The Identity Matrix and Diagonal Matrices - Linear Algebra

Probably the simplest way to see this is true is to take the determinant of the diagonal matrix. We can take the determinant of a diagonal matrix by simply multiplying all of the entries along its main diagonal. Since one of these entries is , then the determinant is , and hence the matrix is not invertible.

The x identity matrix is

For this problem we see that

And so

is a scalar multiple of the identity matrix.

You can verify this directly by proving it, or by multiplying a few examples on your calculator.

is the trace operation. It means to add up the entries along the main diagonal of the matrix. Since has ones along its main diagonal, the trace of is .

Since is a diagonal matrix, we can find it's powers more easily by raising the numbers inside it to the power in question.

We can find the eigenvalues of the identity matrix by finding all values of such that .

Hence we have

So is the only eigenvalue, regardless of the size of the identity matrix.

This is the correct term. Elementary matrices themselves can be used in place of elementary row operations when row reducing other matrices when convenient.

Another way to state this definition is that a square matrix is said to diagonalizable if and only if there exists some invertible matrix and diagonal matrix such that .

An idempotent matrix is one such that . This is satisfied by the identity matrix since the identity matrix times itself is once again the identity matrix.

There is no need to perform any elementary row operations on the identity matrix; it is already in its reduced row echelon form. (There is a leading one in each row, and each column).

A matrix is diagonal if and only if - that is, the element in column , row is equal to zero - for all . The given matrix violates this condition, since and five other elements are equal to nonzero numbers.

A matrix is diagonal if and only if - that is, the element in column , row is equal to zero - for all . The given matrix satisfies this condition, since its only nonzero elements are the first element in Column 1, the second element in Column 2, and so forth.

A matrix is diagonal if and only if - that is, the element in column , row is equal to zero - for all . The given matrix fits this criterion.

is a diagonal matrix - its only nonzero entries are in its main diagonal, which comprises the elements in row , column , for .

The inverse of a such a matrix can be found simply by replacing each element in the main diagonal with its reciprocal. Rewriting the elements in the diagonal matrix as fractions,

,

or

.

Replace each diagonal element with its reciprocal to find :

A diagonal matrix has only zeroes as entries off of its main (upper-left to lower-right) diagonal. has three nonzero entries off this diagonal (Row 1, column 2, for example), so it is not a diagonal matrix.

An matrix is strictly diagonally dominant if, for each , it holds that on Row , the absolute value of the element in Column is greater than the sum of the absolute values of the other elements in that row. Therefore, for to be strictly diagonally dominant, the following must hold:

For Row 1:

or

For Row 2:

or

For Row 3: ,

or

For all three conditions to hold, it is necessary that . This is the correct choice.

is a diagonal matrix, and its dimensions are , so, for some complex and (the problem did not specify that the entries were real),

.

To raise a diagonal matrix to a power, simply raise each nonzero element to that power. It holds that

,

and, consequently, .

Equivalently, both and must be a one-hundredth root of 2, of which there are 100. Therefore, the number of possible matrices for is .

This question does not make sense since there is no such thing as the identity matrix, and it is not possible to take the trace of a matrix that is not square. This question is mostly meant to test your ability to think critically when reading certain mathematics problems.

A matrix is diagonalizable if it can be written as , where is any invertible matrix, and is any diagonal matrix. If is already a diagonal matrix, we can of course write it as . Hence any diagonal matrix is diagonalizable.