Moment problem

In mathematics, a moment problem arises as the result of trying to invert the mapping that takes a measure "μ" to the sequences of moments
More generally, one may consider
for an arbitrary sequence of functions "M""n".
Introduction.
In the classical setting, μ is a measure on the real line, and "M" is the sequence { "x""n" : "n" = 0, 1, 2, ... }. In this form the question appears in probability theory, asking whether there is a probability measure having specified mean, variance and so on, and whether it is unique.
There are three named classical moment problems: the Hamburger moment problem in which the support of μ is allowed to be the whole real line; the Stieltjes moment problem, for [0, +∞); and the Hausdorff moment problem for a bounded interval, which without loss of generality may be taken as [0, 1].
Existence.
A sequence of numbers "m""n" is the sequence of moments of a measure "μ" if and only if a certain positivity condition is fulfilled; namely, the Hankel matrices "H""n",
should be positive semi-definite. This is because a positive-semidefinite Hankel matrix corresponds to a linear functional formula_4 such that formula_5 and formula_6 (non-negative for sum of squares of polynomials). Assume formula_4 can be extended to formula_8. In the univariate case, a non-negative polynomial can always be written as a sum of squares. So the linear functional formula_4 is positive for all the non-negative polynomials in the univariate case. By Haviland's theorem, the linear functional has a measure form, that is formula_10. A condition of similar form is necessary and sufficient for the existence of a measure formula_11 supported on a given interval ["a", "b"].
One way to prove these results is to consider the linear functional formula_12 that sends a polynomial
to
If "m""kn" are the moments of some measure "μ" supported on ["a", "b"], then evidently
Vice versa, if () holds, one can apply the M. Riesz extension theorem and extend formula_15 to a functional on the space of continuous functions with compact support "C"0(["a", "b"]), so that
By the Riesz representation theorem, () holds iff there exists a measure "μ" supported on ["a", "b"], such that
for every "ƒ" ∈ "C"0(["a", "b"]).
Thus the existence of the measure formula_11 is equivalent to (). Using a representation theorem for positive polynomials on ["a", "b"], one can reformulate () as a condition on Hankel matrices.
See and for more details.
Uniqueness (or determinacy).
The uniqueness of "μ" in the Hausdorff moment problem follows from the Weierstrass approximation theorem, which states that polynomials are dense under the uniform norm in the space of continuous functions on [0, 1]. For the problem on an infinite interval, uniqueness is a more delicate question; see Carleman's condition, Krein's condition and .
Variations.
An important variation is the truncated moment problem, which studies the properties of measures with fixed first "k" moments (for a finite "k"). Results on the truncated moment problem have numerous applications to extremal problems, optimisation and limit theorems in probability theory. See also: Chebyshev–Markov–Stieltjes inequalities and .