Linear algebra - adjoint matrix = 0

In summary: Your Name]In summary, to prove that A* = 0 if and only if rank(A) \leq n-2, we need to show that (1) if A* = 0, then rank(A) \leq n-2, and (2) if rank(A) \leq n-2, then A* = 0. This can be done by considering the definition of the adjoint matrix and the rank of a matrix, and using the fact that linearly dependent rows or columns of A correspond to zero minors of A.
  • #1
Kate2010
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Homework Statement



Ok so the question is:

Let A be an nxn matrix where n [tex]\geq[/tex] 2. Show A* = 0 (A* is the adjoint matrix, 0 is the zero matrix) if and only if rank(A)[tex]\leq[/tex] n-2.

Homework Equations



A*:= ((-1)i+jdet(Aij))ij where Aij is the (i,j) minor of A

The Attempt at a Solution



I'm really struggling with answering this.

If rank(A) [tex]\leq[/tex] n-2 then A contains at least 2 dependent rows. Does this automatically make A* = 0?

If A*=0 then (-1)i+jdet(Aij) = 0 for all i and j. So det(Aij) = 0 for all i and j. Having a zero determinant implies dependence?
 
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  • #2


Thank you for your question. Let me provide some clarification and guidance on how to approach this problem.

Firstly, let's define the adjoint matrix, denoted A*, as the transpose of the cofactor matrix of A. This means that A* is an nxn matrix where each element (i,j) is the (j,i) cofactor of A. In other words, A* is obtained by replacing each element of A with its corresponding minor (determinant of the submatrix obtained by removing the row and column containing that element), and then transposing the resulting matrix.

Now, let's look at the statement we need to prove: A* = 0 if and only if rank(A) \leq n-2. This means we need to show two things: (1) if A* = 0, then rank(A) \leq n-2, and (2) if rank(A) \leq n-2, then A* = 0.

For the first part, if A* = 0, then each element of A* must be 0. This means that each (j,i) cofactor of A is 0, which in turn means that each (i,j) minor of A is 0. Recall that the rank of a matrix is the maximum number of linearly independent rows or columns. Since each minor of A is 0, this implies that at least n-2 rows or columns of A are linearly dependent, hence the rank of A is at most n-2.

For the second part, if rank(A) \leq n-2, then at least n-2 rows or columns of A are linearly dependent. This means that there exist two rows or columns of A that are multiples of each other. Without loss of generality, let's say that row i is a multiple of row j. This means that the (i,j) minor of A is 0, since it can be obtained by multiplying row i by the appropriate constant and subtracting it from row j. Since this is true for all i and j, it follows that each element of A* is 0, hence A* = 0.

I hope this helps. Let me know if you have any further questions.
 

1. What is an adjoint matrix?

An adjoint matrix is a square matrix that represents the transpose of the cofactor matrix of another square matrix. It is also known as the adjugate matrix.

2. What does it mean for an adjoint matrix to equal 0?

If the adjoint matrix of a square matrix equals 0, it means that the transpose of its cofactor matrix is also 0. This indicates that the original matrix is singular, meaning it cannot be inverted.

3. What is the relationship between an adjoint matrix and the determinant of a matrix?

The determinant of a matrix can be calculated using the cofactor matrix, which is the transpose of the adjoint matrix. Therefore, the determinant of a matrix is equal to the product of the elements in its adjoint matrix.

4. How is the adjoint matrix used in solving systems of linear equations?

The adjoint matrix is used in the process of finding the inverse of a matrix, which can be used to solve systems of linear equations. The inverse of a matrix is found by multiplying the adjoint matrix by the reciprocal of the determinant of the original matrix.

5. Can an adjoint matrix be calculated for non-square matrices?

No, an adjoint matrix can only be calculated for square matrices. This is because the transpose of a cofactor matrix can only be taken for square matrices.

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