Linear Algebra: The transpose of A equals Inverse A, so

In summary, if the transpose of a matrix A is equal to its inverse, this does not necessarily mean that A is the identity matrix. It simply means that the columns and rows of A are an orthonormal basis. Examples of such matrices include rotation and reflection matrices. This can be seen by considering simple cases and using the equations det(AA^-1)=det(I) and det(A^T)=det(A).
  • #1
jinksys
123
0
If the transpose of A equals the Inverse of A, then det(A)=1.

False. However, I don't follow the logic.

If transA=InverseA, doesn't that mean the matrix is the identity matrix?

The explanation says that det(A)= 1 and -1.
 
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  • #2
jinksys said:
If the transpose of A equals the Inverse of A, then det(A)=1.

False. However, I don't follow the logic.

If transA=InverseA, doesn't that mean the matrix is the identity matrix?

The explanation says that det(A)= 1 and -1.

If the transpose of A is the inverse of A, it does not have to be the identity matrix. All it says is that the columns of A are an orthonormal basis, as are the rows (check this by matrix multiplication).

Examples are rotation matrices, and reflection matrices (try constructing some 2x2 example to be sure).
 
  • #3
Try looking at a simple case. How about 1x1 matrices? There is only one unknown -- write down the equations that define what it means for the transpose to equal the inverse.
 
  • #4
If you start with det(AA^-1)=det(I) and consider that det(A^T)=det(A) you should be able to work this out.
 

FAQ: Linear Algebra: The transpose of A equals Inverse A, so

1. How do you define the transpose of a matrix in linear algebra?

The transpose of a matrix A is a new matrix where the rows and columns of the original matrix are swapped. This means that the first row of A becomes the first column of the transpose, the second row becomes the second column, and so on.

2. What is the purpose of taking the transpose of a matrix?

The transpose of a matrix is useful in many areas of mathematics and science, including linear algebra. It helps to simplify calculations and can also be used to solve systems of equations, find eigenvalues and eigenvectors, and perform other operations on matrices.

3. How is the transpose of a matrix related to the inverse of a matrix?

If a matrix A is invertible, then its inverse is equal to its transpose. This means that if we multiply A by its inverse, we get the identity matrix. Similarly, if we multiply A by its transpose, we also get the identity matrix.

4. Can a matrix have both a transpose and an inverse?

Yes, a matrix can have both a transpose and an inverse. However, not all matrices have both. In order for a matrix to have an inverse, it must be square and have a non-zero determinant. On the other hand, all matrices have a transpose.

5. How can the transpose be used to solve systems of equations?

The transpose of a matrix can be used to solve systems of equations by converting the system into an augmented matrix. Then, by using row operations, we can transform the augmented matrix into its reduced row echelon form, which will give us the solution to the system of equations.

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