The next basic tool we’re going to need is the theory of distributions.


Distributions are extremely useful because they are both fairly general (including both all integrable functions and things like the Dirac delta function) but also allow for operations such as differentiation. So oftentimes we can obtain distribution solutions to differential equations we are interested in.

Actually, we’ll only discuss here tempered distributions. A tempered distribution is a linear functional {\phi: \mathcal{S} \rightarrow \mathbb{C}}. Clearly the tempered distributions form a vector space {\mathcal{S}'}; it is a locally convex space if we endow it with the weak* topology. It must now be seen how distributions generalize functions. So, if {f \in L^p(\mathbb{R}^n)} for any {p, 1 \leq p \leq \infty}, then {f} can be made into a distribution

\displaystyle w \rightarrow \int_{\mathbb{R}^n} wf dx, \ w \in \mathcal{S}.

In fact, we could just assume that {f} grows polynomially. In particular, we have an imbedding {\mathcal{S} \rightarrow S'}.

An example of a distribution that is not a function is the Dirac distribution {\delta} mapping {f \rightarrow f(0)}. (more…)