy, we get a quadratic equation, sofactorize and �nd λ.

5. For a 3×3 matrix, it is not always easy to solve for λ (exceptin some carefully constructed matrices)

6. For a 4×4 and larger matrices, use ofcalculator/software/approximate numerical schemes areprefered.

Page 15: Finding eigenvalues, char poly

Example 2, section 5.2

Find the eigenvalues of the matrix[5 33 5

].

Solution: We have to look at the determinant of the matrix[5 33 5

]−λ

[1 00 1

]=

[5 33 5

]−

[λ 00 λ

]=

[5−λ 33 5−λ

].

In other words, form a matrix where you subtract λ from thediagonal elements (no change to the o� diagonal elements). This isthe case with any square matrix of any size.

Page 16: Finding eigenvalues, char poly

Example 2, section 5.2

Find the eigenvalues of the matrix[5 33 5

].

Solution: We have to look at the determinant of the matrix[5 33 5

]−λ

[1 00 1

]=

[5 33 5

]−

[λ 00 λ

]=

[5−λ 33 5−λ

].

In other words, form a matrix where you subtract λ from thediagonal elements (no change to the o� diagonal elements). This isthe case with any square matrix of any size.

Page 17: Finding eigenvalues, char poly

Example 2, section 5.2

Find the eigenvalues of the matrix[5 33 5

].

Solution: We have to look at the determinant of the matrix[5 33 5

]−λ

[1 00 1

]=

[5 33 5

]−

[λ 00 λ

]=

[5−λ 33 5−λ

].

In other words, form a matrix where you subtract λ from thediagonal elements (no change to the o� diagonal elements). This isthe case with any square matrix of any size.

Page 18: Finding eigenvalues, char poly

Example 2, section 5.2Let us look at the determinant of the new matrix∣∣∣∣ 5−λ 3

3 5−λ∣∣∣∣= (5−λ)2−9.

Simplify this quantity. Some high school algebra will be handy.

(5−λ)2 = 25−10λ+λ2.

(5−λ)2−9= 25−10λ+λ2−9= 16−10λ+λ2.

This quantity must be equal to zero. In other words,

λ2−10λ+16= 0.

Factorize this and we get,

(λ−8)(λ−2)= 0.

Thusλ= 8,λ= 2

are the 2 eigenvalues.

Page 19: Finding eigenvalues, char poly

Example 2, section 5.2Let us look at the determinant of the new matrix∣∣∣∣ 5−λ 3

3 5−λ∣∣∣∣= (5−λ)2−9.

Simplify this quantity. Some high school algebra will be handy.

(5−λ)2 = 25−10λ+λ2.

(5−λ)2−9= 25−10λ+λ2−9= 16−10λ+λ2.

This quantity must be equal to zero. In other words,

λ2−10λ+16= 0.

Factorize this and we get,

(λ−8)(λ−2)= 0.

Thusλ= 8,λ= 2

are the 2 eigenvalues.

Page 20: Finding eigenvalues, char poly

Example 2, section 5.2Let us look at the determinant of the new matrix∣∣∣∣ 5−λ 3

3 5−λ∣∣∣∣= (5−λ)2−9.

Simplify this quantity. Some high school algebra will be handy.

(5−λ)2 = 25−10λ+λ2.

(5−λ)2−9= 25−10λ+λ2−9= 16−10λ+λ2.

This quantity must be equal to zero. In other words,

λ2−10λ+16= 0.

Factorize this and we get,

(λ−8)(λ−2)= 0.

Thusλ= 8,λ= 2

are the 2 eigenvalues.

Page 21: Finding eigenvalues, char poly

Example 2, section 5.2Let us look at the determinant of the new matrix∣∣∣∣ 5−λ 3

3 5−λ∣∣∣∣= (5−λ)2−9.

Simplify this quantity. Some high school algebra will be handy.

(5−λ)2 = 25−10λ+λ2.

(5−λ)2−9= 25−10λ+λ2−9= 16−10λ+λ2.

This quantity must be equal to zero. In other words,

λ2−10λ+16= 0.

