# Continuous function

In mathematics, a **continuous function** is a function that does not have any abrupt changes in value, known as discontinuities. More precisely, a function is continuous if arbitrarily small changes in its output can be assured by restricting to sufficiently small changes in its input. If not continuous, a function is said to be *discontinuous*. Up until the 19th century, mathematicians largely relied on intuitive notions of continuity, during which attempts such as the epsilon–delta definition were made to formalize it.

Continuity of functions is one of the core concepts of topology, which is treated in full generality below. The introductory portion of this article focuses on the special case where the inputs and outputs of functions are real numbers. A stronger form of continuity is uniform continuity. In addition, this article discusses the definition for the more general case of functions between two metric spaces. In order theory, especially in domain theory, one considers a notion of continuity known as Scott continuity. Other forms of continuity do exist but they are not discussed in this article.

As an example, the function *H*(*t*) denoting the height of a growing flower at time t would be considered continuous. In contrast, the function *M*(*t*) denoting the amount of money in a bank account at time t would be considered discontinuous, since it "jumps" at each point in time when money is deposited or withdrawn.

A real function, that is a function from real numbers to real numbers, can be represented by a graph in the Cartesian plane; such a function is continuous if, roughly speaking, the graph is a single unbroken curve whose domain is the entire real line. A more mathematically rigorous definition is given below.^{[7]}

A rigorous definition of continuity of real functions is usually given in a first course in calculus in terms of the idea of a limit. First, a function *f* with variable x is said to be continuous *at the point* c on the real line, if the limit of *f*(*x*), as x approaches that point c, is equal to the value *f*(c); and second, the *function (as a whole)* is said to be *continuous*, if it is continuous at every point. A function is said to be *discontinuous* (or to have a *discontinuity*) at some point when it is not continuous there. These points themselves are also addressed as *discontinuities*.

There are several different definitions of continuity of a function. Sometimes a function is said to be continuous if it is continuous at every point in its domain. In this case, the function *f*(*x*) = tan(*x*), with the domain of all real *x* ≠ (2*n*+1)π/2, *n* any integer, is continuous. Sometimes an exception is made for boundaries of the domain. For example, the graph of the function *f*(*x*) = √*x*, with the domain of all non-negative reals, has a *left-hand* endpoint. In this case only the limit from the *right* is required to equal the value of the function. Under this definition *f* is continuous at the boundary *x* = 0 and so for all non-negative arguments. The most common and restrictive definition is that a function is continuous if it is continuous at all real numbers. In this case, the previous two examples are not continuous, but every polynomial function is continuous, as are the sine, cosine, and exponential functions. Care should be exercised in using the word *continuous*, so that it is clear from the context which meaning of the word is intended.

Using mathematical notation, there are several ways to define continuous functions in each of the three senses mentioned above.

The function *f* is *continuous at some point* *c* of its domain if the limit of *f*(*x*), as *x* approaches *c* through the domain of *f*, exists and is equal to *f*(*c*).^{[8]} In mathematical notation, this is written as

In detail this means three conditions: first, *f* has to be defined at *c* (guaranteed by the requirement that *c* is in the domain of *f*). Second, the limit on the left hand side of that equation has to exist. Third, the value of this limit must equal *f*(*c*).

(Here, we have assumed that the domain of *f* does not have any isolated points.)

This definition only requires that the domain and the codomain are topological spaces and is thus the most general definition. It follows from this definition that a function *f* is automatically continuous at every isolated point of its domain. As a specific example, every real valued function on the set of integers is continuous.

Explicitly including the definition of the limit of a function, we obtain a self-contained definition:
Given a function *f* : *D* → *R* as above and an element *x*_{0} of the domain *D*, *f* is said to be continuous at the point *x*_{0} when the following holds: For any number *ε* > 0, however small, there exists some number *δ* > 0 such that for all *x* in the domain of *f* with *x*_{0} − *δ* < *x* < *x*_{0} + *δ*, the value of *f*(*x*) satisfies

Alternatively written, continuity of *f* : *D* → *R* at *x*_{0} ∈ *D* means that for every *ε* > 0 there exists a *δ* > 0 such that for all *x* ∈ *D* :

More intuitively, we can say that if we want to get all the *f*(*x*) values to stay in some small neighborhood around *f*(*x*_{0}), we simply need to choose a small enough neighborhood for the *x* values around *x*_{0}. If we can do that no matter how small the *f*(*x*) neighborhood is, then *f* is continuous at *x*_{0}.

In modern terms, this is generalized by the definition of continuity of a function with respect to a basis for the topology, here the metric topology.

Weierstrass had required that the interval *x*_{0} − *δ* < *x* < *x*_{0} + *δ* be entirely within the domain *D*, but Jordan removed that restriction.

A function is continuous in *x*_{0} if it is *C*-continuous for some control function *C*.

