Linear Algebra/Exploration/Solutions

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Solutions[edit]

This exercise is recommended for all readers.
Problem 1

Evaluate the determinant of each.

Answer
Problem 2

Evaluate the determinant of each.

Answer
This exercise is recommended for all readers.
Problem 3

Verify that the determinant of an upper-triangular matrix is the product down the diagonal.

Do lower-triangular matrices work the same way?

Answer

For the first, apply the formula in this section, note that any term with a , , or is zero, and simplify. Lower-triangular matrices work the same way.

This exercise is recommended for all readers.
Problem 4

Use the determinant to decide if each is singular or nonsingular.

Answer
  1. Nonsingular, the determinant is .
  2. Nonsingular, the determinant is .
  3. Singular, the determinant is .
Problem 5

Singular or nonsingular? Use the determinant to decide.

Answer
  1. Nonsingular, the determinant is .
  2. Singular, the determinant is .
  3. Singular, the determinant is .
This exercise is recommended for all readers.
Problem 6

Each pair of matrices differ by one row operation. Use this operation to compare with .

Answer
  1. via
  2. via
  3. via
Problem 7

Show this.

Answer

Using the formula for the determinant of a matrix we expand the left side

and by distributing we expand the right side.

Now we can just check that the two are equal. (Remark. This is the case of Vandermonde's determinant which arises in applications).

This exercise is recommended for all readers.
Problem 8

Which real numbers make this matrix singular?

Answer

This equation

has roots and .

Problem 9

Do the Gaussian reduction to check the formula for matrices stated in the preamble to this section.

is nonsingular iff

Answer

We first reduce the matrix to echelon form. To begin, assume that and that .

This step finishes the calculation.

Now assuming that and , the original matrix is nonsingular if and only if the entry above is nonzero. That is, under the assumptions, the original matrix is nonsingular if and only if , as required.

We finish by running down what happens if the assumptions that were taken for convienence in the prior paragraph do not hold. First, if but then we can swap

and conclude that the matrix is nonsingular if and only if either or . The condition " or " is equivalent to the condition "". Multiplying out and using the case assumption that to substitute for gives this.

Since , we have that the matrix is nonsingular if and only if . Therefore, in this and case, the matrix is nonsingular when .

The remaining cases are routine. Do the but case and the and but case by first swapping rows and then going on as above. The , , and case is easy— that matrix is singular since the columns form a linearly dependent set, and the determinant comes out to be zero.

Problem 10

Show that the equation of a line in thru and is expressed by this determinant.

Answer

Figuring the determinant and doing some algebra gives this.

Note that this is the equation of a line (in particular, in contains the familiar expression for the slope), and note that and satisfy it.

This exercise is recommended for all readers.
Problem 11

Many people know this mnemonic for the determinant of a matrix: first repeat the first two columns and then sum the products on the forward diagonals and subtract the products on the backward diagonals. That is, first write

and then calculate this.

  1. Check that this agrees with the formula given in the preamble to this section.
  2. Does it extend to other-sized determinants?
Answer
  1. The comparison with the formula given in the preamble to this section is easy.
  2. While it holds for matrices
    it does not hold for matrices. An example is that this matrix is singular because the second and third rows are equal
    but following the scheme of the mnemonic does not give zero.
Problem 12

The cross product of the vectors

is the vector computed as this determinant.

Note that the first row is composed of vectors, the vectors from the standard basis for . Show that the cross product of two vectors is perpendicular to each vector.

Answer

The determinant is . To check perpendicularity, we check that the dot product with the first vector is zero

and the dot product with the second vector is also zero.

Problem 13

Prove that each statement holds for matrices.

  1. The determinant of a product is the product of the determinants .
  2. If is invertible then the determinant of the inverse is the inverse of the determinant .

Matrices and are similar if there is a nonsingular matrix such that . (This definition is in Chapter Five.) Show that similar matrices have the same determinant.

Answer
  1. Plug and chug: the determinant of the product is this
    while the product of the determinants is this.
    Verification that they are equal is easy.
  2. Use the prior item.

That similar matrices have the same determinant is immediate from the above two: .

This exercise is recommended for all readers.
Problem 14

Prove that the area of this region in the plane

Linalg parallelogram.png

is equal to the value of this determinant.

Compare with this.

Answer

One way is to count these areas

Linalg parallelogram area.png

by taking the area of the entire rectangle and subtracting the area of the upper-left rectangle, the upper-middle triangle, the upper-right triangle, the lower-left triangle, the lower-middle triangle, and the lower-right rectangle . Simplification gives the determinant formula.

This determinant is the negative of the one above; the formula distinguishes whether the second column is counterclockwise from the first.

Problem 15

Prove that for matrices, the determinant of a matrix equals the determinant of its transpose. Does that also hold for matrices?

Answer

The computation for matrices, using the formula quoted in the preamble, is easy. It does also hold for matrices; the computation is routine.

This exercise is recommended for all readers.
Problem 16

Is the determinant function linear — is ?

Answer

No. Recall that constants come out one row at a time.

This contradicts linearity (here we didn't need , i.e., we can take to be the zero matrix).

Problem 17

Show that if is then for any scalar .

Answer

Bring out the 's one row at a time.

Problem 18

Which real numbers make

singular? Explain geometrically.

Answer

There are no real numbers that make the matrix singular because the determinant of the matrix is never , it equals for all . Geometrically, with respect to the standard basis, this matrix represents a rotation of the plane through an angle of . Each such map is one-to-one — for one thing, it is invertible.

? Problem 19

If a third order determinant has elements , , ..., , what is the maximum value it may have? (Haggett & Saunders 1955)

Answer

This is how the answer was given in the cited source. Let be the sum of the three positive terms of the determinant and the sum of the three negative terms. The maximum value of is

The minimum value of consistent with is

Any change in would result in lowering that sum by more than . Therefore the maximum value for the determinant and one form for the determinant is

References[edit]

  • Haggett, Vern (proposer); Saunders, F. W. (solver) (Apr. 1955), "Elementary problem 1135", American Mathematical Monthly (American Mathematical Society) 62 (5): 257