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

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
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 .

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) All sets with are open in , where .
(3) All superlevel sets with are 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 .

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) All sets with are open in , where .
(3) All sublevel sets with are closed in .
(4) The epigraph is closed in .
(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.[3] 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.[4] 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.

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 from semicontinuity over the whole domain.

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.
And 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.
(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.)

See also

Notes

  1. ^ In the context of convex analysis, the characteristic function of a set is defined differently, as if and if . With that definition, the characteristic function of any closed set is lower semicontinuous, and the characteristic function of any open set is upper semicontinuous.
  2. ^ 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.)

References

  1. ^ Verry, Matthieu. "Histoire des mathématiques - René Baire".
  2. ^ a b Stromberg, p. 132, Exercise 4
  3. ^ Willard, p. 49, problem 7K
  4. ^ 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.
  5. ^ Puterman, Martin L. (2005). Markov Decision Processes Discrete Stochastic Dynamic Programming. Wiley-Interscience. pp. 602. ISBN 978-0-471-72782-8.
  6. ^ Moore, James C. (1999). Mathematical methods for economic theory. Berlin: Springer. p. 143. ISBN 9783540662358.
  7. ^ "To show that the supremum of any collection of lower semicontinuous functions is lower semicontinuous".
  8. ^ Stromberg, p. 132, Exercise 4(g)
  9. ^ "Show that lower semicontinuous function is the supremum of an increasing sequence of continuous functions".

Bibliography