Factorize this and we get,

(λ−8)(λ−2)= 0.

Thusλ= 8,λ= 2

are the 2 eigenvalues.

Page 22: Finding eigenvalues, char poly

Example 2, section 5.2Let us look at the determinant of the new matrix∣∣∣∣ 5−λ 3

3 5−λ∣∣∣∣= (5−λ)2−9.

Simplify this quantity. Some high school algebra will be handy.

(5−λ)2 = 25−10λ+λ2.

(5−λ)2−9= 25−10λ+λ2−9= 16−10λ+λ2.

This quantity must be equal to zero. In other words,

λ2−10λ+16= 0.

Factorize this and we get,

(λ−8)(λ−2)= 0.

Thusλ= 8,λ= 2

are the 2 eigenvalues.

Page 23: Finding eigenvalues, char poly

Example 2, section 5.2Let us look at the determinant of the new matrix∣∣∣∣ 5−λ 3

3 5−λ∣∣∣∣= (5−λ)2−9.

Simplify this quantity. Some high school algebra will be handy.

(5−λ)2 = 25−10λ+λ2.

(5−λ)2−9= 25−10λ+λ2−9= 16−10λ+λ2.

This quantity must be equal to zero. In other words,

λ2−10λ+16= 0.

Factorize this and we get,

(λ−8)(λ−2)= 0.

Thusλ= 8,λ= 2

are the 2 eigenvalues.

Page 24: Finding eigenvalues, char poly

Comments

1. The equation det(A−λI )= 0 is called the characteristicequation of A.

2. The polynomial involving λ you get after computing thedeterminant (and simplifying) in step 1 is called thecharacteristic polynomial of A.

3. Thus the characteristic polynomial of A is a quadratic equationif A is a 2×2 matrix, a cubic equation if A is a 3×3 matrix etc.

4. The characteristic polynomial may not be nicely factorizable inall cases. In that case you may need your high schoolquadratic formula.

Page 25: Finding eigenvalues, char poly

Comments

1. The equation det(A−λI )= 0 is called the characteristicequation of A.

2. The polynomial involving λ you get after computing thedeterminant (and simplifying) in step 1 is called thecharacteristic polynomial of A.

3. Thus the characteristic polynomial of A is a quadratic equationif A is a 2×2 matrix, a cubic equation if A is a 3×3 matrix etc.

4. The characteristic polynomial may not be nicely factorizable inall cases. In that case you may need your high schoolquadratic formula.

Page 26: Finding eigenvalues, char poly

Comments

1. The equation det(A−λI )= 0 is called the characteristicequation of A.

2. The polynomial involving λ you get after computing thedeterminant (and simplifying) in step 1 is called thecharacteristic polynomial of A.

3. Thus the characteristic polynomial of A is a quadratic equationif A is a 2×2 matrix, a cubic equation if A is a 3×3 matrix etc.

4. The characteristic polynomial may not be nicely factorizable inall cases. In that case you may need your high schoolquadratic formula.

Page 27: Finding eigenvalues, char poly

Comments

1. The equation det(A−λI )= 0 is called the characteristicequation of A.

2. The polynomial involving λ you get after computing thedeterminant (and simplifying) in step 1 is called thecharacteristic polynomial of A.

3. Thus the characteristic polynomial of A is a quadratic equationif A is a 2×2 matrix, a cubic equation if A is a 3×3 matrix etc.

4. The characteristic polynomial may not be nicely factorizable inall cases. In that case you may need your high schoolquadratic formula.

Page 28: Finding eigenvalues, char poly

Back to High School

If you have a quadratic equation

ax2+bx +c = 0,

the 2 roots (values of x that solve the above equation) are given by

−b+pb2−4ac

2a

and−b−

pb2−4ac

2a

This works for any quadratic equation. If you cannot �gure out thefactorization immediately, this is a safe option. (provided you won'tmake mistakes of course).

