Английская Википедия:Functional derivative

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Шаблон:Short description In the calculus of variations, a field of mathematical analysis, the functional derivative (or variational derivative) relates a change in a functional (a functional in this sense is a function that acts on functions) to a change in a function on which the functional depends.

In the calculus of variations, functionals are usually expressed in terms of an integral of functions, their arguments, and their derivatives. In an integrand Шаблон:Math of a functional, if a function Шаблон:Math is varied by adding to it another function Шаблон:Math that is arbitrarily small, and the resulting integrand is expanded in powers of Шаблон:Math, the coefficient of Шаблон:Math in the first order term is called the functional derivative.

For example, consider the functional <math display="block"> J[f] = \int_a^b L( \, x, f(x), f \, '(x) \, ) \, dx \ , </math> where Шаблон:Math. If Шаблон:Math is varied by adding to it a function Шаблон:Math, and the resulting integrand Шаблон:Math is expanded in powers of Шаблон:Math, then the change in the value of Шаблон:Math to first order in Шаблон:Math can be expressed as follows: <math display="block"> \delta J = \int_a^b \left( \frac{\partial L}{\partial f} \delta f(x) + \frac{\partial L}{\partial f'} \frac{d}{dx} \delta f(x) \right) \, dx \, = \int_a^b \left( \frac{\partial L}{\partial f} - \frac{d}{dx} \frac{\partial L}{\partial f'} \right) \delta f(x) \, dx \, + \, \frac{\partial L}{\partial f'} (b) \delta f(b) \, - \, \frac{\partial L}{\partial f'} (a) \delta f(a) \, </math> where the variation in the derivative, Шаблон:Math was rewritten as the derivative of the variation Шаблон:Math, and integration by parts was used in these derivatives.

Definition

In this section, the functional differential (or variation or first variation) is defined. Then the functional derivative is defined in terms of the functional differential.

Functional differential

Suppose <math>B</math> is a Banach space and <math>F</math> is a functional defined on <math>B</math>. The differential of <math>F</math> at a point <math>\rho\in B</math> is the linear functional <math>\delta F[\rho,\cdot]</math> on <math>B</math> defined by the condition that, for all <math>\phi\in B</math>, <math display="block"> F[\rho+\phi] - F[\rho] = \delta F [\rho; \phi] + \epsilon\cdot\|\phi\| </math> where <math>\epsilon</math> is a real number that depends on <math>\|\phi\|</math> in such a way that <math>\epsilon\to 0</math> as <math>\|\phi\|\to 0</math>. This means that <math>\delta F[\rho,\cdot]</math> is the Fréchet derivative of <math>F</math> at <math>\rho</math>.

However, this notion of functional differential is so strong it may not exist, and in those cases a weaker notion, like the Gateaux derivative is preferred. In many practical cases, the functional differential is defined as the directional derivative <math display=block> \begin{align} \delta F[\rho,\phi] &= \lim_{\varepsilon\to 0}\frac{F[\rho+\varepsilon \phi]-F[\rho]}{\varepsilon} \\ &= \left [ \frac{d}{d\varepsilon}F[\rho+\varepsilon \phi]\right ]_{\varepsilon=0}. \end{align} </math> Note that this notion of the functional differential can even be defined without a norm.

Functional derivative

In many applications, the domain of the functional <math>F</math> is a space of differentiable functions <math>\rho</math> defined on some space <math>\Omega</math> and <math>F</math> is of the form <math display="block"> F[\rho] = \int_\Omega L(x,\rho(x),D\rho(x))\,dx </math> for some function <math>L(x,\rho(x),D\rho(x))</math> that may depend on <math>x</math>, the value <math>\rho(x)</math> and the derivative <math>D\rho(x)</math>. If this is the case and, moreover, <math>\delta F[\rho,\phi]</math> can be written as the integral of <math>\phi</math> times another function (denoted Шаблон:Math) <math display="block">\delta F [\rho, \phi] = \int_\Omega \frac {\delta F} {\delta \rho}(x) \ \phi(x) \ dx</math> then this function Шаблон:Math is called the functional derivative of Шаблон:Math at Шаблон:Math. If <math>F</math> is restricted to only certain functions <math>\rho</math> (for example, if there are some boundary conditions imposed) then <math>\phi</math> is restricted to functions such that <math>\rho+\epsilon\phi</math> continues to satisfy these conditions.

