A finite regular complex measure of total variation one can be approximated on a finite-dimensional vector subspace of continuous functions by a finite sum of phased point evaluations with . The Krein-Milman theorem and the extreme points of the dual unit ball of C(K) give weak-star approximation by convex combinations of phased point masses. A finite norm net of the vector subspace unit ball turns finitely many scalar approximations into one uniform estimate. Repeated nodes may be kept separate to retain the exact coefficient-magnitude sum.
The Riesz-Markov-Kakutani representation theorem says that a positive linear functional on has the form for a unique finite positive regular Borel measure , with norm . Its complex form says that every bounded complex linear functional is represented by a unique finite regular complex measure , and
The extension from positive to arbitrary linear functionals follows by positive/negative decomposition of real linear functionals and then real/imaginary decomposition. The last quantity is the total variation norm of a measure, so this identifies the dual isometrically.
An extreme point of a convex set cannot be written as with and distinct . The Krein-Milman theorem, applied with the underlying real locally convex weak-star topology, states
We next prove Milman's converse to the Krein-Milman theorem. Suppose an extreme point were outside the weak-star closure of . A basic weak-star neighborhood of disjoint from uses finitely many real coordinates: real and imaginary parts of evaluations at elements of . Its complement is the union of finitely many closed half-spaces
Intersect these with , discard empty intersections, and call the resulting compact convex sets . They cover , and none contains .
The convex hull of their union is compact. Every point in it can be written with in the finite simplex and , by combining terms from the same convex set. The map from the simplex times to that sum is weak-star continuous, so its image is compact and closed. It therefore contains , in particular . But extremality forces every having a positive coefficient in a representation of to equal , contradicting . Hence
Assume . We claim that the extreme points of the dual unit ball of C(K) are
A measure of norm less than one is not extreme, since it admits a small nonzero perturbation within the ball. For a measure of norm one, suppose is not a point mass. There is a Borel set with : if the measure support has two points, choose disjoint neighborhoods of positive mass; a regular probability measure supported at just one point is the corresponding point mass. Then
is a convex combination of distinct norm-one measures. Thus an extreme measure must have variation concentrated at one point, and must be with .
Conversely, if with , then
Equality throughout forces both measures to have all their variation at , and forces their phases to be . Hence , proving extremality. If , the dual ball is and its sole extreme point is .
Every finite Borel measure on is regular, so the given belongs to the dual unit ball of . Apply Banach-Alaoglu theorem and Krein-Milman theorem to that ball. It is the weak-star closed convex hull of these phased point masses. The unit ball of the finite-dimensional vector subspace is norm compact. Choose a finite -net in it. There is a convex combination
whose integrals differ from those of by less than on every . Put . Then and . For any in the unit ball of , choose with . The linear functional has norm at most two, so
Scaling yields the requested estimate for every . This is atomic approximation on finite-dimensional spaces of continuous functions. Repeated nodes are allowed: keeping their individual terms preserves the exact sum of coefficient magnitudes even if their phases cancel. If , one point with coefficient one suffices.
The Radon-Nikodym theorem for positive measures says: if and are sigma-finite measures on the same measurable space, and is absolutely continuous with respect to , then there is a nonnegative measurable function , unique -almost everywhere, such that
Here sigma-finiteness means that the space is a countable union of measurable sets of finite measure; absolute continuity of measures, written , means that implies . The function is the Radon-Nikodym derivative. For a finite signed or complex measure of finite total variation norm of a measure, absolutely continuous with respect to a sigma-finite , the corresponding density belongs to . This follows by applying the positive theorem to the positive and negative parts of the real and imaginary parts of .
For every measure space and , is isometrically , where . We use the complex-linear pairing
With the convention , the same identification is conjugate-linear in . By Hölder's inequality, is a bounded linear functional with . If , set
interpreting the numerator as zero where . The identity gives and . Thus
It remains to represent an arbitrary , rather than merely produce functionals from .
We prove Lp duality on an arbitrary measure space without imposing sigma-finiteness on . Write . For every measurable set with , define a complex measure on by
It is countably additive: for disjoint , the partial sums of their indicator functions tend in to , because the measure of the omitted tail tends to zero. It is absolutely continuous with respect to , since indicator functions of null sets represent zero in .
Its total variation norm of a measure is finite. For any finite measurable partition , choose scalars of modulus with . Then
Taking the supremum over partitions gives the variation bound. Since is finite, the Radon-Nikodym theorem supplies with . By uniform approximation with simple functions,
for every bounded measurable supported in .
To improve from to , test with the bounded function
If , then
Thus when , and the same bound is trivial when it is zero. The monotone convergence theorem gives
If both have finite measure, the densities agree almost everywhere on : their integrals over every measurable subset of the intersection equal the same functional value. This is uniqueness in the Radon-Nikodym theorem.
We now perform support localization of an Lp functional. Set
Choose finite-measure sets whose displayed integrals tend to , and let , . If , take . Compatibility allows us to define a measurable function on by taking on the disjoint measurable sets , and put off . It agrees almost everywhere with on every . Moreover,
Indeed each integral is at most , and it is at least the integral over , which tends to .
For any finite-measure set , compatibility on the disjoint union gives
Letting forces almost everywhere. For an arbitrary finite-measure set , compatibility on and the preceding conclusion on show that almost everywhere on . Consequently for every simple function supported on a finite-measure set.
Those simple functions are dense in even for this arbitrary measure space. To see the needed finite-support property, for the sets have finite measure, bounded by . First truncate to such sets and to bounded values, then approximate by simple functions; the discarded integral tends to zero. Continuity of and Hölder's inequality therefore extend the representation to every .
We have constructed with , and the previously proved norm identity gives . It also proves uniqueness: if , then . This completes the isometric duality of Lp spaces.
The dominated sequence actually converges to zero in norm, and hence weakly. The assumptions give and almost everywhere. The dominated convergence theorem yields
For every , . Therefore
Support of a measure 2026-10-06
For a positive Borel measure on a topological space, the support consists of the points whose every open neighborhood has positive measure. For a finite regular complex measure use its variation measure. Regularity makes the complement of the support null: compact subsets of that open complement have finite covers by null neighborhoods. A regular probability measure on a compact Hausdorff space whose support is a single point is therefore a Dirac measure.