This definition is useful in descriptive set theory to study the set of discontinuities and continuous points – the continuous points are the intersection of the sets where the oscillation is less than *ε* (hence a G_{δ} set) – and gives a very quick proof of one direction of the Lebesgue integrability condition.^{[10]}

The oscillation is equivalent to the *ε*-*δ* definition by a simple re-arrangement, and by using a limit (lim sup, lim inf) to define oscillation: if (at a given point) for a given *ε*_{0} there is no *δ* that satisfies the *ε*-*δ* definition, then the oscillation is at least *ε*_{0}, and conversely if for every *ε* there is a desired *δ*, the oscillation is 0. The oscillation definition can be naturally generalized to maps from a topological space to a metric space.

Cauchy defined continuity of a function in the following intuitive terms: an infinitesimal change in the independent variable corresponds to an infinitesimal change of the dependent variable (see *Cours d'analyse*, page 34). Non-standard analysis is a way of making this mathematically rigorous. The real line is augmented by the addition of infinite and infinitesimal numbers to form the hyperreal numbers. In nonstandard analysis, continuity can be defined as follows.

(see microcontinuity). In other words, an infinitesimal increment of the independent variable always produces to an infinitesimal change of the dependent variable, giving a modern expression to Augustin-Louis Cauchy's definition of continuity.

Checking the continuity of a given function can be simplified by checking one of the above defining properties for the building blocks of the given function. It is straightforward to show that the sum of two functions, continuous on some domain, is also continuous on this domain. Given

In the same way it can be shown that the *reciprocal of a continuous function*

is defined for all real numbers *x* ≠ −2 and is continuous at every such point. Thus it is a continuous function. The question of continuity at *x* = −2 does not arise, since *x* = −2 is not in the domain of *y*. There is no continuous function *F*: **R** → **R** that agrees with *y*(*x*) for all *x* ≠ −2.

Since the function sine is continuous on all reals, the sinc function *G*(*x*) = sin(*x*)/*x*, is defined and continuous for all real *x* ≠ 0. However, unlike the previous example, *G* *can* be extended to a continuous function on *all* real numbers, by *defining* the value *G*(0) to be 1, which is the limit of *G*(*x*), when *x* approaches 0, i.e.,

the sinc-function becomes a continuous function on all real numbers. The term *removable singularity* is used in such cases, when (re)defining values of a function to coincide with the appropriate limits make a function continuous at specific points.

A more involved construction of continuous functions is the function composition. Given two continuous functions

Besides plausible continuities and discontinuities like above, there are also functions with a behavior, often coined pathological, for example, Thomae's function,

is continuous at all irrational numbers and discontinuous at all rational numbers. In a similar vein, Dirichlet's function, the indicator function for the set of rational numbers,

The intermediate value theorem is an existence theorem, based on the real number property of completeness, and states:

For example, if a child grows from 1 m to 1.5 m between the ages of two and six years, then, at some time between two and six years of age, the child's height must have been 1.25 m.

As a consequence, if *f* is continuous on [*a*, *b*] and *f*(*a*) and *f*(*b*) differ in sign, then, at some point *c* in [*a*, *b*], *f*(*c*) must equal zero.

The extreme value theorem states that if a function *f* is defined on a closed interval [*a*,*b*] (or any closed and bounded set) and is continuous there, then the function attains its maximum, i.e. there exists *c* ∈ [*a*,*b*] with *f*(*c*) ≥ *f*(*x*) for all *x* ∈ [*a*,*b*]. The same is true of the minimum of *f*. These statements are not, in general, true if the function is defined on an open interval (*a*,*b*) (or any set that is not both closed and bounded), as, for example, the continuous function *f*(*x*) = 1/*x*, defined on the open interval (0,1), does not attain a maximum, being unbounded above.

is continuous, as can be shown. The converse does not hold: for example, the absolute value function

is everywhere continuous. However, it is not differentiable at *x* = 0 (but is so everywhere else). Weierstrass's function is also everywhere continuous but nowhere differentiable.

The derivative *f′*(*x*) of a differentiable function *f*(*x*) need not be continuous. If *f′*(*x*) is continuous, *f*(*x*) is said to be continuously differentiable. The set of such functions is denoted *C*^{1}((*a*, *b*)). More generally, the set of functions

(from an open interval (or open subset of **R**) Ω to the reals) such that *f* is *n* times differentiable and such that the *n*-th derivative of *f* is continuous is denoted *C*^{n}(Ω). See differentiability class. In the field of computer graphics, properties related (but not identical) to *C*^{0}, *C*^{1}, *C*^{2} are sometimes called *G*^{0} (continuity of position), *G*^{1} (continuity of tangency), and *G*^{2} (continuity of curvature); see Smoothness of curves and surfaces.

is integrable (for example in the sense of the Riemann integral). The converse does not hold, as the (integrable, but discontinuous) sign function shows.

exists for all *x* in *D*, the resulting function *f*(*x*) is referred to as the pointwise limit of the sequence of functions (*f*_{n})_{n∈N}. The pointwise limit function need not be continuous, even if all functions *f*_{n} are continuous, as the animation at the right shows. However, *f* is continuous if all functions *f*_{n} are continuous and the sequence converges uniformly, by the uniform convergence theorem. This theorem can be used to show that the exponential functions, logarithms, square root function, and trigonometric functions are continuous.

