Dirac delta function
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In mathematical analysis, the Dirac delta function (or
The delta function was introduced by physicist Paul Dirac, and has since been applied routinely in physics and engineering to model point masses and instantaneous impulses. It is called the delta function because it is a continuous analogue of the Kronecker delta function, which is usually defined on a discrete domain and takes values 0 and 1. The mathematical rigor of the delta function was disputed until Laurent Schwartz developed the theory of distributions, where it is defined as a linear form acting on functions.
Motivation and overview
[edit]The graph of the Dirac delta is usually thought of as following the whole x-axis and the positive y-axis.[5]: 174 The Dirac delta is used to model a tall narrow spike function (an impulse), and other similar abstractions such as a point charge, point mass or electron point. For example, to calculate the dynamics of a billiard ball being struck, one can approximate the force of the impact by a Dirac delta. In doing so, one not only simplifies the equations, but one also is able to calculate the motion of the ball, by only considering the total impulse of the collision, without a detailed model of all of the elastic energy transfer at subatomic levels (for instance).
To be specific, suppose that a billiard ball is at rest. At time it is struck by another ball, imparting it with a momentum P, with units kg⋅m⋅s−1. The exchange of momentum is not actually instantaneous, being mediated by elastic processes at the molecular and subatomic level, but for practical purposes it is convenient to consider that energy transfer as effectively instantaneous. The force therefore is P
To model this situation more rigorously, suppose that the force instead is uniformly distributed over a small time interval . That is,
Then the momentum at any time t is found by integration:
Now, the model situation of an instantaneous transfer of momentum requires taking the limit as
Here the functions are thought of as useful approximations to the idea of instantaneous transfer of momentum.
The delta function allows us to construct an idealized limit of these approximations. Unfortunately, the actual limit of the functions (in the sense of pointwise convergence) is zero everywhere but a single point, where it is infinite. To make proper sense of the Dirac delta, we should instead insist that the property
which holds for all , should continue to hold in the limit. So, in the equation , it is understood that the limit is always taken outside the integral.
In applied mathematics, as we have done here, the delta function is often manipulated as a kind of limit (a weak limit) of a sequence of functions, each member of which has a tall spike at the origin: for example, a sequence of Gaussian distributions centered at the origin with variance tending to zero.
The Dirac delta is not truly a function, at least not a usual one with domain and range in real numbers. For example, the objects f(x) =
History
[edit]Joseph Fourier presented what is now called the Fourier integral theorem in his treatise Théorie analytique de la chaleur in the form:[6]
which is tantamount to the introduction of the
Later, Augustin Cauchy expressed the theorem using exponentials:[8][9]
Cauchy pointed out that in some circumstances the order of integration is significant in this result (contrast Fubini's theorem).[10][11]
As justified using the theory of distributions, the Cauchy equation can be rearranged to resemble Fourier's original formulation and expose the
where the
A rigorous interpretation of the exponential form and the various limitations upon the function f necessary for its application extended over several centuries. The problems with a classical interpretation are explained as follows:[12]
- The greatest drawback of the classical Fourier transformation is a rather narrow class of functions (originals) for which it can be effectively computed. Namely, it is necessary that these functions decrease sufficiently rapidly to zero (in the neighborhood of infinity) to ensure the existence of the Fourier integral. For example, the Fourier transform of such simple functions as polynomials does not exist in the classical sense. The extension of the classical Fourier transformation to distributions considerably enlarged the class of functions that could be transformed and this removed many obstacles.
Further developments included generalization of the Fourier integral, "beginning with Plancherel's pathbreaking L2-theory (1910), continuing with Wiener's and Bochner's works (around 1930) and culminating with the amalgamation into L. Schwartz's theory of distributions (1945) ...",[13] and leading to the formal development of the Dirac delta function.
An infinitesimal formula for an infinitely tall, unit impulse delta function (infinitesimal version of Cauchy distribution) explicitly appears in an 1827 text of Augustin-Louis Cauchy. [14] Siméon Denis Poisson considered the issue in connection with the study of wave propagation as did Gustav Kirchhoff somewhat later. Kirchhoff and Hermann von Helmholtz also introduced the unit impulse as a limit of Gaussians, which also corresponded to Lord Kelvin's notion of a point heat source. At the end of the 19th century, Oliver Heaviside used formal Fourier series to manipulate the unit impulse.[15] The Dirac delta function as such was introduced by Paul Dirac in his 1927 paper The Physical Interpretation of the Quantum Dynamics[16] and used in his textbook The Principles of Quantum Mechanics.[3] He called it the "delta function" since he used it as a continuous analogue of the discrete Kronecker delta.
Definitions
[edit]The Dirac delta function can be loosely thought of as a function on the real line which is zero everywhere except at the origin, where it is infinite,
and which is also constrained to satisfy the identity[17]
This is merely a heuristic characterization. The Dirac delta is not a function in the traditional sense as no extended real number valued function defined on the real numbers has these properties.[18]
As a measure
[edit]One way to rigorously capture the notion of the Dirac delta function is to define a measure, called Dirac measure, which accepts a subset A of the real line R as an argument, and returns
for all continuous compactly supported functions f. The measure
holds.[20] As a result, the latter notation is a convenient abuse of notation, and not a standard (Riemann or Lebesgue) integral.
