Examples

Continuous (C⁰) but not differentiable

The function $${\displaystyle f(x)={\begin{cases}x&{\mbox{if }}x\geq 0,\\0&{\text{if }}x<0\end{cases}}}$$ is continuous, but not differentiable at x = 0, so it is of class C⁰, but not of class C¹.

Multivariate differentiability classes

A function ${\displaystyle f:U\subseteq \mathbb {R} ^{n}\to \mathbb {R} }$ defined on an open set ${\displaystyle U}$ of ${\displaystyle \mathbb {R} ^{n}}$ is said^[3] to be of class ${\displaystyle C^{k}}$ on ${\displaystyle U}$, for a positive integer ${\displaystyle k}$, if all partial derivatives $${\displaystyle D^{\alpha }f={\frac {\partial ^{|\alpha |}f}{\partial x_{1}^{\alpha _{1}}\,\partial x_{2}^{\alpha _{2}}\,\cdots \,\partial x_{n}^{\alpha _{n}}}}}$$ exist and are continuous for every multi-index ${\displaystyle \alpha =(\alpha _{1},\alpha _{2},\ldots ,\alpha _{n})}$ of non-negative integers with ${\displaystyle |\alpha |=\alpha _{1}+\alpha _{2}+\cdots +\alpha _{n}\leq k}$. Equivalently, in finite dimensions, ${\displaystyle f}$ is of class ${\displaystyle C^{k}}$ on ${\displaystyle U}$ if it is ${\displaystyle k}$ times continuously Fréchet differentiable on ${\displaystyle U}$. The function ${\displaystyle f}$ is said to be of class ${\displaystyle C}$ or ${\displaystyle C^{0}}$ if it is continuous on ${\displaystyle U}$. Functions of class ${\displaystyle C^{1}}$ are also said to be continuously differentiable.

A function ${\displaystyle f:U\subset \mathbb {R} ^{n}\to \mathbb {R} ^{m}}$, defined on an open set ${\displaystyle U}$ of ${\displaystyle \mathbb {R} ^{n}}$, is said to be of class ${\displaystyle C^{k}}$ on ${\displaystyle U}$, for a positive integer ${\displaystyle k}$, if all of its components $${\displaystyle f_{i}=\pi _{i}\circ f\quad {\text{for }}i=1,2,3,\ldots ,m}$$ are of class ${\displaystyle C^{k}}$, where ${\displaystyle \pi _{i}}$ are the natural projections ${\displaystyle \pi _{i}:\mathbb {R} ^{m}\to \mathbb {R} }$ defined by ${\displaystyle \pi _{i}(x_{1},x_{2},\ldots ,x_{m})=x_{i}}$. It is said to be of class ${\displaystyle C}$ or ${\displaystyle C^{0}}$ if it is continuous, or equivalently, if all components ${\displaystyle f_{i}}$ are continuous, on ${\displaystyle U}$.

Open domains

Let ${\displaystyle D}$ be an open subset of ${\displaystyle \mathbb {R} ^{n}}$. The set of all real-valued ${\displaystyle C^{k}}$ functions on ${\displaystyle D}$ is denoted ${\displaystyle C^{k}(D)}$. With the compact-open ${\displaystyle C^{k}}$ topology, ${\displaystyle C^{k}(D)}$ is a Fréchet space. One way to describe this topology is by the family of seminorms $${\displaystyle p_{K,\alpha }(f)=\sup _{x\in K}|D^{\alpha }f(x)|,}$$ where ${\displaystyle K}$ ranges over compact subsets of ${\displaystyle D}$ and ${\displaystyle \alpha }$ ranges over multi-indices with ${\displaystyle |\alpha |\leq k}$.

Compact domains

If ${\displaystyle U\subset \mathbb {R} ^{n}}$ is bounded and open, then ${\displaystyle C^{k}({\overline {U}})}$ denotes the space of functions on ${\displaystyle U}$ whose partial derivatives of order at most ${\displaystyle k}$ extend continuously to the compact set ${\displaystyle {\overline {U}}}$.^[4] It is a Banach space with the norm $${\displaystyle \|f\|_{C^{k}({\overline {U}})}=\max _{|\alpha |\leq k}\sup _{x\in {\overline {U}}}|D^{\alpha }f(x)|.}$$ Equivalently, one may use the sum of these suprema over ${\displaystyle |\alpha |\leq k}$; the resulting norm is equivalent.

Under pointwise addition and multiplication, ${\displaystyle C^{k}({\overline {U}})}$ is a commutative Banach algebra. The algebra property follows from the Leibniz rule, which expresses each derivative of a product in terms of derivatives of the factors of order at most ${\displaystyle k}$.