Page 29: Finding eigenvalues, char poly

Back to High School

If you have a quadratic equation

ax2+bx +c = 0,

the 2 roots (values of x that solve the above equation) are given by

−b+pb2−4ac

2a

and−b−

pb2−4ac

2a

This works for any quadratic equation. If you cannot �gure out thefactorization immediately, this is a safe option. (provided you won'tmake mistakes of course).

Page 30: Finding eigenvalues, char poly

Trace of a Matrix

De�nition

Trace of any square matrix A is the sum of the diagonal elementsof A. It is denoted by tr A.

Why is the trace useful? The trace of any square matrix is equal tothe sum of the eigenvalues of A (irrespective of the size of A).Thus, it is a good check to your eigenvalue calculations.

The product of the eigenvalues of A = detA.

Page 31: Finding eigenvalues, char poly

Trace of a Matrix

De�nition

Trace of any square matrix A is the sum of the diagonal elementsof A. It is denoted by tr A.

Why is the trace useful? The trace of any square matrix is equal tothe sum of the eigenvalues of A (irrespective of the size of A).Thus, it is a good check to your eigenvalue calculations.

The product of the eigenvalues of A = detA.

Page 32: Finding eigenvalues, char poly

Trace of a Matrix

De�nition

Trace of any square matrix A is the sum of the diagonal elementsof A. It is denoted by tr A.

Why is the trace useful? The trace of any square matrix is equal tothe sum of the eigenvalues of A (irrespective of the size of A).Thus, it is a good check to your eigenvalue calculations.

The product of the eigenvalues of A = detA.

Page 33: Finding eigenvalues, char poly

How many eigenvalues?

A quadratic equation has exactly 2 roots, if complex roots areincluded. (could be the same root repeated)

A cubic equation has exactly 3 roots, if complex roots are included(one or more roots could be repeated)

In general, a square matrix of size n×n will have exactly n

eigenvalues.

Page 34: Finding eigenvalues, char poly

How many eigenvalues?

A quadratic equation has exactly 2 roots, if complex roots areincluded. (could be the same root repeated)

A cubic equation has exactly 3 roots, if complex roots are included(one or more roots could be repeated)

In general, a square matrix of size n×n will have exactly n

eigenvalues.

Page 35: Finding eigenvalues, char poly

How many eigenvalues?

A quadratic equation has exactly 2 roots, if complex roots areincluded. (could be the same root repeated)

A cubic equation has exactly 3 roots, if complex roots are included(one or more roots could be repeated)

In general, a square matrix of size n×n will have exactly n

eigenvalues.

Page 36: Finding eigenvalues, char poly

Example

Find the characteristic equation, characteristic polynomial and theeigenvalues of the matrix

A=

5 3 7 90 5 9 10 0 2 80 0 0 2

.

Observe that this is a triangular matrix (and hence convenient towork with). The characteristic equation is found by solving theequation det(A−λI )= 0 which is∣∣∣∣∣∣∣∣∣

5−λ 3 7 90 5−λ 9 10 0 2−λ 80 0 0 2−λ

∣∣∣∣∣∣∣∣∣= 0.

Page 37: Finding eigenvalues, char poly

Example

Find the characteristic equation, characteristic polynomial and theeigenvalues of the matrix

A=

5 3 7 90 5 9 10 0 2 80 0 0 2

.

Observe that this is a triangular matrix (and hence convenient towork with). The characteristic equation is found by solving theequation det(A−λI )= 0 which is

∣∣∣∣∣∣∣∣∣5−λ 3 7 90 5−λ 9 10 0 2−λ 80 0 0 2−λ

∣∣∣∣∣∣∣∣∣= 0.

Page 38: Finding eigenvalues, char poly

Example

Find the characteristic equation, characteristic polynomial and theeigenvalues of the matrix

A=

5 3 7 90 5 9 10 0 2 80 0 0 2

.

Observe that this is a triangular matrix (and hence convenient towork with). The characteristic equation is found by solving theequation det(A−λI )= 0 which is∣∣∣∣∣∣∣∣∣

5−λ 3 7 90 5−λ 9 10 0 2−λ 80 0 0 2−λ

∣∣∣∣∣∣∣∣∣= 0.

