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{{Short description|Mathematical method for integrodifferential equations}}
The '''Wiener-Hopf''' technique is a mathematical technique widely used in [[applied mathematics]]. It was initially developed by [[Norbert Wiener]] as a method to solve simultaneous [[integral equations]], but has found wider use in solving two-dimensional [[partial differential equations]] with mixed [[boundary conditions]] on the same boundary. In general, the method works by exploiting the [[Complex analysis|complex-analytical]] properties of transformed functions. Usually, the standard [[Fourier transform]] is used, but examples exist using other transforms, such as the [[Mellin transform]].
The '''Wiener–Hopf method''' is a mathematical technique widely used in [[applied mathematics]]. It was initially developed by [[Norbert Wiener]] and [[Eberhard Hopf]] as a method to solve systems of [[integral equation]]s, but has found wider use in solving two-dimensional [[partial differential equation]]s with mixed [[boundary conditions]] on the same boundary. In general, the method works by exploiting the [[Complex analysis|complex-analytical]] properties of transformed functions. Typically, the standard [[Fourier transform]] is used, but examples exist using other transforms, such as the [[Mellin transform]].
 
In general, the governing equations and boundary conditions are transformed and these transforms are used to define a pair of complex functions (typically denoted with '+' and '-' subscripts) which are respectively [[analytic function|analytic]] in the upper and lower halves of the complex plane, and have growth no faster than polynomials in these regions. These two functions will also be equal to one anothercoincide on some small subsetregion of the [[complex plane]], (typically, a thin strip containing the [[real line)]]. [[Analytic continuation]] guarantees that these two functions define a single function analytic throughoutin the entire complex plane, and [[Liouville's theorem (complex analysis)|Liouville's theorem]] tells usimplies that this function mustis bean identicalunknown to[[polynomial]], somewhich unknownis often zero or polynomialconstant. Analysis of the conditions at the edges and corners of the boundary willallows findone to determine the orderdegree of this polynomial (which is often a constant, or even zero).
 
== Wiener-HopfWiener–Hopf Decompositiondecomposition ==
The fundamental equation that appears in the Wiener-Hopf method is of the form
The key step in many W-H problems is to decompose an arbitrary function <math>\Phi</math> into two functions <math>\Phi_{\pm}</math> with the desired properties outlined above. In general, this can be done by writing
:<math>A(\alpha)\Xi_+(\alpha) + B(\alpha)\Psi_-(\alpha) + C(\alpha) =0, </math>
where <math>A</math>, <math>B</math>, <math>C</math> are known [[holomorphic function]]s, the functions <math>\Xi_+(\alpha)</math>, <math>\Psi_-(\alpha)</math> are unknown and the equation holds in a strip <math>\tau_- < \mathfrak{Im}(\alpha) < \tau_+</math> in the [[Complex_plane|complex <math>\alpha</math> plane]]. Finding <math>\Xi_+(\alpha)</math>, <math>\Psi_-(\alpha)</math> is what's called the '''Wiener-Hopf problem'''.{{sfn | Noble | 1958 | loc=§4.2}}
 
The key step in many Wiener–Hopf problems is to decompose an arbitrary function <math>\Phi</math> into two functions <math>\Phi_{\pm}</math> with the desired properties outlined above. In general, this can be done by writing
<math>\Phi_+(\alpha) = \frac{1}{2\pi i} \int_{C_1} \Phi(z) \frac{dz}{z-\alpha}</math> and
 
: <math>\Phi_-+(\alpha) = - \frac{1}{2\pi i} \int_{C_2C_1} \Phi(z) \frac{dz}{z-\alpha}</math>,
 
and
where the contours <math>C_1</math> and <math>C_2</math> are parallel to the real line, but pass above and below the point <math>z=\alpha</math>, respectively.
 
