Canonical Isomorphism and Tensor Products

In summary, the problem is asking to find the linear transformation $\alpha(t)(v)$ for given tensors $t$ and $v$. This is done by using the canonical isomorphism $\alpha$ from $V^*\otimes V$ to $L(V,V)$ and identifying the basis of elementary tensors with that of elementary matrices. The values of $\alpha(t)(v)$ can be computed by taking the coordinates of $v$ and placing them in the appropriate slots in the matrix representation of $T$.
  • #1
Sudharaka
Gold Member
MHB
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Hi everyone, :)

Here's a problem that I have trouble understanding. Specifically I am not quite getting what it means by the expression \(\alpha (t)(v)\). Hope somebody can help me to improve my understanding. :)

Problem:

Let \(\alpha\) be the canonical isomorphism from \(V^*\otimes V\) to \(L(V,\, V)\). Find \(\alpha(t)(v)\) where \(t=(e^1+e^2)\otimes (e_3+e_4)\) and \(v=2e_1+3e_2+2e_3+3e_4\).
 
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  • #2
Sudharaka said:
Hi everyone, :)

Here's a problem that I have trouble understanding. Specifically I am not quite getting what it means by the expression \(\alpha (t)(v)\). Hope somebody can help me to improve my understanding. :)

Problem:

Let \(\alpha\) be the canonical isomorphism from \(V^*\otimes V\) to \(L(V,\, V)\). Find \(\alpha(t)(v)\) where \(t=(e^1+e^2)\otimes (e_3+e_4)\) and \(v=2e_1+3e_2+2e_3+3e_4\).
With the usual caveat that I'm not really at home with this tensor notation, the idea is that an element of $V^*\otimes V$ gives rise to a linear transformation from $V$ to $V$. The elementary tensor $e^i\otimes e_j$ gives rise to the linear transformation $T = \alpha(e^i\otimes e_j)$ defined by $T(v) = \alpha(e^i\otimes e_j)(v) = \langle e^i,v\rangle e_j$ (for all $v\in V$), where the angled brackets $\langle x,v\rangle$ denote the action of $x\in V^*$ on the element $x\in V$ under the duality between the two spaces. Thus $\alpha(e^i\otimes e_j)(e_k) = \begin{cases}e_j& \text{ if }k=i, \\ 0&\text{ if }k\ne i. \end{cases}$
 
  • #3
Opalg said:
With the usual caveat that I'm not really at home with this tensor notation, the idea is that an element of $V^*\otimes V$ gives rise to a linear transformation from $V$ to $V$. The elementary tensor $e^i\otimes e_j$ gives rise to the linear transformation $T = \alpha(e^i\otimes e_j)$ defined by $T(v) = \alpha(e^i\otimes e_j)(v) = \langle e^i,v\rangle e_j$ (for all $v\in V$), where the angled brackets $\langle x,v\rangle$ denote the action of $x\in V^*$ on the element $x\in V$ under the duality between the two spaces. Thus $\alpha(e^i\otimes e_j)(e_k) = \begin{cases}e_j& \text{ if }k=i, \\ 0&\text{ if }k\ne i. \end{cases}$

Thanks so much for your reply. I took a long time to understand this due to my limited knowledge about tensors, but I think now I am getting there. :)
 
  • #4
As I indicated in another thread the basis of elementary tensors $e^j \otimes e_i$ of $V^{\ast} \otimes V$ can be identified with the basis of elementary matrices $E_{ij}$ of $\text{Hom}(V,V)$.

Note that this identification uses a basis choice for $V$, but it is possible to do this in a completely basis-free manner.

One thing to remember is that linear functionals (at least for finite-dimensional vector spaces) are pretty much just "glorified inner products". That is, every element $f \in V^{\ast}$ can be thought of as the function:

$\langle u,\_\rangle$ for some vector $u$.

For example, we have $e^j = \langle e_j,\_ \rangle$ for the standard basis for $V$.

***Note*** Vector spaces, of course, do not always come equipped with a "natural" inner product. However, any non-degenerate bilinear form $B$ can be used to induce an isomorphism (only in the finite-dimensional case, n.b.) between $V$ and $V^{\ast}$, and the "go-to" non-degenerate bilinear form in an inner product space is, of course, the inner product (BUT...in complex vector spaces, it is often more convenient to use a sesquilinear form, due to the peculiarities of the complex conjugate).

In particular, it is natural to identify the 1-form (dual basis element) $e^j$ with the $j$-th projection function.

*******

Computing the values of these mappings is often tedious. $\alpha(e^i \otimes e_j) (v)$ basically takes the $i$-th coordinate of $v$ (in the given "$e$" basis) and sticks it in the $j$-th slot, with every other coordinate 0. To extend this to the entire tensor $t$ we extend by (multi-, in this case, bi-) linearity.