As a probability measure on R, the delta measure is characterized by its cumulative distribution function, which is the unit step function.[21]
This means that H(x) is the integral of the cumulative indicator function 1(−∞, x] with respect to the measure
the latter being the measure of this interval. Thus in particular the integration of the delta function against a continuous function can be properly understood as a Riemann–Stieltjes integral:[22]
All higher moments of
As a distribution
[edit]In the theory of distributions, a generalized function is considered not a function in itself but only through how it affects other functions when "integrated" against them.[23] In keeping with this philosophy, to define the delta function properly, it is enough to say what the "integral" of the delta function is against a sufficiently "good" test function
A typical space of test functions consists of all smooth functions on R with compact support that have as many derivatives as required. As a distribution, the Dirac delta is a linear functional on the space of test functions and is defined by[24]
(1) |
for every test function
For
where sup represents the supremum. With the
The delta distribution can also be defined in several equivalent ways. For instance, it is the distributional derivative of the Heaviside step function. This means that for every test function
Intuitively, if integration by parts were permitted, then the latter integral should simplify to
and indeed, a form of integration by parts is permitted for the Stieltjes integral, and in that case, one does have
In the context of measure theory, the Dirac measure gives rise to distribution by integration. Conversely, equation (1) defines a Daniell integral on the space of all compactly supported continuous functions
Generally, when the term Dirac delta function is used, it is in the sense of distributions rather than measures, the Dirac measure being among several terms for the corresponding notion in measure theory. Some sources may also use the term Dirac delta distribution.
Generalizations
[edit]The delta function can be defined in n-dimensional Euclidean space Rn as the measure such that
for every compactly supported continuous function f. As a measure, the n-dimensional delta function is the product measure of the 1-dimensional delta functions in each variable separately. Thus, formally, with x = (x1, x2, ..., xn), one has[26]
(2) |
The delta function can also be defined in the sense of distributions exactly as above in the one-dimensional case.[27] However, despite widespread use in engineering contexts, (2) should be manipulated with care, since the product of distributions can only be defined under quite narrow circumstances.[28][29]
The notion of a Dirac measure makes sense on any set.[30] Thus if X is a set, x0 ∈ X is a marked point, and
is the delta measure or unit mass concentrated at x0.
Another common generalization of the delta function is to a differentiable manifold where most of its properties as a distribution can also be exploited because of the differentiable structure. The delta function on a manifold M centered at the point x0 ∈ M is defined as the following distribution:
(3) |
for all compactly supported smooth real-valued functions
On a locally compact Hausdorff space X, the Dirac delta measure concentrated at a point x is the Radon measure associated with the Daniell integral (3) on compactly supported continuous functions
Properties
[edit]Scaling and symmetry
[edit]The delta function satisfies the following scaling property for a non-zero scalar
and so
(4) |
Scaling property proof: where a change of variable x′ = ax is used. If a is negative, i.e., a = −|a|, then Thus, .
In particular, the delta function is an even distribution (symmetry), in the sense that
which is homogeneous of degree −1.
Algebraic properties
[edit]The distributional product of
More generally, for all positive integers .
Conversely, if xf(x) = xg(x), where f and g are distributions, then
for some constant c.[35]
Translation
[edit]The integral of the time-delayed Dirac delta is[36]
This is sometimes referred to as the sifting property[37] or the sampling property.[38] The delta function is said to "sift out" the value of f(t) at t = T.[39]
It follows that the effect of convolving a function f(t) with the time-delayed Dirac delta is to time-delay f(t) by the same amount:
The sifting property holds under the precise condition that f be a tempered distribution (see the discussion of the Fourier transform below). As a special case, for instance, we have the identity (understood in the distribution sense)
Composition with a function
[edit]More generally, the delta distribution may be composed with a smooth function g(x) in such a way that the familiar change of variables formula holds, that
provided that g is a continuously differentiable function with g′ nowhere zero.[40] That is, there is a unique way to assign meaning to the distribution so that this identity holds for all compactly supported test functions f. Therefore, the domain must be broken up to exclude the g′ = 0 point. This distribution satisfies
It is natural therefore to define the composition
where the sum extends over all roots (i.e., all the different ones) of g(x), which are assumed to be simple. Thus, for example
In the integral form, the generalized scaling property may be written as
Indefinite integral
[edit]For a constant and a "well-behaved" arbitrary real-valued function y(x), where H(x) is the Heaviside step function and c is an integration constant.
Properties in n dimensions
[edit]The delta distribution in an n-dimensional space satisfies the following scaling property instead,
so that
Under any reflection or rotation
As in the one-variable case, it is possible to define the composition of
Using the coarea formula from geometric measure theory, one can also define the composition of the delta function with a submersion from one Euclidean space to another one of different dimension; the result is a type of current. In the special case of a continuously differentiable function g : Rn → R such that the gradient of g is nowhere zero, the following identity holds[42] where the integral on the right is over g−1(0), the (n − 1)-dimensional surface defined by g(x) = 0 with respect to the Minkowski content measure. This is known as a simple layer integral.
