L1 Space: Difference between revisions

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<li><math>f+g</math>  
<li><math>f+g</math>  
<li><math>cf</math>, for <math> c\in\mathbb{R}</math>
<li><math>cf</math>, for <math> c\in\mathbb{R}</math>
<ol>
</ol>
   
   
This shows that the set of integrable functions on any measurable space is a vector space. Furthermore, integration is a linear functional on this vector space, ie a linear function sending elements in our vector space to <math>\mathbb{R}</math>.
This shows that the set of integrable functions on any measurable space is a vector space. Furthermore, integration is a linear functional on this vector space, ie a linear function sending elements in our vector space to <math>\mathbb{R}</math>, one would like to use integration to define a norm on our vector space. However, if one were to check the axioms for a norm, one finds that if <math>f=0</math> almost everywhere, then <math>\int f=\int 0=0</math>. This motivates our definition of <math>L^1(\mu)</math> to be the set of integrable functions up to equivalence to sets of measure zero.
 
===<math>L^1(\mu)</math> Space===
In this section, we will construct <math>L^1(\mu)</math>. We first show the following theorem:




==References==
==References==

Revision as of 08:31, 15 December 2020

Introduction

Let be a measure space. From our study of integration, we know that if are integrable functions, the following functions are also integrable:

  1. , for

This shows that the set of integrable functions on any measurable space is a vector space. Furthermore, integration is a linear functional on this vector space, ie a linear function sending elements in our vector space to , one would like to use integration to define a norm on our vector space. However, if one were to check the axioms for a norm, one finds that if almost everywhere, then . This motivates our definition of to be the set of integrable functions up to equivalence to sets of measure zero.

Space

In this section, we will construct . We first show the following theorem:


References