Page 39: Finding eigenvalues, char poly

Example Contd.

Since A−λI is a triangular matrix, we have

(5−λ)2︸ ︷︷ ︸(2−λ)2︸ ︷︷ ︸= 0

This is the characteristic equation. To �nd the char. polynomial,we have to expand both terms

(25−10λ+λ2)︸ ︷︷ ︸(4−4λ+λ2)︸ ︷︷ ︸=⇒ 100−100λ︸ ︷︷ ︸+︷ ︸︸ ︷

25λ2−40λ︸︷︷︸+︷ ︸︸ ︷40λ2−10λ3+

︷︸︸︷4λ2 −4λ3+λ4

=⇒ 100−140λ︸ ︷︷ ︸+︷ ︸︸ ︷69λ2−14λ3+λ4

Page 40: Finding eigenvalues, char poly

Example Contd.

Since A−λI is a triangular matrix, we have

(5−λ)2︸ ︷︷ ︸(2−λ)2︸ ︷︷ ︸= 0

This is the characteristic equation. To �nd the char. polynomial,we have to expand both terms

(25−10λ+λ2)︸ ︷︷ ︸(4−4λ+λ2)︸ ︷︷ ︸

=⇒ 100−100λ︸ ︷︷ ︸+︷ ︸︸ ︷25λ2−40λ︸︷︷︸+︷ ︸︸ ︷

40λ2−10λ3+︷︸︸︷4λ2 −4λ3+λ4

=⇒ 100−140λ︸ ︷︷ ︸+︷ ︸︸ ︷69λ2−14λ3+λ4

Page 41: Finding eigenvalues, char poly

Example Contd.

Since A−λI is a triangular matrix, we have

(5−λ)2︸ ︷︷ ︸(2−λ)2︸ ︷︷ ︸= 0

This is the characteristic equation. To �nd the char. polynomial,we have to expand both terms

(25−10λ+λ2)︸ ︷︷ ︸(4−4λ+λ2)︸ ︷︷ ︸=⇒ 100−100λ︸ ︷︷ ︸+︷ ︸︸ ︷

25λ2−40λ︸︷︷︸+︷ ︸︸ ︷40λ2−10λ3+

︷︸︸︷4λ2 −4λ3+λ4

=⇒ 100−140λ︸ ︷︷ ︸+︷ ︸︸ ︷69λ2−14λ3+λ4

Page 42: Finding eigenvalues, char poly

Example Contd.

Since A−λI is a triangular matrix, we have

(5−λ)2︸ ︷︷ ︸(2−λ)2︸ ︷︷ ︸= 0

This is the characteristic equation. To �nd the char. polynomial,we have to expand both terms

(25−10λ+λ2)︸ ︷︷ ︸(4−4λ+λ2)︸ ︷︷ ︸=⇒ 100−100λ︸ ︷︷ ︸+︷ ︸︸ ︷

25λ2−40λ︸︷︷︸+︷ ︸︸ ︷40λ2−10λ3+

︷︸︸︷4λ2 −4λ3+λ4

=⇒ 100−140λ︸ ︷︷ ︸+︷ ︸︸ ︷69λ2−14λ3+λ4

Page 43: Finding eigenvalues, char poly

Example Contd.

What about the eigenvalues of A? Since A is triangular, thediagonal entries are its eigenvalues.

Here the eigenvalues are 5, 5, 2 and 2.

We say that 5 has multiplicity 2 and 2 has multiplicity 2. In otherwords, we have repeated eigenvalues.

Page 44: Finding eigenvalues, char poly

Example Contd.

What about the eigenvalues of A? Since A is triangular, thediagonal entries are its eigenvalues.

Here the eigenvalues are 5, 5, 2 and 2.

We say that 5 has multiplicity 2 and 2 has multiplicity 2. In otherwords, we have repeated eigenvalues.

Page 45: Finding eigenvalues, char poly

Example Contd.

What about the eigenvalues of A? Since A is triangular, thediagonal entries are its eigenvalues.

