Dual Norm Spaces (isomorphism/isometric)

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In summary, dual norm spaces are mathematical spaces with two associated norms, one for the original space and one for the dual space. They are not generally isomorphic, but can be in certain cases. Isomorphism and isometry differ in what they preserve, with isomorphism preserving the structure and isometry preserving distance between points. Dual norm spaces are important in functional analysis for studying linear functionals and their relationship with elements in a space. Examples of dual norm spaces include finite-dimensional vector spaces and their dual spaces, as well as spaces of continuous and square integrable functions with their respective dual spaces.
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Homework Statement


If X and Y are normed spaces, define [itex]\alpha : X^* x X^*\rightarrow (X x X)^*[/itex] by [itex]\alpha(f,g)(x,y) = f(x)+g(y)[/itex].
Then [itex]\alpha[/itex] is an isometric isomorphism if we use the norm [itex]||(x,y)|| = max(||x||,||y||)[/itex] on [itex]X x Y[/itex], the corresponding operator norm on [itex](X x Y)^*[/itex], and the norm [itex]||(f,g)||=||f||+||g||[/itex] on [itex]X^* x Y^*[/itex].


Homework Equations


[itex]||x||=sup[|f(x)|:f\in X^*, ||f||\leq 1][/itex]
[itex]||f||=sup[|f(x)|:x\in X, ||x||\leq 1][/itex]




The Attempt at a Solution



to show it is isomorphism,
suppose [itex]\alpha (f,g) = f(x) + g(y) = m(x) + n(y) = \alpha (m,n)[/itex]
but this can only happen if f(x)=m(x) and g(y)=n(y) since they depend on x and y respectfully.

but i am having trouble with proving it is isometric
here is my attempt:
I assume i want to show that ||(f,g)||=||(x,y)||

[itex]||(f,g)||=sup[|f(x)|:x\in X, ||x||\leq 1] + sup[|g(y)|:y\in Y, ||y||\leq 1]
=sup[|f(x)|+|g(y)|:x\in X, y\in Y, ||y||\leq 1, ||x||\leq 1][/itex]


also
[itex]||(x,y)||=max(sup[|f(x)|:f\in X^*, ||f||\leq 1],sup[|g(y)|:g\in X^*, ||f||\leq 1])[/itex]

but I don't know what else to do.
 
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First, we need to show that \alpha is a linear map. Let (f1,g1), (f2,g2) be elements of X^* x Y^*. Then for any (x,y)\in X x Y, we have:

\alpha((f1,g1)+(f2,g2))(x,y) = (f1+f2)(x)+(g1+g2)(y) = f1(x)+f2(x)+g1(y)+g2(y)
= (f1(x)+g1(y))+(f2(x)+g2(y)) = \alpha(f1,g1)(x,y)+\alpha(f2,g2)(x,y)

So, \alpha is indeed a linear map. Now, let's show that it is an isometry. For any (f,g)\in X^* x Y^*, we have:

||(f,g)|| = ||f||+||g|| = sup[|f(x)|:x\in X, ||x||\leq 1] + sup[|g(y)|:y\in Y, ||y||\leq 1]
= sup[|f(x)|+|g(y)|:x\in X, y\in Y, ||y||\leq 1, ||x||\leq 1]

On the other hand, for any (x,y)\in X x Y, we have:

||(x,y)|| = max(||x||,||y||) = sup[|f(x)|:f\in X^*, ||f||\leq 1] + sup[|g(y)|:g\in X^*, ||g||\leq 1]
= sup[|f(x)|+|g(y)|:f,g\in X^*, ||f||\leq 1, ||g||\leq 1]

Since both ||(f,g)|| and ||(x,y)|| are equal to sup[|f(x)|+|g(y)|:x\in X, y\in Y, ||y||\leq 1, ||x||\leq 1], we can conclude that \alpha is an isometry. This means that it preserves distances between elements in X^* x Y^*, and hence is an isometric isomorphism.
 

What are dual norm spaces?

Dual norm spaces are a type of mathematical space where each element has two associated norms, one for the original space and one for the dual space. The dual space is a separate space that contains all linear functionals on the original space, while the norms measure the size or magnitude of the elements in the space.

Are dual norm spaces isomorphic?

In general, dual norm spaces are not isomorphic. Isomorphism is a one-to-one mapping between two spaces that preserves the structure, and it is very rare for two dual norm spaces to have the same structure. However, there are certain cases where dual norm spaces can be isomorphic, such as when the original space is finite-dimensional.

What is the difference between isomorphism and isometry in relation to dual norm spaces?

Isomorphism and isometry are both types of mappings between spaces, but they differ in what they preserve. Isomorphism preserves the structure of the space, while isometry preserves the distance between points. In the context of dual norm spaces, isomorphism means that the norms on the original space and dual space are equivalent, while isometry means that the norms are equal.

Why are dual norm spaces important in functional analysis?

Dual norm spaces play a crucial role in functional analysis because they provide a way to study linear functionals and their relationship with elements in a space. They also allow for the use of techniques such as duality theory and Hahn-Banach theorem, which are fundamental in understanding the properties of normed spaces.

What are some examples of dual norm spaces?

Some common examples of dual norm spaces include finite-dimensional vector spaces and their dual spaces, such as $\mathbb{R}^n$ and $(\mathbb{R}^n)^*$. Other examples include the space of continuous functions and its dual space of measures, as well as the space of square integrable functions and its dual space of square summable sequences.

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