Differentiation of Distributions
Buildup
The distribution cannot be differentiated in the same manner as functions defined over real numbers since its domain is a function space. However, for regular distributions, there is a corresponding locally integrable function , expressed as follows.
Hence, the action on could yield ; if remains a locally integrable function, then there exists a corresponding distribution . Therefore, the idea is to think of the action on as if it were the action on . This idea is extended over all distributions to define the differentiation of distributions.
Below, we assume , although it’s not strictly necessary. You could also simply discuss up to the th derivative with .
Let’s say a smooth function is given. The test function has a compact support, so it’s harmless to assume that is defined over some compact set that contains the support of the test function. Since smooth functions on a compact set are locally integrable, we can consider the corresponding regular distribution for .
Meanwhile, , being a smooth function, is differentiable, and , being locally integrable, has a corresponding regular distribution . Thus, by applying the integration by parts to the test function , it can be represented as follows.
Here, since has compact support, the first term is . Hence, we obtain the following.
Definition1
The derivative of the distribution is defined as follows.
Here, is the differentiation operator. For the multi-index , it is as follows.
Since the derivative of a test function is also a test function, there is no problem with the domain, and apart from that aspect, it is simply multiplied by the constant term , thus is also a distribution. Of course, this can be proved using the definition of distributions, but it is not strictly necessary.
Gerald B. Folland, Fourier Analysis and Its Applications (1992), p308-309 ↩︎