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\pdf_title "Accelerating lattice mode calculations with T-matrix method"
\pdf_author "Marek Nečada"
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\begin_body
\begin_layout Standard
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\end_layout
\begin_layout Title
Accelerating lattice mode calculations with
\begin_inset Formula $T$
\end_inset
-matrix method
\end_layout
\begin_layout Author
Marek Nečada
\end_layout
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\begin_layout Abstract
The
\begin_inset Formula $T$
\end_inset
-matrix approach is the method of choice for simulating optical response
of a reasonably small system of compact linear scatterers on isotropic
background.
However, its direct utilisation for problems with infinite lattices is
problematic due to slowly converging sums over the lattice.
Here I develop a way to compute the problematic sums in the reciprocal
space, making the
\begin_inset Formula $T$
\end_inset
-matrix method very suitable for infinite periodic systems as well.
\end_layout
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\begin_layout Section
Formulation of the problem
\end_layout
\begin_layout Standard
Assume a system of compact EM scatterers in otherwise homogeneous and isotropic
medium, and assume that the system, i.e.
both the medium and the scatterers, have linear response.
A scattering problem in such system can be written as
\begin_inset Formula
\[
A_{α }=T_{α }P_{α }=T_{α }(\sum_{β}S_{α \leftarrowβ}A_{β}+P_{0α })
\]
\end_inset
where
\begin_inset Formula $T_{α }$
\end_inset
is the
\begin_inset Formula $T$
\end_inset
-matrix for scatterer α ,
\begin_inset Formula $A_{α }$
\end_inset
is its vector of the scattered wave expansion coefficient (the multipole
indices are not explicitely indicated here) and
\begin_inset Formula $P_{α }$
\end_inset
is the local expansion of the incoming sources.
\begin_inset Formula $S_{α \leftarrowβ}$
\end_inset
is ...
and ...
is ...
\end_layout
\begin_layout Standard
...
\end_layout
\begin_layout Standard
\begin_inset Formula
\[
\sum_{β}(\delta_{αβ}-T_{α }S_{α \leftarrowβ})A_{β}=T_{α }P_{0α }.
\]
\end_inset
\end_layout
\begin_layout Standard
Now suppose that the scatterers constitute an infinite lattice
\end_layout
\begin_layout Standard
\begin_inset Formula
\[
\sum_{\vect bβ}(\delta_{\vect{ab}}\delta_{αβ}-T_{\vect aα }S_{\vect aα \leftarrow\vect bβ})A_{\vect bβ}=T_{\vect aα }P_{0\vect aα }.
\]
\end_inset
Due to the periodicity, we can write
\begin_inset Formula $S_{\vect aα \leftarrow\vect bβ}=S_{α \leftarrowβ}(\vect b-\vect a)$
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\end_inset
and
\begin_inset Formula $T_{\vect aα }=T_{\alpha}$
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\end_inset
.
In order to find lattice modes, we search for solutions with zero RHS
\begin_inset Formula
\[
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\sum_{\vect bβ}(\delta_{\vect{ab}}\delta_{αβ}-T_{α }S_{\vect aα \leftarrow\vect bβ})A_{\vect bβ}=0
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\]
\end_inset
and we assume periodic solution
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\begin_inset Formula $A_{\vect b\beta}(\vect k)=A_{\vect a\beta}e^{i\vect k\cdot\vect r_{\vect b-\vect a}}$
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\end_inset
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, yielding
\begin_inset Formula
\begin{eqnarray*}
\sum_{\vect bβ}(\delta_{\vect{ab}}\delta_{αβ}-T_{α }S_{\vect aα \leftarrow\vect bβ})A_{\vect a\beta}\left(\vect k\right)e^{i\vect k\cdot\vect r_{\vect b-\vect a}} & = & 0,\\
\sum_{\vect bβ}(\delta_{\vect{0b}}\delta_{αβ}-T_{α }S_{\vect 0α \leftarrow\vect bβ})A_{\vect 0\beta}\left(\vect k\right)e^{i\vect k\cdot\vect r_{\vect b}} & = & 0,\\
\sum_{β}(\delta_{αβ}-T_{α }\underbrace{\sum_{\vect b}S_{\vect 0α \leftarrow\vect bβ}e^{i\vect k\cdot\vect r_{\vect b}}}_{W_{\alpha\beta}(\vect k)})A_{\vect 0\beta}\left(\vect k\right) & = & 0,\\
A_{\vect 0\alpha}\left(\vect k\right)-T_{α }\sum_{\beta}W_{\alpha\beta}\left(\vect k\right)A_{\vect 0\beta}\left(\vect k\right) & = & 0.
