Semi-continuity

Last updated

In mathematical analysis, semicontinuity (or semi-continuity) is a property of extended real-valued functions that is weaker than continuity. An extended real-valued function is upper (respectively, lower) semicontinuous at a point if, roughly speaking, the function values for arguments near are not much higher (respectively, lower) than

Contents

A function is continuous if and only if it is both upper and lower semicontinuous. If we take a continuous function and increase its value at a certain point to for some , then the result is upper semicontinuous; if we decrease its value to then the result is lower semicontinuous.

An upper semicontinuous function that is not lower semicontinuous. The solid blue dot indicates
f
(
x
0
)
.
{\displaystyle f\left(x_{0}\right).} Upper semi.svg
An upper semicontinuous function that is not lower semicontinuous. The solid blue dot indicates
A lower semicontinuous function that is not upper semicontinuous. The solid blue dot indicates
f
(
x
0
)
.
{\displaystyle f\left(x_{0}\right).} Lower semi.svg
A lower semicontinuous function that is not upper semicontinuous. The solid blue dot indicates

The notion of upper and lower semicontinuous function was first introduced and studied by René Baire in his thesis in 1899. [1]

Definitions

Assume throughout that is a topological space and is a function with values in the extended real numbers .

Upper semicontinuity

A function is called upper semicontinuous at a point if for every real there exists a neighborhood of such that for all . [2] Equivalently, is upper semicontinuous at if and only if where lim sup is the limit superior of the function at the point

If is a metric space with distance function and this can also be restated using an - formulation, similar to the definition of continuous function. Namely, for each there is a such that whenever

A function is called upper semicontinuous if it satisfies any of the following equivalent conditions: [2]

(1) The function is upper semicontinuous at every point of its domain.
(2) For each , the set is open in , where .
(3) For each , the -superlevel set is closed in .
(4) The hypograph is closed in .
(5) The function is continuous when the codomain is given the left order topology. This is just a restatement of condition (2) since the left order topology is generated by all the intervals .

Lower semicontinuity

A function is called lower semicontinuous at a point if for every real there exists a neighborhood of such that for all . Equivalently, is lower semicontinuous at if and only if where is the limit inferior of the function at point

If is a metric space with distance function and this can also be restated as follows: For each there is a such that whenever

A function is called lower semicontinuous if it satisfies any of the following equivalent conditions:

(1) The function is lower semicontinuous at every point of its domain.
(2) For each , the set is open in , where .
(3) For each , the -sublevel set is closed in .
(4) The epigraph is closed in . [3] :207
(5) The function is continuous when the codomain is given the right order topology. This is just a restatement of condition (2) since the right order topology is generated by all the intervals .

Examples

Consider the function piecewise defined by: This function is upper semicontinuous at but not lower semicontinuous.

The floor function which returns the greatest integer less than or equal to a given real number is everywhere upper semicontinuous. Similarly, the ceiling function is lower semicontinuous.

Upper and lower semicontinuity bear no relation to continuity from the left or from the right for functions of a real variable. Semicontinuity is defined in terms of an ordering in the range of the functions, not in the domain. [4] For example the function is upper semicontinuous at while the function limits from the left or right at zero do not even exist.

If is a Euclidean space (or more generally, a metric space) and is the space of curves in (with the supremum distance ), then the length functional which assigns to each curve its length is lower semicontinuous. [5] As an example, consider approximating the unit square diagonal by a staircase from below. The staircase always has length 2, while the diagonal line has only length .

Let be a measure space and let denote the set of positive measurable functions endowed with the topology of convergence in measure with respect to Then by Fatou's lemma the integral, seen as an operator from to is lower semicontinuous.

Tonelli's theorem in functional analysis characterizes the weak lower semicontinuity of nonlinear functionals on Lp spaces in terms of the convexity of another function.

Properties

Unless specified otherwise, all functions below are from a topological space to the extended real numbers Several of the results hold for semicontinuity at a specific point, but for brevity they are only stated for semicontinuity over the whole domain.

Binary Operations on Semicontinuous Functions

Let .