: <math>\Phi_-(\alpha) = - \frac{1}{2\pi i} \int_{C_2} \Phi(z) \frac{dz}{z-\alpha},</math>
Similarly, arbitrary scalar functions may be decomposed into a product of +/- functions, i.e. <math>K(\alpha) = K_+(\alpha)K_-(\alpha)</math>, by first taking the logarithm, and then performing a sum decomposition. Product decompositions of matrix functions (which occur in coupled multi-modal systems such as elastic waves) are considerably more problematic since the logarithm is not well defined, and any decomposition might be expected to be non-commutative. A small subclass of commutative decompositions were obtained by Khrapkov, and various approximate methods have also been developed.
 
where the contours <math>C_1</math> and <math>C_2</math> are parallel to the real line, but pass above and below the point <math>z=\alpha</math>, respectively.{{sfn | Noble | 1958 | loc=Chapter 1}}
 
Similarly, arbitrary scalar functions may be decomposed into a product of +/− functions, i.e. <math>K(\alpha) = K_+(\alpha)K_-(\alpha)</math>, by first taking the logarithm, and then performing a sum decomposition. Product decompositions of matrix functions (which occur in coupled multi-modal systems such as elastic waves) are considerably more problematic since the logarithm is not well defined, and any decomposition might be expected to be non-commutative. A small subclass of commutative decompositions were obtained by Khrapkov, and various approximate methods have also been developed.{{citation needed|date=May 2020}}
 
==Example==
Let us considerConsider the linear [[Partial differential equation|partial differential equation]] <br>
:<math>\boldsymbol{L}_{xy}f(x,y)=0,</math>
<center>
where <math>\boldsymbol{L}_{xy}</math> is a linear operator which contains derivatives with respect to {{mvar|x}} and {{mvar|y}}, subject to the mixed conditions on {{mvar|y}}&nbsp;=&nbsp;0, for some prescribed function {{math|''g''(''x'')}},
<math>
:<math>f=g(x)\text{ for }x\leq 0, \quad f_y=0\text{ when }x>0</math>
\boldsymbol{L}_{xy}f(x,y)=0,
and decay at infinity i.e. {{mvar|f}}&nbsp;→&nbsp;0 as <math>\boldsymbol{x}\rightarrow \infty</math>.
</math>
 
</center>
Taking a [[Fourier transform]] with respect to {{mvar|x}} results in the following [[ordinary differential equation]]
where <math>\boldsymbol{L}_{xy}</math> is a linear operator which contains
: <math>\boldsymbol{L}_y \widehat{f}(k,y)-P(k,y)\widehat{f}(k,y)=0,</math>
derivatives with respect to <math>x</math> and <math>y</math>,
where <math>\boldsymbol{L}_{y}</math> is a linear operator containing {{mvar|y}} derivatives only, {{math|''P''(''k,y'')}} is a known function of {{mvar|y}} and {{mvar|k}} and
subject to the mixed conditions on <math>y=0</math>, for some prescribed
: <math> \widehat{f}(k,y)=\int_{-\infty}^\infty f(x,y)e^{-ikx} \, \textrm{d}x. </math>
function <math>g(x)</math>,
 
<br>
If a particular solution of this ordinary differential equation which satisfies the necessary decay at infinity is denoted {{math| ''F''(''k'',''y'')}}, a general solution can be written as
<center>
: <math> \widehat{f}(k,y)=C(k)F(k,y), </math>
<math>
where {{math|''C''(''k'')}} is an unknown function to be determined by the boundary conditions on {{mvar|y}}=0.
f=g(x)</math> for <math>x\leq 0,
 
</math>
The key idea is to split <math>\widehat{f}</math> into two separate functions, <math>\widehat{f}_{+}</math> and <math>\widehat{f}_{-}</math> which are analytic in the lower- and upper-halves of the complex plane, respectively,
</center>
: <math> \widehat{f}_{+}(k,y)=\int_0^\infty f(x,y)e^{-ikx}\,\textrm{d}x, </math>
<br>
: <math> \widehat{f}_{-}(k,y)=\int_{-\infty}^0 f(x,y)e^{-ikx}\,\textrm{d}x. </math>
<center>
<math>
f_{y}=0</math> when <math>x>0
</math>.
</center>
and decay at infinity i.e. <math>f\rightarrow 0</math>
as <math>\boldsymbol{x}\rightarrow \infty</math>. Taking a [[Fourier transform]] with respect to x results in the following [[Ordinary differential equation|ODE]]
<center>
<math>
\boldsymbol{L}_{y}\hat{f}(k,y)-P(k,y)\hat{f}(k,y)=0,
</math>
</center>
where <math>\boldsymbol{L}_{y}</math> is a linear operator containing
<math>y</math> derivatives only, <math>P(k,y)</math> is a known function
of <math>y</math> and <math>k</math> and
<br>
<center>
<math>
\hat{f}(k)=\int_{-\infty}^{\infty} f(x,y)e^{-ikx}\textrm{d}x.
</math>
</center>
If a particular solution of the ODE which satisfies the necessary decay at infinity
is denoted <math>\hat{F}(k,y)</math>, a general
solution can be written as
<center>
<math>
\hat{f}=C(k)\hat{F}(k,y)
</math>
</center>
where <math>C(k)</math> is an unknown function to be determined by the boundary conditions on <math>y=0</math>.
 
