Convolution
Convolution combines two functions by sliding one against the other and integrating the overlap. In Fourier analysis, it is important because convolution in one representation becomes multiplication in the transformed representation.
For functions on the real line, a common convention is
The operation is associative and commutative under standard hypotheses, but in applications the order often carries interpretation: a source is acted on by a response kernel, or a wavefunction is mixed by a potential.
Why Convolution Matters
Section titled “Why Convolution Matters”Convolution appears whenever a linear translation-invariant system builds its output by superposing shifted copies of one fixed response:
Here is a source and is the response to a point source. This is the full-line, translation-invariant version of a Green-function formula. When boundaries or nonuniform coefficients break translation invariance, the kernel usually depends on both variables separately as instead of only on .
Convolution Theorem in the k Convention
Section titled “Convolution Theorem in the k Convention”For the ordinary -space convention
the convolution theorem is
The product theorem is the companion identity:
The placement of the factor depends on the Fourier convention. This is one reason to check Fourier Transform Conventions before comparing formulas across sources.
Proof of the Convolution Theorem
Section titled “Proof of the Convolution Theorem”For sufficiently well-behaved functions,
The second line uses . For distributions and less regular functions, this calculation must be interpreted with the appropriate functional-analytic hypotheses.
Site Wavefunction Convention
Section titled “Site Wavefunction Convention”The wave-mechanics pages use the unitary convention
With this symmetric normalization,
The product theorem becomes
Thus a local product in position space becomes momentum mixing. In one-dimensional quantum mechanics, if multiplies a wavefunction , then in momentum space the potential term has the form
where is the momentum-space wavefunction. Local potentials are therefore not usually diagonal in momentum representation.
For the operator dictionary that uses this fact, see Momentum Representation.
Delta Functions and Shifts
Section titled “Delta Functions and Shifts”The delta distribution is the identity for convolution:
More generally, let
Then
This identity says that a shifted point source produces a shifted response. It is the simplest way to remember why a Green function is the response to a source located at in a translation-invariant problem.
Green Functions as Convolution Kernels
Section titled “Green Functions as Convolution Kernels”Let be a translation-invariant differential operator on the real line. If
then the solution of
is formally
Fourier transformation turns the differential equation into algebra. If has Fourier symbol , then
The Green function is the inverse transform of , and multiplication by in Fourier space is convolution by in position space.
For example, with
the Fourier symbol is
Thus
Then
solves
under the full-line decay condition. For the broader operator-and-boundary-condition perspective, see Green Functions.
Response Interpretation
Section titled “Response Interpretation”In response language, is an impulse response. A general source is decomposed into point sources, each point source produces a shifted response , and integration adds all responses:
Fourier space says the same thing differently:
The response kernel becomes a transfer function. Frequencies or momenta for which is large are amplified; those for which is small are suppressed. In quantum scattering, propagators and resolvents play the same structural role, though their boundary prescriptions and normalization conventions must be stated explicitly.
Common Mistakes
Section titled “Common Mistakes”- Confusing convolution with pointwise multiplication.
- Dropping the factor of or when changing Fourier conventions.
- Using a translation-invariant convolution formula when the boundary conditions require a two-variable Green function .
- Treating products or convolutions of distributions as automatically defined.
- Confusing convolution with correlation, where one of the functions is reversed or conjugated.
- Forgetting that a local potential in position space generally becomes a momentum-space convolution.
Cross-Links
Section titled “Cross-Links”- Fourier Transform
- Inverse Fourier Transform
- Plancherel and Parseval Theorems
- Momentum Representation
- Delta Function
- Green Functions
- Fourier Transform Table
- Position and Momentum Representations
References
Section titled “References”- G. B. Folland, Fourier Analysis and Its Applications, American Mathematical Society, 1992.
- E. M. Stein and R. Shakarchi, Fourier Analysis: An Introduction, Princeton University Press, 2003.
- G. B. Arfken, H. J. Weber, and F. E. Harris, Mathematical Methods for Physicists, 7th ed., Academic Press, 2013.
- G. F. Roach, Green’s Functions, 2nd ed., Cambridge University Press, 1982.
- E. N. Economou, Green’s Functions in Quantum Physics, 3rd ed., Springer, 2006.
Exercises
Section titled “Exercises”- Prove the convolution theorem in the convention.
Solution
Start from the definition:
Set , so and . Then
Because multiplication is commutative, this is .
- Let . Compute .
Solution
Using the convolution definition,
The delta distribution evaluates the integrand at , giving
- In the unitary convention, why does a product become a convolution in momentum space?
Solution
Write both factors by inverse Fourier transforms:
and
Multiplying and transforming back gives a delta constraint , so
Thus each output momentum receives contributions from many input momenta.
- Let satisfy for a translation-invariant operator . Show formally that solves .
Solution
Because acts on the variable and is translation-invariant,
Using gives
This formal argument assumes the convolution is defined and that can be moved through the integral. Boundary-value problems require the corresponding Green-function kernel and domain conditions.