Here the eigenvalues are 5, 5, 2 and 2.

We say that 5 has multiplicity 2 and 2 has multiplicity 2. In otherwords, we have repeated eigenvalues.

Page 46: Finding eigenvalues, char poly

Example

The characteristic polynomial of a 5×5 matrix is

λ5−4λ4−12λ3.

Find the eigenvalues and their multiplicities.

Solution: This polynomial (in spite of being of degree 5) can befactorized easily as follows.

λ3(λ2−4λ−12)= λ3(λ−6)(λ+2).

Thus we have λ3 = 0=⇒ λ= 0, λ= 6 and λ=−2.

Zero has multiplicity 3 (repeated roots), others have multiplicity 1each.

Page 47: Finding eigenvalues, char poly

Example

The characteristic polynomial of a 5×5 matrix is

λ5−4λ4−12λ3.

Find the eigenvalues and their multiplicities.

Solution: This polynomial (in spite of being of degree 5) can befactorized easily as follows.

λ3(λ2−4λ−12)= λ3(λ−6)(λ+2).

Thus we have λ3 = 0=⇒ λ= 0, λ= 6 and λ=−2.

Zero has multiplicity 3 (repeated roots), others have multiplicity 1each.

Page 48: Finding eigenvalues, char poly

Example

The characteristic polynomial of a 5×5 matrix is

λ5−4λ4−12λ3.

Find the eigenvalues and their multiplicities.

Solution: This polynomial (in spite of being of degree 5) can befactorized easily as follows.

λ3(λ2−4λ−12)= λ3(λ−6)(λ+2).

Thus we have λ3 = 0=⇒ λ= 0, λ= 6 and λ=−2.

Zero has multiplicity 3 (repeated roots), others have multiplicity 1each.

Page 49: Finding eigenvalues, char poly

Example

The characteristic polynomial of a 5×5 matrix is

λ5−4λ4−12λ3.

Find the eigenvalues and their multiplicities.

Solution: This polynomial (in spite of being of degree 5) can befactorized easily as follows.

λ3(λ2−4λ−12)= λ3(λ−6)(λ+2).

Thus we have λ3 = 0=⇒ λ= 0, λ= 6 and λ=−2.

Zero has multiplicity 3 (repeated roots), others have multiplicity 1each.

Page 50: Finding eigenvalues, char poly

Example 4, section 5.2

Find the char. polynomial and eigenvalues of the matrix[5 −3−4 3

].

Solution: The characteristic equation is found by solving theequation det(A−λI )= 0 which is∣∣∣∣ 5−λ −3

−4 3−λ∣∣∣∣= 0.

(5−λ)(3−λ)−12= 0

15−8λ+λ2−12= 0

3−8λ+λ2 = 0=⇒ λ2−8λ+3= 0

λ2−8λ+3 is the char.polynomial.

Page 51: Finding eigenvalues, char poly

Example 4, section 5.2

Find the char. polynomial and eigenvalues of the matrix[5 −3−4 3

].

Solution: The characteristic equation is found by solving theequation det(A−λI )= 0 which is∣∣∣∣ 5−λ −3

−4 3−λ∣∣∣∣= 0.

(5−λ)(3−λ)−12= 0

15−8λ+λ2−12= 0

3−8λ+λ2 = 0=⇒ λ2−8λ+3= 0

λ2−8λ+3 is the char.polynomial.

Page 52: Finding eigenvalues, char poly

Example 4, section 5.2

Find the char. polynomial and eigenvalues of the matrix[5 −3−4 3

].

Solution: The characteristic equation is found by solving theequation det(A−λI )= 0 which is∣∣∣∣ 5−λ −3

−4 3−λ∣∣∣∣= 0.

(5−λ)(3−λ)−12= 0

15−8λ+λ2−12= 0

3−8λ+λ2 = 0=⇒ λ2−8λ+3= 0

λ2−8λ+3 is the char.polynomial.

Page 53: Finding eigenvalues, char poly

Example 4, section 5.2

Find the char. polynomial and eigenvalues of the matrix[5 −3−4 3

].