More generally, if S is a smooth hypersurface of Rn, then we can associate to S the distribution that integrates any compactly supported smooth function g over S:
where
where n is the outward normal.[43][44] For a proof, see e.g. the article on the surface delta function.
In three dimensions, the delta function is represented in spherical coordinates by:
Fourier transform
[edit]The delta function is a tempered distribution, and therefore it has a well-defined Fourier transform. Formally, one finds[45]
Properly speaking, the Fourier transform of a distribution is defined by imposing self-adjointness of the Fourier transform under the duality pairing of tempered distributions with Schwartz functions. Thus is defined as the unique tempered distribution satisfying
for all Schwartz functions
As a result of this identity, the convolution of the delta function with any other tempered distribution S is simply S:
That is to say that
The inverse Fourier transform of the tempered distribution f(
In these terms, the delta function provides a suggestive statement of the orthogonality property of the Fourier kernel on R. Formally, one has
This is, of course, shorthand for the assertion that the Fourier transform of the tempered distribution is which again follows by imposing self-adjointness of the Fourier transform.
By analytic continuation of the Fourier transform, the Laplace transform of the delta function is found to be[46]
Derivatives
[edit]The derivative of the Dirac delta distribution, denoted
The first equality here is a kind of integration by parts, for if
By mathematical induction, the k-th derivative of
In particular,
The first derivative of the delta function is the distributional limit of the difference quotients:[48]
More properly, one has
where
In the theory of electromagnetism, the first derivative of the delta function represents a point magnetic dipole situated at the origin. Accordingly, it is referred to as a dipole or the doublet function.[49]
The derivative of the delta function satisfies a number of basic properties, including:[50] which can be shown by applying a test function and integrating by parts.
The latter of these properties can also be demonstrated by applying distributional derivative definition, Liebniz 's theorem and linearity of inner product:[51]
Furthermore, the convolution of
which follows from the properties of the distributional derivative of a convolution.
Higher dimensions
[edit]More generally, on an open set U in the n-dimensional Euclidean space , the Dirac delta distribution centered at a point a ∈ U is defined by[52]
for all , the space of all smooth functions with compact support on U. If is any multi-index with and denotes the associated mixed partial derivative operator, then the
That is, the
The first partial derivatives of the delta function are thought of as double layers along the coordinate planes. More generally, the normal derivative of a simple layer supported on a surface is a double layer supported on that surface and represents a laminar magnetic monopole. Higher derivatives of the delta function are known in physics as multipoles.
Higher derivatives enter into mathematics naturally as the building blocks for the complete structure of distributions with point support. If S is any distribution on U supported on the set {a} consisting of a single point, then there is an integer m and coefficients c
Representations of the delta function
[edit]The delta function can be viewed as the limit of a sequence of functions
where
(5) |
for all continuous functions f having compact support, or that this limit holds for all smooth functions f with compact support. The difference between these two slightly different modes of weak convergence is often subtle: the former is convergence in the vague topology of measures, and the latter is convergence in the sense of distributions.
Approximations to the identity
[edit]Typically a nascent delta function
In n dimensions, one uses instead the scaling
Then a simple change of variables shows that
The
This limit holds in the sense of mean convergence (convergence in L1). Further conditions on the
If the initial
In some situations such as numerical analysis, a piecewise linear approximation to the identity is desirable. This can be obtained by taking
which are all continuous and compactly supported, although not smooth and so not a mollifier.
Probabilistic considerations
[edit]In the context of probability theory, it is natural to impose the additional condition that the initial
Another example is with the Wigner semicircle distribution
This is continuous and compactly supported, but not a mollifier because it is not smooth.
Semigroups
[edit]Nascent delta functions often arise as convolution semigroups.[58] This amounts to the further constraint that the convolution of
for all
In practice, semigroups approximating the delta function arise as fundamental solutions or Green's functions to physically motivated elliptic or parabolic partial differential equations. In the context of applied mathematics, semigroups arise as the output of a linear time-invariant system. Abstractly, if A is a linear operator acting on functions of x, then a convolution semigroup arises by solving the initial value problem
in which the limit is as usual understood in the weak sense. Setting
Some examples of physically important convolution semigroups arising from such a fundamental solution include the following.
The heat kernel
[edit]The heat kernel, defined by
represents the temperature in an infinite wire at time t > 0, if a unit of heat energy is stored at the origin of the wire at time t = 0. This semigroup evolves according to the one-dimensional heat equation:
In probability theory,
In higher-dimensional Euclidean space Rn, the heat kernel is
and has the same physical interpretation, mutatis mutandis. It also represents a nascent delta function in the sense that
The Poisson kernel
[edit]The Poisson kernel
is the fundamental solution of the Laplace equation in the upper half-plane.[59] It represents the electrostatic potential in a semi-infinite plate whose potential along the edge is held at fixed at the delta function. The Poisson kernel is also closely related to the Cauchy distribution and Epanechnikov and Gaussian kernel functions.[60] This semigroup evolves according to the equation
where the operator is rigorously defined as the Fourier multiplier
Oscillatory integrals
[edit]In areas of physics such as wave propagation and wave mechanics, the equations involved are hyperbolic and so may have more singular solutions. As a result, the nascent delta functions that arise as fundamental solutions of the associated Cauchy problems are generally oscillatory integrals. An example, which comes from a solution of the Euler–Tricomi equation of transonic gas dynamics,[61] is the rescaled Airy function
Although using the Fourier transform, it is easy to see that this generates a semigroup in some sense—it is not absolutely integrable and so cannot define a semigroup in the above strong sense. Many nascent delta functions constructed as oscillatory integrals only converge in the sense of distributions (an example is the Dirichlet kernel below), rather than in the sense of measures.