Optimization of Semicontinuous Functions

In particular, the limit of a monotone increasing sequence of continuous functions is lower semicontinuous. (The Theorem of Baire below provides a partial converse.) The limit function will only be lower semicontinuous in general, not continuous. An example is given by the functions defined for for
Likewise, the infimum of an arbitrary family of upper semicontinuous functions is upper semicontinuous. And the limit of a monotone decreasing sequence of continuous functions is upper semicontinuous.
(Proof for the upper semicontinuous case: By condition (5) in the definition, is continuous when is given the left order topology. So its image is compact in that topology. And the compact sets in that topology are exactly the sets with a maximum. For an alternative proof, see the article on the extreme value theorem.)

Other Properties

and
If does not take the value , the continuous functions can be taken to be real-valued. [9] [10]
Additionally, every upper semicontinuous function is the limit of a monotone decreasing sequence of extended real-valued continuous functions on if does not take the value the continuous functions can be taken to be real-valued.

Semicontinuity of Set-valued Functions

For set-valued functions, several concepts of semicontinuity have been defined, namely upper, lower, outer, and inner semicontinuity, as well as upper and lower hemicontinuity . A set-valued function from a set to a set is written For each the function defines a set The preimage of a set under is defined as That is, is the set that contains every point in such that is not disjoint from . [11]

Upper and Lower Semicontinuity

A set-valued map is upper semicontinuous at if for every open set such that , there exists a neighborhood of such that [11] :Def. 2.1

A set-valued map is lower semicontinuous at if for every open set such that there exists a neighborhood of such that [11] :Def. 2.2

Upper and lower set-valued semicontinuity are also defined more generally for a set-valued maps between topological spaces by replacing and in the above definitions with arbitrary topological spaces. [11]

Note, that there is not a direct correspondence between single-valued lower and upper semicontinuity and set-valued lower and upper semicontinuouty. An upper semicontinuous single-valued function is not necessarily upper semicontinuous when considered as a set-valued map. [11] :18 For example, the function defined by is upper semicontinuous in the single-valued sense but the set-valued map is not upper semicontinuous in the set-valued sense.

Inner and Outer Semicontinuity

A set-valued function is called inner semicontinuous at if for every and every convergent sequence in such that , there exists a sequence in such that and for all sufficiently large [12] [note 2]

A set-valued function is called outer semicontinuous at if for every convergence sequence in such that and every convergent sequence in such that for each the sequence converges to a point in (that is, ). [12]

See also

Notes

  1. The result was proved by René Baire in 1904 for real-valued function defined on . It was extended to metric spaces by Hans Hahn in 1917, and Hing Tong showed in 1952 that the most general class of spaces where the theorem holds is the class of perfectly normal spaces. (See Engelking, Exercise 1.7.15(c), p. 62 for details and specific references.)
  2. In particular, there exists such that for every natural number . The necessisty of only considering the tail of comes from the fact that for small values of the set may be empty.

Related Research Articles

In mathematics, a continuous function is a function such that a small variation of the argument induces a small variation of the value of the function. This implies there are no abrupt changes in value, known as discontinuities. More precisely, a function is continuous if arbitrarily small changes in its value can be assured by restricting to sufficiently small changes of its argument. A discontinuous function is a function that is not continuous. Until the 19th century, mathematicians largely relied on intuitive notions of continuity and considered only continuous functions. The epsilon–delta definition of a limit was introduced to formalize the definition of continuity.

In mathematics, the branch of real analysis studies the behavior of real numbers, sequences and series of real numbers, and real functions. Some particular properties of real-valued sequences and functions that real analysis studies include convergence, limits, continuity, smoothness, differentiability and integrability.

In mathematics, a topological space is called separable if it contains a countable, dense subset; that is, there exists a sequence of elements of the space such that every nonempty open subset of the space contains at least one element of the sequence.

<span class="mw-page-title-main">Tietze extension theorem</span> Continuous maps on a closed subset of a normal space can be extended

In topology, the Tietze extension theorem states that any real-valued, continuous function on a closed subset of a normal topological space can be extended to the entire space, preserving boundedness if necessary.