Solution: The characteristic equation is found by solving theequation det(A−λI )= 0 which is∣∣∣∣ 5−λ −3

−4 3−λ∣∣∣∣= 0.

(5−λ)(3−λ)−12= 0

15−8λ+λ2−12= 0

3−8λ+λ2 = 0=⇒ λ2−8λ+3= 0

λ2−8λ+3 is the char.polynomial.

Page 54: Finding eigenvalues, char poly

Example 4, section 5.2

Find the char. polynomial and eigenvalues of the matrix[5 −3−4 3

].

Solution: The characteristic equation is found by solving theequation det(A−λI )= 0 which is∣∣∣∣ 5−λ −3

−4 3−λ∣∣∣∣= 0.

(5−λ)(3−λ)−12= 0

15−8λ+λ2−12= 0

3−8λ+λ2 = 0=⇒ λ2−8λ+3= 0

λ2−8λ+3 is the char.polynomial.

Page 55: Finding eigenvalues, char poly

Example 4, section 5.2

Use the quadratic formula (factorization will not work here)

λ=8±

√82−4(1)(3)

2(1)= 8±p

52

2

Since 52=4× 13 we have

λ= 8±p4.13

2= 8±2

p13

2= 4±

p13

The sum of these eigenvalues is

4+p13+4−

p13= 8

and the trace of the given matrix is 5+3=8.

Page 56: Finding eigenvalues, char poly

Example 4, section 5.2

Use the quadratic formula (factorization will not work here)

λ=8±

√82−4(1)(3)

2(1)= 8±p

52

2

Since 52=4× 13 we have

λ= 8±p4.13

2= 8±2

p13

2= 4±

p13

The sum of these eigenvalues is

4+p13+4−

p13= 8

and the trace of the given matrix is 5+3=8.

Page 57: Finding eigenvalues, char poly

Example 4, section 5.2

Use the quadratic formula (factorization will not work here)

λ=8±

√82−4(1)(3)

2(1)= 8±p

52

2

Since 52=4× 13 we have

λ= 8±p4.13

2= 8±2

p13

2= 4±

p13

The sum of these eigenvalues is

4+p13+4−

p13= 8

and the trace of the given matrix is 5+3=8.

Page 58: Finding eigenvalues, char poly

Example 8, section 5.2Find the char. polynomial and eigenvalues of the matrix[

7 −22 3

].

Solution: The characteristic equation is found by solving theequation det(A−λI )= 0 which is∣∣∣∣ 7−λ −2

2 3−λ∣∣∣∣= 0.

(7−λ)(3−λ)+4= 0

21−10λ+λ2+4= 0

25−10λ+λ2 = 0=⇒ λ2−10λ+25= 0

λ2−10λ+25 is the char.polynomial. What about eigenvalues? Tryit yourself!!!!

Page 59: Finding eigenvalues, char poly

Example 8, section 5.2Find the char. polynomial and eigenvalues of the matrix[

7 −22 3

].

Solution: The characteristic equation is found by solving theequation det(A−λI )= 0 which is∣∣∣∣ 7−λ −2

2 3−λ∣∣∣∣= 0.

(7−λ)(3−λ)+4= 0

21−10λ+λ2+4= 0

25−10λ+λ2 = 0=⇒ λ2−10λ+25= 0

λ2−10λ+25 is the char.polynomial. What about eigenvalues? Tryit yourself!!!!

Page 60: Finding eigenvalues, char poly

Example 8, section 5.2Find the char. polynomial and eigenvalues of the matrix[

7 −22 3

].

Solution: The characteristic equation is found by solving theequation det(A−λI )= 0 which is∣∣∣∣ 7−λ −2

2 3−λ∣∣∣∣= 0.

(7−λ)(3−λ)+4= 0

21−10λ+λ2+4= 0

25−10λ+λ2 = 0=⇒ λ2−10λ+25= 0

λ2−10λ+25 is the char.polynomial. What about eigenvalues? Tryit yourself!!!!