Another example is the Cauchy problem for the wave equation in R1+1:[62]
The solution u represents the displacement from equilibrium of an infinite elastic string, with an initial disturbance at the origin.
Other approximations to the identity of this kind include the sinc function (used widely in electronics and telecommunications)
and the Bessel function
Plane wave decomposition
[edit]One approach to the study of a linear partial differential equation
where L is a differential operator on Rn, is to seek first a fundamental solution, which is a solution of the equation
When L is particularly simple, this problem can often be resolved using the Fourier transform directly (as in the case of the Poisson kernel and heat kernel already mentioned). For more complicated operators, it is sometimes easier first to consider an equation of the form
where h is a plane wave function, meaning that it has the form
for some vector
Such a decomposition of the delta function into plane waves was part of a general technique first introduced essentially by Johann Radon, and then developed in this form by Fritz John (1955).[63] Choose k so that n + k is an even integer, and for a real number s, put
Then
The Laplacian here is interpreted as a weak derivative, so that this equation is taken to mean that, for any test function
The result follows from the formula for the Newtonian potential (the fundamental solution of Poisson's equation). This is essentially a form of the inversion formula for the Radon transform because it recovers the value of
where R
An alternative equivalent expression of the plane wave decomposition is:[64]
Fourier kernels
[edit]In the study of Fourier series, a major question consists of determining whether and in what sense the Fourier series associated with a periodic function converges to the function. The n-th partial sum of the Fourier series of a function f of period 2
Despite this, the result does not hold for all compactly supported continuous functions: that is DN does not converge weakly in the sense of measures. The lack of convergence of the Fourier series has led to the introduction of a variety of summability methods to produce convergence. The method of Cesàro summation leads to the Fejér kernel[65]
The Fejér kernels tend to the delta function in a stronger sense that[66]
for every compactly supported continuous function f. The implication is that the Fourier series of any continuous function is Cesàro summable to the value of the function at every point.
Hilbert space theory
[edit]The Dirac delta distribution is a densely defined unbounded linear functional on the Hilbert space L2 of square-integrable functions. Indeed, smooth compactly supported functions are dense in L2, and the action of the delta distribution on such functions is well-defined. In many applications, it is possible to identify subspaces of L2 and to give a stronger topology on which the delta function defines a bounded linear functional.
Sobolev spaces
[edit]The Sobolev embedding theorem for Sobolev spaces on the real line R implies that any square-integrable function f such that
is automatically continuous, and satisfies in particular
Thus
Spaces of holomorphic functions
[edit]In complex analysis, the delta function enters via Cauchy's integral formula, which asserts that if D is a domain in the complex plane with smooth boundary, then
for all holomorphic functions f in D that are continuous on the closure of D. As a result, the delta function
Moreover, let H2(∂D) be the Hardy space consisting of the closure in L2(∂D) of all holomorphic functions in D continuous up to the boundary of D. Then functions in H2(∂D) uniquely extend to holomorphic functions in D, and the Cauchy integral formula continues to hold. In particular for z ∈ D, the delta function
Resolutions of the identity
[edit]Given a complete orthonormal basis set of functions {
Letting I denote the identity operator on the Hilbert space, the expression
is called a resolution of the identity. When the Hilbert space is the space L2(D) of square-integrable functions on a domain D, the quantity:
is an integral operator, and the expression for f can be rewritten
The right-hand side converges to f in the L2 sense. It need not hold in a pointwise sense, even when f is a continuous function. Nevertheless, it is common to abuse notation and write
resulting in the representation of the delta function:[70]
With a suitable rigged Hilbert space (
Infinitesimal delta functions
[edit]Cauchy used an infinitesimal
Non-standard analysis allows one to rigorously treat infinitesimals. The article by Yamashita (2007) contains a bibliography on modern Dirac delta functions in the context of an infinitesimal-enriched continuum provided by the hyperreals. Here the Dirac delta can be given by an actual function, having the property that for every real function F one has as anticipated by Fourier and Cauchy.
Dirac comb
[edit]![](https://upload.wikimedia.org/wikipedia/commons/thumb/4/49/Dirac_comb.svg/220px-Dirac_comb.svg.png)
A so-called uniform "pulse train" of Dirac delta measures, which is known as a Dirac comb, or as the Sha distribution, creates a sampling function, often used in digital signal processing (DSP) and discrete time signal analysis. The Dirac comb is given as the infinite sum, whose limit is understood in the distribution sense,
which is a sequence of point masses at each of the integers.