The key idea is to
split <math>\hat{f}</math> into two separate functions, <math>\hat{f}_{+}</math> and <math>\hat{f}_{-}</math> which are analytic in the lower- and upper-halves of the complex plane, respectively
<br>
<center>
<math>
\hat{f}_{+}(k,y)=\int_{0}^{\infty} f(x,y)e^{-ikx}\textrm{d}x,
</math>
</br>
<math>
\hat{f}_{-}(k,y)=\int_{-\infty}^{0} f(x,y)e^{-ikx}\textrm{d}x.
</math>
</center>
The boundary conditions then give
: <math> \widehat{g\,}(k)+\widehat{f}_{+}(k,0) = \widehat{f}_{-}(k,0)+\widehat{f}_{+}(k,0) = \widehat{f}(k,0) = C(k)F(k,0) </math>
<br>
<center>
<math>
\hat{f}_{-}(k,0)+\hat{f}_{+}(k,0)
=
\hat{g}(k)+\hat{f}_{+}(k,0)
=
C(k)F(k,0)</math>
</center><br>
and, on taking derivatives with respect to <math>y</math>,
: <math> \widehat{f}'_{-}(k,0) = \widehat{f}'_{-}(k,0)+\widehat{f}'_{+}(k,0) = \widehat{f}'(k,0) = C(k)F'(k,0). </math>
<br>
 
<center>
<math>
\hat{f}'_{-}(k,0)+\hat{f}'_{+}(k,0)
=
\hat{f}'_{-}(k,0)
=
C(k)F'(k,0).
</math>
</center>
Eliminating <math>C(k)</math> yields
: <math> \widehat{g\,}(k)+\widehat{f}_{+}(k,0) = \widehat{f}'_{-}(k,0)/K(k), </math>
<br>
<center>
<math>
\hat{g}(k)+\hat{f}_{+}(k,0)
-
\hat{f}'_{-}(k,0)/K(k)</math>
=
0,
</center>
where
: <math> K(k)=\frac{F'(k,0)}{F(k,0)}. </math>
<center>
 
<math>
Now <math>K(k)</math> can be decomposed into the product of functions <math>K^{-}</math> and <math>K^{+}</math> which are analytic in the upper and lower half-planes respectively.
K(k)
 
=
To be precise, <math> K(k)=K^{+}(k)K^{-}(k), </math> where
\frac{F'(k,0)}{F(k,0)}.
: <math> \log K^{-} = \frac{1}{2\pi i}\int_{-\infty}^\infty \frac{\log(K(z))}{z-k} \,\textrm{d}z, \quad \operatorname{Im}k>0, </math>
</math>
: <math> \log K^{+} = -\frac{1}{2\pi i}\int_{-\infty}^\infty \frac{\log(K(z))}{z-k} \,\textrm{d}z, \quad \operatorname{Im}k<0. </math>
</center>
Now(Note that this sometimes involves scaling <math>K(</math> so that it tends to <math>1</math> as <math>k)\rightarrow\infty</math>.) canWe bealso decomposeddecompose <math>K^{+}\widehat{g\,}</math> into the productsum of two functions <math>KG^{-+}</math> and <math>KG^{+-}</math> which are analytic in the upper-halflower planeand orupper lower-half-planes planerespectively, respectivelyi.e.,
: <math> K^{+}(k)\widehat{g\,}(k)=G^{+}(k)+G^{-}(k). </math>
<center>
 
