Proving disjoint of Kernel and Image of a linear mapping

In summary, the conversation discusses a problem involving a linear transformation $F$ and the intersection of its kernel and image. The solution is provided, with the only unclear step being the fact that $F^2(0) = 0$. This is then clarified by showing that for any linear transformation $F$, $F(\mathbf 0) = \mathbf 0$. This follows from the definition of a linear mapping, where $F(cx) = cF(x)$ and setting $c = 0$ leads to $F(\mathbf 0) = \mathbf 0$.
  • #1
rputra
35
0
I am working on a problem that goes like this:

Show that $Ker (F) \cap I am (F) = \{0\}$ if $F: W \rightarrow W$ is linear and if $F^4 = F.$

I have the solution but there is one step which I need help: (the delineation is mine)

(1) Suppose that there exists $x$, such that $x \in Ker(F) \cap Im(F)$
(2) From $x \in Ker(F)$, we have $F(x) = 0$, by definition of kernel of a mapping
(3) From $x \in Im(F)$, there exists $w \in W$, such that $F(w) = x$
(4) Then we have
$$\begin{align}
F^4(w) &= F^3(F(w))\\
&= F^3(x)\\
&= F^2(F(x))\\
&= F^2(0)\\
&= 0.
\end{align}$$
(5) Since we have $F^4(w) = 0, F^4(w) = F(w)$, and $F(w) = x$, we conclude that $x = 0$. Hence $Ker(F) \cap Im(F) = \{0\}$, as desired.

Here is the one step I did not understand: In the last line of step (4), why is that $F^2(0) = 0$? Any help would be very much appreciated. Thank you for your time in advance.
 
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  • #2
Tarrant said:
I am working on a problem that goes like this:

Show that $Ker (F) \cap I am (F) = \{0\}$ if $F: W \rightarrow W$ is linear and if $F^4 = F.$

I have the solution but there is one step which I need help: (the delineation is mine)

(1) Suppose that there exists $x$, such that $x \in Ker(F) \cap Im(F)$
(2) From $x \in Ker(F)$, we have $F(x) = 0$, by definition of kernel of a mapping
(3) From $x \in Im(F)$, there exists $w \in W$, such that $F(w) = x$
(4) Then we have
$$\begin{align}
F^4(w) &= F^3(F(w))\\
&= F^3(x)\\
&= F^2(F(x))\\
&= F^2(0)\\
&= 0.
\end{align}$$
(5) Since we have $F^4(w) = 0, F^4(w) = F(w)$, and $F(w) = x$, we conclude that $x = 0$. Hence $Ker(F) \cap Im(F) = \{0\}$, as desired.

Here is the one step I did not understand: In the last line of step (4), why is that $F^2(0) = 0$? Any help would be very much appreciated. Thank you for your time in advance.

Hey Tarrant!

For a linear transformation $F$, we have that $F(\mathbf 0)=\mathbf 0$.
Proof
Suppose $F(\mathbf 0)\ne \mathbf 0$, then for any $\mathbf u$ we have that $F(\mathbf 0) = F(0\cdot \mathbf u)=0\cdot F(\mathbf u)=\mathbf 0$. Contradiction. Therefore $F(\mathbf 0)=\mathbf 0$.
 
  • #3
I like Serena said:
Hey Tarrant!

For a linear transformation $F$, we have that $F(\mathbf 0)=\mathbf 0$.
Proof
Suppose $F(\mathbf 0)\ne \mathbf 0$, then for any $\mathbf u$ we have that $F(\mathbf 0) = F(0\cdot \mathbf u)=0\cdot F(\mathbf u)=\mathbf 0$. Contradiction. Therefore $F(\mathbf 0)=\mathbf 0$.

Ok, thanks. It follows the definition of linear mapping: For $c$ an arbitrary real number, $F(cx) = cF(x)$ which leads to $F(0) = 0$ for $c = 0.$ Thank you again for your time.
 

What does it mean for the kernel and image of a linear mapping to be disjoint?

When the kernel and image of a linear mapping are disjoint, it means that there are no vectors that are simultaneously in the kernel and the image of the mapping. In other words, the only vector that is mapped to the zero vector (in the kernel) is the zero vector itself.

Why is proving disjointness of the kernel and image important in linear algebra?

Proving that the kernel and image of a linear mapping are disjoint is important because it allows us to make conclusions about the structure of the mapping. For example, if the kernel and image are disjoint, then the mapping is one-to-one, and we can find a unique solution to linear equations involving the mapping.

How can we prove that the kernel and image of a linear mapping are disjoint?

To prove disjointness of the kernel and image, we can use the definition of the kernel, which is the set of all vectors that are mapped to the zero vector. If we can show that the only vector that is mapped to the zero vector is the zero vector itself, then we have proven that the kernel and image are disjoint.

What are some common techniques for proving disjointness of the kernel and image?

Some common techniques for proving disjointness of the kernel and image include using the definition of the kernel, showing that the kernel only contains the zero vector, using properties of linear transformations, and using contradiction by assuming there is a vector in both the kernel and image.

Are there any applications of proving disjointness of the kernel and image in real-world problems?

Yes, there are many applications of proving disjointness of the kernel and image in real-world problems. For example, in data compression, proving that the kernel and image of a linear mapping are disjoint can help us find a unique solution to a system of linear equations, which can then be used to compress data. In computer graphics, disjointness of the kernel and image can help us identify if a transformation is reversible or not, which is important for creating realistic graphics.

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