Support (measure theory)

In mathematics, the support (sometimes topological support or spectrum) of a measure μ on a measurable topological space (X, Borel(X)) is a precise notion of where in the space X the measure "lives". It is defined to be the largest (closed) subset of X for which every open neighbourhood of every point of the set has positive measure.


A (non-negative) measure   on a measurable space   is really a function  . Therefore, in terms of the usual definition of support, the support of   is a subset of the σ-algebra  :


where the overbar denotes set closure. However, this definition is somewhat unsatisfactory: we use the notion of closure, but we do not even have a topology on  . What we really want to know is where in the space   the measure   is non-zero. Consider two examples:

  1. Lebesgue measure   on the real line  . It seems clear that   "lives on" the whole of the real line.
  2. A Dirac measure   at some point  . Again, intuition suggests that the measure   "lives at" the point  , and nowhere else.

In light of these two examples, we can reject the following candidate definitions in favour of the one in the next section:

  1. We could remove the points where   is zero, and take the support to be the remainder  . This might work for the Dirac measure  , but it would definitely not work for  : since the Lebesgue measure of any singleton is zero, this definition would give   empty support.
  2. By comparison with the notion of strict positivity of measures, we could take the support to be the set of all points with a neighbourhood of positive measure:
(or the closure of this). It is also too simplistic: by taking   for all points  , this would make the support of every measure except the zero measure the whole of  .

However, the idea of "local strict positivity" is not too far from a workable definition:


Let (XT) be a topological space; let B(T) denote the Borel σ-algebra on X, i.e. the smallest sigma algebra on X that contains all open sets U ∈ T. Let μ be a measure on (X, B(T)). Then the support (or spectrum) of μ is defined as the set of all points x in X for which every open neighbourhood Nx of x has positive measure:


Some authors prefer to take the closure of the above set. However, this is not necessary: see "Properties" below.

An equivalent definition of support is as the largest C ∈ B(T) (with respect to inclusion) such that every open set which has non-empty intersection with C has positive measure, i.e. the largest C such that:



  • A measure μ on X is strictly positive if and only if it has support supp(μ) = X. If μ is strictly positive and x ∈ X is arbitrary, then any open neighbourhood of x, since it is an open set, has positive measure; hence, x ∈ supp(μ), so supp(μ) = X. Conversely, if supp(μ) = X, then every non-empty open set (being an open neighbourhood of some point in its interior, which is also a point of the support) has positive measure; hence, μ is strictly positive.
  • The support of a measure is closed in X as its complement is the union of the open sets of measure 0.
  • In general the support of a nonzero measure may be empty: see the examples below. However, if X is a topological Hausdorff space and μ is a Radon measure, a measurable set A outside the support has measure zero:
The converse is true if A is open, but it is not true in general: it fails if there exists a point x ∈ supp(μ) such that μ({x}) = 0 (e.g. Lebesgue measure).
Thus, one does not need to "integrate outside the support": for any measurable function f : X → R or C,
  • The concept of support of a measure and that of spectrum of a self-adjoint linear operator on a Hilbert space are closely related. Indeed, if   is a regular Borel measure on the line  , then the multiplication operator   is self-adjoint on its natural domain
and its spectrum coincides with the essential range of the identity function  , which is precisely the support of  .[1]


Lebesgue measureEdit

In the case of Lebesgue measure λ on the real line R, consider an arbitrary point x ∈ R. Then any open neighbourhood Nx of x must contain some open interval (x − εx + ε) for some ε > 0. This interval has Lebesgue measure 2ε > 0, so λ(Nx) ≥ 2ε > 0. Since x ∈ R was arbitrary, supp(λ) = R.

Dirac measureEdit

In the case of Dirac measure δp, let x ∈ R and consider two cases:

  1. if x = p, then every open neighbourhood Nx of x contains p, so δp(Nx) = 1 > 0;
  2. on the other hand, if x ≠ p, then there exists a sufficiently small open ball B around x that does not contain p, so δp(B) = 0.

We conclude that supp(δp) is the closure of the singleton set {p}, which is {p} itself.

In fact, a measure μ on the real line is a Dirac measure δp for some point p if and only if the support of μ is the singleton set {p}. Consequently, Dirac measure on the real line is the unique measure with zero variance [provided that the measure has variance at all].

A uniform distributionEdit

Consider the measure μ on the real line R defined by


i.e. a uniform measure on the open interval (0, 1). A similar argument to the Dirac measure example shows that supp(μ) = [0, 1]. Note that the boundary points 0 and 1 lie in the support: any open set containing 0 (or 1) contains an open interval about 0 (or 1), which must intersect (0, 1), and so must have positive μ-measure.

A nontrivial measure whose support is emptyEdit

The space of all countable ordinals with the topology generated by "open intervals", is a locally compact Hausdorff space. The measure ("Dieudonné measure") that assigns measure 1 to Borel sets containing an unbounded closed subset and assigns 0 to other Borel sets is a Borel probability measure whose support is empty.

A nontrivial measure whose support has measure zeroEdit

On a compact Hausdorff space the support of a non-zero measure is always non-empty, but may have measure 0. An example of this is given by adding the first uncountable ordinal Ω to the previous example: the support of the measure is the single point Ω, which has measure 0.

Signed and complex measuresEdit

Suppose that μ : Σ → [−∞, +∞] is a signed measure. Use the Hahn decomposition theorem to write


where μ± are both non-negative measures. Then the support of μ is defined to be


Similarly, if μ : Σ → C is a complex measure, the support of μ is defined to be the union of the supports of its real and imaginary parts.


  1. ^ Mathematical methods in Quantum Mechanics with applications to Schrödinger Operators
  • Ambrosio, L., Gigli, N. & Savaré, G. (2005). Gradient Flows in Metric Spaces and in the Space of Probability Measures. ETH Zürich, Birkhäuser Verlag, Basel. ISBN 3-7643-2428-7.CS1 maint: multiple names: authors list (link)
  • Parthasarathy, K. R. (2005). Probability measures on metric spaces. AMS Chelsea Publishing, Providence, RI. p. xii+276. ISBN 0-8218-3889-X. MR2169627 (See chapter 2, section 2.)
  • Teschl, Gerald (2009). Mathematical methods in Quantum Mechanics with applications to Schrödinger Operators. AMS.(See chapter 3, section 2)