\end{eqnarray*}
\end_inset
Therefore, in order to solve the modes, we need to compute the
\begin_inset Quotes eld
\end_inset
lattice Fourier transform
\begin_inset Quotes erd
\end_inset
of the translation operator,
\begin_inset Formula
\begin{equation}
W_{\alpha\beta}(\vect k)\equiv\sum_{\vect b}S_{\vect 0α \leftarrow\vect bβ}e^{i\vect k\cdot\vect r_{\vect b}}.\label{eq:W definition}
\end{equation}
\end_inset
\end_layout
\begin_layout Section
Computing the Fourier sum of the translation operator
\end_layout
\begin_layout Standard
The problem evaluating
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:W definition"
\end_inset
is the asymptotic behaviour of the translation operator,
\begin_inset Formula $S_{\vect 0α \leftarrow\vect bβ}\sim\left|\vect r_{\vect b}\right|^{-1}e^{ik_{0}\left|\vect r_{\vect b}\right|}$
\end_inset
that makes the convergence of the sum quite problematic for any
\begin_inset Formula $d>1$
\end_inset
-dimensional lattice.
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\begin_inset Foot
status open
\begin_layout Plain Layout
Note that
\begin_inset Formula $d$
\end_inset
here is dimensionality of the lattice, not the space it lies in, which
I for certain reasons assume to be three.
(TODO few notes on integration and reciprocal lattices in some appendix)
\end_layout
\end_inset
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In electrostatics, one can solve this problem with Ewald summation.
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Its basic idea is that if what asymptoticaly decays poorly in the direct
space, will perhaps decay fast in the Fourier space.
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I use the same idea here, but everything will be somehow harder than in
electrostatics.
\end_layout
\begin_layout Standard
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Let us re-express the sum in
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:W definition"
\end_inset
in terms of integral with a delta comb
\end_layout
\begin_layout Standard
\begin_inset Formula
\begin{equation}
W_{\alpha\beta}(\vect k)=\int\ud^{d}\vect r\dc{\basis u}(\vect r)S(\vect r_{\alpha}\leftarrow\vect r+\vect r_{\beta})e^{i\vect k\cdot\vect r}.\label{eq:W integral}
\end{equation}
\end_inset
The translation operator
\begin_inset Formula $S$
\end_inset
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is now a function defined in the whole 3d space;
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\begin_inset Formula $\vect r_{\alpha},\vect r_{\beta}$
\end_inset
are the displacements of scatterers
\begin_inset Formula $\alpha$
\end_inset
and
\begin_inset Formula $\beta$
\end_inset
in a unit cell.
The arrow notation
\begin_inset Formula $S(\vect r_{\alpha}\leftarrow\vect r+\vect r_{\beta})$
\end_inset
means
\begin_inset Quotes eld
\end_inset
translation operator for spherical waves originating in
\begin_inset Formula $\vect r+\vect r_{\beta}$
\end_inset
evaluated in
\begin_inset Formula $\vect r_{\alpha}$
\end_inset
\begin_inset Quotes erd
\end_inset
and obviously
\begin_inset Formula $S$
\end_inset
is in fact a function of a single 3d argument,
\begin_inset Formula $S(\vect r_{\alpha}\leftarrow\vect r+\vect r_{\beta})=S(\vect 0\leftarrow\vect r+\vect r_{\beta}-\vect r_{\alpha})=S(-\vect r-\vect r_{\beta}+\vect r_{\alpha}\leftarrow\vect 0)=S(-\vect r-\vect r_{\beta}+\vect r_{\alpha})$
\end_inset
.
Expression
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:W integral"
\end_inset
can be rewritten as
\begin_inset Formula
\[
W_{\alpha\beta}(\vect k)=\left(2\pi\right)^{\frac{d}{2}}\uaft{(\dc{\basis u}S(\vect{\bullet}-\vect r_{\beta}+\vect r_{\alpha}\leftarrow\vect 0))\left(\vect k\right)}
\]
\end_inset
where changed the sign of
\begin_inset Formula $\vect r/\vect{\bullet}$
\end_inset
has been swapped under integration, utilising evenness of
\begin_inset Formula $\dc{\basis u}$
\end_inset
.
