Kernel of the Symmetrizing Map

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In summary, we have shown that any element in the kernel of $sym$ can be written as a sum of tensors of the form (1), where $\beta$ is a pure tensor and $\tau$ is a transposition. I hope this helps with your proof. Let me know if you have any further questions. Best of luck!
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caffeinemachine
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Let $V$ be a finite dimensional vector space over a field of characteristic $0$ and let $sym:\bigotimes^k V\to \bigotimes^k V$ be the map defined as
$$
sym(\alpha)=\frac{1}{r!}\sum_{\sigma\in S_k}{^\sigma}\alpha
$$
where $S_k$ is the permutation group on $k$ letters and ${^\sigma}\alpha$ denotes the action of $\sigma$ on $\alpha$.

Since $sym^2=sym$, the kernel of $sym$ is $range(I-sym)$.

I want to show that each member of the kernel of $sym$ can be written as as a sum of the tensors of the form
$$
\beta-{^\tau}\beta\tag{1}
$$
where $\beta\in \bigotimes^k V$ is a pure tensor and $\tau$ is a transposition.

So for an example take $k=3$ and choose $u_1\otimes u_2\otimes u_3-u_2\otimes u_3\otimes u_1$ in $\ker sym$.
How do I write this in the desired form?

Thanks.
 
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Thank you for your question. It seems like you have already made some progress in understanding the map $sym$ and its kernel. Let me provide some further explanation and guidance to help you prove the desired result.

Firstly, let's recall that a transposition $\tau$ is a permutation that swaps two elements and leaves the rest unchanged. In the case of $k=3$, the transpositions are $\tau_1=(1,2)$, $\tau_2=(1,3)$, and $\tau_3=(2,3)$. Note that these transpositions generate the permutation group $S_3$.

Now, let's consider the pure tensor $\alpha=u_1\otimes u_2\otimes u_3-u_2\otimes u_3\otimes u_1$. We want to write this in the form of (1), with $\beta\in \bigotimes^3 V$ and $\tau$ a transposition. From the definition of $sym$, we have
$$
sym(\alpha)=\frac{1}{r!}\sum_{\sigma\in S_3}{^\sigma}\alpha=\frac{1}{3}(u_1\otimes u_2\otimes u_3-u_2\otimes u_3\otimes u_1+u_2\otimes u_1\otimes u_3-u_1\otimes u_3\otimes u_2+u_3\otimes u_1\otimes u_2-u_3\otimes u_2\otimes u_1).
$$
Note that this sum contains all possible permutations of the elements in $\alpha$. Now, let's consider the difference $\alpha-sym(\alpha)$. This is equal to
$$
\alpha-sym(\alpha)=\frac{2}{3}(u_1\otimes u_2\otimes u_3-u_2\otimes u_3\otimes u_1).
$$
We can see that this is a scalar multiple of $\alpha$, which is in the kernel of $sym$. Therefore, we can write $\alpha$ as a sum of tensors of the form (1), with $\beta=\frac{2}{3}(u_1\otimes u_2\otimes u_3-u_2\
 

1. What is the "Kernel of the Symmetrizing Map"?

The Kernel of the Symmetrizing Map refers to the set of vectors that are mapped to the zero vector by the symmetrizing map. In other words, it is the set of vectors that do not change under the operation of symmetrization.

2. Why is the "Kernel of the Symmetrizing Map" important?

The Kernel of the Symmetrizing Map plays a crucial role in understanding the symmetrization process and its effects on vectors. It also helps in determining the eigenvalues and eigenvectors of a matrix, as the eigenvectors will be in the Kernel of the Symmetrizing Map.

3. How is the "Kernel of the Symmetrizing Map" calculated?

The Kernel of the Symmetrizing Map can be calculated by finding the null space of the symmetrizing matrix. This can be done by solving a system of linear equations, where the coefficients of the equations are the elements of the symmetrizing matrix.

4. What are some applications of the "Kernel of the Symmetrizing Map"?

The Kernel of the Symmetrizing Map has various applications in mathematics, physics, and computer science. It is used in solving differential equations, analyzing quantum systems, and in image and signal processing algorithms.

5. Can the "Kernel of the Symmetrizing Map" be empty?

Yes, the Kernel of the Symmetrizing Map can be empty if the symmetrizing map is invertible. In this case, all vectors will be mapped to unique vectors and there will be no vectors in the Kernel. However, if the symmetrizing map is not invertible, the Kernel will contain at least the zero vector.

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