Heuristically, <math>\phi</math> is the change in <math>\rho</math>, so we 'formally' have <math>\phi = \delta\rho</math>, and then this is similar in form to the total differential of a function <math>F(\rho_1,\rho_2,\dots,\rho_n)</math>, <math display="block"> dF = \sum_{i=1} ^n \frac {\partial F} {\partial \rho_i} \ d\rho_i ,</math> where <math>\rho_1,\rho_2,\dots,\rho_n</math> are independent variables. Comparing the last two equations, the functional derivative <math>\delta F/\delta\rho(x)</math> has a role similar to that of the partial derivative <math>\partial F/\partial\rho_i</math>, where the variable of integration <math>x</math> is like a continuous version of the summation index <math>i</math>. One thinks of Шаблон:Math as the gradient of Шаблон:Math at the point Шаблон:Math, so the value Шаблон:Math measures how much the functional Шаблон:Math will change if the function Шаблон:Math is changed at the point Шаблон:Math. Hence the formula <math display="block">\int \frac{\delta F}{\delta\rho}(x) \phi(x) \; dx</math> is regarded as the directional derivative at point <math>\rho</math> in the direction of <math>\phi</math>. This is analogous to vector calculus, where the inner product of a vector <math>v</math> with the gradient gives the directional derivative in the direction of <math>v</math>.

Properties

Like the derivative of a function, the functional derivative satisfies the following properties, where Шаблон:Math and Шаблон:Math are functionals:

• Linearity: <math display="block">\frac{\delta(\lambda F + \mu G)[\rho ]}{\delta \rho(x)} = \lambda \frac{\delta F[\rho]}{\delta \rho(x)} + \mu \frac{\delta G[\rho]}{\delta \rho(x)},</math> where Шаблон:Math are constants.
• Product rule: <math display="block">\frac{\delta(FG)[\rho]}{\delta \rho(x)} = \frac{\delta F[\rho]}{\delta \rho(x)} G[\rho] + F[\rho] \frac{\delta G[\rho]}{\delta \rho(x)} \, , </math>
• Chain rules:
  • If Шаблон:Math is a functional and Шаблон:Math another functional, then <math display="block">\frac{\delta F[G[\rho]] }{\delta\rho(y)} = \int dx \frac{\delta F[G]}{\delta G(x)}_{G = G[\rho]}\cdot\frac {\delta G[\rho](x)} {\delta\rho(y)} \ . </math>
  • If Шаблон:Math is an ordinary differentiable function (local functional) Шаблон:Math, then this reduces to <math display="block">\frac{\delta F[g(\rho)] }{\delta\rho(y)} = \frac{\delta F[g(\rho)]}{\delta g[\rho(y) ]} \ \frac {dg(\rho)} {d\rho(y)} \ . </math>

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 <math display="block">F[\rho] = \int f( \boldsymbol{r}, \rho(\boldsymbol{r}), \nabla\rho(\boldsymbol{r}) )\, d\boldsymbol{r},</math> and a function <math>\phi(\boldsymbol{r})</math> that vanishes on the boundary of the region of integration, from a previous section Definition, <math display="block">\begin{align} \int \frac{\delta F}{\delta\rho(\boldsymbol{r})} \, \phi(\boldsymbol{r}) \, d\boldsymbol{r} & = \left [ \frac{d}{d\varepsilon} \int f( \boldsymbol{r}, \rho + \varepsilon \phi, \nabla\rho+\varepsilon\nabla\phi )\, d\boldsymbol{r} \right ]_{\varepsilon=0} \\ & = \int \left( \frac{\partial f}{\partial\rho} \, \phi + \frac{\partial f}{\partial\nabla\rho} \cdot \nabla\phi \right) d\boldsymbol{r} \\ & = \int \left[ \frac{\partial f}{\partial\rho} \, \phi + \nabla \cdot \left( \frac{\partial f}{\partial\nabla\rho} \, \phi \right) - \left( \nabla \cdot \frac{\partial f}{\partial\nabla\rho} \right) \phi \right] d\boldsymbol{r} \\ & = \int \left[ \frac{\partial f}{\partial\rho} \, \phi - \left( \nabla \cdot \frac{\partial f}{\partial\nabla\rho} \right) \phi \right] d\boldsymbol{r} \\ & = \int \left( \frac{\partial f}{\partial\rho} - \nabla \cdot \frac{\partial f}{\partial\nabla\rho} \right) \phi(\boldsymbol{r}) \ d\boldsymbol{r} \, . \end{align}</math>

The second line is obtained using the total derivative, where Шаблон:Math is a derivative of a scalar with respect to a vector.

