Support of a Distribution¶
A distribution is said to be supported in a closed set if for all with .
The support of , denoted , is the smallest set such that is supported in .
Example 1
The support of the Dirac delta is .
If is a continuous function, .
Local Structure¶
Two distributions and are equal on an open set if for all .
If is a regular distribution and on an open set , then almost everywhere on .
Distributions with Point Support¶
A fundamental result: If is a distribution supported at a single point , then is a finite linear combination of derivatives of the delta function at :
where is the order of .
The Structure Theorem for Distributions¶
The results above characterize distributions with point support. The structure theorem generalizes this to all distributions: every distribution is, locally, a finite-order derivative of a continuous function.
Theorem 1 (Structure theorem for distributions)
Let and let be compact. Then there exist an integer and continuous functions , , such that
If has finite order globally (i.e., the seminorm bound holds with the same for all compact ), then we can take uniformly.
Proof 1
We sketch the argument in one dimension for clarity; the general case is identical in structure.
Step 1: From the order bound to a norm estimate. On a compact set , the distribution has some finite order :
This means is a continuous linear functional on equipped with the norm.
Step 2: Extension to a continuous linear functional. The space is a subspace of . By the Hahn-Banach theorem, extends to a continuous linear functional on .
Step 3: Representation via antiderivatives. A continuous linear functional on can be written as a finite sum of integrals against Radon measures , :
Each Radon measure on a compact subset of has a continuous antiderivative: there exists such that for test functions . (In one dimension, this is just the fact that the antiderivative of a measure is a function of bounded variation, and one more antiderivative gives a continuous function.) Substituting:
where accounts for the additional antiderivatives needed in dimensions.
Remark 1 (Distributions are derivatives of continuous functions)
The structure theorem demystifies distributions: no matter how singular a distribution may appear, it is always locally a finite sum of derivatives of continuous functions. The Dirac delta is (derivative of the Heaviside function, which is bounded and measurable — or the second derivative of the continuous function ). The derivative is the third derivative of . And so on.
The price of increased singularity is simply a higher derivative order, not a fundamentally different kind of object.
The structure theorem immediately implies the point support result stated above:
If with , then .
Proof 2
By the structure theorem, on a ball around , we have for continuous . Since , the distribution vanishes on , which means each is a polynomial of degree at most on , and by continuity on all of . A polynomial supported at a point must be constant times a suitable derivative of . Collecting terms gives where is the order of .