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Fourier transform of product is convolution of Fourier transforms, so (using
formula
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:Dirac comb uaFt"
\end_inset
for the Fourier transform of Dirac comb)
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\begin_inset Formula
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\begin{eqnarray}
W_{\alpha\beta}(\vect k) & = & \left(\left(\uaft{\dc{\basis u}}\right)\ast\left(\uaft{S(\vect{\bullet}-\vect r_{\beta}+\vect r_{\alpha}\leftarrow\vect 0)}\right)\right)(\vect k)\nonumber \\
& = & \frac{\left|\det\recb{\basis u}\right|}{\left(2\pi\right)^{\frac{d}{2}}}\left(\dc{\recb{\basis u}}^{(d)}\ast\left(\uaft{S(\vect{\bullet}-\vect r_{\beta}+\vect r_{\alpha}\leftarrow\vect 0)}\right)\right)\left(\vect k\right)\nonumber \\
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& = & \frac{\left|\det\rec{\basis u}\right|}{\left(2\pi\right)^{\frac{d}{2}}}\sum_{\vect K\in\recb{\basis u}\ints^{d}}\left(\uaft{S(\vect{\bullet}-\vect r_{\beta}+\vect r_{\alpha}\leftarrow\vect 0)}\right)\left(\vect k-\vect K\right)\label{eq:W sum in reciprocal space}\\
& = & \frac{\left|\det\rec{\basis u}\right|}{\left(2\pi\right)^{\frac{d}{2}}}\sum_{\vect K\in\recb{\basis u}\ints^{d}}e^{i\left(\vect k-\vect K\right)\cdot\left(-\vect r_{\beta}+\vect r_{\alpha}\right)}\left(\uaft{S(\vect{\bullet}\leftarrow\vect 0)}\right)\left(\vect k-\vect K\right)\nonumber
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\end{eqnarray}
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\end_inset
\begin_inset Note Note
status open
\begin_layout Plain Layout
Factor
\begin_inset Formula $\left(2\pi\right)^{\frac{d}{2}}$
\end_inset
cancels out with the
\begin_inset Formula $\left(2\pi\right)^{-\frac{d}{2}}$
\end_inset
factor appearing in the convolution/product formula in the unitary angular
momentum convention.
\end_layout
\end_inset
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As such, this is not extremely helpful because the the
\emph on
whole
\emph default
translation operator
\begin_inset Formula $S$
\end_inset
has singularities in origin, hence its Fourier transform
\begin_inset Formula $\uaft S$
\end_inset
will decay poorly.
\end_layout
\begin_layout Standard
However, Fourier transform is linear, so we can in principle separate
\begin_inset Formula $S$
\end_inset
in two parts,
\begin_inset Formula $S=S^{\textup{L}}+S^{\textup{S}}$
\end_inset
.
\begin_inset Formula $S^{\textup{S}}$
\end_inset
is a short-range part that decays sufficiently fast with distance so that
its direct-space lattice sum converges well;
\begin_inset Formula $S^{\textup{S}}$
\end_inset
must as well contain all the singularities of
\begin_inset Formula $S$
\end_inset
in the origin.
The other part,
\begin_inset Formula $S^{\textup{L}}$
\end_inset
, will retain all the slowly decaying terms of
\begin_inset Formula $S$
\end_inset
but it also has to be smooth enough in the origin, so that its Fourier
transform
\begin_inset Formula $\uaft{S^{\textup{L}}}$
\end_inset
decays fast enough.
(The same idea lies behind the Ewald summation in electrostatics.) Using
the linearity of Fourier transform and formulae
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:W definition"
\end_inset
and
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:W sum in reciprocal space"
\end_inset
, the operator
\begin_inset Formula $W_{\alpha\beta}$
\end_inset
can then be re-expressed as
\begin_inset Formula
\begin{eqnarray}
W_{\alpha\beta}\left(\vect k\right) & = & W_{\alpha\beta}^{\textup{S}}\left(\vect k\right)+W_{\alpha\beta}^{\textup{L}}\left(\vect k\right)\nonumber \\
W_{\alpha\beta}^{\textup{S}}\left(\vect k\right) & = & \sum_{\vect R\in\basis u\ints^{d}}S^{\textup{S}}(\vect 0\leftarrow\vect R+\vect r_{\beta}-\vect r_{\alpha})e^{i\vect k\cdot\vect R}\label{eq:W Short definition}\\
W_{\alpha\beta}^{\textup{L}}\left(\vect k\right) & = & \frac{\left|\det\rec{\basis u}\right|}{\left(2\pi\right)^{\frac{d}{2}}}\sum_{\vect K\in\recb{\basis u}\ints^{d}}\left(\uaft{S^{\textup{L}}(\vect{\bullet}-\vect r_{\beta}+\vect r_{\alpha}\leftarrow\vect 0)}\right)\left(\vect k-\vect K\right)\label{eq:W Long definition}
\end{eqnarray}
\end_inset
where both sums should converge nicely.