So if:

$t = (e^1 + e^2) \otimes (e_3 + e_4) = e^1 \otimes e_3 + e^1 \otimes e_4 + e^2 \otimes e_3 + e^2 \otimes e_4$

Then:

$\alpha(t)(v) = 2e_3 + 2e_4 + 3e_3 + 3e_4 = 5e_3 + 5e_4$

or, perhaps more understandably, relative to our given basis $S$ of $V$:

$[T]_S([v]_S) = [T]_S(2,3,2,3)^T = (0,0,5,5)^T$

(if I have done my arithmetic correctly), that is relative to the given basis, our linear mapping $T$ has the matrix:

$\begin{bmatrix}0&0&0&0\\0&0&0&0\\1&1&0&0\\1&1&0&0 \end{bmatrix}$
 
  • #5
Deveno said:
As I indicated in another thread the basis of elementary tensors $e^j \otimes e_i$ of $V^{\ast} \otimes V$ can be identified with the basis of elementary matrices $E_{ij}$ of $\text{Hom}(V,V)$.

Note that this identification uses a basis choice for $V$, but it is possible to do this in a completely basis-free manner.

One thing to remember is that linear functionals (at least for finite-dimensional vector spaces) are pretty much just "glorified inner products". That is, every element $f \in V^{\ast}$ can be thought of as the function:

$\langle u,\_\rangle$ for some vector $u$.

For example, we have $e^j = \langle e_j,\_ \rangle$ for the standard basis for $V$.

***Note*** Vector spaces, of course, do not always come equipped with a "natural" inner product. However, any non-degenerate bilinear form $B$ can be used to induce an isomorphism (only in the finite-dimensional case, n.b.) between $V$ and $V^{\ast}$, and the "go-to" non-degenerate bilinear form in an inner product space is, of course, the inner product (BUT...in complex vector spaces, it is often more convenient to use a sesquilinear form, due to the peculiarities of the complex conjugate).

In particular, it is natural to identify the 1-form (dual basis element) $e^j$ with the $j$-th projection function.

*******

Computing the values of these mappings is often tedious. $\alpha(e^i \otimes e_j) (v)$ basically takes the $i$-th coordinate of $v$ (in the given "$e$" basis) and sticks it in the $j$-th slot, with every other coordinate 0. To extend this to the entire tensor $t$ we extend by (multi-, in this case, bi-) linearity.

So if:

$t = (e^1 + e^2) \otimes (e_3 + e_4) = e^1 \otimes e_3 + e^1 \otimes e_4 + e^2 \otimes e_3 + e^2 \otimes e_4$

Then:

$\alpha(t)(v) = 2e_3 + 2e_4 + 3e_3 + 3e_4 = 5e_3 + 5e_4$

or, perhaps more understandably, relative to our given basis $S$ of $V$:

$[T]_S([v]_S) = [T]_S(2,3,2,3)^T = (0,0,5,5)^T$

(if I have done my arithmetic correctly), that is relative to the given basis, our linear mapping $T$ has the matrix:

$\begin{bmatrix}0&0&0&0\\0&0&0&0\\1&1&0&0\\1&1&0&0 \end{bmatrix}$

Thanks so much. I will read all the details slowly to grab hold of them. The problem this tensor mathematics is that I find a lot of different approaches to a given problem with sometimes confuses me. :)
 

FAQ: Canonical Isomorphism and Tensor Products

1. What is a canonical isomorphism?

A canonical isomorphism is a type of isomorphism (a bijective map between two mathematical structures) that is defined in a specific, natural way. It is often used to show that two seemingly different mathematical objects are actually equivalent, or isomorphic, in some way.

2. How is a canonical isomorphism different from a regular isomorphism?

Unlike regular isomorphisms, which can be chosen arbitrarily, a canonical isomorphism is uniquely defined and cannot be altered. It is also considered to be more natural and fundamental than a regular isomorphism, which may depend on specific choices or constructions.

3. What is the significance of canonical isomorphism in mathematics?

Canonical isomorphisms play a crucial role in many areas of mathematics, including algebra, topology, and geometry. They provide a way to identify and compare different mathematical structures, and often reveal deeper connections between seemingly unrelated objects.

4. What is a tensor product?

A tensor product is a mathematical operation that combines two vector spaces to create a new, larger vector space. It is defined in a way that preserves certain properties of the original vector spaces, such as their dimension and basis vectors. Tensor products are frequently used in physics, engineering, and other fields to model and solve complex problems.

5. How is a tensor product related to canonical isomorphism?

In many cases, the tensor product of two vector spaces can be thought of as a canonical isomorphism between them. This means that the tensor product reveals a natural, fundamental connection between the two vector spaces, and can be used to compare and transform them in a consistent way. Additionally, canonical isomorphisms are often used to construct tensor products in a way that is independent of any specific representations or bases.

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