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In mathematics, more precisely in measure theory, a measure on the
real line In elementary mathematics, a number line is a picture of a graduated straight line that serves as visual representation of the real numbers. Every point of a number line is assumed to correspond to a real number, and every real number to a po ...
is called a discrete measure (in respect to the
Lebesgue measure In measure theory, a branch of mathematics, the Lebesgue measure, named after French mathematician Henri Lebesgue, is the standard way of assigning a measure to subsets of ''n''-dimensional Euclidean space. For ''n'' = 1, 2, or 3, it coincides ...
) if it is concentrated on an at most countable set. The support need not be a discrete set. Geometrically, a discrete measure (on the real line, with respect to Lebesgue measure) is a collection of point masses.


Definition and properties

A measure \mu defined on the Lebesgue measurable sets of the real line with values in , \infty/math> is said to be discrete if there exists a (possibly finite)
sequence In mathematics, a sequence is an enumerated collection of objects in which repetitions are allowed and order matters. Like a set, it contains members (also called ''elements'', or ''terms''). The number of elements (possibly infinite) is called ...
of numbers : s_1, s_2, \dots \, such that : \mu(\mathbb R\backslash\)=0. The simplest example of a discrete measure on the real line is the Dirac delta function \delta. One has \delta(\mathbb R\backslash\)=0 and \delta(\)=1. More generally, if s_1, s_2, \dots is a (possibly finite) sequence of real numbers, a_1, a_2, \dots is a sequence of numbers in , \infty/math> of the same length, one can consider the Dirac measures \delta_ defined by : \delta_(X) = \begin 1 & \mbox s_i \in X\\ 0 & \mbox s_i \not\in X\\ \end for any Lebesgue measurable set X. Then, the measure : \mu = \sum_ a_i \delta_ is a discrete measure. In fact, one may prove that any discrete measure on the real line has this form for appropriately chosen sequences s_1, s_2, \dots and a_1, a_2, \dots


Extensions

One may extend the notion of discrete measures to more general
measure space A measure space is a basic object of measure theory, a branch of mathematics that studies generalized notions of volumes. It contains an underlying set, the subsets of this set that are feasible for measuring (the -algebra) and the method that ...
s. Given a measurable space (X, \Sigma), and two measures \mu and \nu on it, \mu is said to be discrete in respect to \nu if there exists an at most countable subset S of X such that # All singletons \ with s \in S are measurable (which implies that any subset of S is measurable) # \nu(S)=0\, # \mu(X\backslash S)=0.\, Notice that the first two requirements are always satisfied for an at most countable subset of the real line if \nu is the Lebesgue measure, so they were not necessary in the first definition above. As in the case of measures on the real line, a measure \mu on (X, \Sigma) is discrete in respect to another measure \nu on the same space if and only if \mu has the form : \mu = \sum_ a_i \delta_ where S=\, the singletons \ are in \Sigma, and their \nu measure is 0. One can also define the concept of discreteness for signed measures. Then, instead of conditions 2 and 3 above one should ask that \nu be zero on all measurable subsets of S and \mu be zero on measurable subsets of X\backslash S.


References

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External links

* {{Measure theory Measures (measure theory)