Up to an overall normalizing constant, the Dirac comb is equal to its own Fourier transform. This is significant because if f is any Schwartz function, then the periodization of f is given by the convolution In particular, is precisely the Poisson summation formula.[73][74] More generally, this formula remains to be true if f is a tempered distribution of rapid descent or, equivalently, if is a slowly growing, ordinary function within the space of tempered distributions.
Sokhotski–Plemelj theorem
[edit]The Sokhotski–Plemelj theorem, important in quantum mechanics, relates the delta function to the distribution p.v. 1/x, the Cauchy principal value of the function 1/x, defined by
Sokhotsky's formula states that[75]
Here the limit is understood in the distribution sense, that for all compactly supported smooth functions f,
Relationship to the Kronecker delta
[edit]The Kronecker delta
for all integers i, j. This function then satisfies the following analog of the sifting property: if ai (for i in the set of all integers) is any doubly infinite sequence, then
Similarly, for any real or complex valued continuous function f on R, the Dirac delta satisfies the sifting property
This exhibits the Kronecker delta function as a discrete analog of the Dirac delta function.[76]
Applications
[edit]Probability theory
[edit]In probability theory and statistics, the Dirac delta function is often used to represent a discrete distribution, or a partially discrete, partially continuous distribution, using a probability density function (which is normally used to represent absolutely continuous distributions). For example, the probability density function f(x) of a discrete distribution consisting of points x = {x1, ..., xn}, with corresponding probabilities p1, ..., pn, can be written as
As another example, consider a distribution in which 6/10 of the time returns a standard normal distribution, and 4/10 of the time returns exactly the value 3.5 (i.e. a partly continuous, partly discrete mixture distribution). The density function of this distribution can be written as
The delta function is also used to represent the resulting probability density function of a random variable that is transformed by continuously differentiable function. If Y = g(X) is a continuous differentiable function, then the density of Y can be written as
The delta function is also used in a completely different way to represent the local time of a diffusion process (like Brownian motion). The local time of a stochastic process B(t) is given by and represents the amount of time that the process spends at the point x in the range of the process. More precisely, in one dimension this integral can be written where is the indicator function of the interval
Quantum mechanics
[edit]The delta function is expedient in quantum mechanics. The wave function of a particle gives the probability amplitude of finding a particle within a given region of space. Wave functions are assumed to be elements of the Hilbert space L2 of square-integrable functions, and the total probability of finding a particle within a given interval is the integral of the magnitude of the wave function squared over the interval. A set {|
where
where cn = ⟨
Here the eigenvalues are assumed to be discrete, but the set of eigenvalues of an observable can also be continuous. An example is the position operator, Q
The eigenfunctions of the position operator are called the eigenstates and are denoted by
Similar considerations apply to the eigenstates of the momentum operator, or indeed any other (unbounded) self-adjoint operator P on the Hilbert space, provided the spectrum of P is continuous and there are no degenerate eigenvalues. In that case, there is a set
That is,
then for any test function
where c(y) = ⟨
where the operator-valued integral is again understood in the weak sense. If the spectrum of P has both continuous and discrete parts, then the resolution of the identity involves a summation over the discrete spectrum and an integral over the continuous spectrum.
The delta function also has many more specialized applications in quantum mechanics, such as the delta potential models for a single and double potential well.
Structural mechanics
[edit]The delta function can be used in structural mechanics to describe transient loads or point loads acting on structures. The governing equation of a simple mass–spring system excited by a sudden force impulse I at time t = 0 can be written
where m is the mass,
As another example, the equation governing the static deflection of a slender beam is, according to Euler–Bernoulli theory,
where EI is the bending stiffness of the beam, w is the deflection, x is the spatial coordinate, and q(x) is the load distribution. If a beam is loaded by a point force F at x = x0, the load distribution is written
As the integration of the delta function results in the Heaviside step function, it follows that the static deflection of a slender beam subject to multiple point loads is described by a set of piecewise polynomials.
Also, a point moment acting on a beam can be described by delta functions. Consider two opposing point forces F at a distance d apart. They then produce a moment M = Fd acting on the beam. Now, let the distance d approach the limit zero, while M is kept constant. The load distribution, assuming a clockwise moment acting at x = 0, is written
Point moments can thus be represented by the derivative of the delta function. Integration of the beam equation again results in piecewise polynomial deflection.
See also
[edit]Notes
[edit]- ^ atis 2013, unit impulse.
- ^ Arfken & Weber 2000, p. 84.
- ^ a b Dirac 1930, §22 The
δ function. - ^ Gelfand & Shilov 1966–1968, Volume I, §1.1.
- ^ Zhao, Ji-Cheng (2011-05-05). Methods for Phase Diagram Determination. Elsevier. ISBN 978-0-08-054996-5.
- ^ Fourier, JB (1822). The Analytical Theory of Heat (English translation by Alexander Freeman, 1878 ed.). The University Press. p. [1]., cf. https://books.google.com/books?id=-N8EAAAAYAAJ&pg=PA449 and pp. 546–551. Original French text.
- ^ Komatsu, Hikosaburo (2002). "Fourier's hyperfunctions and Heaviside's pseudodifferential operators". In Takahiro Kawai; Keiko Fujita (eds.). Microlocal Analysis and Complex Fourier Analysis. World Scientific. p. [2]. ISBN 978-981-238-161-3.
