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In the calculus of variations, functionals are usually expressed in terms of an integral of functions, their arguments, and their derivatives. In an integral L of a functional, if a function f is varied by adding to it another function δf that is arbitrarily small, and the resulting integrand is expanded in powers of δf, the coefficient of δf in the first order term is called the functional derivative.
For example, consider the functional
where f ′(x) ≡ df/dx. If f is varied by adding to it a function δf, and the resulting integrand L(x, f +δf, f '+δf ′) is expanded in powers of δf, then the change in the value of J to first order in δf can be expressed as follows:[1][Note 1]
where the variation in the derivative, δf ′ was rewritten as the derivative of the variation (δf) ′, and integration by parts was used.
Definition
In this section, the functional derivative is defined. Then the functional differential is defined in terms of the functional derivative.
One thinks of the function δF/δρ as the gradient of F at the point ρ and
as the directional derivative at point ρ in the direction of ϕ. Then analogous to vector calculus, the inner product with the gradient gives the directional derivative.
Functional differential
The differential (or variation or first variation) of the functional is [3][Note 2]
Heuristically, is the change in , so we 'formally' have , and then
this is similar in form to the total differential of a function ,
where are independent variables.
Comparing the last two equations, the functional derivative has a role similar to that of the partial derivative , where the variable of integration is like a continuous version of the summation index .[4]
Rigorous description
The definition of a functional derivative may be made more mathematically precise and rigorous by defining the space of functions more carefully. For example, when the space of functions is a Banach space, the functional derivative becomes known as the Fréchet derivative, while one uses the Gateaux derivative on more general locally convex spaces. Note that Hilbert spaces are special cases of Banach spaces. The more rigorous treatment allows many theorems from ordinary calculus and analysis to be generalized to corresponding theorems in functional analysis, as well as numerous new theorems to be stated.
Properties
Like the derivative of a function, the functional derivative satisfies the following properties, where F[ρ] and G[ρ] are functionals:[Note 3]
If F is a functional and G another functional, then[7]
If G is an ordinary differentiable function (local functional) g, then this reduces to[8]
Determining functional derivatives
A formula to determine functional derivatives for a common class of functionals can be written as the integral of a function and its derivatives. This is a generalization of the Euler–Lagrange equation: indeed, the functional derivative was introduced in physics within the derivation of the Lagrange equation of the second kind from the principle of least action in Lagrangian mechanics (18th century). The first three examples below are taken from density functional theory (20th century), the fourth from statistical mechanics (19th century).
Formula
Given a functional
and a function ϕ(r) that vanishes on the boundary of the region of integration, from a previous section Definition,
where ρ = ρ(r) and f = f (r, ρ, ∇ρ). This formula is for the case of the functional form given by F[ρ] at the beginning of this section. For other functional forms, the definition of the functional derivative can be used as the starting point for its determination. (See the example Coulomb potential energy functional.)
The above equation for the functional derivative can be generalized to the case that includes higher dimensions and higher order derivatives. The functional would be,
where the vector r ∈ ℝn, and ∇(i) is a tensor whose ni components are partial derivative operators of order i,
The first and second terms on the right hand side of the last equation are equal, since r and r′ in the second term can be interchanged without changing the value of the integral. Therefore,
and the functional derivative of the electron-electron coulomb potential energy functional J[ρ] is,[10]
The second functional derivative is
Weizsäcker kinetic energy functional
In 1935 von Weizsäcker proposed to add a gradient correction to the Thomas-Fermi kinetic energy functional to make it suit better a molecular electron cloud:
where
Using a previously derived formula for the functional derivative,
A function can be written in the form of an integral like a functional. For example,
Since the integrand does not depend on derivatives of ρ, the functional derivative of ρ(r) is,
Functional derivative of iterated function
The functional derivative of the iterated function is given by:
and
In general:
Putting in N=0 gives:
Using the delta function as a test function
In physics, it is common to use the Dirac delta function in place of a generic test function , for yielding the functional derivative at the point (this is a point of the whole functional derivative as a partial derivative is a component of the gradient):[12]
This works in cases when formally can be expanded as a series (or at least up to first order) in . The formula is however not mathematically rigorous, since is usually not even defined.
The definition given in a previous section is based on a relationship that holds for all test functions ϕ, so one might think that it should hold also when ϕ is chosen to be a specific function such as the delta function. However, the latter is not a valid test function (it is not even a proper function).
In the definition, the functional derivative describes how the functional changes as a result of a small change in the entire function . The particular form of the change in is not specified, but it should stretch over the whole interval on which is defined. Employing the particular form of the perturbation given by the delta function has the meaning that is varied only in the point . Except for this point, there is no variation in .
Frigyik, Béla A.; Srivastava, Santosh; Gupta, Maya R. (January 2008), Introduction to Functional Derivatives(PDF), UWEE Tech Report, vol. UWEETR-2008-0001, Seattle, WA: Department of Electrical Engineering at the University of Washington, p. 7, archived from the original(PDF) on 2017-02-17, retrieved 2013-10-23.