Discontinuous functions may be discontinuous in a restricted way, giving rise to the concept of directional continuity (or right and left continuous functions) and semi-continuity. Roughly speaking, a function is *right-continuous* if no jump occurs when the limit point is approached from the right. Formally, *f* is said to be right-continuous at the point *c* if the following holds: For any number *ε* > 0 however small, there exists some number *δ* > 0 such that for all *x* in the domain with *c* < *x* < *c* + *δ*, the value of *f*(*x*) will satisfy

This is the same condition as for continuous functions, except that it is required to hold for *x* strictly larger than *c* only. Requiring it instead for all *x* with *c* − *δ* < *x* < *c* yields the notion of *left-continuous* functions. A function is continuous if and only if it is both right-continuous and left-continuous.

A function *f* is *lower semi-continuous* if, roughly, any jumps that might occur only go down, but not up. That is, for any *ε* > 0, there exists some number *δ* > 0 such that for all *x* in the domain with |x − c| < *δ*, the value of *f*(*x*) satisfies

The concept of continuous real-valued functions can be generalized to functions between metric spaces. A metric space is a set *X* equipped with a function (called metric) *d*_{X}, that can be thought of as a measurement of the distance of any two elements in *X*. Formally, the metric is a function

that satisfies a number of requirements, notably the triangle inequality. Given two metric spaces (*X*, d_{X}) and (*Y*, d_{Y}) and a function

then *f* is continuous at the point *c* in *X* (with respect to the given metrics) if for any positive real number ε, there exists a positive real number δ such that all *x* in *X* satisfying d_{X}(*x*, *c*) < δ will also satisfy d_{Y}(*f*(*x*), *f*(*c*)) < ε. As in the case of real functions above, this is equivalent to the condition that for every sequence (*x*_{n}) in *X* with limit lim *x*_{n} = *c*, we have lim *f*(*x*_{n}) = *f*(*c*). The latter condition can be weakened as follows: *f* is continuous at the point *c* if and only if for every convergent sequence (*x*_{n}) in *X* with limit *c*, the sequence (*f*(*x*_{n})) is a Cauchy sequence, and *c* is in the domain of *f*.

The set of points at which a function between metric spaces is continuous is a G_{δ} set – this follows from the ε-δ definition of continuity.

This notion of continuity is applied, for example, in functional analysis. A key statement in this area says that a linear operator

between normed vector spaces *V* and *W* (which are vector spaces equipped with a compatible norm, denoted ||*x*||)
is continuous if and only if it is bounded, that is, there is a constant *K* such that

The concept of continuity for functions between metric spaces can be strengthened in various ways by limiting the way δ depends on ε and *c* in the definition above. Intuitively, a function *f* as above is uniformly continuous if the δ does
not depend on the point *c*. More precisely, it is required that for every real number *ε* > 0 there exists *δ* > 0 such that for every *c*, *b* ∈ *X* with *d*_{X}(*b*, *c*) < *δ*, we have that *d*_{Y}(*f*(*b*), *f*(*c*)) < *ε*. Thus, any uniformly continuous function is continuous. The converse does not hold in general, but holds when the domain space *X* is compact. Uniformly continuous maps can be defined in the more general situation of uniform spaces.^{[13]}

A function is Hölder continuous with exponent α (a real number) if there is a constant *K* such that for all *b* and *c* in *X*, the inequality

holds. Any Hölder continuous function is uniformly continuous. The particular case α = 1 is referred to as Lipschitz continuity. That is, a function is Lipschitz continuous if there is a constant *K* such that the inequality

holds for any *b*, *c* in *X*.^{[14]} The Lipschitz condition occurs, for example, in the Picard–Lindelöf theorem concerning the solutions of ordinary differential equations.

Another, more abstract, notion of continuity is continuity of functions between topological spaces in which there generally is no formal notion of distance, as there is in the case of metric spaces. A topological space is a set *X* together with a topology on *X*, which is a set of subsets of *X* satisfying a few requirements with respect to their unions and intersections that generalize the properties of the open balls in metric spaces while still allowing to talk about the neighbourhoods of a given point. The elements of a topology are called open subsets of *X* (with respect to the topology).

between two topological spaces *X* and *Y* is continuous if for every open set *V* ⊆ *Y*, the inverse image

is an open subset of *X*. That is, *f* is a function between the sets *X* and *Y* (not on the elements of the topology *T _{X}*), but the continuity of

*f*depends on the topologies used on

*X*and

*Y*.