- ^ Myint-U., Tyn; Debnath, Lokenath (2007). Linear Partial Differential Equations for Scientists And Engineers (4th ed.). Springer. p. [3]. ISBN 978-0-8176-4393-5.
- ^ Debnath, Lokenath; Bhatta, Dambaru (2007). Integral Transforms And Their Applications (2nd ed.). CRC Press. p. [4]. ISBN 978-1-58488-575-7.
- ^ Grattan-Guinness, Ivor (2009). Convolutions in French Mathematics, 1800–1840: From the Calculus and Mechanics to Mathematical Analysis and Mathematical Physics, Volume 2. Birkhäuser. p. 653. ISBN 978-3-7643-2238-0.
- ^
See, for example, Cauchy, Augustin-Louis (1789-1857) Auteur du texte (1882–1974). "Des intégrales doubles qui se présentent sous une forme indéterminèe". Oeuvres complètes d'Augustin Cauchy. Série 1, tome 1 / publiées sous la direction scientifique de l'Académie des sciences et sous les auspices de M. le ministre de l'Instruction publique...
{{cite book}}
: CS1 maint: numeric names: authors list (link) - ^ Mitrović, Dragiša; Žubrinić, Darko (1998). Fundamentals of Applied Functional Analysis: Distributions, Sobolev Spaces. CRC Press. p. 62. ISBN 978-0-582-24694-2.
- ^ Kracht, Manfred; Kreyszig, Erwin (1989). "On singular integral operators and generalizations". In Themistocles M. Rassias (ed.). Topics in Mathematical Analysis: A Volume Dedicated to the Memory of A.L. Cauchy. World Scientific. p. https://books.google.com/books?id=xIsPrSiDlZIC&pg=PA553 553]. ISBN 978-9971-5-0666-7.
- ^ Laugwitz 1989, p. 230.
- ^ A more complete historical account can be found in van der Pol & Bremmer 1987, §V.4.
- ^ Dirac, P. A. M. (January 1927). "The physical interpretation of the quantum dynamics". Proceedings of the Royal Society of London. Series A, Containing Papers of a Mathematical and Physical Character. 113 (765): 621–641. Bibcode:1927RSPSA.113..621D. doi:10.1098/rspa.1927.0012. ISSN 0950-1207. S2CID 122855515.
- ^ Gelfand & Shilov 1966–1968, Volume I, §1.1, p. 1.
- ^ Dirac 1930, p. 63.
- ^ Rudin 1966, §1.20
- ^ Hewitt & Stromberg 1963, §19.61.
- ^ Driggers 2003, p. 2321 See also Bracewell 1986, Chapter 5 for a different interpretation. Other conventions for the assigning the value of the Heaviside function at zero exist, and some of these are not consistent with what follows.
- ^ Hewitt & Stromberg 1963, §9.19.
- ^ Hazewinkel 2011, p. 41.
- ^ Strichartz 1994, §2.2.
- ^ Hörmander 1983, Theorem 2.1.5.
- ^ Bracewell 1986, Chapter 5.
- ^ Hörmander 1983, §3.1.
- ^ Strichartz 1994, §2.3.
- ^ Hörmander 1983, §8.2.
- ^ Rudin 1966, §1.20.
- ^ Dieudonné 1972, §17.3.3.
- ^ Krantz, Steven G.; Parks, Harold R. (2008-12-15). Geometric Integration Theory. Springer Science & Business Media. ISBN 978-0-8176-4679-0.
- ^ Federer 1969, §2.5.19.
- ^ Strichartz 1994, Problem 2.6.2.
- ^ Vladimirov 1971, Chapter 2, Example 3(d).
- ^ Rottwitt, Karsten; Tidemand-Lichtenberg, Peter (2014-12-11). Nonlinear Optics: Principles and Applications. CRC Press. p. [5] 276. ISBN 978-1-4665-6583-8.
- ^ Weisstein, Eric W. "Sifting Property". MathWorld.
- ^ Karris, Steven T. (2003). Signals and Systems with MATLAB Applications. Orchard Publications. p. 15. ISBN 978-0-9709511-6-8.
- ^ Roden, Martin S. (2014-05-17). Introduction to Communication Theory. Elsevier. p. [6]. ISBN 978-1-4831-4556-3.
- ^ Gelfand & Shilov 1966–1968, Vol. 1, §II.2.5.
- ^ Further refinement is possible, namely to submersions, although these require a more involved change of variables formula.
- ^ Hörmander 1983, §6.1.
- ^ Lange 2012, pp.29–30.
- ^ Gelfand & Shilov 1966–1968, p. 212.
- ^ The numerical factors depend on the conventions for the Fourier transform.
- ^ Bracewell 1986.
- ^ Gelfand & Shilov 1966–1968, p. 26.
- ^ Gelfand & Shilov 1966–1968, §2.1.
- ^ Weisstein, Eric W. "Doublet Function". MathWorld.
- ^ Bracewell 2000, p. 86.
- ^ "Gugo82's comment on the distributional derivative of Dirac's delta". matematicamente.it. 12 September 2010.