More generally, if ${\displaystyle M}$ is a compact smooth manifold, possibly with boundary, then ${\displaystyle C^{k}(M)}$ is a Banach space. Its norm may be defined using a finite collection of coordinate charts and a partition of unity; different such choices give equivalent norms. With pointwise multiplication, ${\displaystyle C^{k}(M)}$ is again a Banach algebra. By contrast, ${\displaystyle C^{\infty }(M)}$ is generally not a Banach space; on a compact manifold it is naturally a Fréchet space, with seminorms controlling derivatives of all orders.

The Gelfand spectrum of ${\displaystyle C^{k}(M)}$ is ${\displaystyle M}$ itself. Thus the Gelfand transform gives an injective (but not surjective) map ${\displaystyle C^{k}(M)\to C^{0}(M)}$.^{[5]: Exercise 11.9}

Density

The above spaces occur naturally in applications where functions having derivatives of certain orders are necessary; however, particularly in the study of partial differential equations, it can sometimes be more fruitful to work instead with Sobolev spaces.

Smooth compactly supported functions are dense in many function spaces used in analysis, such as ${\displaystyle L^{p}}$ spaces and Sobolev spaces under suitable hypotheses. These correspond to putting topologies on the smooth functions that are weaker than those of uniform convergence (like the ${\displaystyle L^{p}}$ norm). This makes smooth functions useful as test functions and as approximations to less regular functions.

Parametric continuity

Parametric continuity (C^k) is a concept applied to parametric curves, which describes the smoothness of the curve as a function of its parameter. A (parametric) curve ${\displaystyle s:[0,1]\to \mathbb {R} ^{n}}$ is said to be of class C^k if the derivatives of ${\displaystyle s}$ up to order ${\displaystyle k}$ exist and are continuous on ${\displaystyle [0,1]}$, where derivatives at the end-points ${\displaystyle 0}$ and ${\displaystyle 1}$ are taken to be one-sided derivatives (from the right at ${\displaystyle 0}$ and from the left at ${\displaystyle 1}$).

As a practical application of this concept, a curve describing the motion of an object with a parameter of time has C¹ continuity when its velocity varies continuously, and C² continuity when its acceleration varies continuously. For smoother motion, such as that of a camera's path while making a film, higher orders of parametric continuity may be required.

Order of parametric continuity

The various orders of parametric continuity can be described as follows:^[10]

• ${\displaystyle C^{0}}$: zeroth derivative is continuous (curves are continuous)
• ${\displaystyle C^{1}}$: zeroth and first derivatives are continuous
• ${\displaystyle C^{2}}$: zeroth, first and second derivatives are continuous
• ${\displaystyle C^{n}}$: 0-th through ${\displaystyle n}$-th derivatives are continuous

Geometric continuity

A curve or surface can be described as having ${\displaystyle G^{n}}$ continuity, with ${\displaystyle n}$ being an increasing measure of smoothness. Consider the segments on either side of a point on a curve:

• ${\displaystyle G^{0}}$: The curves touch at the join point.
• ${\displaystyle G^{1}}$: The curves also share a common tangent direction at the join point.
• ${\displaystyle G^{2}}$: The curves also share a common center of curvature at the join point.

In general, ${\displaystyle G^{n}}$ continuity holds when the curves can be reparameterized so that they have ${\displaystyle C^{n}}$ parametric continuity.^[11][12] A reparametrization of the curve is geometrically identical to the original; only the parameter is affected.

Equivalently, two vector functions ${\displaystyle f(t)}$ and ${\displaystyle g(t)}$ such that ${\displaystyle f(1)=g(0)}$ have ${\displaystyle G^{n}}$ continuity at the point where they meet if they satisfy equations known as Beta-constraints. For example, the Beta-constraints for ${\displaystyle G^{4}}$ continuity are:

${\displaystyle {\begin{aligned}g^{(1)}(0)&=\beta _{1}f^{(1)}(1)\\g^{(2)}(0)&=\beta _{1}^{2}f^{(2)}(1)+\beta _{2}f^{(1)}(1)\\g^{(3)}(0)&=\beta _{1}^{3}f^{(3)}(1)+3\beta _{1}\beta _{2}f^{(2)}(1)+\beta _{3}f^{(1)}(1)\\g^{(4)}(0)&=\beta _{1}^{4}f^{(4)}(1)+6\beta _{1}^{2}\beta _{2}f^{(3)}(1)+(4\beta _{1}\beta _{3}+3\beta _{2}^{2})f^{(2)}(1)+\beta _{4}f^{(1)}(1)\\\end{aligned}}}$

where ${\displaystyle \beta _{2}}$, ${\displaystyle \beta _{3}}$, and ${\displaystyle \beta _{4}}$ are arbitrary, but ${\displaystyle \beta _{1}}$ is constrained to be positive.^[11]: 65 In the case ${\displaystyle n=1}$, this reduces to ${\displaystyle f'(1)\neq 0}$ and ${\displaystyle f'(1)=kg'(0)}$, for a scalar ${\displaystyle k>0}$ (i.e., the direction, but not necessarily the magnitude, of the two vectors is equal).

