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 Briefly, a function on a ___domain is lower semi-continuous if its epigraph is closed in , and upper semi-continuous if is lower semi-continuous.

An upper semicontinuous function that is not lower semicontinuous at . The solid blue dot indicates
A lower semicontinuous function that is not upper semicontinuous at . The solid blue dot indicates

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.

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

Definitions

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

Upper semicontinuity

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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   Here the limit superior is defined as   where the supremum is taken over all neighborhoods of  .

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

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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

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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  .

A fundamental example in real analysis is Fatou's lemma. It asserts that if   is a sequence of non-negative measurable functions, then   where   denotes the (pointwise) limit inferior. What this means, in full generality, is that if   be a measure space and   denotes the set of positive measurable functions endowed with the topology of convergence in measure with respect to   then the integral, seen as an operator from   to   is lower semicontinuous.

Properties

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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.

  • A function   is continuous if and only if it is both upper and lower semicontinuous.
  • The characteristic function or indicator function of a set   (defined by   if   and   if  ) is upper semicontinuous if and only if   is a closed set. It is lower semicontinuous if and only if   is an open set.
  • In the field 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.

Binary operations on semicontinuous functions

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Let  .

  • If   and   are lower semicontinuous, then the sum   is lower semicontinuous[6] (provided the sum is well-defined, i.e.,   is not the indeterminate form  ). The same holds for upper semicontinuous functions.
  • If   and   are lower semicontinuous and non-negative, then the product function   is lower semicontinuous. The corresponding result holds for upper semicontinuous functions.
  • The function   is lower semicontinuous if and only if   is upper semicontinuous.
  • If   and   are upper semicontinuous and   is non-decreasing, then the composition   is upper semicontinuous. On the other hand, if   is not non-decreasing, then   may not be upper semicontinuous. For example take   defined as  . Then   is continuous and  , which is not upper semicontinuous unless   is continuous.
  • If   and   are lower semicontinuous, their (pointwise) maximum and minimum (defined by   and  ) are also lower semicontinuous. Consequently, the set of all lower semicontinuous functions from   to   (or to  ) forms a lattice. The corresponding statements also hold for upper semicontinuous functions.

Optimization of semicontinuous functions

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  • The (pointwise) supremum of an arbitrary family   of lower semicontinuous functions   (defined by  ) is lower semicontinuous.[7]
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.
  • If   is a compact space (for instance a closed bounded interval  ) and   is upper semicontinuous, then   attains a maximum on   If   is lower semicontinuous on   it attains a minimum on  
(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

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  • (Theorem of Baire)[note 1] Let   be a metric space. Every lower semicontinuous function   is the limit of a point-wise increasing sequence of extended real-valued continuous functions on   In particular, there exists a sequence   of continuous functions   such that
  and
 
If   does not take the value  , the continuous functions can be taken to be real-valued.[8][9]
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.
  • Any upper semicontinuous function   on an arbitrary topological space   is locally constant on some dense open subset of  
  • If the topological space   is sequential, then   is upper semi-continuous if and only if it is sequentially upper semi-continuous, that is, if for any   and any sequence   that converges towards  , there holds  . Equivalently, in a sequential space,   is upper semicontinuous if and only if its superlevel sets   are sequentially closed for all  . In general, upper semicontinuous functions are sequentially upper semicontinuous, but the converse may be false.

Semicontinuity of set-valued functions

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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  .[10]

Upper and lower semicontinuity

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A set-valued map   is upper semicontinuous at   if for every open set   such that  , there exists a neighborhood   of   such that  [10]: 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  [10]: 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.[10]

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.[10]: 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

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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  [11][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,  ).[11]

Hulls

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Because the supremum of a family of lower semicontinuous functions is lower semicontinuous, if   is an arbitrary extended-real valued function on a topological space  , the supremum of the set of lower semicontinuous functions majorized by   is lower semicontinuous. This greatest lower semicontinuous function majorized by   is the lower semicontinuous hull of  .[12] The hull   is defined pointwise by the relation[13]   The hull   has the property that its epigraph is the closure of the epigraph of  .

The lower semicontinuous hull plays a role in convex analysis. Given a convex (extended real) function, the epigraph might not be closed. But the lower semicontinuous hull of a convex function is convex, and is known as the closure of the original convex function.

Some operations in convex analysis, such as the Legendre transform automatically produce closed convex functions. The Legendre transform applied twice to a convex function gives the closure of the original function, rather than the original function. Thus the lower semicontinuous hull is a way of regularizing convex functions, by modifying it at boundary points of its effective ___domain.

