Is the mapping from $\mathcal{L}^p(X,\mu)$ to $\mathcal{L}^1(X,\mu)$ continuous?

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  • Thread starter Euge
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    2016
In summary, continuity in function spaces refers to the preservation of properties under small changes in the input function. The mapping from $\mathcal{L}^p(X,\mu)$ to $\mathcal{L}^1(X,\mu)$ is a function that transforms functions from one function space to another. Continuity in this mapping ensures the preservation of properties of functions. It can be proven using mathematical techniques such as the epsilon-delta definition or the Lipschitz continuity definition.
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Euge
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Here is this week's POTW:

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Let $(X,\mu)$ be a positive measure space. For $0 < p < \infty$, why is the mapping $\mathcal{L}^p(X,\mu) \to \mathcal{L}^1(X,\mu)$ sending $f$ to $\lvert f\rvert^p$, continuous?-----Remember to read the http://www.mathhelpboards.com/showthread.php?772-Problem-of-the-Week-%28POTW%29-Procedure-and-Guidelines to find out how to http://www.mathhelpboards.com/forms.php?do=form&fid=2!
 
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No one answered this week's problem. You can read my solution below.
For all pairs of nonnegative numbers $a, b$, $\lvert a^p - b^p\rvert \le \lvert a - b\rvert^p$ if $0 < p < 1$, and $\lvert a^p - b^p\rvert \le p(a^{p-1} + b^{p-1})\lvert a - b\rvert$ if $p \ge 1$. Thus, for all $f, g\in \mathcal{L}^p(X,\mu)$,

$$\| \lvert f\rvert^p - \lvert g\rvert^p \|_1 \le \|f - g\|_p^p \quad (0 < p < \infty)$$

and for $1\le p < \infty$,

$$\|\lvert f\rvert^p - \lvert g\rvert^p\|_1 \le p\int_X \lvert f\rvert^{p-1}\lvert f - g\rvert\, d\mu + p\int_X \lvert g\rvert^{p-1}\lvert f - g\vert\, d\mu \le p(\|f\|_p\|f - g\|_p + \|g\|_p\|f - g\|_p) = p(\|f\|_p + \|g\|_p)\|f - g\|_p$$

using Hölder's inequality in the penultimate step. These inequalities imply continuity of the map $f\mapsto \lvert f\rvert^p$ from $\mathcal{L}^p(X,\mu)$ to $\mathcal{L}^1(X,\mu)$.
 

1. What is the definition of continuity in function spaces?

In function spaces, continuity refers to the preservation of certain properties of functions under small changes in the input. In this case, it means that a small change in the input function should result in a small change in the output function.

2. What is the mapping from $\mathcal{L}^p(X,\mu)$ to $\mathcal{L}^1(X,\mu)$?

The mapping from $\mathcal{L}^p(X,\mu)$ to $\mathcal{L}^1(X,\mu)$ is a function that takes a function in the function space $\mathcal{L}^p(X,\mu)$ and maps it to a function in the function space $\mathcal{L}^1(X,\mu)$. This mapping is used to transform functions from one function space to another, and it is important in many areas of mathematics and science.

3. How is continuity defined in the context of function spaces?

In the context of function spaces, continuity is defined as the property that small changes in the input function result in small changes in the output function. This means that if the input function is close to another function in the function space, then the output function will also be close to the output of that other function.

4. What is the significance of continuity in the mapping from $\mathcal{L}^p(X,\mu)$ to $\mathcal{L}^1(X,\mu)$?

The significance of continuity in this mapping is that it ensures that the properties of functions in the function space $\mathcal{L}^p(X,\mu)$ are preserved when they are transformed to the function space $\mathcal{L}^1(X,\mu)$. This allows us to study and analyze functions in different function spaces while still maintaining their important properties.

5. How is continuity of the mapping from $\mathcal{L}^p(X,\mu)$ to $\mathcal{L}^1(X,\mu)$ proven?

The continuity of this mapping can be proven using mathematical techniques such as the epsilon-delta definition of continuity or the definition of a Lipschitz continuous function. In general, it involves showing that small changes in the input function result in small changes in the output function, and that these changes can be bounded by a constant factor.

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