Epi-convergence
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mathematical analysis Analysis is the branch of mathematics dealing with continuous functions, limit (mathematics), limits, and related theories, such as Derivative, differentiation, Integral, integration, measure (mathematics), measure, infinite sequences, series ( ...
, epi-convergence is a type of convergence for
real-valued In mathematics, value may refer to several, strongly related notions. In general, a mathematical value may be any definite mathematical object. In elementary mathematics, this is most often a number – for example, a real number such as or an ...
and extended real-valued functions. Epi-convergence is important because it is the appropriate notion of convergence with which to approximate minimization problems in the field of
mathematical optimization Mathematical optimization (alternatively spelled ''optimisation'') or mathematical programming is the selection of a best element, with regard to some criteria, from some set of available alternatives. It is generally divided into two subfiel ...
. The symmetric notion of hypo-convergence is appropriate for maximization problems.
Mosco convergence In mathematical analysis, Mosco convergence is a notion of convergence for functionals that is used in nonlinear analysis and set-valued analysis. It is a particular case of Γ-convergence. Mosco convergence is sometimes phrased as “weak Γ-li ...
is a generalization of epi-convergence to infinite dimensional spaces.


Definition

Let X be a
metric space In mathematics, a metric space is a Set (mathematics), set together with a notion of ''distance'' between its Element (mathematics), elements, usually called point (geometry), points. The distance is measured by a function (mathematics), functi ...
, and f_: X \to \mathbb a real-valued function for each
natural number In mathematics, the natural numbers are the numbers 0, 1, 2, 3, and so on, possibly excluding 0. Some start counting with 0, defining the natural numbers as the non-negative integers , while others start with 1, defining them as the positive in ...
n . We say that the sequence (f^) epi-converges to a function f: X \to \mathbb if for each x \in X : \begin & \liminf_ f_(x_n) \geq f(x) \text x_n \to x \text \\ & \limsup_ f_n(x_n) \leq f(x) \text x_n \to x. \end


Extended real-valued extension

The following extension allows epi-convergence to be applied to a sequence of functions with non-constant domain. Denote by \overline= \mathbb \cup \ the
extended real numbers In mathematics, the extended real number system is obtained from the real number system \R by adding two elements denoted +\infty and -\infty that are respectively greater and lower than every real number. This allows for treating the potential ...
. Let f_n be a function f_n:X \to \overline for each n \in \mathbb . The sequence (f_n) epi-converges to f: X \to \overline if for each x \in X : \begin & \liminf_ f_(x_n) \geq f(x) \text x_n \to x \text \\ & \limsup_ f_n(x_n) \leq f(x) \text x_n \to x. \end In fact, epi-convergence coincides with the \Gamma-convergence in first countable spaces.


Hypo-convergence

Epi-convergence is the appropriate topology with which to approximate minimization problems. For maximization problems one uses the symmetric notion of hypo-convergence. (f_n) hypo-converges to f if : \limsup_ f_n(x_n) \leq f(x) \text x_n \to x and : \liminf_ f_n(x_n) \geq f(x) \text x_n \to x.


Relationship to minimization problems

Assume we have a difficult minimization problem : \inf_ g(x) where g: X \to \mathbb and C \subseteq X . We can attempt to approximate this problem by a sequence of easier problems : \inf_ g_n(x) for functions g_n and sets C_n . Epi-convergence provides an answer to the question: In what sense should the approximations converge to the original problem in order to guarantee that approximate solutions converge to a solution of the original? We can embed these optimization problems into the epi-convergence framework by defining extended real-valued functions : \begin f(x) & = \begin g(x), & x \in C, \\ \infty, & x \not \in C, \end \\ ptf_n(x) & = \begin g_n(x), & x \in C_n, \\ \infty, & x \not \in C_n. \end \end So that the problems \inf_ f(x) and \inf_ f_n(x) are equivalent to the original and approximate problems, respectively. If (f_n) epi-converges to f , then \limsup_ inf f_n\leq \inf f . Furthermore, if x is a limit point of minimizers of f_n , then x is a minimizer of f . In this sense, : \lim_ \operatorname f_n \subseteq \operatorname f. Epi-convergence is the weakest notion of convergence for which this result holds.


Properties

* (f_n) epi-converges to f if and only if (-f_n) hypo-converges to -f . * (f_n) epi-converges to f if and only if (\operatorname f_n) converges to \operatorname f as sets, in the Painlevé–Kuratowski sense of set convergence. Here, \operatorname f is the epigraph of the function f . * If f_n epi-converges to f , then f is lower semi-continuous. * If f_n is convex for each n \in \mathbb and (f_n) epi-converges to f , then f is convex. * If f^1_ \leq f_n \leq f^2_ and both (f^1_n) and (f^2_n) epi-converge to f , then (f_n) epi-converges to f . * If (f_n) converges uniformly to f on each compact set of \mathbb_n and (f_n) are continuous, then (f_n) epi-converges and hypo-converges to f . * In general, epi-convergence neither implies nor is implied by
pointwise convergence In mathematics, pointwise convergence is one of Modes of convergence (annotated index), various senses in which a sequence of function (mathematics), functions can Limit (mathematics), converge to a particular function. It is weaker than uniform co ...
. Additional assumptions can be placed on an pointwise convergent family of functions to guarantee epi-convergence.


References

* * * {{cite journal , last1=Attouch , first1=Hedy , last2=Wets , first2=Roger , authorlink2=Roger Wets , title=Epigraphical analysis , journal=Annales de l'Institut Henri Poincaré C , volume=6 , pages=73–100 , date=1989 , doi=10.1016/S0294-1449(17)30036-7, bibcode=1989AIHPC...6...73A Series (mathematics) Topology of function spaces Convergence (mathematics)