In categorical terms, the lower semicontinuous hull of a function   is the (left) Kan extension of   along the inclusion of the poset of open neighborhoods (ordered by reverse inclusion) into the topological space  . Explicitly, the value of the hull   at a point   is given by the colimit:   which coincides with  , the left Kan extension under the inclusion functor  . In this formulation, the process of taking the semicontinuous envelope is a special case of the Kan extension machinery in enriched category theory. The upper semicontinuous hull is a right Kan extension.[citation needed]

Other types of hulls are often considered in applications. For example, the infimum of the set of continuous affine functions that majorize a given function on a convex subset of a topological vector space is upper semicontinuous. This fact is used in the proof of the Choquet theorem.[14] Similar ideas applied to subharmonic functions are used in the Perron method for solving the Dirichlet problem for the Laplace operator in a ___domain. The key condition for the class of subharmonic solutions is upper semicontinuity, particularly near the boundary where the boundary conditions are applied.

Applications

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Calculus of variations

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An important application of semicontinuity is to the calculus of variations. It derives its significance in this context due to the following theorem.[15] Let   be a topological space, and  . A minimizing sequence is a sequence   in   such that   The theorem is that if   is sequentially lower semicontinuous and   is a minimizing sequence that converges to  , then   That is,   is an absolute minimum of  .

This is often combined with results such as Tonelli's theorem in functional analysis, which characterizes the weak lower semicontinuity of nonlinear functionals on Lp spaces in terms of the convexity of another function. More specialized results of this kind are useful in variational formulations of problems in partial differential equations, which relate semicontinuity of functionals given by integration to the convexity properties of the integrand, often defined on some Sobolev space. The prototypical example is the Dirichlet problem for the Laplace operator, which can be formulated as a minimization problem of the energy, subject to boundary conditions,   i.e., the integral of the squared norm of the gradient of a function over a bounded ___domain in Euclidean space. The integrand is convex in an appropriate Sobolev space, so the limit of a minimizing sequence is a solution of the Dirichlet problem. This has implications, for instance, for finite element solutions, which gives a way to construct a minimizing sequence.

Existence of saddle points

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Together with convexity assumptions, both upper and lower semicontinuity play a role in theorems guaranteeing the existence of saddle points of functions, on locally convex topological vector spaces. One such result is the minimax theorem of Fan and Sion.[16] It states that if   is a function from a pair of non-empty closed, convex sets   belonging to reflexive Banach spaces, such that

  •   is concave and upper semicontinuous for each   and
  •   is convex and lower semicontinuous for each  ,

then the set of saddle points of   is convex. If both convexity and concavity are strict, then there is at most one saddle point. If the sets   and   are bounded, then the set of saddle points is non-empty. A saddle point is by definition a point   at which  

Dimension

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Illustration of the face-dimension function   on a hexagon in the plane

Many integer-valued functions of importance are also semicontinuous. For a simple example, suppose one has a polyhedron   (or, more generally, a closed convex set) in an  -dimensional vector space. A face of   is by definition the set of maxima of some linear functional on  . Define the function   Then   is lower semicontinuous. This is intuitively because under any small perturbations, you can move from a face of lower dimension, such as an edge or vertex, to one of higher dimension, but any point of a higher dimensional face cannot be moved to one of lower dimension if the perturbation is small enough.

Another example of a similar character is that matrix rank is a lower semicontinuous function on the space of   matrices. This is because the rank can go up at matrices which are nearby, but not down. As a result of this, together with the implicit function theorem, when a Lie group acts smoothly on a smooth manifold, the dimension of the orbit through a point is lower semicontinuous (i.e., the function  ).[17]

Algebraic geometry

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More sophisticated versions of this same idea play a fundamental role in algebraic geometry, where many dimension maps with codomain in the integers are known to be semicontinuous. (For example as applied to a Newton–Okounkov body.)

In general, let   and   be schemes and   a flat and proper morphism of finite presentation. Let   be an  -module flat and of finite presentation over  . Then for any   the function   is upper semicontinuous.[18] An important special case of this theorem when additionally   are noetherian,   is projective and   is coherent can be found in the standard textbook of Hartshorne.[19]: 288  Original work in the language of hypercohomology can be found in EGA III[20] Théorème (7.7.5), citing also previous work, in particular Grauert for the complex-analytic setting.

Let   be schemes and   a morphism of finite type. The function   associates to any   the dimension of the fiber  . If   is a flat morphism of schemes of finite presentation, then   is lower semicontinuous.[21] If   is a proper morphism of schemes, then   is upper semicontinuous.[22]

Vakil collected a list of further semicontinuity results in algebraic geometry.[23]

Descriptive set theory

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Semicontinuous functions are used in descriptive set theory to define stratifications of topological spaces by complexity measures such as dimension, rank, or ordinal height.[24][25][26] Such functions often take values in an ordinal, and their semicontinuity ensures that the sets   are closed (and hence Borel in a Polish space).

A central example is the rank function on well-founded trees. Let   be a tree coded by a point in Baire space  . The rank   is defined as the supremum of the lengths of descending sequences in  . The function assigning the rank   to each tree is lower semicontinuous with respect to the natural topology on tree codes. This rank stratifies the space of trees into closed sets  , analogous to how matrix rank stratifies  .