<math>
This can be done in the same way that we factorised <math> K(k). </math>
K(k)=K^{+}(k)K^{-}(k),
Consequently,
</math>
: <math> G^{+}(k) + K_{+}(k)\widehat{f}_{+}(k,0) = \widehat{f}'_{-}(k,0)/K_{-}(k) - G^{-}(k). </math>
</center>
 
<br>
Now, as the left-hand side of the above equation is analytic in the lower half-plane, whilst the right-hand side is analytic in the upper half-plane, analytic continuation guarantees existence of an entire function which coincides with the left- or right-hand sides in their respective half-planes. Furthermore, since it can be shown that the functions on either side of the above equation decay at large {{mvar|k}}, an application of [[Liouville's theorem (complex analysis)|Liouville's theorem]] shows that this entire function is identically zero, therefore
<center>
:<math> \widehat{f}_{+}(k,0) = -\frac{G^{+}(k)}{K^{+}(k)}, </math>
<math>
\hbox{log}
K^{-}
=
\frac{1}{2\pi i}\int_{-\infty}^{\infty} \frac{\hbox{log}(K(z))}{z-k} \textrm{d}z,
\quad
\hbox{Im}k>0,
</math>
<br>
<math>
\hbox{log}
K^{+}
=
-\frac{1}{2\pi i}\int_{-\infty}^{\infty} \frac{\hbox{log}(K(z))}{z-k} \textrm{d}z,
\quad
\hbox{Im}k<0.
</math>
</center>
Consequently
<br>
<center>
<math>
K_{+}(k)\hat{g}_{+}(k)
+
K_{+}(k)\hat{f}_{+}(k,0)
=
\hat{f}'_{-}(k,0)/K_{-}(k)
-
K_{+}(k)\hat{g}_{-}(k),
</math>
</center>
where it has been assumed that <math>g</math> can be broken down into functions analytic in the lower-half plane
<math>g_{+}</math> and upper-half plane <math>g_{-}</math>, respectively.
Now, as the left-hand side of the above equation is analytic in the lower-half
plane, whilst the right-hand side is analytic in the upper-half plane, analytic
continution guarantees existence of an entire function which coincides with the
left- or right-hand sides in their respective half-planes. Furthermore, since it can
be shown that the functions on either side of the above equation decay at large
<math>k</math>, [[Liouville's theorem (complex analysis)]] tells us that this entire function
is identically zero, therefore
<br>
<center>
<math>
\hat{f}_{+}(k,0)
=
-\hat{g}_{+}(k),
</math>
</center>
and so
: <math> C(k) = \frac{K^{+}(k)\widehat{g\,}(k)-G^{+}(k)}{K^{+}(k)F(k,0)}. </math>
<br>
 
<center>
== See also ==
<math>
 
C(k)
* [[Wiener filter]]
=
*[[Riemann–Hilbert problem]]
\frac{\hat{g}(k)-\hat{g}_{+}(k)}{F(k,0)}.
</math>
</center>
 
==External linksNotes ==
{{reflist}}
== References ==
 
*[http {{Cite web|title=Category:Wiener-Hopf - WikiWaves|url=https://www.wikiwaves.org/index.php/Category:Wiener-Hopf Wiener|website=wikiwaves.org|access-Hopf for Linear Water Waves]date=2020-05-19}}
* {{SpringerEOM |id=W/w097910|title=Wiener-Hopf method}}
* {{Cite book|last=Fornberg, Bengt|title=Complex variables and analytic functions : an illustrated introduction|others=Piret, Cécile.|date=2020 |isbn=978-1-61197-597-0|___location=Philadelphia|oclc=1124781689}}
* {{cite book | last=Noble | first=Ben | title=Methods Based on the Wiener-Hopf Technique for the Solution of Partial Differential Equations | publisher=Taylor & Francis US | publication-place=New York, N.Y | date=1958 | isbn=978-0-8284-0332-0}}
 
{{DEFAULTSORT:Wiener-Hopf method}}
[[Category:Partial differential equations]]