About orthogonality and nullspaces

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SUMMARY

The discussion focuses on the relationship between the nullspace of the transpose of matrix A (A^T) and the column space of matrix A. It is established that the nullspace of A^T consists solely of the zero vector, indicating that it is orthogonal to every vector in the column space of A. The example provided demonstrates that the vectors (1,5), (3,2), and (4,7), which form the columns of A, are orthogonal to the nullspace of A^T, reinforcing the theorem that the nullspace of A^T is orthogonal to the column space of A.

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Hi:
I see an example about nullspace and orthogonality, the example is following:

$$Ax=\begin{bmatrix} 1 & 3 &4\\ 5 & 2& 7 \end{bmatrix} \times \left[ \begin{array}{c} 1 \\ 1\\-1 \end{array} \right]=\begin{bmatrix} 0\\0\end{bmatrix}$$

The conclusion says the nullspace of [itex]A^T[/itex] is only the zero vector(orthogonal to every vector). I don't know why the columns of A and nullspace of [itex]A^T[/itex] are orthogonal spaces.
I know nullspace is the solution of Ax=0; but in this theorem, why columns of A is related
to nullsapce of [itex]A^T[/itex].
Thanks.
 
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Notice the null space of A^T is orthogonal to (1,5), (3,2) and (4,7). So it is orthogonal to the space spanned by the vectors, which is the column space of A.
 
[tex]A^T= \begin{bmatrix}1 & 5 \\ 3 & 2 \\ 4 & 7\end{bmatrix}[/tex]
so that the condition that a vector be in the null space of [itex]A^T[/itex] is
[tex]\begin{bmatrix}1 & 5 \\ 3 & 2 \\ 4 & 7\end{bmatrix}\begin{bmatrix}x \\ y \end{bmatrix}= \begin{bmatrix}0 \\ 0 \\ 0 \end{bmatrix}[/tex]
which is the same as
[tex]\begin{bmatrix}x+ 5y \\ 3x+ 2y \\ 4x+ 7y\end{bmatrix}= \begin{bmatrix}0 \\ 0 \\ 0 \end{bmatrix}[/tex]
Do you see now, how the columns of A, which become the rows of AT, are relevant here?
 

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