In topology, the closure of a subset S of points in a topological space consists of all points in S together with all limit points of S. The closure of S may equivalently be defined as the union of S and its boundary, and also as the intersection of all closed sets containing S. Intuitively, the closure can be thought of as all the points that are either in S or "very near" S. A point which is in the closure of S is a point of closure of S. The notion of closure is in many ways dual to the notion of interior.

<span class="mw-page-title-main">Extended real number line</span> Real numbers with +∞ and −∞ added

In mathematics, the extended real number system is obtained from the real number system by adding two elements denoted and that are respectively greater and lower than every real number. This allows for treating the potential infinities of infinitely increasing sequences and infinitely decreasing series as actual infinities. For example, the infinite sequence of the natural numbers increases infinitively and has no upper bound in the real number system ; in the extended real number line, the sequence has as its least upper bound and as its limit. In calculus and mathematical analysis, the use of and as actual limits extends significantly the possible computations. It is the Dedekind–MacNeille completion of the real numbers.

Distributions, also known as Schwartz distributions or generalized functions, are objects that generalize the classical notion of functions in mathematical analysis. Distributions make it possible to differentiate functions whose derivatives do not exist in the classical sense. In particular, any locally integrable function has a distributional derivative.

In mathematics, a function space is a set of functions between two fixed sets. Often, the domain and/or codomain will have additional structure which is inherited by the function space. For example, the set of functions from any set X into a vector space has a natural vector space structure given by pointwise addition and scalar multiplication. In other scenarios, the function space might inherit a topological or metric structure, hence the name function space.

In mathematics, more specifically in topology, an open map is a function between two topological spaces that maps open sets to open sets. That is, a function is open if for any open set in the image is open in Likewise, a closed map is a function that maps closed sets to closed sets. A map may be open, closed, both, or neither; in particular, an open map need not be closed and vice versa.

In functional analysis and related areas of mathematics, locally convex topological vector spaces (LCTVS) or locally convex spaces are examples of topological vector spaces (TVS) that generalize normed spaces. They can be defined as topological vector spaces whose topology is generated by translations of balanced, absorbent, convex sets. Alternatively they can be defined as a vector space with a family of seminorms, and a topology can be defined in terms of that family. Although in general such spaces are not necessarily normable, the existence of a convex local base for the zero vector is strong enough for the Hahn–Banach theorem to hold, yielding a sufficiently rich theory of continuous linear functionals.

In general topology and related areas of mathematics, the final topology on a set with respect to a family of functions from topological spaces into is the finest topology on that makes all those functions continuous.

In mathematics, upper hemicontinuity and lower hemicontinuity are extensions of the notions of upper and lower semicontinuity of single-valued functions to set-valued functions. A set-valued function that is both upper and lower hemicontinuous is said to be continuous in an analogy to the property of the same name for single-valued functions.

In the field of mathematical analysis for the calculus of variations, Γ-convergence (Gamma-convergence) is a notion of convergence for functionals. It was introduced by Ennio De Giorgi.

In mathematics, subharmonic and superharmonic functions are important classes of functions used extensively in partial differential equations, complex analysis and potential theory.

In mathematics, Tonelli's theorem in functional analysis is a fundamental result on the weak lower semicontinuity of nonlinear functionals on Lp spaces. As such, it has major implications for functional analysis and the calculus of variations. Roughly, it shows that weak lower semicontinuity for integral functionals is equivalent to convexity of the integral kernel. The result is attributed to the Italian mathematician Leonida Tonelli.

In mathematics, Kuratowski convergence or Painlevé-Kuratowski convergence is a notion of convergence for subsets of a topological space. First introduced by Paul Painlevé in lectures on mathematical analysis in 1902, the concept was popularized in texts by Felix Hausdorff and Kazimierz Kuratowski. Intuitively, the Kuratowski limit of a sequence of sets is where the sets "accumulate".

