How to Prove the Dimension of Ker $\phi^2$ in a Finite-Dimensional Vector Space?

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In summary, the dimension of Ker $\phi^2$ is the number of linearly independent vectors in the null space of the transformation $\phi^2$ in a finite-dimensional vector space. To prove the dimension of Ker $\phi^2$, you can use the rank-nullity theorem and subtract the dimension of the range of $\phi^2$ from the dimension of the vector space. The dimension of Ker $\phi^2$ cannot exceed the dimension of the vector space, and it is always equal to or less than the dimension of Ker $\phi$. Additionally, the dimension of Ker $\phi^2$ cannot be negative.
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Chris L T521
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Thanks to those who participated in last week's POTW. I'll just say it's no fun unless more people participate!

This week's problem was again proposed by yours truly (it would be nice if more people proposed some problems! (Smile)).

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Problem: Let $\phi:V\rightarrow V$ be a linear operator on a finite-dimensional vector space $V$. Let $k=\text{dim}(\ker \phi)$, and let $d=\text{dim}(V)$. Let $\phi^2:V\otimes V\rightarrow V\otimes V$ be the unique linear operator which satisfies $\phi^2(v_1\otimes v_2) = \phi(v_1)\otimes \phi(v_2)$ for all $v_1, v_2\in V$. Prove that $\text{dim}(\ker\phi^2) = 2dk-k^2$.

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I will provide some hints for this week's problem:

Apply the rank-nullity theorem. Also note that if $V$ and $W$ are finite-dimensional vector spaces and $V\otimes W$ is the tensor product of $V$ with $W$, then $\text{dim}(V\otimes W) = \text{dim}(V)\cdot\text{dim}(W)$.

Remember to read the http://www.mathhelpboards.com/showthread.php?772-Problem-of-the-Week-(POTW)-Procedure-and-Guidelines to find out how to http://www.mathhelpboards.com/forms.php?do=form&fid=2!
 
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The week 5 POTW was correctly answered Sudharaka. Here's my solution:

Proof: By the rank-nullity theory, we know that

\[\text{dim}(\ker\phi) + \text{dim}(\text{Im}\,\phi) = \text{dim}(V).\]Thus, $\text{dim}(\text{Im}\,\phi) = \text{dim}(V) - \text{dim}(\ker\phi) = d-k$. Now, if we consider the map $\phi^2:V\otimes V\rightarrow V\otimes V$, we apply rank-nullity theorem again to obtain that \[\text{dim}(\ker\phi^2) + \text{dim}(\text{Im}\,\phi^2) = \text{dim}(V\otimes V)\]implying that\[\text{dim}(\ker\phi^2) = \text{dim}(V\otimes V) - \text{dim}(\text{Im}\,\phi^2).\]By properties of tensor product, we see that for a finite-dimensional vector space, $\text{dim}(V\otimes V) = (\text{dim}(V))^2$. Thus, we have in our case that\[\text{dim}(\ker\phi^2) = d^2 - \text{dim}(\text{Im}\,\phi^2).\]Now, observe that under $\phi^2$, $v_1\otimes v_2 \mapsto \phi(v_1)\otimes \phi(v_2)$. Since $\phi(v_1),\phi(v_2)\in\text{Im}\,\phi$, we have $\text{Im}(\phi^2)\subseteq\text{Im}(\phi)\otimes \text{Im}(\phi)$. In a similar fashion, one can show that $\text{Im}(\phi)\otimes \text{Im}(\phi)\subseteq\text{Im}(\phi^2)$, implying that $\text{Im}(\phi)\otimes \text{Im}(\phi)=\text{Im}(\phi^2)$. Thus, $\text{dim}(\text{Im}\,\phi^2) = (\text{dim}(\text{Im},\phi))^2=(d-k)^2$. Therefore, $\text{dim}(\ker\phi^2)= d^2 - (d-k)^2 = (d-(d-k))(d+(d-k)) = k(2d-k)=2dk-k^2$. Q.E.D.

and here's Sudharaka's solution:

By the Rank-Nullity Theorem,

\[\text{dim}(V\otimes V)=\text{dim}(\ker\phi^2)+\text{dim}(\text{im }\phi^2)\]Since, \(\text{dim}(V\otimes V) = \text{dim}(V)\cdot\text{dim}(V)=d^2\)\[\text{dim}(\ker\phi^2)=d^2-\text{dim}(\text{im }\phi^2)~~~~~~~~~~(1)\]\[\text{im }\phi^2=\{\phi^2(v_1\otimes v_2)~|~v_1\otimes v_2\in V\otimes V\}\]\[\Rightarrow \text{im }\phi^2=\{\phi(v_1)\otimes\phi(v_2)~|~v_1\otimes v_2\in V\otimes V\}=\phi(V)\otimes\phi(V)=(\text{im }\phi)\otimes(\text{im }\phi)\]\[\Rightarrow \text{dim}(\text{im }\phi^2)=\{\text{dim}(\text{im }\phi)\}^2~~~~~~~~(2)\]Considering the linear operator \(\phi\) and using the Rank-Nullity theorem we get,\[\text{dim}(V)=\text{dim}(\ker\phi)+\text{dim} (\text{im }\phi)\]\[\Rightarrow \text{dim} (\text{im }\phi)=d-k\]\[\Rightarrow \{\text{dim} (\text{im }\phi)\}^2=(d-k)^2~~~~~~~~~(3)\]By (2) and (3),\[\text{dim}(\text{im }\phi^2)=(d-k)^2\]Now by (1),\[\text{dim}(\ker\phi^2)=d^2-(d-k)^2=2dk-k^2\]
 

Related to How to Prove the Dimension of Ker $\phi^2$ in a Finite-Dimensional Vector Space?

1. What is the definition of the dimension of Ker $\phi^2$?

The dimension of Ker $\phi^2$ is the number of linearly independent vectors in the null space of the transformation $\phi^2$ in a finite-dimensional vector space.

2. How do you prove the dimension of Ker $\phi^2$?

To prove the dimension of Ker $\phi^2$, you can use the rank-nullity theorem, which states that the dimension of the null space (ker) plus the dimension of the range (image) equals the dimension of the vector space. Therefore, you can find the dimension of Ker $\phi^2$ by subtracting the dimension of the range of $\phi^2$ from the dimension of the vector space.

3. Can the dimension of Ker $\phi^2$ be greater than the dimension of the vector space?

No, the dimension of Ker $\phi^2$ cannot be greater than the dimension of the vector space. This is because the number of linearly independent vectors in the null space of $\phi^2$ cannot exceed the total number of vectors in the vector space.

4. What is the relationship between the dimension of Ker $\phi^2$ and the dimension of Ker $\phi$?

The dimension of Ker $\phi^2$ is always equal to or less than the dimension of Ker $\phi$. This is because the null space of $\phi^2$ contains vectors that are also in the null space of $\phi$, but it may also contain additional vectors that are not in the null space of $\phi$.

5. Can the dimension of Ker $\phi^2$ be negative?

No, the dimension of Ker $\phi^2$ cannot be negative. This is because the dimension of a vector space, including its null space, is always a non-negative integer.

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