- ^ a b c Hörmander 1983, p. 56.
- ^ Rudin 1991, Theorem 6.25.
- ^ Stein & Weiss 1971, Theorem 1.18.
- ^ Rudin 1991, §II.6.31.
- ^ More generally, one only needs
η =η 1 to have an integrable radially symmetric decreasing rearrangement. - ^ Saichev & Woyczyński 1997, §1.1 The "delta function" as viewed by a physicist and an engineer, p. 3.
- ^ Milovanović, Gradimir V.; Rassias, Michael Th (2014-07-08). Analytic Number Theory, Approximation Theory, and Special Functions: In Honor of Hari M. Srivastava. Springer. p. 748. ISBN 978-1-4939-0258-3.
- ^ Stein & Weiss 1971, §I.1.
- ^ Mader, Heidy M. (2006). Statistics in Volcanology. Geological Society of London. p. 81. ISBN 978-1-86239-208-3.
- ^ Vallée & Soares 2004, §7.2.
- ^ Hörmander 1983, §7.8.
- ^ Courant & Hilbert 1962, §14.
- ^ Gelfand & Shilov 1966–1968, I, §3.10.
- ^ Lang 1997, p. 312.
- ^ In the terminology of Lang (1997), the Fejér kernel is a Dirac sequence, whereas the Dirichlet kernel is not.
- ^ Hazewinkel 1995, p. 357.
- ^ The development of this section in bra–ket notation is found in (Levin 2002, Coordinate-space wave functions and completeness, pp.=109ff)
- ^ Davis & Thomson 2000, Perfect operators, p.344.
- ^ Davis & Thomson 2000, Equation 8.9.11, p. 344.
- ^ de la Madrid, Bohm & Gadella 2002.
- ^ Laugwitz 1989.
- ^ Córdoba 1988.
- ^ Hörmander 1983, §7.2.
- ^ Vladimirov 1971, §5.7.
- ^ Hartmann 1997, pp. 154–155.
- ^ Isham 1995, §6.2.
References
[edit]- Aratyn, Henrik; Rasinariu, Constantin (2006), A short course in mathematical methods with Maple, World Scientific, ISBN 978-981-256-461-0.
- Arfken, G. B.; Weber, H. J. (2000), Mathematical Methods for Physicists (5th ed.), Boston, Massachusetts: Academic Press, ISBN 978-0-12-059825-0.
- atis (2013), ATIS Telecom Glossary, archived from the original on 2013-03-13
- Bracewell, R. N. (1986), The Fourier Transform and Its Applications (2nd ed.), McGraw-Hill.
- Bracewell, R. N. (2000), The Fourier Transform and Its Applications (3rd ed.), McGraw-Hill.
- Córdoba, A. (1988), "La formule sommatoire de Poisson", Comptes Rendus de l'Académie des Sciences, Série I, 306: 373–376.
- Courant, Richard; Hilbert, David (1962), Methods of Mathematical Physics, Volume II, Wiley-Interscience.
- Davis, Howard Ted; Thomson, Kendall T (2000), Linear algebra and linear operators in engineering with applications in Mathematica, Academic Press, ISBN 978-0-12-206349-7
- Dieudonné, Jean (1976), Treatise on analysis. Vol. II, New York: Academic Press [Harcourt Brace Jovanovich Publishers], ISBN 978-0-12-215502-4, MR 0530406.
- Dieudonné, Jean (1972), Treatise on analysis. Vol. III, Boston, Massachusetts: Academic Press, MR 0350769
- Dirac, Paul (1930), The Principles of Quantum Mechanics (1st ed.), Oxford University Press.
- Driggers, Ronald G. (2003), Encyclopedia of Optical Engineering, CRC Press, Bibcode:2003eoe..book.....D, ISBN 978-0-8247-0940-2.
- Duistermaat, Hans; Kolk (2010), Distributions: Theory and applications, Springer.
- Federer, Herbert (1969), Geometric measure theory, Die Grundlehren der mathematischen Wissenschaften, vol. 153, New York: Springer-Verlag, pp. xiv+676, ISBN 978-3-540-60656-7, MR 0257325.
- Gannon, Terry (2008), "Vertex operator algebras", Princeton Companion to Mathematics, Princeton University Press, ISBN 978-1400830398.
- Gelfand, I. M.; Shilov, G. E. (1966–1968), Generalized functions, vol. 1–5, Academic Press, ISBN 9781483262246.
- Hartmann, William M. (1997), Signals, sound, and sensation, Springer, ISBN 978-1-56396-283-7.
- Hazewinkel, Michiel (1995). Encyclopaedia of Mathematics (set). Springer Science & Business Media. ISBN 978-1-55608-010-4.
- Hazewinkel, Michiel (2011). Encyclopaedia of mathematics. Vol. 10. Springer. ISBN 978-90-481-4896-7. OCLC 751862625.
- Hewitt, E; Stromberg, K (1963), Real and abstract analysis, Springer-Verlag.
- Hörmander, L. (1983), The analysis of linear partial differential operators I, Grundl. Math. Wissenschaft., vol. 256, Springer, doi:10.1007/978-3-642-96750-4, ISBN 978-3-540-12104-6, MR 0717035.