In topology and related areas of mathematics, a subset A of a topological space X is said to be dense in X if every point of X either belongs to A or else is arbitrarily "close" to a member of A — for instance, the rational numbers are a dense subset of the real numbers because every real number either is a rational number or has a rational number arbitrarily close to it. Formally, is dense in if the smallest closed subset of containing is itself.

In mathematics, the direct method in the calculus of variations is a general method for constructing a proof of the existence of a minimizer for a given functional, introduced by Stanisław Zaremba and David Hilbert around 1900. The method relies on methods of functional analysis and topology. As well as being used to prove the existence of a solution, direct methods may be used to compute the solution to desired accuracy.

In the mathematical discipline of functional analysis, a differentiable vector-valued function from Euclidean space is a differentiable function valued in a topological vector space (TVS) whose domains is a subset of some finite-dimensional Euclidean space. It is possible to generalize the notion of derivative to functions whose domain and codomain are subsets of arbitrary topological vector spaces (TVSs) in multiple ways. But when the domain of a TVS-valued function is a subset of a finite-dimensional Euclidean space then many of these notions become logically equivalent resulting in a much more limited number of generalizations of the derivative and additionally, differentiability is also more well-behaved compared to the general case. This article presents the theory of -times continuously differentiable functions on an open subset of Euclidean space , which is an important special case of differentiation between arbitrary TVSs. This importance stems partially from the fact that every finite-dimensional vector subspace of a Hausdorff topological vector space is TVS isomorphic to Euclidean space so that, for example, this special case can be applied to any function whose domain is an arbitrary Hausdorff TVS by restricting it to finite-dimensional vector subspaces.

In mathematical analysis, the spaces of test functions and distributions are topological vector spaces (TVSs) that are used in the definition and application of distributions. Test functions are usually infinitely differentiable complex-valued functions on a non-empty open subset that have compact support. The space of all test functions, denoted by is endowed with a certain topology, called the canonical LF-topology, that makes into a complete Hausdorff locally convex TVS. The strong dual space of is called the space of distributions on and is denoted by where the "" subscript indicates that the continuous dual space of denoted by is endowed with the strong dual topology.

References

  1. Verry, Matthieu. "Histoire des mathématiques - René Baire".
  2. 1 2 Stromberg, p. 132, Exercise 4
  3. Kurdila, A. J., Zabarankin, M. (2005). "Convex Functional Analysis". Lower Semicontinuous Functionals. Systems & Control: Foundations & Applications (1st ed.). Birkhäuser-Verlag. pp. 205–219. doi:10.1007/3-7643-7357-1_7. ISBN   978-3-7643-2198-7.
  4. Willard, p. 49, problem 7K
  5. Giaquinta, Mariano (2007). Mathematical analysis : linear and metric structures and continuity. Giuseppe Modica (1 ed.). Boston: Birkhäuser. Theorem 11.3, p.396. ISBN   978-0-8176-4514-4. OCLC   213079540.
  6. Puterman, Martin L. (2005). Markov Decision Processes Discrete Stochastic Dynamic Programming . Wiley-Interscience. pp.  602. ISBN   978-0-471-72782-8.
  7. Moore, James C. (1999). Mathematical methods for economic theory . Berlin: Springer. p.  143. ISBN   9783540662358.
  8. "To show that the supremum of any collection of lower semicontinuous functions is lower semicontinuous".
  9. Stromberg, p. 132, Exercise 4(g)
  10. "Show that lower semicontinuous function is the supremum of an increasing sequence of continuous functions".
  11. 1 2 3 4 5 Freeman, R. A., Kokotović, P. (1996). Robust Nonlinear Control Design. Birkhäuser Boston. doi:10.1007/978-0-8176-4759-9. ISBN   978-0-8176-4758-2..
  12. 1 2 Goebel, R. K. (January 2024). "Set-Valued, Convex, and Nonsmooth Analysis in Dynamics and Control: An Introduction". Chapter 2: Set convergence and set-valued mappings. Other Titles in Applied Mathematics. Society for Industrial and Applied Mathematics. pp. 21–36. doi:10.1137/1.9781611977981.ch2. ISBN   978-1-61197-797-4.

Bibliography