In the calculus of variations, a field of mathematical analysis, the functional derivative (or variational derivative) relates a change in a functional to a change in a function that the functional depends on.
In the calculus of variations, functionals are usually expressed in terms of an integral of functions, their arguments, and their derivatives. In an integrand L of a functional, if a function f is varied by adding to it another function δf that is arbitrarily small, and the resulting L 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:[Note 1]
The coefficient of δf(x), denoted as δJ/δf(x), is called the functional derivative of J with respect to f at the point x. For this example functional, the functional derivative is the left hand side of the Euler-Lagrange equation,
- 1 Definition
- 2 Properties
- 3 Determining functional derivatives
- 4 Using the delta function as a test function
- 5 Notes
- 6 Footnotes
- 7 References
The functional derivative is defined. Then the functional differential is defined in terms of the functional derivative.
the functional derivative of F[ρ], denoted δF/δρ, is defined by
where is an arbitrary function. is called the variation of ρ.
where ρ1, ρ2, ... , ρn are independent variables. Comparing the last two equations, the functional derivative δF/δρ(x) has a role similar to that of the partial derivative ∂F/∂ρi , where the variable of integration x is like a continuous version of the summation index i.
The definition of a functional derivative may be made more mathematically precise and formal 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 Gâteaux derivative on more general locally convex spaces. Note that the well-known Hilbert spaces are special cases of Banach spaces. The more formal 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.
Like the derivative of a function, the functional derivative satisfies the following properties, where F[ρ] and G[ρ] are functionals:
- Product rule:
- Chain rules:
Determining functional derivatives
We give a formula to determine functional derivatives for a common class of functionals that 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).
Given a functional
and a function ϕ(r) that vanishes on the boundary of the region of integration, from a previous section Definition,
The second line is obtained using the total derivative, where ∂f /∂∇ρ is a derivative of a scalar with respect to a vector.[Note 3] The third line was obtained by use of a product rule for divergence. The fourth line was obtained using the divergence theorem and the condition that ϕ=0 on the boundary of the region of integration. Since ϕ is also an arbitrary function, applying the fundamental lemma of calculus of variations to the last line, the functional derivative is
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,
An analogous application of the definition of the functional derivative yields
In the last two equations, the ni components of the tensor are partial derivatives of f with respect to partial derivatives of ρ,
and the tensor scalar product is,
Thomas–Fermi kinetic energy functional
Since the integrand of TTF[ρ] does not involve derivatives of ρ(r), the functional derivative of TTF[ρ] is,
Coulomb potential energy functional
For the electron-nucleus potential, Thomas and Fermi employed the Coulomb potential energy functional
Applying the definition of functional derivative,
For the classical part of the electron-electron interaction, Thomas and Fermi employed the Coulomb potential energy functional
From the definition of the functional derivative,
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,
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:
Using a previously derived formula for the functional derivative,
and the result is,
Using the delta function as a test function,
Functional derivative of a function
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,
Using the delta function as a test function
In physics, it's 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):
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.
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 .
- According to Giaquinta & Hildebrandt (1996, p. 18), this notation is customary in physical literature.
- Called differential in (Parr & Yang 1989, p. 246), variation or first variation in (Courant & Hilbert 1953, p. 186), and variation or differential in (Gelfand & Fomin 2000, p. 11, § 3.2).
- For a three-dimensional cartesian coordinate system,
- For example, for the case of three dimensions (n = 3) and second order derivatives (i = 2), the tensor ∇(2) has components,
- For example, for the case n = 3 and i = 2, the tensor scalar product is,
- (Giaquinta & Hildebrandt 1996, p. 18)
- (Parr & Yang 1989, p. 246).
- (Gelfand & Fomin 2000, p. 28)
- (Parr & Yang 1989, p. 246, Eq. A.2).
- (Parr & Yang 1989, p. 246, Eq. A.1).
- (Parr & Yang 1989, p. 247, Eq. A.3).
- (Parr & Yang 1989, p. 247, Eq. A.4).
- (Greiner & Reinhardt 1996, p. 38, Eq. 7).
- (Parr & Yang 1989, p. 251, Eq. A.34).
- (Parr & Yang 1989, p. 247, Eq. A.6).
- (Parr & Yang 1989, p. 248, Eq. A.11).
- (Parr & Yang 1989, p. 247, Eq. A.9).
- Courant, Richard; Hilbert, David (1953). "Chapter IV. The Calculus of Variations". Methods of Mathematical Physics. Vol. I (First English ed.). New York, New York: Interscience Publishers, Inc. pp. 164–274. ISBN 978-0471504474. MR 0065391. Zbl 0001.00501..
- Frigyik, Béla A.; Srivastava, Santosh; Gupta, Maya R. (January 2008), Introduction to Functional Derivatives, UWEE Tech Report, UWEETR-2008-0001, Seattle, WA: Department of Electrical Engineering at the University of Washington, p. 7.
- Gelfand, I. M.; Fomin, S. V. (2000) , Calculus of variations, translated and edited by Richard A. Silverman (Revised English ed.), Mineola, N.Y.: Dover Publications, ISBN 978-0486414485, MR 0160139, Zbl 0127.05402.
- Giaquinta, Mariano; Hildebrandt, Stefan (1996), Calculus of Variations 1. The Lagrangian Formalism, Grundlehren der Mathematischen Wissenschaften 310 (1st ed.), Berlin: Springer-Verlag, ISBN 3-540-50625-X, MR 1368401, Zbl 0853.49001.
- Greiner, Walter; Reinhardt, Joachim (1996), "Section 2.3 – Functional derivatives", Field quantization, With a foreword by D. A. Bromley, Berlin–Heidelberg–New York: Springer-Verlag, pp. 36–38, ISBN 3-540-59179-6, MR 1383589, Zbl 0844.00006.
- Parr, R. G.; Yang, W. (1989). "Appendix A, Functionals". Density-Functional Theory of Atoms and Molecules. New York: Oxford University Press. pp. 246–254. ISBN 978-0195042795.