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 <math>\phi=0</math> on the boundary of the region of integration. Since <math>\phi</math> is also an arbitrary function, applying the fundamental lemma of calculus of variations to the last line, the functional derivative is <math display="block">\frac{\delta F}{\delta\rho(\boldsymbol{r})} = \frac{\partial f}{\partial\rho} - \nabla \cdot \frac{\partial f}{\partial\nabla\rho} </math>

where Шаблон:Math and Шаблон:Math. This formula is for the case of the functional form given by Шаблон:Math 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, <math display="block">F[\rho(\boldsymbol{r})] = \int f( \boldsymbol{r}, \rho(\boldsymbol{r}), \nabla\rho(\boldsymbol{r}), \nabla^{(2)}\rho(\boldsymbol{r}), \dots, \nabla^{(N)}\rho(\boldsymbol{r}))\, d\boldsymbol{r},</math>

where the vector Шаблон:Math, and Шаблон:Math is a tensor whose Шаблон:Math components are partial derivative operators of order Шаблон:Math, <math display="block"> \left [ \nabla^{(i)} \right ]_{\alpha_1 \alpha_2 \cdots \alpha_i} = \frac {\partial^{\, i}} {\partial r_{\alpha_1} \partial r_{\alpha_2} \cdots \partial r_{\alpha_i} } \qquad \qquad \text{where} \quad \alpha_1, \alpha_2, \cdots, \alpha_i = 1, 2, \cdots , n \ . </math>

An analogous application of the definition of the functional derivative yields <math display="block">\begin{align} \frac{\delta F[\rho]}{\delta \rho} &{} = \frac{\partial f}{\partial\rho} - \nabla \cdot \frac{\partial f}{\partial(\nabla\rho)} + \nabla^{(2)} \cdot \frac{\partial f}{\partial\left(\nabla^{(2)}\rho\right)} + \dots + (-1)^N \nabla^{(N)} \cdot \frac{\partial f}{\partial\left(\nabla^{(N)}\rho\right)} \\ &{} = \frac{\partial f}{\partial\rho} + \sum_{i=1}^N (-1)^{i}\nabla^{(i)} \cdot \frac{\partial f}{\partial\left(\nabla^{(i)}\rho\right)} \ . \end{align}</math>

In the last two equations, the Шаблон:Math components of the tensor <math> \frac{\partial f}{\partial\left(\nabla^{(i)}\rho\right)} </math> are partial derivatives of Шаблон:Math with respect to partial derivatives of ρ, <math display="block"> \left [ \frac {\partial f} {\partial \left (\nabla^{(i)}\rho \right ) } \right ]_{\alpha_1 \alpha_2 \cdots \alpha_i} = \frac {\partial f} {\partial \rho_{\alpha_1 \alpha_2 \cdots \alpha_i} } \qquad \qquad \text{where} \quad \rho_{\alpha_1 \alpha_2 \cdots \alpha_i} \equiv \frac {\partial^{\, i}\rho} {\partial r_{\alpha_1} \, \partial r_{\alpha_2} \cdots \partial r_{\alpha_i} } \ , </math> and the tensor scalar product is, <math display="block"> \nabla^{(i)} \cdot \frac{\partial f}{\partial\left(\nabla^{(i)}\rho\right)} = \sum_{\alpha_1, \alpha_2, \cdots, \alpha_i = 1}^n \ \frac {\partial^{\, i} } {\partial r_{\alpha_1} \, \partial r_{\alpha_2} \cdots \partial r_{\alpha_i} } \ \frac {\partial f} {\partial \rho_{\alpha_1 \alpha_2 \cdots \alpha_i} } \ . </math>