While it may be obvious that a curve would require ${\displaystyle G^{1}}$ continuity to appear smooth, for good aesthetics, such as those aspired to in architecture and sports car design, higher levels of geometric continuity are required. For example, class A surface requires ${\displaystyle G^{2}}$ or higher continuity to ensure smooth reflections in a car body.

A rounded rectangle (with ninety-degree circular arcs at the four corners) has ${\displaystyle G^{1}}$ continuity, but does not have ${\displaystyle G^{2}}$ continuity. The same is true for a rounded cube, with octants of a sphere at its corners and quarter-cylinders along its edges. If an editable curve with ${\displaystyle G^{2}}$ continuity is required, then cubic splines are typically chosen; these curves are frequently used in industrial design.

Relation to analyticity

While all analytic functions are smooth on the set on which they are analytic, examples such as bump functions (mentioned above) show that the converse is not true for functions on the reals: there exist smooth real functions that are not analytic. Simple examples of functions that are smooth but not analytic at any point can be made by means of Fourier series; another example is the Fabius function. Although it might seem that such functions are the exception rather than the rule, analytic functions form a small subclass of smooth functions; for example, with suitable topologies on spaces of smooth functions, analytic functions form a meagre subset of the smooth functions.^[13] Furthermore, for every open subset A of the real line, there exist smooth functions that are analytic on A and nowhere else.^[14]

The situation thus described is in marked contrast to complex differentiable functions. If a complex function is holomorphic on an open set, it is infinitely differentiable and analytic on that set.^[15]

A theorem of Émile Borel states that every formal power series occurs as the Taylor series of some smooth function. This is another way in which smooth functions differ from analytic functions, whose Taylor series determine them locally.

Smoothness and the Fourier transform

Under suitable hypotheses, higher differentiability of a function is related to faster decay of its Laplace transform or Fourier transform. For example, integration by parts gives decay estimates for Fourier transforms of functions whose derivatives satisfy appropriate integrability or boundary conditions. These relationships are related to results such as the Paley–Wiener theorem.

Conversely, decay of the Fourier transform can imply differentiability or continuity properties of the original function. This is often formulated using Sobolev spaces: Fourier-transform decay gives Sobolev regularity, and the Sobolev embedding theorem gives conditions under which Sobolev regularity implies classical ${\displaystyle C^{k}}$ smoothness.

Test functions and distributions

Smooth compactly supported functions, usually denoted ${\displaystyle C_{c}^{\infty }(U)}$, are called test functions. They are used to define distributions and weak derivatives.

Smooth partitions of unity

Smooth functions with suitably controlled support, especially smooth functions with compact support, are used in the construction of smooth partitions of unity (see partition of unity and topology glossary); these are essential in the study of smooth manifolds, for example to show that Riemannian metrics can be defined globally starting from their local existence. A simple case is that of a bump function on the real line, that is, a smooth function f that takes the value 0 outside an interval [a,b] and such that $${\displaystyle f(x)>0\quad {\text{ for }}\quad a<x<b.\,}$$

Given a locally finite collection of overlapping intervals on the line, bump functions can be constructed on each of them, and on semi-infinite intervals ${\displaystyle (-\infty ,c]}$ and ${\displaystyle [d,+\infty )}$ to cover the whole line, such that the sum of the functions is always 1.

From what has just been said, partitions of unity do not apply to holomorphic functions in the same way; for example, there are no nonzero holomorphic functions with compact support on a connected complex domain. Their different behavior relative to existence and analytic continuation is one of the roots of sheaf theory. In contrast, sheaves of smooth functions are fine and hence have different cohomological behavior.

Smooth functions on and between manifolds

Given a smooth manifold ${\displaystyle M}$, of dimension ${\displaystyle m,}$ and an atlas ${\displaystyle {\mathfrak {U}}=\{(U_{\alpha },\phi _{\alpha })\}_{\alpha },}$ a map ${\displaystyle f:M\to \mathbb {R} }$ is smooth on ${\displaystyle M}$ if, for every ${\displaystyle p\in M}$, there is a chart ${\displaystyle (U,\phi )\in {\mathfrak {U}},}$ with ${\displaystyle p\in U,}$ such that ${\displaystyle f\circ \phi ^{-1}:\phi (U)\to \mathbb {R} }$ is a smooth function from the open subset ${\displaystyle \phi (U)}$ of ${\displaystyle \mathbb {R} ^{m}}$ to ${\displaystyle \mathbb {R} }$. Similarly, ${\displaystyle f}$ is of class ${\displaystyle C^{k}}$ if these coordinate representations are of class ${\displaystyle C^{k}}$. Smoothness can be checked with respect to any chart of the atlas that contains ${\displaystyle p,}$ since the smoothness requirements on the transition functions between charts ensure that if ${\displaystyle f}$ is smooth near ${\displaystyle p}$ in one chart it will be smooth near ${\displaystyle p}$ in any other chart.

