Logarithmically concave measure
Encyclopedia
In mathematics
, a Borel measure μ on n-dimension
al Euclidean space
Rn is called logarithmically concave (or log-concave for short) if, for any compact subsets A and B of Rn and 0 < λ < 1, one has
where λ A + (1 − λ) B denotes the Minkowski sum of λ A and (1 − λ) B.
asserts that the Lebesgue measure
is log-concave. The restriction of the Lebesgue measure to any convex set
is also log-concave.
By a theorem of Borell, a measure is log-concave if and only if it has a density with respect to the Lebesgue measure on some affine hyperplane, and this density is a logarithmically concave function. Thus, any Gaussian measure
is log-concave.
The Prékopa–Leindler inequality shows that a convolution
of log-concave measures is log-concave.
Mathematics
Mathematics is the study of quantity, space, structure, and change. Mathematicians seek out patterns and formulate new conjectures. Mathematicians resolve the truth or falsity of conjectures by mathematical proofs, which are arguments sufficient to convince other mathematicians of their validity...
, a Borel measure μ on n-dimension
Dimension
In physics and mathematics, the dimension of a space or object is informally defined as the minimum number of coordinates needed to specify any point within it. Thus a line has a dimension of one because only one coordinate is needed to specify a point on it...
al Euclidean space
Euclidean space
In mathematics, Euclidean space is the Euclidean plane and three-dimensional space of Euclidean geometry, as well as the generalizations of these notions to higher dimensions...
Rn is called logarithmically concave (or log-concave for short) if, for any compact subsets A and B of Rn and 0 < λ < 1, one has
where λ A + (1 − λ) B denotes the Minkowski sum of λ A and (1 − λ) B.
Examples
The Brunn-Minkowski inequalityBrunn-Minkowski theorem
In mathematics, the Brunn–Minkowski theorem is an inequality relating the volumes of compact subsets of Euclidean space. The original version of the Brunn–Minkowski theorem applied to convex sets; the generalization to compact nonconvex sets stated here is due to L.A...
asserts that the Lebesgue measure
Lebesgue measure
In measure theory, 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 with the standard measure of length, area, or volume. In general, it is also called...
is log-concave. The restriction of the Lebesgue measure to any convex set
Convex set
In Euclidean space, an object is convex if for every pair of points within the object, every point on the straight line segment that joins them is also within the object...
is also log-concave.
By a theorem of Borell, a measure is log-concave if and only if it has a density with respect to the Lebesgue measure on some affine hyperplane, and this density is a logarithmically concave function. Thus, any Gaussian measure
Gaussian measure
In mathematics, Gaussian measure is a Borel measure on finite-dimensional Euclidean space Rn, closely related to the normal distribution in statistics. There is also a generalization to infinite-dimensional spaces...
is log-concave.
The Prékopa–Leindler inequality shows that a convolution
Convolution
In mathematics and, in particular, functional analysis, convolution is a mathematical operation on two functions f and g, producing a third function that is typically viewed as a modified version of one of the original functions. Convolution is similar to cross-correlation...
of log-concave measures is log-concave.