Egerov's Theorem: Difference between revisions

From Optimal Transport Wiki
Jump to navigation Jump to search
Line 6: Line 6:


==Proof==
==Proof==
WLOG assume <math> f_n \rightarrow f </math> for all <math> x \in E </math> since the set of points at which <math>f_n \rightarrow f</math> is a null set. Fix <math>\epsilon>0 </math> and for <math> n, k \in \N </math> we define
WLOG assume <math> f_n \rightarrow f </math> for all <math> x \in E </math> since the set of points at which <math>f_n \nrightarrow f</math> is a null set. Fix <math>\epsilon>0 </math> and for <math> n, k \in \N </math> we define
<math> E_k^n=\{x \in E: |f_j(x)-f(x)|<\frac{1}{n} \text{  for all  } j>k\} </math>. Since <math>f_n,f </math> are measurable so is their difference. Then since the absolute value of a measurable function is measurable each <math>E_k^n </math> is measurable.  
<math> E_k^n=\{x \in E: |f_j(x)-f(x)|<\frac{1}{n} \text{  for all  } j>k\} </math>. Since <math>f_n,f </math> are measurable so is their difference. Then since the absolute value of a measurable function is measurable each <math>E_k^n </math> is measurable.  



Revision as of 10:18, 7 December 2020

Statement

Suppose is a locally finite Borel measure and is a sequence of measurable functions defined on a measurable set with and a.e. on E.

Then: Given we may find a closed subset such that and uniformly on [1]

Proof

WLOG assume for all since the set of points at which is a null set. Fix and for we define . Since are measurable so is their difference. Then since the absolute value of a measurable function is measurable each is measurable.

Now for fixed we have that and . Therefore using continuity from below we may find a such that . Now choose so that and define . By countable subadditivity we have that .

Fix any . We choose such that . Since if then . And by definition if then whenever . Hence uniformly on .

Finally, since is measurable, using HW5 problem 6 there exists a closed set such that . Therefore and on

References

  1. Stein & Shakarchi, Real Analysis: Measure Theory, Integration, and Hilbert Spaces, Chapter 1 §4.3