Examples

Thomas–Fermi kinetic energy functional

The Thomas–Fermi model of 1927 used a kinetic energy functional for a noninteracting uniform electron gas in a first attempt of density-functional theory of electronic structure: <math display="block">T_\mathrm{TF}[\rho] = C_\mathrm{F} \int \rho^{5/3}(\mathbf{r}) \, d\mathbf{r} \, .</math> Since the integrand of Шаблон:Math does not involve derivatives of Шаблон:Math, the functional derivative of Шаблон:Math is, <math display="block">\begin{align} \frac{\delta T_{\mathrm{TF}}}{\delta \rho (\boldsymbol{r}) } & = C_\mathrm{F} \frac{\partial \rho^{5/3}(\mathbf{r})}{\partial \rho(\mathbf{r})} \\ & = \frac{5}{3} C_\mathrm{F} \rho^{2/3}(\mathbf{r}) \, . \end{align}</math>

Coulomb potential energy functional

For the electron-nucleus potential, Thomas and Fermi employed the Coulomb potential energy functional <math display="block">V[\rho] = \int \frac{\rho(\boldsymbol{r})}{|\boldsymbol{r}|} \ d\boldsymbol{r}.</math>

Applying the definition of functional derivative, <math display="block">\begin{align} \int \frac{\delta V}{\delta \rho(\boldsymbol{r})} \ \phi(\boldsymbol{r}) \ d\boldsymbol{r} & {} = \left [ \frac{d}{d\varepsilon} \int \frac{\rho(\boldsymbol{r}) + \varepsilon \phi(\boldsymbol{r})}{|\boldsymbol{r}|} \ d\boldsymbol{r} \right ]_{\varepsilon=0} \\ & {} = \int \frac {1} {|\boldsymbol{r}|} \, \phi(\boldsymbol{r}) \ d\boldsymbol{r} \, . \end{align}</math> So, <math display="block"> \frac{\delta V}{\delta \rho(\boldsymbol{r})} = \frac{1}{|\boldsymbol{r}|} \ . </math>

For the classical part of the electron-electron interaction, Thomas and Fermi employed the Coulomb potential energy functional <math display="block">J[\rho] = \frac{1}{2}\iint \frac{\rho(\mathbf{r}) \rho(\mathbf{r}')}{| \mathbf{r}-\mathbf{r}' |}\, d\mathbf{r} d\mathbf{r}' \, .</math> From the definition of the functional derivative, <math display="block">\begin{align} \int \frac{\delta J}{\delta\rho(\boldsymbol{r})} \phi(\boldsymbol{r})d\boldsymbol{r} & {} = \left [ \frac {d \ }{d\epsilon} \, J[\rho + \epsilon\phi] \right ]_{\epsilon = 0} \\ & {} = \left [ \frac {d \ }{d\epsilon} \, \left ( \frac{1}{2}\iint \frac {[\rho(\boldsymbol{r}) + \epsilon \phi(\boldsymbol{r})] \, [\rho(\boldsymbol{r}') + \epsilon \phi(\boldsymbol{r}')] }{| \boldsymbol{r}-\boldsymbol{r}' |}\, d\boldsymbol{r} d\boldsymbol{r}' \right ) \right ]_{\epsilon = 0} \\ & {} = \frac{1}{2}\iint \frac {\rho(\boldsymbol{r}') \phi(\boldsymbol{r}) }{| \boldsymbol{r}-\boldsymbol{r}' |}\, d\boldsymbol{r} d\boldsymbol{r}' + \frac{1}{2}\iint \frac {\rho(\boldsymbol{r}) \phi(\boldsymbol{r}') }{| \boldsymbol{r}-\boldsymbol{r}' |}\, d\boldsymbol{r} d\boldsymbol{r}' \\ \end{align}</math> The first and second terms on the right hand side of the last equation are equal, since Шаблон:Math and Шаблон:Math in the second term can be interchanged without changing the value of the integral. Therefore, <math display="block"> \int \frac{\delta J}{\delta\rho(\boldsymbol{r})} \phi(\boldsymbol{r})d\boldsymbol{r} = \int \left ( \int \frac {\rho(\boldsymbol{r}') }{| \boldsymbol{r}-\boldsymbol{r}' |} d\boldsymbol{r}' \right ) \phi(\boldsymbol{r}) d\boldsymbol{r} </math> and the functional derivative of the electron-electron Coulomb potential energy functional Шаблон:Math[ρ] is, <math display="block"> \frac{\delta J}{\delta\rho(\boldsymbol{r})} = \int \frac {\rho(\boldsymbol{r}') }{| \boldsymbol{r}-\boldsymbol{r}' |} d\boldsymbol{r}' \, . </math>

