Very much not finished
Introduction
Let
be a measure space. From our study of integration, we know that if
are integrable functions, the following functions are also integrable:
, 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 integration fails to be a norm by taking
almost everywhere, then
. In other words, there are non zero functions which has a zero integral. 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
.
Definition
Let
denote the set of integrable functions on
, ie
. Define an equivalence relation:
if
a.e. Then
.
To make sense of the definition, we need the following proposition:
Proposition: Let
, then the following are equivalent:
-
for all
-
a.e.
Proof
Since
a.e.,
a.e. Take a simple function,
, such that Failed to parse (unknown function "\math"): {\displaystyle 0\leq \phi\leq |f-g|<\math>, such <math>\phi}
must be
a.e. Therefore,
With the proposition, we define our norm on
to be
. This is indeed a norm since:
a.e
Convergence in 
With our norm defined, we can the metric to be
. With a metric, one can talk about convergence in
. This gives us a fourth mode of convergence for a sequence of functions. It is useful to compare these mode of convergence:
Uniform Convergence
Pointwise Convergence
Pointwise a.e. Convergence
However, convergence in
does not imply pointwise a.e. convergence and vice versa. To see that, we look at the following examples:
References