This is equivalent to the condition that the preimages of the closed sets (which are the complements of the open subsets) in *Y* are closed in *X*.

An extreme example: if a set *X* is given the discrete topology (in which every subset is open), all functions

to any topological space *T* are continuous. On the other hand, if *X* is equipped with the indiscrete topology (in which the only open subsets are the empty set and *X*) and the space *T* set is at least T_{0}, then the only continuous functions are the constant functions. Conversely, any function whose range is indiscrete is continuous.

The translation in the language of neighborhoods of the (ε, δ)-definition of continuity leads to the following definition of the continuity at a point:

This definition is equivalent to the same statement with neighborhoods restricted to open neighborhoods and can be restated in several ways by using preimages rather than images.

If *X* and *Y* are metric spaces, it is equivalent to consider the neighborhood system of open balls centered at *x* and *f*(*x*) instead of all neighborhoods. This gives back the above δ-ε definition of continuity in the context of metric spaces. In general topological spaces, there is no notion of nearness or distance. If however the target space is a Hausdorff space, it is still true that *f* is continuous at *a* if and only if the limit of *f* as *x* approaches *a* is *f*(*a*). At an isolated point, every function is continuous.

Several equivalent definitions for a topological structure exist and thus there are several equivalent ways to define a continuous function.

In several contexts, the topology of a space is conveniently specified in terms of limit points. In many instances, this is accomplished by specifying when a point is the limit of a sequence, but for some spaces that are too large in some sense, one specifies also when a point is the limit of more general sets of points indexed by a directed set, known as nets. A function is (Heine-)continuous only if it takes limits of sequences to limits of sequences. In the former case, preservation of limits is also sufficient; in the latter, a function may preserve all limits of sequences yet still fail to be continuous, and preservation of nets is a necessary and sufficient condition.

In detail, a function *f*: *X* → *Y* is **sequentially continuous** if whenever a sequence (*x*_{n}) in *X* converges to a limit *x*, the sequence (*f*(*x*_{n})) converges to *f*(*x*). Thus sequentially continuous functions "preserve sequential limits". Every continuous function is sequentially continuous. If *X* is a first-countable space and countable choice holds, then the converse also holds: any function preserving sequential limits is continuous. In particular, if *X* is a metric space, sequential continuity and continuity are equivalent. For non first-countable spaces, sequential continuity might be strictly weaker than continuity. (The spaces for which the two properties are equivalent are called sequential spaces.) This motivates the consideration of nets instead of sequences in general topological spaces. Continuous functions preserve limits of nets, and in fact this property characterizes continuous functions.

For instance, consider the case of real-valued functions of one real variable:^{[16]}

If *f*: *X* → *Y* and *g*: *Y* → *Z* are continuous, then so is the composition *g* ∘ *f*: *X* → *Z*. If *f*: *X* → *Y* is continuous and

The possible topologies on a fixed set *X* are partially ordered: a topology τ_{1} is said to be coarser than another topology τ_{2} (notation: τ_{1} ⊆ τ_{2}) if every open subset with respect to τ_{1} is also open with respect to τ_{2}. Then, the identity map

is continuous if and only if τ_{1} ⊆ τ_{2} (see also comparison of topologies). More generally, a continuous function

stays continuous if the topology τ_{Y} is replaced by a coarser topology and/or τ_{X} is replaced by a finer topology.

Symmetric to the concept of a continuous map is an open map, for which *images* of open sets are open. In fact, if an open map *f* has an inverse function, that inverse is continuous, and if a continuous map *g* has an inverse, that inverse is open. Given a bijective function *f* between two topological spaces, the inverse function *f*^{−1} need not be continuous. A bijective continuous function with continuous inverse function is called a *homeomorphism*.

If a continuous bijection has as its domain a compact space and its codomain is Hausdorff, then it is a homeomorphism.

where *X* is a topological space and *S* is a set (without a specified topology), the final topology on *S* is defined by letting the open sets of *S* be those subsets *A* of *S* for which *f*^{−1}(*A*) is open in *X*. If *S* has an existing topology, *f* is continuous with respect to this topology if and only if the existing topology is coarser than the final topology on *S*. Thus the final topology can be characterized as the finest topology on *S* that makes *f* continuous. If *f* is surjective, this topology is canonically identified with the quotient topology under the equivalence relation defined by *f*.

between two categories is called *continuous*, if it commutes with small limits. That is to say,

A *continuity space* is a generalization of metric spaces and posets,^{[20]}^{[21]} which uses the concept of quantales, and that can be used to unify the notions of metric spaces and domains.^{[22]}