Reference articles on history, science, culture and more
Surprise meSurprise meSubscribe
Encyclopedia

Functional (mathematics)

Types of mappings in mathematics

Wikipedia contributorsAdapted for Fathomly · View authors
3 min read
Source updated November 5, 2024
Image credit is listed at the end of this article.

In mathematics, a functional is a certain type of function. The exact definition of the term varies depending on the subfield (and sometimes even the author).

This article is mainly concerned with the second concept, which arose in the early 18th century as part of the calculus of variations. The first concept, which is more modern and abstract, is discussed in detail in a separate article, under the name linear form. The third concept is detailed in the computer science article on higher-order functions.

In the case where the space X is a space of functions, the functional is a "function of a function", and some older authors actually define the term "functional" to mean "function of a function". However, the fact that X is a space of functions is not mathematically essential, so this older definition is no longer prevalent.

The term originates from the calculus of variations, where one searches for a function that minimizes (or maximizes) a given functional. A particularly important application in physics is search for a state of a system that minimizes (or maximizes) the action, or in other words the time integral of the Lagrangian.

01Details

Duality

The mapping x_{0}\mapsto f(x_{0}) is a function, where x_{0} is an argument of a function f. At the same time, the mapping of a function to the value of the function at a point f\mapsto f(x_{0}) is a functional; here, x_{0} is a parameter.

Provided that f is a linear function from a vector space to the underlying scalar field, the above linear maps are dual to each other, and in functional analysis both are called linear functionals.

Definite integral

Integrals such as f\mapsto I[f]=\int _{\Omega }H(f(x),f'(x),\ldots )\;\mu (\mathrm {d} x) form a special class of functionals. They map a function f into a real number, provided that H is real-valued. Examples include

  • the area underneath the graph of a positive function f f\mapsto \int _{x_{0}}^{x_{1}}f(x)\;\mathrm {d} x
  • L^{p} norm of a function on a set E f\mapsto \left(\int _{E}|f|^{p}\;\mathrm {d} x\right)^{1/p}
  • the arclength of a curve in 2-dimensional Euclidean space f\mapsto \int _{x_{0}}^{x_{1}}{\sqrt {1+|f'(x)|^{2}}}\;\mathrm {d} x

Inner product spaces

Given an inner product space X, and a fixed vector {\vec {x}}\in X, the map defined by {\vec {y}}\mapsto {\vec {x}}\cdot {\vec {y}} is a linear functional on X. The set of vectors {\vec {y}} such that {\vec {x}}\cdot {\vec {y}} is zero is a vector subspace of X, called the null space or kernel of the functional, or the orthogonal complement of {\vec {x}}, denoted \{{\vec {x}}\}^{\perp }.

For example, taking the inner product with a fixed function g\in L^{2}([-\pi ,\pi ]) defines a (linear) functional on the Hilbert space L^{2}([-\pi ,\pi ]) of square integrable functions on [-\pi ,\pi ]: f\mapsto \langle f,g\rangle =\int _{[-\pi ,\pi ]}{\bar {f}}g

Locality

If a functional's value can be computed for small segments of the input curve and then summed to find the total value, the functional is called local. Otherwise it is called non-local. For example: F(y)=\int _{x_{0}}^{x_{1}}y(x)\;\mathrm {d} x is local while F(y)={\frac {\int _{x_{0}}^{x_{1}}y(x)\;\mathrm {d} x}{\int _{x_{0}}^{x_{1}}(1+[y(x)]^{2})\;\mathrm {d} x}} is non-local. This occurs commonly when integrals occur separately in the numerator and denominator of an equation such as in calculations of center of mass.

The arc length functional has as its domain the vector space of rectifiable curves, a subspace of, and outputs a real scalar. This is an example of a non-linear functional.
The arc length functional has as its domain the vector space of rectifiable curves, a subspace of, and outputs a real scalar. This is an example of a non-linear functional.

02Functional equations

The traditional usage also applies when one talks about a functional equation, meaning an equation between functionals: an equation F=G between functionals can be read as an 'equation to solve', with solutions being themselves functions. In such equations there may be several sets of variable unknowns, like when it is said that an additive map f is one satisfying Cauchy's functional equation: f(x+y)=f(x)+f(y)\qquad {\text{ for all }}x,y.

03Derivative and integration

Functional derivatives are used in Lagrangian mechanics. They are derivatives of functionals; that is, they carry information on how a functional changes when the input function changes by a small amount.

Richard Feynman used functional integrals as the central idea in his sum over the histories formulation of quantum mechanics. This usage implies an integral taken over some function space.

Watch videos about Functional (mathematics)Explainers and documentaries on YouTube (opens in a new tab)

Sources and credits

This article is adapted from the Wikipedia article “Functional (mathematics)”, written by its contributors and licensed under CC BY-SA 4.0. Fathomly has changed the layout, removed citation markers, navigation and maintenance notices, and adjusted punctuation. This adapted version is shared under the same license. For references, see the original article.

Images, from Wikimedia Commons:

Fathomly is not affiliated with or endorsed by the Wikimedia Foundation. Spotted a problem? Tell us.

Continue exploring

Related topics

Linear form

In mathematics, a linear form is a linear map from a vector space to its field of scalars (often, the real numbers or the complex numbers). If V is a vector space over a field k, the set of all linear functionals from V to k is itself a vector space over k with addition and scalar multiplication defined pointwise.

Mathematical optimization

Mathematical optimization or mathematical programming is the selection of a best element, with regard to some criteria, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization.

Tensor

In mathematics, a tensor is an algebraic object that describes a multilinear relationship between sets of algebraic objects associated with a vector space. Tensors may map between different objects such as vectors, scalars, and even other tensors.