Geometric measure theory

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Short description: Study of geometric properties of sets through measure theory

In mathematics, geometric measure theory (GMT) is the study of geometric properties of sets (typically in Euclidean space) through measure theory. It allows mathematicians to extend tools from differential geometry to a much larger class of surfaces that are not necessarily smooth.

History

Geometric measure theory was born out of the desire to solve Plateau's problem (named after Joseph Plateau) which asks if for every smooth closed curve in 3 there exists a surface of least area among all surfaces whose boundary equals the given curve. Such surfaces mimic soap films.

The problem had remained open since it was posed in 1760 by Lagrange. It was solved independently in the 1930s by Jesse Douglas and Tibor Radó under certain topological restrictions. In 1960 Herbert Federer and Wendell Fleming used the theory of currents with which they were able to solve the orientable Plateau's problem analytically without topological restrictions, thus sparking geometric measure theory. Later Jean Taylor after Fred Almgren proved Plateau's laws for the kind of singularities that can occur in these more general soap films and soap bubbles clusters.

Important notions

The following objects are central in geometric measure theory:

The following theorems and concepts are also central:

Examples

The Brunn–Minkowski inequality for the n-dimensional volumes of convex bodies K and L,

vol((1λ)K+λL)1/n(1λ)vol(K)1/n+λvol(L)1/n,

can be proved on a single page and quickly yields the classical isoperimetric inequality. The Brunn–Minkowski inequality also leads to Anderson's theorem in statistics. The proof of the Brunn–Minkowski inequality predates modern measure theory; the development of measure theory and Lebesgue integration allowed connections to be made between geometry and analysis, to the extent that in an integral form of the Brunn–Minkowski inequality known as the Prékopa–Leindler inequality the geometry seems almost entirely absent.

Gauss curvature measure

The Gauss map provides a mapping from every point on a curve or a surface to a corresponding point on a unit sphere. In this example, the curvature of a 2D-surface is mapped onto a 1D unit circle.

Consider the Gauss map, which sends each point on a smooth surface to the unit vector orthogonal to its local tangent plane. This can be generalized. Let K be a closed surface in n containing the origin, and enclosing a convex region, then each point on K has one or more local supporting planes. For any zK, define NK(z) to be the set of orthogonal directions to all local supporting planes to K at z.

Now we define the multivalued Gauss map GK:𝕊n1𝕊n1 defined by GK(x)=NK(ρ(x)x)where ρ(x)x is the intersection of the ray 0x with K. This map then maps the uniform measure μ on 𝕊n1 to another measure 𝕊n1 by μK(E):=μ(GK(E))for any Borel set. This is the Gaussian curvature measure associated with K. It is a Borel measure for any K.

This then induces the inverse problem: Given a Borel measure on the sphere, is it a Gaussian curvature measure? Alexandrov showed the following:[1]: Thm. 2.21 

  • Given a Borel measure ν, there exists some such K such that ν=μK iff {v(𝕊n1)=n1(𝕊n1)v(𝕊n1ω)>n1(ω*),ω𝕊n1 compact and convex. 
  • If such a K exists, then it is unique up to dilation.

Such K can be constructed as follows: Approximate ν as the weak limit of a sequence of point-mass measures. Each is the Gaussian curvature measure of a polytope, and the sequence of polytopes converge to K.

If μK has a bounded probability density function (in the sense of a Radon–Nikodym derivative):dμKdμ(y)=ρ(y),ρ:𝕊n1[0,c]then K is continuously differentiable (that is, its tangent planes are unique and varies continuously over its surface).[1]: Thm. 2.22 

Surface area measure

Similarly, we define the surface area measure of K byνK(E):=μ(NK1(E))for any Borel set. It is a Borel measure for any K. This has an intuitive picture in as follows: Consider an open set U𝕊n1 with a single connected continuous boundary U. For each n^U, produce the supporting plane of K perpendicular to n^. As n^ runs over U, the supporting planes rub all over K and the contact points produces a (n2)-dimensional closed subset of K that encloses a (n1)-dimensional region of K. Then νK(U) is its measure.

For example, if K is a rectangle of side lengths 2a,2b in the plane, then μK is the sum of four equal point mass measures 14(δ(a,b)/a2+b2+δ(a,b)/a2+b2+δ(a,b)/a2+b2+δ(a,b)/a2+b2)but νK is the sum of four point mass measures 2bδ(1,0)+2bδ(1,0)+2aδ(0,1)+2aδ(0,1).

Others

Given a convex function u:Ω where Ω is an open subset of n, its associated Monge–Ampère measure μu on Ω is defined as μu(E):=μ(xΩu(x)), where is the subdifferential function, and μ is the Lebesque measure on n. This has applications in the study of weak solutions to the Monge–Ampère equation. It is a nonnegative, locally finite, Borel measure.[1]: Sec. 2.1 

See also

References

  1. 1.0 1.1 1.2 Figalli, Alessio (2017). The Monge-Ampère equation and its applications. Zurich lectures in advanced mathematics. Zürich: European Mathematical Society. ISBN 978-3-03719-170-5.