Norm in R^d with Lebesgue measure

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Discussion Overview

The discussion revolves around properties of functions in the space \( L^p \) with respect to the Lebesgue measure in \( \mathbb{R}^d \). Participants explore the implications of translation invariance of the Lebesgue measure and the convergence of translated functions in the \( L^p \) norm. The focus is on proving specific properties related to the translation of functions and their norms.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Homework-related

Main Points Raised

  • Some participants assert that the translation invariance of the Lebesgue measure implies that if \( f \in L^p \), then \( f_y \in L^p \) and \( ||f||_p = ||f_y||_p \).
  • Others suggest that to prove the convergence \( \lim_{y \rightarrow 0} ||f - f_y||_p = 0 \), one should first establish the result for continuous functions with compact support or simple functions in \( L^p \), and then extend it to all \( L^p \) functions.
  • One participant proposes a proof strategy involving approximating \( f \) with a continuous function \( g \) and using properties of \( L^p \) norms to show convergence.
  • Another participant questions the necessity of proving the result for continuous functions with compact support first, seeking clarification on the reasoning behind this approach.
  • Some participants provide detailed steps for proving the properties of \( f_y \) and discuss the implications of using Minkowski's inequality in the context of the \( L^p \) norm.

Areas of Agreement / Disagreement

Participants generally agree on the translation invariance of the Lebesgue measure and its implications for \( L^p \) functions. However, there is no consensus on the best approach to prove the convergence of \( ||f - f_y||_p \) as \( y \) approaches zero, with differing opinions on the necessity of starting with continuous functions with compact support.

Contextual Notes

Some limitations include the dependence on the choice of function classes for proving general results in \( L^p \) spaces, as well as the unresolved steps in the proof of convergence for arbitrary functions.

mathmari
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Hey! :o

In $\mathbb{R}^d$ with the Lebesgue measure if $f \in L^p, 1 \leq p < +\infty$, and if for each $y$ we set $f_y(x)=f(x+y)$ then:
  1. $f_y \in L^p$ and $||f||_p=||f_y||_p$
  2. $\lim_{y \rightarrow 0} ||f-f_y||_p=0$

Could you give me some hints how to show that?? (Wondering)
 
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1. follows from the fact that Lebesgue measure is translation-invariant.

For 2., I think that you may need to start by proving this for some class of functions that is dense in $L^p$. For example, can you show that it holds for continuous functions with compact support, or alternatively for simple functions in $L^p$? Then deduce that the result holds for all $L^p$ functions.
 
Opalg said:
1. follows from the fact that Lebesgue measure is translation-invariant.

For 2., I think that you may need to start by proving this for some class of functions that is dense in $L^p$. For example, can you show that it holds for continuous functions with compact support, or alternatively for simple functions in $L^p$? Then deduce that the result holds for all $L^p$ functions.

  1. $$L_p=\{f: X \rightarrow \overline{\mathbb{R}} \text{ or } \mathbb{C} : f \text{ measurable and } \int |f|^pd \mu<+\infty\}$$

    We have that $f \in L^p$, so $\int |f|^p d \mu < +\infty$.

    $\int |f_y|^pd \mu=\int |f(x+y)|^pd \mu \ \ \ \ \ \overset{\text{ translation-invariant }}{=} \ \ \ \ \ \int |f(x)|^pd \mu < +\infty$

    So, $\int |f_y|^p d \mu<+\infty$ that means that $f_y \in L^p$.

    Is this correct?? (Wondering)$||f||_p= \left ( \int |f|^p d \mu \right )^{1/p} \ \ \ \ \ \overset{\text{ translation-invariant }}{=} \ \ \ \ \ \left ( \int |f(x+y)|^p d \mu \right )^{1/p}=\left ( \int |f_y|^p d \mu \right )^{1/p}=||f_y||_p$

    Is this right?? (Wondering)
  2. $||f-f_y||_p \ \ \ \ \ \overset{\text{ Minkowsi }}{ \leq } \ \ \ \ \ ||f||_p+||f_y||_p=||f||_p+||f||_p=2||f||_p$

    Can we use this?? Or isn't it correct?? (Wondering)
 