On a smooth manifold ${\displaystyle M}$, smooth vector fields can be identified with derivations of the algebra ${\displaystyle C^{\infty }(M)}$. That is, a vector field ${\displaystyle X}$ acts on smooth functions by ${\displaystyle f\mapsto Xf}$ and satisfies the Leibniz rule $${\displaystyle X(fg)=fX(g)+gX(f).}$$

If ${\displaystyle F:M\to N}$ is a map from ${\displaystyle M}$ to an ${\displaystyle n}$-dimensional manifold ${\displaystyle N}$, then ${\displaystyle F}$ is smooth if, for every ${\displaystyle p\in M,}$ there is a chart ${\displaystyle (U,\phi )}$ containing ${\displaystyle p,}$ and a chart ${\displaystyle (V,\psi )}$ containing ${\displaystyle F(p)}$ such that ${\displaystyle F(U)\subset V,}$ and ${\displaystyle \psi \circ F\circ \phi ^{-1}:\phi (U)\to \psi (V)}$ is a smooth function between open subsets of Euclidean spaces.

Smooth maps between manifolds induce linear maps between tangent spaces: for ${\displaystyle F:M\to N}$, at each point the pushforward (or differential) maps tangent vectors at ${\displaystyle p}$ to tangent vectors at ${\displaystyle F(p)}$: ${\displaystyle F_{*,p}:T_{p}M\to T_{F(p)}N,}$ and on the level of the tangent bundle, the pushforward is a vector bundle homomorphism: ${\displaystyle F_{*}:TM\to TN.}$ The dual to the pushforward is the pullback, which "pulls" covectors on ${\displaystyle N}$ back to covectors on ${\displaystyle M,}$ and ${\displaystyle k}$-forms to ${\displaystyle k}$-forms: ${\displaystyle F^{*}:\Omega ^{k}(N)\to \Omega ^{k}(M).}$ In this way smooth functions between manifolds can transport local data, like vector fields and differential forms, from one manifold to another, or down to Euclidean space where computations like integration are well understood.

Preimages and images of smooth maps are, in general, not manifolds without additional assumptions. Preimages of regular values are manifolds; this means that, for a smooth map ${\displaystyle F:M\to N}$ and a value ${\displaystyle q\in N}$, the differential ${\displaystyle dF_{p}:T_{p}M\to T_{q}N}$ is surjective at every point ${\displaystyle p\in F^{-1}(q)}$. This is the preimage theorem. Similarly, the image of an embedding is an embedded submanifold.^[16]

Smoothness is also defined for sections of vector bundles. A section is smooth if its coordinate components are smooth in local trivializations. Smooth vector fields, differential forms, and tensor fields are examples of smooth sections.

Smooth functions between subsets of manifolds

There is a corresponding notion of smooth map for arbitrary subsets of manifolds. If ${\displaystyle f:X\to Y}$ is a function whose domain and codomain are subsets of manifolds ${\displaystyle X\subseteq M}$ and ${\displaystyle Y\subseteq N}$, respectively, then ${\displaystyle f}$ is said to be smooth if for all ${\displaystyle x\in X}$ there is an open set ${\displaystyle U\subseteq M}$ with ${\displaystyle x\in U}$ and a smooth function ${\displaystyle F:U\to N}$ such that ${\displaystyle F(p)=f(p)}$ for all ${\displaystyle p\in U\cap X.}$

Hölder spaces

For ${\displaystyle 0<\alpha \leq 1}$, the Hölder spaces ${\displaystyle C^{k,\alpha }(U)}$ on an open set ${\displaystyle U}$ in ${\displaystyle \mathbb {R} ^{n}}$ are functions that are ${\displaystyle C^{k}}$ on ${\displaystyle U}$ and whose ${\displaystyle k}$-th partials satisfy a Hölder condition on ${\displaystyle U}$: $${\displaystyle |\partial ^{k}f(x)-\partial ^{k}(y)|\leq C\|x-y\|^{\alpha }.}$$ This condition is stronger than ordinary continuity. When ${\displaystyle \alpha =1}$, it implies the Lipschitz continuity of the k-th derivative, which is weaker than their differentiability. Thus, for ${\displaystyle 0<\alpha <1}$, and on a non-empty open domain ${\displaystyle U}$, $${\displaystyle C^{k}(U)\subsetneq C^{k,\alpha }(U)\subsetneq C^{k,1}(U)\subsetneq C^{k+1}(U).}$$