Are the columns space and row space same for idempotent matrix?

In summary: The row space of a matrix is the vector space spanned by the row vectors of the matrix and the column space of a matrix is the vector space spanned by the column vectors of the matrixThe row space of a matrix is the vector space spanned by the row vectors of the matrix and the column space of a matrix is the vector space spanned by the column vectors of the matrixThe row space of a matrix is the vector space spanned by the row vectors of the matrix and the column space of a matrix is the vector space spanned by the column vectors of the matrixThe row space of a matrix is the vector space spanned by the row vectors of the matrix and the column space of a matrix is the same as the
  • #1
arpon
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Suppose, ##A## is an idempotent matrix, i.e, ##A^2=A##.
For idempotent matrix, the eigenvalues are ##1## and ##0##.
Here, the eigenspace corresponding to eigenvalue ##1## is the column space, and the eigenspace corresponding to eigenvalue ##0## is the null space.
But eigenspaces for distinct eigenvalues of a matrix have intersection ##\{0\}##.
So, null space and column space are complementary for idempotent matrix. That means the row space and column space are the same for idempotent matrix.
Is this argument correct?
 
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  • #2
There's a contradiction in your conclusion. If you have an eigenvalue ##0##, then there is a vector ##v \neq 0## with ##A.v=0##, i.e. the eigenspace of eigenvalue ##0## cannot be ##\{0\}##.
 
  • #3
fresh_42 said:
There's a contradiction in your conclusion. If you have an eigenvalue ##0##, then there is a vector ##v \neq 0## with ##A.v=0##, i.e. the eigenspace of eigenvalue ##0## cannot be ##\{0\}##.
I have not said that the eigenspace of eigenvalue ##0## is ##\{0\}##.
 
  • #4
Yep, I translated it wrongly. I'm used to the term kernel for what you call nullspace. Sorry.

Before I also misinterpret column or row spaces I simply ask: What about ##\begin{bmatrix}1 & 0 \\ 1 & 0 \end{bmatrix}##?
 
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  • #5
fresh_42 said:
Yep, I translated it wrongly. I'm used to the term kernel for what you call nullspace. Sorry.

Before I also misinterpret column or row spaces I simply ask: What about ##\begin{bmatrix}1 & 0 \\ 1 & 0 \end{bmatrix}##?
The column space and row space are not the same in the example. But I cannot figure out what was wrong in my argument.
The row space of a matrix is the vector space spanned by the row vectors of the matrix and the column space of a matrix is the vector space spanned by the column vectors of the matrix
 
  • #6
You must not handle subspaces like sets. The error is the usage of "complementary". As in the example you can have ##V=V_1 \oplus V_2## and ##V=V_1 \oplus V_3## without ##V_2## and ##V_3## even being contained in one another. Not to speak of being equal. Think of two lines through the origin. Together with, say the ##x-##axis each of them span the plane, although they only have ##0## in common.

You may conclude that ##V/V_1 \cong V_2 \cong V_3## are isomorphic, but not equal. To conclude equality, one always has to show a real inclusion ##V_2 \subseteq V_3##, too, when dealing with vector spaces.
 
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  • #7
you seem to have argued that because two subspaces are complementary to the same subspace that they are equal. but "complementary" (in the algebraic sense) simply means as you say, their intersection is zero (and their dimensions are complementary). Can you give an example of two different subspaces of the x,y plane that both intersect the x-axis at only the origin? (it would be different if both subspaces were orthogonal complements of the same subspace.)
 
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1. What is an idempotent matrix?

An idempotent matrix is a square matrix that, when multiplied by itself, results in the same matrix. This means that the matrix is unchanged by repeated multiplication.

2. How can you determine if a matrix is idempotent?

A matrix is idempotent if and only if it satisfies the equation A^2 = A, where A is the matrix and ^2 represents matrix multiplication.

3. Are the columns space and row space the same for an idempotent matrix?

Yes, the columns space and row space are the same for an idempotent matrix. This is because when a matrix is idempotent, its columns and rows are linearly dependent on each other, resulting in the same vector space.

4. Can an idempotent matrix have non-zero eigenvalues?

Yes, an idempotent matrix can have non-zero eigenvalues. In fact, all idempotent matrices have at least one eigenvalue of either 0 or 1.

5. What are some real-world applications of idempotent matrices?

Idempotent matrices have many applications in various fields such as engineering, physics, and computer science. One example is in control systems, where idempotent matrices are used to model the behavior of systems that reach a steady state. They are also used in cryptography for generating and encrypting data.

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