Linear dependence of square matrices

In summary, the question is whether it is possible to construct a square matrix A such that the columns of A are linearly dependent, but the columns of the transpose of A are linearly independent. The intuition is that this is not possible, and it has been tried to prove by constructing several matrices with this property, but it always holds that the determinant of the transpose is equal to the determinant of the original matrix. Therefore, the columns and rows of a square matrix cannot have different linear dependency properties.
  • #1
snu
1
0
I am studying the subject of linear dependence right now and had a question on this topic. Is it possible to construct a square matrix A such that the columns of A are linearly dependent, but the columns of the transpose of A are linearly independent? My intuition tells me no, but I'm not sure how I would prove this to be the case in general. I've tried constructing several square matrices that are linearly dependent and taken the transpose and found that to be linearly dependent as well, but I'm not sure if this always holds.
 
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  • #2
All matrices have the property that the determinant of the transpose is equal to the determinant of the original matrix.

From this I would gather that you can't have the property you have described above.

Look at this site:

http://mathworld.wolfram.com/Determinant.html
 
  • #3
It's actually stronger than that: the column rank of any matrix (=dimension of space spanned by its columns) equals the row rank. In particular, for square matrices, if the columns are linearly dependent (column rank is smaller than matrix dimension), so are the rows.
 

Related to Linear dependence of square matrices

1. What is the definition of linear dependence of square matrices?

The linear dependence of square matrices refers to a situation in which one or more matrices can be expressed as a linear combination of other matrices. In other words, the matrices are not independent and can be written in terms of each other.

2. How can I determine if a set of square matrices are linearly dependent?

To determine if a set of square matrices are linearly dependent, you can perform row operations on the matrices and see if any of them can be reduced to a row of zeros. If this is the case, then the matrices are linearly dependent.

3. What are the implications of linear dependence for solving systems of equations?

If a set of square matrices are linearly dependent, then there is no unique solution to the system of equations. This means that the system is either inconsistent (has no solution) or has infinitely many solutions.

4. Can square matrices be linearly dependent even if they have different dimensions?

Yes, square matrices can be linearly dependent even if they have different dimensions. This is because linear dependence is determined by the relationships between the rows and columns of the matrices, not their dimensions.

5. How does linear dependence affect the invertibility of a square matrix?

If a square matrix is linearly dependent, then it is not invertible. This is because an invertible matrix must have linearly independent rows or columns. If the matrix is not invertible, then it cannot be used to solve systems of equations.

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