As Opalg suggested, in part 2, first prove the result when $f$ is continuous with compact support. In the general case, given $\varepsilon > 0$, there exists a continuous function $g$ with compact support such that $||f - g||_p < \frac{\varepsilon}{3}$. Choose $\delta > 0$ such that $||g - g_y||_p < \frac{\varepsilon}{3}$ whenever $|y| < \delta$. By translation invariance of the Lebesgue measure, $\|g_y - f_y\|_p = \|g - f\|_p < \frac{\varepsilon}{3}$ for all $y$. Thus

$$ \|f - f_y\|_p \le \|f - g\|_p + \|g - g_y\|_p + \|g_y - f_y\|_p < \frac{\varepsilon}{3} + \frac{\varepsilon}{3} + \frac{\varepsilon}{3} = \varepsilon$$

for all $y$ with $|y| < \delta$. Since $\varepsilon$ was arbitrary, the result follows.
 
Euge said:
As Opalg suggested, in part 2, first prove the result when $f$ is continuous with compact support. In the general case, given $\varepsilon > 0$, there exists a continuous function $g$ with compact support such that $||f - g||_p < \frac{\varepsilon}{3}$. Choose $\delta > 0$ such that $||g - g_y||_p < \frac{\varepsilon}{3}$ whenever $|y| < \delta$. By translation invariance of the Lebesgue measure, $\|g_y - f_y\|_p = \|g - f\|_p < \frac{\varepsilon}{3}$ for all $y$. Thus

$$ \|f - f_y\|_p \le \|f - g\|_p + \|g - g_y\|_p + \|g_y - f_y\|_p < \frac{\varepsilon}{3} + \frac{\varepsilon}{3} + \frac{\varepsilon}{3} = \varepsilon$$

for all $y$ with $|y| < \delta$. Since $\varepsilon$ was arbitrary, the result follows.

Ok, I will think about it! (Wait)

Is my proof of the first sentence correct?? (Wondering)
 
mathmari said:
Is my proof of the first sentence correct?? (Wondering)

What you have is almost correct, but it's not a proof yet. Here's an example of a proof of part 1:

For each $y\in \Bbb R^d$, $f_y$ is the composition of the measurable function $f$ and the continuous map $x \mapsto x + y$ from $\Bbb R^d$ to $\Bbb R^d$. Hence $f_y$ is measurable for every $y$. By translational invariance of the Lebesgue measure, for all $y\in \Bbb R^d$,

$$\|f_y\|_p^p = \int_{\Bbb R^d}|f(x - y)|^p\, dx = \int_{\Bbb R^d} |f(x)|^p\, dx = \|f\|_p^p < \infty$$

Therefore, for all $y\in \Bbb R^d$, $f_y\in L^p$ with $\|f_y\|_p = \|f\|_p$.
 
Opalg said:
For 2., I think that you may need to start by proving this for some class of functions that is dense in $L^p$. For example, can you show that it holds for continuous functions with compact support, or alternatively for simple functions in $L^p$? Then deduce that the result holds for all $L^p$ functions.

Euge said:
As Opalg suggested, in part 2, first prove the result when $f$ is continuous with compact support. In the general case, given $\varepsilon > 0$, there exists a continuous function $g$ with compact support such that $||f - g||_p < \frac{\varepsilon}{3}$. Choose $\delta > 0$ such that $||g - g_y||_p < \frac{\varepsilon}{3}$ whenever $|y| < \delta$. By translation invariance of the Lebesgue measure, $\|g_y - f_y\|_p = \|g - f\|_p < \frac{\varepsilon}{3}$ for all $y$. Thus

$$ \|f - f_y\|_p \le \|f - g\|_p + \|g - g_y\|_p + \|g_y - f_y\|_p < \frac{\varepsilon}{3} + \frac{\varepsilon}{3} + \frac{\varepsilon}{3} = \varepsilon$$

for all $y$ with $|y| < \delta$. Since $\varepsilon$ was arbitrary, the result follows.

Could you explain it further to me?? (Wondering)
 
Which part do you need more explanation, mathmari?
 
Euge said:
Which part do you need more explanation, mathmari?

Why do we have to show it first for continuous functions with compact support??
 
  • #10
It doesn't have to be (look at Opalg's suggestions), but it makes things easier to find estimates for $\|f - f_y\|_p$ for compactly supported continuous functions $f$, as you have seen. Once the result is proven for this class of functions, then we can prove the general case by the argument I showed before or by application of Fatou's lemma. These are common methods of proof when dealing with convergence theorems involving $L^p$ norms.
 

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