- Isham, C. J. (1995), Lectures on quantum theory: mathematical and structural foundations, Imperial College Press, ISBN 978-81-7764-190-5.
- John, Fritz (1955), Plane waves and spherical means applied to partial differential equations, Interscience Publishers, New York-London, ISBN 9780486438047, MR 0075429.
- Lang, Serge (1997), Undergraduate analysis, Undergraduate Texts in Mathematics (2nd ed.), Berlin, New York: Springer-Verlag, doi:10.1007/978-1-4757-2698-5, ISBN 978-0-387-94841-6, MR 1476913.
- Lange, Rutger-Jan (2012), "Potential theory, path integrals and the Laplacian of the indicator", Journal of High Energy Physics, 2012 (11): 29–30, arXiv:1302.0864, Bibcode:2012JHEP...11..032L, doi:10.1007/JHEP11(2012)032, S2CID 56188533.
- Laugwitz, D. (1989), "Definite values of infinite sums: aspects of the foundations of infinitesimal analysis around 1820", Arch. Hist. Exact Sci., 39 (3): 195–245, doi:10.1007/BF00329867, S2CID 120890300.
- Levin, Frank S. (2002), "Coordinate-space wave functions and completeness", An introduction to quantum theory, Cambridge University Press, pp. 109ff, ISBN 978-0-521-59841-5
- Li, Y. T.; Wong, R. (2008), "Integral and series representations of the Dirac delta function", Commun. Pure Appl. Anal., 7 (2): 229–247, arXiv:1303.1943, doi:10.3934/cpaa.2008.7.229, MR 2373214, S2CID 119319140.
- de la Madrid, R.; Bohm, A.; Gadella, M. (2002), "Rigged Hilbert Space Treatment of Continuous Spectrum", Fortschr. Phys., 50 (2): 185–216, arXiv:quant-ph/0109154, Bibcode:2002ForPh..50..185D, doi:10.1002/1521-3978(200203)50:2<185::AID-PROP185>3.0.CO;2-S, S2CID 9407651.
- McMahon, D. (2005-11-22), "An Introduction to State Space" (PDF), Quantum Mechanics Demystified, A Self-Teaching Guide, Demystified Series, New York: McGraw-Hill, p. 108, ISBN 978-0-07-145546-6, retrieved 2008-03-17.
- van der Pol, Balth.; Bremmer, H. (1987), Operational calculus (3rd ed.), New York: Chelsea Publishing Co., ISBN 978-0-8284-0327-6, MR 0904873.
- Rudin, Walter (1966). Devine, Peter R. (ed.). Real and complex analysis (3rd ed.). New York: McGraw-Hill (published 1987). ISBN 0-07-100276-6.
- Rudin, Walter (1991), Functional Analysis (2nd ed.), McGraw-Hill, ISBN 978-0-07-054236-5.
- Vallée, Olivier; Soares, Manuel (2004), Airy functions and applications to physics, London: Imperial College Press, ISBN 9781911299486.
- Saichev, A I; Woyczyński, Wojbor Andrzej (1997), "Chapter1: Basic definitions and operations", Distributions in the Physical and Engineering Sciences: Distributional and fractal calculus, integral transforms, and wavelets, Birkhäuser, ISBN 978-0-8176-3924-2
- Schwartz, L. (1950), Théorie des distributions, vol. 1, Hermann.
- Schwartz, L. (1951), Théorie des distributions, vol. 2, Hermann.
- Stein, Elias; Weiss, Guido (1971), Introduction to Fourier Analysis on Euclidean Spaces, Princeton University Press, ISBN 978-0-691-08078-9.
- Strichartz, R. (1994), A Guide to Distribution Theory and Fourier Transforms, CRC Press, ISBN 978-0-8493-8273-4.
- Vladimirov, V. S. (1971), Equations of mathematical physics, Marcel Dekker, ISBN 978-0-8247-1713-1.
- Weisstein, Eric W. "Delta Function". MathWorld.
- Yamashita, H. (2006), "Pointwise analysis of scalar fields: A nonstandard approach", Journal of Mathematical Physics, 47 (9): 092301, Bibcode:2006JMP....47i2301Y, doi:10.1063/1.2339017
- Yamashita, H. (2007), "Comment on "Pointwise analysis of scalar fields: A nonstandard approach" [J. Math. Phys. 47, 092301 (2006)]", Journal of Mathematical Physics, 48 (8): 084101, Bibcode:2007JMP....48h4101Y, doi:10.1063/1.2771422
External links
[edit]Media related to Dirac distribution at Wikimedia Commons
- "Delta-function", Encyclopedia of Mathematics, EMS Press, 2001 [1994]
- KhanAcademy.org video lesson
- The Dirac Delta function, a tutorial on the Dirac delta function.
- Video Lectures – Lecture 23, a lecture by Arthur Mattuck.
- The Dirac delta measure is a hyperfunction
- We show the existence of a unique solution and analyze a finite element approximation when the source term is a Dirac delta measure
- Non-Lebesgue measures on R. Lebesgue-Stieltjes measure, Dirac delta measure. Archived 2008-03-07 at the Wayback Machine