Page 61: Finding eigenvalues, char poly

Example 8, section 5.2Find the char. polynomial and eigenvalues of the matrix[

7 −22 3

].

Solution: The characteristic equation is found by solving theequation det(A−λI )= 0 which is∣∣∣∣ 7−λ −2

2 3−λ∣∣∣∣= 0.

(7−λ)(3−λ)+4= 0

21−10λ+λ2+4= 0

25−10λ+λ2 = 0=⇒ λ2−10λ+25= 0

λ2−10λ+25 is the char.polynomial. What about eigenvalues? Tryit yourself!!!!

Page 62: Finding eigenvalues, char poly

Example 10, section 5.2

Find the char. polynomial of the matrix 0 3 13 0 21 2 0

.

For a 3×3 matrix, �nding the char equation (and the charpolynomial) is more involved.You could do a cofactor expansion or the Sarru's mnemonic rule(where you repeat the �rst 2 rows and strike through) of A−λI .

NEVER do a reduction to echeleon form. The eigenvalues of theechelon form are totally di�erent from that of the original matrix.

Page 63: Finding eigenvalues, char poly

Example 10, section 5.2

Find the char. polynomial of the matrix 0 3 13 0 21 2 0

.

For a 3×3 matrix, �nding the char equation (and the charpolynomial) is more involved.You could do a cofactor expansion or the Sarru's mnemonic rule(where you repeat the �rst 2 rows and strike through) of A−λI .

NEVER do a reduction to echeleon form. The eigenvalues of theechelon form are totally di�erent from that of the original matrix.

Page 64: Finding eigenvalues, char poly

Example 10, section 5.2

Find the char. polynomial of the matrix 0 3 13 0 21 2 0

.

For a 3×3 matrix, �nding the char equation (and the charpolynomial) is more involved.You could do a cofactor expansion or the Sarru's mnemonic rule(where you repeat the �rst 2 rows and strike through) of A−λI .

NEVER do a reduction to echeleon form. The eigenvalues of theechelon form are totally di�erent from that of the original matrix.

Page 65: Finding eigenvalues, char poly

Example 10, section 5.2

Solution: The characteristic equation is found by solving theequation det(A−λI )= 0 which is∣∣∣∣∣∣

0−λ 3 13 0−λ 21 2 0−λ

∣∣∣∣∣∣= 0.

−λ∣∣∣∣ −λ 2

2 −λ∣∣∣∣︸ ︷︷ ︸

λ2−4

−3∣∣∣∣ 3 21 −λ

∣∣∣∣︸ ︷︷ ︸−3λ−2

+1∣∣∣∣ 3 −λ1 2

∣∣∣∣︸ ︷︷ ︸6+λ

−λ(λ2−4)−3(−3λ−2)+6+λ= 0

−λ3+4λ+9λ+6+6+λ= 0=⇒−λ3+14λ+12= 0

−λ3+14λ+12 is the char.polynomial.

Page 66: Finding eigenvalues, char poly

Example 10, section 5.2

Solution: The characteristic equation is found by solving theequation det(A−λI )= 0 which is∣∣∣∣∣∣

0−λ 3 13 0−λ 21 2 0−λ

∣∣∣∣∣∣= 0.

−λ∣∣∣∣ −λ 2

2 −λ∣∣∣∣︸ ︷︷ ︸

λ2−4

−3∣∣∣∣ 3 21 −λ

∣∣∣∣︸ ︷︷ ︸−3λ−2

+1∣∣∣∣ 3 −λ1 2

∣∣∣∣︸ ︷︷ ︸6+λ

−λ(λ2−4)−3(−3λ−2)+6+λ= 0

−λ3+4λ+9λ+6+6+λ= 0=⇒−λ3+14λ+12= 0

−λ3+14λ+12 is the char.polynomial.

Page 67: Finding eigenvalues, char poly

Example 10, section 5.2

Solution: The characteristic equation is found by solving theequation det(A−λI )= 0 which is∣∣∣∣∣∣

0−λ 3 13 0−λ 21 2 0−λ

∣∣∣∣∣∣= 0.