More generally, ordinal-valued lower semicontinuous functions are used to measure the complexity of points or structures in a Polish space—such as Scott ranks of countable structures, projective ranks of sets, or Lusin–Novikov complexities of equivalence relations. These functions enable fine classification and are crucial in defining universal sets and effective parametrizations in higher levels of the projective hierarchy.

Because the preimage of an interval   under a lower semicontinuous function is closed, such functions yield canonical stratifications of topological spaces into closed (thus Borel) pieces of increasing complexity. This property is often used in proofs of reflection principles, separation theorems, and in the effective classification of Borel equivalence relations.

Dynamical systems

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In ergodic theory and topological dynamics, semicontinuity arises naturally when studying functionals on the space of invariant measures of a dynamical system. The most important example is the entropy function, which assigns to each invariant measure its measure-theoretic entropy.[27][28][29]

Let   be a topological dynamical system with   compact and   continuous. The space   of  -invariant Borel probability measures is a compact convex subset of the dual of   under the weak-* topology. The entropy map   is an upper semicontinuous function on  :  

This property plays a key role in the variational principle, which asserts that the topological entropy   is the supremum of   over all invariant measures. Upper semicontinuity guarantees that this supremum is attained when the space of measures is compact.

More generally, many functionals of interest—such as Lyapunov exponents, dimension spectra, or return time statistics—are semicontinuous on the space of invariant measures. In some cases, these semicontinuity properties are used to prove existence of measures maximizing or minimizing a given quantity, or to establish structural properties of the simplex   (e.g., that ergodic measures form a residual—dense  —set).

Similar ideas appear in the theory of joinings, where one studies invariant couplings between systems. The set of joinings is compact in the weak-* topology, and semicontinuity is used to analyze disjointness and uniqueness of invariant couplings.

See also

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Notes

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  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.

References

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  1. ^ Verry, Matthieu. "Histoire des mathématiques - René Baire".
  2. ^ a b Stromberg, p. 132, Exercise 4
  3. ^ Kurdila, A. J., Zabarankin, M. (2005). "Lower Semicontinuous Functionals". Convex Functional Analysis. 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. ^ "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".
  10. ^ a b c d e 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..
  11. ^ a b Goebel, R. K. (January 2024). "Chapter 2: Set convergence and set-valued mappings". Set-Valued, Convex, and Nonsmooth Analysis in Dynamics and Control: An Introduction. 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.
  12. ^ Rockafellar 1970.
  13. ^ Bourbaki 1966, IV.6.2.
  14. ^ Phelps 1966, Chapter 3.
  15. ^ Giusti 2003.
  16. ^ Ekeland & Témam 1999, Chapter 4.
  17. ^ Alexandrino, M. M. and Bettiol, R. G.(2015). Proper and isometric group actions. In Lecture Notes of the Unione Matematica Italiana (Vol. 23, pp. 51-84). Springer.
  18. ^ "Stacks Project — Lemma 36.32.1". Stacks.math.columbia.edu. Retrieved 2025-04-27.
  19. ^ Hartshorne, Robin (1977), Algebraic Geometry, Berlin, New York: Springer-Verlag, ISBN 978-0-387-90244-9, MR 0463157, Zbl 0367.14001, Ch. III Theorem 12.8
  20. ^ Grothendieck, Alexandre; Dieudonné, Jean (1963). "Éléments de géométrie algébrique: III. Étude cohomologique des faisceaux cohérents, Seconde partie". Publications Mathématiques de l'IHÉS. 17: 67. doi:10.1007/bf02684890. MR 0163911.
  21. ^ "Stacks Project — Lemma 37.30.4". Stacks.math.columbia.edu. Retrieved 2025-04-27.
  22. ^ "Stacks Project — Lemma 37.30.5". Stacks.math.columbia.edu. Retrieved 2025-04-27.
  23. ^ Ravi D., Vakil (2011-06-08). "Favorite semicontinuous functions?". math216.wordpress.com. Stanford University: Wordpress. Retrieved 2025-04-27.
  24. ^ Kechris, A. S. (1995). Classical Descriptive Set Theory. Springer.
  25. ^ Moschovakis, Y. N. (1980). Descriptive Set Theory. North-Holland.
  26. ^ Friedman, H., & Stanley, L. (1989). A Borel reducibility theory for classes of countable structures. J. Symbolic Logic, 54(3), 894–914.
  27. ^ Walters, P. (1982). An Introduction to Ergodic Theory. Springer.
  28. ^ Glasner, E. (2003). Ergodic Theory via Joinings. American Mathematical Society.
  29. ^ Downarowicz, T. (2011). Entropy in Dynamical Systems. Cambridge University Press.

Bibliography

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