\end_layout
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\begin_layout Standard
\begin_inset Note Note
status collapsed
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\begin_layout Section
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Finding a good decomposition – deprecated
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\end_layout
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\begin_layout Plain Layout
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The remaining challenge is therefore finding a suitable decomposition
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\begin_inset Formula $S^{\textup{L}}+S^{\textup{S}}$
\end_inset
such that both
\begin_inset Formula $S^{\textup{S}}$
\end_inset
and
\begin_inset Formula $\uaft{S^{\textup{L}}}$
\end_inset
decay fast enough with distance and are expressable analytically.
With these requirements, I do not expect to find gaussian asymptotics as
in the electrostatic Ewald formula—having
\begin_inset Formula $\sim x^{-t}$
\end_inset
,
\begin_inset Formula $t>d$
\end_inset
asymptotics would be nice, making the sums in
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:W Short definition"
\end_inset
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,
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:W Long definition"
\end_inset
absolutely convergent.
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\end_layout
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\begin_layout Plain Layout
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The translation operator
\begin_inset Formula $S$
\end_inset
for compact scatterers in 3d can be expressed as
\begin_inset Formula
\[
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S_{l',m',t'\leftarrow l,m,t}\left(\vect r\leftarrow\vect 0\right)=\sum_{p}c_{p}^{l',m',t'\leftarrow l,m,t}\ush p{m'-m}\left(\theta_{\vect r},\phi_{\vect r}\right)z_{p}^{(J)}\left(k_{0}\left|\vect r\right|\right)
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\]
\end_inset
where
\begin_inset Formula $Y_{l,m}\left(\theta,\phi\right)$
\end_inset
are the spherical harmonics,
\begin_inset Formula $z_{p}^{(J)}\left(r\right)$
\end_inset
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some of the Bessel or Hankel functions (probably
\begin_inset Formula $h_{p}^{(1)}$
\end_inset
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in all meaningful cases; TODO) and
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\begin_inset Formula $c_{p}^{l,m,t\leftarrow l',m',t'}$
\end_inset
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are some ugly but known coefficients (REF Xu 1996, eqs.
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76,77).
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\end_layout
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\begin_layout Plain Layout
The spherical Hankel functions can be expressed analytically as
\begin_inset CommandInset citation
LatexCommand cite
after "10.49.6, 10.49.1"
key "NIST:DLMF"
\end_inset
\begin_inset Note Note
status open
\begin_layout Plain Layout
(REF DLMF 10.49.6, 10.49.1)
\end_layout
\end_inset
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\begin_inset Formula
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\begin{equation}
h_{n}^{(1)}(r)=e^{ir}\sum_{k=0}^{n}\frac{i^{k-n-1}}{r^{k+1}}\frac{\left(n+k\right)!}{2^{k}k!\left(n-k\right)!},\label{eq:spherical Hankel function series}
\end{equation}
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\end_inset
so if we find a way to deal with the radial functions
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\begin_inset Formula $s_{k_{0},q}(r)=e^{ik_{0}r}\left(k_{0}r\right)^{-q}$
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\end_inset
,
\begin_inset Formula $q=1,2$
\end_inset
in 2d case or
\begin_inset Formula $q=1,2,3$
\end_inset
in 3d case, we get absolutely convergent summations in the direct space.
\end_layout
\begin_layout Subsection
2d
\end_layout
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\begin_layout Plain Layout
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Assume that all scatterers are placed in the plane
\begin_inset Formula $\vect z=0$
\end_inset
, so that the 2d Fourier transform of the long-range part of the translation
operator in terms of Hankel transforms, according to
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:Fourier v. Hankel tf 2d"
\end_inset
, reads
\end_layout
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\begin_layout Plain Layout
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\begin_inset Formula
\begin{multline*}
\uaft{S_{l',m',t'\leftarrow l,m,t}^{\textup{L}}\left(\vect{\bullet}\leftarrow\vect 0\right)}(\vect k)=\\
\sum_{p}c_{p}^{l',m',t'\leftarrow l,m,t}\ush p{m'-m}\left(\frac{\pi}{2},0\right)e^{i(m'-m)\phi}i^{m'-m}\pht{m'-m}{h_{p}^{(1)\textup{L}}\left(k_{0}\vect{\bullet}\right)}\left(\left|\vect k\right|\right)
\end{multline*}
\end_inset
Here
\begin_inset Formula $h_{p}^{(1)\textup{L}}=h_{p}^{(1)}-h_{p}^{(1)\textup{S}}$
\end_inset
is a long range part of a given spherical Hankel function which has to
be found and which contains all the terms with far-field (
\begin_inset Formula $r\to\infty$
\end_inset
) asymptotics proportional to
\begin_inset Formula $\sim e^{ik_{0}r}\left(k_{0}r\right)^{-q}$
\end_inset
,
\begin_inset Formula $q\le Q$
\end_inset
where
\begin_inset Formula $Q$
\end_inset
is at least two in order to achieve absolute convergence of the direct-space
sum, but might be higher in order to speed the convergence up.