−λ∣∣∣∣ −λ 2

2 −λ∣∣∣∣︸ ︷︷ ︸

λ2−4

−3∣∣∣∣ 3 21 −λ

∣∣∣∣︸ ︷︷ ︸−3λ−2

+1∣∣∣∣ 3 −λ1 2

∣∣∣∣︸ ︷︷ ︸6+λ

−λ(λ2−4)−3(−3λ−2)+6+λ= 0

−λ3+4λ+9λ+6+6+λ= 0=⇒−λ3+14λ+12= 0

−λ3+14λ+12 is the char.polynomial.

Page 68: Finding eigenvalues, char poly

Example 10, section 5.2

Solution: The characteristic equation is found by solving theequation det(A−λI )= 0 which is∣∣∣∣∣∣

0−λ 3 13 0−λ 21 2 0−λ

∣∣∣∣∣∣= 0.

−λ∣∣∣∣ −λ 2

2 −λ∣∣∣∣︸ ︷︷ ︸

λ2−4

−3∣∣∣∣ 3 21 −λ

∣∣∣∣︸ ︷︷ ︸−3λ−2

+1∣∣∣∣ 3 −λ1 2

∣∣∣∣︸ ︷︷ ︸6+λ

−λ(λ2−4)−3(−3λ−2)+6+λ= 0

−λ3+4λ+9λ+6+6+λ= 0=⇒−λ3+14λ+12= 0

−λ3+14λ+12 is the char.polynomial.

Page 69: Finding eigenvalues, char poly

Example 14, section 5.2Find the char. polynomial of the matrix 5 −2 3

0 1 06 7 −2

.

Solution: The characteristic equation is found by solving theequation det(A−λI )= 0 which is∣∣∣∣∣∣

5−λ −2 30 1−λ 06 7 −2−λ

∣∣∣∣∣∣= 0.

Expand along second row, we get

(1−λ)

∣∣∣∣ 5−λ 36 −2−λ

∣∣∣∣︸ ︷︷ ︸(5−λ)(−2−λ)−18=−10−3λ+λ2−18=λ2−3λ−28

= 0

Page 70: Finding eigenvalues, char poly

Example 14, section 5.2Find the char. polynomial of the matrix 5 −2 3

0 1 06 7 −2

.

Solution: The characteristic equation is found by solving theequation det(A−λI )= 0 which is∣∣∣∣∣∣

5−λ −2 30 1−λ 06 7 −2−λ

∣∣∣∣∣∣= 0.

Expand along second row, we get

(1−λ)

∣∣∣∣ 5−λ 36 −2−λ

∣∣∣∣︸ ︷︷ ︸(5−λ)(−2−λ)−18=−10−3λ+λ2−18=λ2−3λ−28

= 0

Page 71: Finding eigenvalues, char poly

Example 14, section 5.2

(1−λ)(λ2−3λ−28)= 0

λ2−3λ−28−λ3+3λ2+28λ= 0

4λ2+25λ−28−λ3 = 0

The char polynomial is thus 4λ2+25λ−28−λ3.

Page 72: Finding eigenvalues, char poly

Example 14, section 5.2

(1−λ)(λ2−3λ−28)= 0

λ2−3λ−28−λ3+3λ2+28λ= 0

4λ2+25λ−28−λ3 = 0

The char polynomial is thus 4λ2+25λ−28−λ3.

Page 73: Finding eigenvalues, char poly

Example 14, section 5.2

(1−λ)(λ2−3λ−28)= 0

λ2−3λ−28−λ3+3λ2+28λ= 0

4λ2+25λ−28−λ3 = 0

The char polynomial is thus 4λ2+25λ−28−λ3.

Page 74: Finding eigenvalues, char poly

Similarity

De�nition

Let A and B be 2 square matrices. We say that A is similar to B ifwe can �nd an invertible matrix P such that

P−1AP =B

Theorem

If n×n matrices A and B are similar, they have the same char

polynomial and hence the same eigenvalues (with same

multiplicities).