L-infinity explained
In mathematics,
, the (real or complex)
vector space of bounded sequences with the
supremum norm, and
Linfty=Linfty(X,\Sigma,\mu)
, the vector space of
essentially bounded measurable functions with the
essential supremum norm, are two closely related
Banach spaces. In fact the former is a special case of the latter. As a Banach space they are the continuous dual of the Banach spaces
of absolutely summable sequences, and
of absolutely integrable measurable functions (if the measure space fulfills the conditions of being localizable and therefore semifinite).
[1] Pointwise multiplication gives them the structure of a
Banach algebra, and in fact they are the standard examples of abelian
Von Neumann algebras.
Sequence space
The vector space
is a
sequence space whose elements are the
bounded sequences. The vector space operations, addition and scalar multiplication, are applied coordinate by coordinate. With respect to the norm
is a standard example of a
Banach space. In fact,
can be considered as the
space with the largest
.
This space is the strong dual space of
: indeed, every
defines a continuous functional on the space
of absolutely summable sequences by component-wise multiplication and summing:
\begin{align}
\ellinfty&\to({\ell1})'\\
x&\mapsto\left(y\mapsto
xiyi\right)
\end{align}
By evaluating on
we see that every continuous linear functional on
arises in this way. i.e.
However, not every continuous linear functional on
arises from an absolutely summable series in
and hence
is not a
reflexive Banach space.
Function space
is a
function space. Its elements are the
essentially bounded measurable functions.
[2] More precisely,
is defined based on an underlying
measure space,
Start with the set of all measurable functions from
to
which are
essentially bounded, that is, bounded except on a set of measure zero. Two such functions are identified if they are equal almost everywhere. Denote the resulting set by
For a function
in this set, its
essential supremum serves as an appropriate norm:
This norm is the
uniform norm, it is an
norm for
The sequence space is a special case of the function space:
where the natural numbers are equipped with the counting measure.
Applications
One application of
and
is in
economics, particularly in the study of economies with infinitely many commodities.
[3] In simple economic models, it is common to assume that there is only a finite number of different commodities, e.g. houses, fruits, cars, etc., so every bundle can be represented by a finite vector, and the
consumption set is a vector space with a finite dimension. But in reality, the number of different commodities may be infinite. For example, a "house" is not a single commodity type since the value of a house depends on its location. So the number of different commodities is the number of different locations, which may be considered infinite. In this case, the consumption set is naturally represented by
Notes and References
- Web site: Elementary set theory - Why every localizable measure space is semifinite measure space?.
- Book: Brezis . Haim . Functional Analysis, Sobolev Spaces and Partial Differential Equations . 2010 . Springer . 978-0-387-70913-0 . 91.
- Bewley. T. F.. Existence of equilibria in economies with infinitely many commodities. 1972. Journal of Economic Theory. 4. 3. 514–540. 10.1016/0022-0531(72)90136-6.