The second functional derivative is <math display="block">\frac{\delta^2 J[\rho]}{\delta \rho(\mathbf{r}')\delta\rho(\mathbf{r})} = \frac{\partial}{\partial \rho(\mathbf{r}')} \left ( \frac{\rho(\mathbf{r}')}{| \mathbf{r}-\mathbf{r}' |} \right ) = \frac{1}{| \mathbf{r}-\mathbf{r}' |}.</math>

Weizsäcker kinetic energy functional

In 1935 von Weizsäcker proposed to add a gradient correction to the Thomas-Fermi kinetic energy functional to make it better suit a molecular electron cloud: <math display="block">T_\mathrm{W}[\rho] = \frac{1}{8} \int \frac{\nabla\rho(\mathbf{r}) \cdot \nabla\rho(\mathbf{r})}{ \rho(\mathbf{r}) } d\mathbf{r} = \int t_\mathrm{W} \ d\mathbf{r} \, ,</math> where <math display="block"> t_\mathrm{W} \equiv \frac{1}{8} \frac{\nabla\rho \cdot \nabla\rho}{ \rho } \qquad \text{and} \ \ \rho = \rho(\boldsymbol{r}) \ . </math> Using a previously derived formula for the functional derivative, <math display="block">\begin{align} \frac{\delta T_\mathrm{W}}{\delta \rho(\boldsymbol{r})} & = \frac{\partial t_\mathrm{W}}{\partial \rho} - \nabla\cdot\frac{\partial t_\mathrm{W}}{\partial \nabla \rho} \\ & = -\frac{1}{8}\frac{\nabla\rho \cdot \nabla\rho}{\rho^2} - \left ( \frac {1}{4} \frac {\nabla^2\rho} {\rho} - \frac {1}{4} \frac {\nabla\rho \cdot \nabla\rho} {\rho^2} \right ) \qquad \text{where} \ \ \nabla^2 = \nabla \cdot \nabla \ , \end{align}</math> and the result is, <math display="block"> \frac{\delta T_\mathrm{W}}{\delta \rho(\boldsymbol{r})} = \ \ \, \frac{1}{8}\frac{\nabla\rho \cdot \nabla\rho}{\rho^2} - \frac{1}{4}\frac{\nabla^2\rho}{\rho} \ . </math>

Entropy

The entropy of a discrete random variable is a functional of the probability mass function.

<math display="block">H[p(x)] = -\sum_x p(x) \log p(x)</math> Thus, <math display="block">\begin{align} \sum_x \frac{\delta H}{\delta p(x)} \, \phi(x) & {} = \left[ \frac{d}{d\epsilon} H[p(x) + \epsilon\phi(x)] \right]_{\epsilon=0}\\ & {} = \left [- \, \frac{d}{d\varepsilon} \sum_x \, [p(x) + \varepsilon\phi(x)] \ \log [p(x) + \varepsilon\phi(x)] \right]_{\varepsilon=0} \\ & {} = -\sum_x \, [1+\log p(x)] \ \phi(x) \, . \end{align}</math> Thus, <math display="block">\frac{\delta H}{\delta p(x)} = -1-\log p(x).</math>

Exponential

Let <math display="block"> F[\varphi(x)]= e^{\int \varphi(x) g(x)dx}.</math>

Using the delta function as a test function, <math display="block">\begin{align} \frac{\delta F[\varphi(x)]}{\delta \varphi(y)} & {} = \lim_{\varepsilon\to 0}\frac{F[\varphi(x)+\varepsilon\delta(x-y)]-F[\varphi(x)]}{\varepsilon}\\ & {} = \lim_{\varepsilon\to 0}\frac{e^{\int (\varphi(x)+\varepsilon\delta(x-y)) g(x)dx}-e^{\int \varphi(x) g(x)dx}}{\varepsilon}\\ & {} = e^{\int \varphi(x) g(x)dx}\lim_{\varepsilon\to 0}\frac{e^{\varepsilon \int \delta(x-y) g(x)dx}-1}{\varepsilon}\\ & {} = e^{\int \varphi(x) g(x)dx}\lim_{\varepsilon\to 0}\frac{e^{\varepsilon g(y)}-1}{\varepsilon}\\ & {} = e^{\int \varphi(x) g(x)dx}g(y). \end{align}</math>

Thus, <math display="block"> \frac{\delta F[\varphi(x)]}{\delta \varphi(y)} = g(y) F[\varphi(x)]. </math>

This is particularly useful in calculating the correlation functions from the partition function in quantum field theory.

Functional derivative of a function

A function can be written in the form of an integral like a functional. For example, <math display="block">\rho(\boldsymbol{r}) = F[\rho] = \int \rho(\boldsymbol{r}') \delta(\boldsymbol{r}-\boldsymbol{r}')\, d\boldsymbol{r}'.</math> Since the integrand does not depend on derivatives of ρ, the functional derivative of ρШаблон:Math is, <math display="block">\begin{align} \frac {\delta \rho(\boldsymbol{r})} {\delta\rho(\boldsymbol{r}')} \equiv \frac {\delta F} {\delta\rho(\boldsymbol{r}')} & = \frac{\partial \ \ }{\partial \rho(\boldsymbol{r}')} \, [\rho(\boldsymbol{r}') \delta(\boldsymbol{r}-\boldsymbol{r}')] \\ & = \delta(\boldsymbol{r}-\boldsymbol{r}'). \end{align}</math>

Functional derivative of iterated function

The functional derivative of the iterated function <math>f(f(x))</math> is given by: <math display="block">\frac{\delta f(f(x))}{\delta f(y) } = f'(f(x))\delta(x-y) + \delta(f(x)-y)</math> and <math display="block">\frac{\delta f(f(f(x)))}{\delta f(y) } = f'(f(f(x))(f'(f(x))\delta(x-y) + \delta(f(x)-y)) + \delta(f(f(x))-y)</math>

In general: <math display="block">\frac{\delta f^N(x)}{\delta f(y)} = f'( f^{N-1}(x) ) \frac{ \delta f^{N-1}(x)}{\delta f(y)} + \delta( f^{N-1}(x) - y ) </math>

Putting in Шаблон:Math gives: <math display="block"> \frac{\delta f^{-1}(x)}{\delta f(y) } = - \frac{ \delta(f^{-1}(x)-y ) }{ f'(f^{-1}(x)) }</math>

Using the delta function as a test function

In physics, it is common to use the Dirac delta function <math>\delta(x-y)</math> in place of a generic test function <math>\phi(x)</math>, for yielding the functional derivative at the point <math>y</math> (this is a point of the whole functional derivative as a partial derivative is a component of the gradient): <math display="block">\frac{\delta F[\rho(x)]}{\delta \rho(y)}=\lim_{\varepsilon\to 0}\frac{F[\rho(x)+\varepsilon\delta(x-y)]-F[\rho(x)]}{\varepsilon}.</math>

This works in cases when <math>F[\rho(x)+\varepsilon f(x)]</math> formally can be expanded as a series (or at least up to first order) in <math>\varepsilon</math>. The formula is however not mathematically rigorous, since <math>F[\rho(x)+\varepsilon\delta(x-y)]</math> is usually not even defined.

The definition given in a previous section is based on a relationship that holds for all test functions <math>\phi(x)</math>, so one might think that it should hold also when <math>\phi(x)</math> 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 <math>F[\rho(x)]</math> changes as a result of a small change in the entire function <math>\rho(x)</math>. The particular form of the change in <math>\rho(x)</math> is not specified, but it should stretch over the whole interval on which <math>x</math> is defined. Employing the particular form of the perturbation given by the delta function has the meaning that <math>\rho(x)</math> is varied only in the point <math>y</math>. Except for this point, there is no variation in <math>\rho(x)</math>.

References

• Шаблон:Cite book.
• Шаблон:Citation.
• Шаблон:Citation.
• Шаблон:Citation.
• Шаблон:Citation.
• Шаблон:Cite book

External links

• Шаблон:Springer