\end_layout
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\begin_layout Plain Layout
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Obviously, all the terms
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\begin_inset Formula $\propto s_{k_{0},q}(r)=e^{ik_{0}r}\left(k_{0}r\right)^{-q}$
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\end_inset
,
\begin_inset Formula $q>Q$
\end_inset
of the spherical Hankel function
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:spherical Hankel function series"
\end_inset
can be kept untouched as part of
\begin_inset Formula $h_{p}^{(1)\textup{S}}$
\end_inset
, as they decay fast enough.
\end_layout
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\begin_layout Plain Layout
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The remaining task is therefore to find a suitable decomposition of
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\begin_inset Formula $s_{k_{0},q}(r)=e^{ik_{0}r}\left(k_{0}r\right)^{-q}$
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\end_inset
,
\begin_inset Formula $q\le Q$
\end_inset
into short-range and long-range parts,
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\begin_inset Formula $s_{k_{0},q}(r)=s_{k_{0},q}^{\textup{S}}(r)+s_{k_{0},q}^{\textup{L}}(r)$
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\end_inset
, such that
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\begin_inset Formula $s_{k_{0},q}^{\textup{L}}(r)$
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\end_inset
contains all the slowly decaying asymptotics and its Hankel transforms
decay desirably fast as well,
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\begin_inset Formula $\pht n{s_{k_{0},q}^{\textup{L}}}\left(k\right)=o(z^{-Q})$
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\end_inset
,
\begin_inset Formula $z\to\infty$
\end_inset
.
The latter requirement calls for suitable regularisation functions—
\begin_inset Formula $s_{q}^{\textup{L}}$
\end_inset
must be sufficiently smooth in the origin, so that
\begin_inset Formula
\begin{equation}
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\pht n{s_{k_{0},q}^{\textup{L}}}\left(k\right)=\int_{0}^{\infty}s_{k_{0},q}^{\textup{L}}\left(r\right)rJ_{n}\left(kr\right)\ud r=\int_{0}^{\infty}s_{k_{0},q}\left(r\right)\rho\left(r\right)rJ_{n}\left(kr\right)\ud r\label{eq:2d long range regularisation problem statement}
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\end{equation}
\end_inset
exists and decays fast enough.
\begin_inset Formula $J_{\nu}(r)\sim\left(r/2\right)^{\nu}/\Gamma\left(\nu+1\right)$
\end_inset
(REF DLMF 10.7.3) near the origin, so the regularisation function should
be
\begin_inset Formula $\rho(r)=o(r^{q-n-1})$
\end_inset
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only to make
\begin_inset Formula $\pht n{s_{q}^{\textup{L}}}$
\end_inset
converge.
The additional decay speed requirement calls for at least
\begin_inset Formula $\rho(r)=o(r^{q-n+Q-1})$
\end_inset
, I guess.
At the same time,
\begin_inset Formula $\rho(r)$
\end_inset
must converge fast enough to one for
\begin_inset Formula $r\to\infty$
\end_inset
.
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\end_layout
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\begin_layout Plain Layout
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The electrostatic Ewald summation uses regularisation with
\begin_inset Formula $1-e^{-cr^{2}}$
\end_inset
.
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However, such choice does not seem to lead to an analytical solution (really?
could not something be dug out of DLMF 10.22.54?) for the current problem
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\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:2d long range regularisation problem statement"
\end_inset
.
But it turns out that the family of functions
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\begin_inset Formula
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\begin{equation}
\rho_{\kappa,c}(r)\equiv\left(1-e^{-cr}\right)^{\text{\kappa}},\quad c>0,\kappa\in\nats\label{eq:binom regularisation function}
\end{equation}
\end_inset
might lead to satisfactory results; see below.
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\end_layout
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\begin_layout Plain Layout
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\begin_inset Note Note
status open
\begin_layout Plain Layout
In natural/dimensionless units;
\begin_inset Formula $x=k_{0}r$
\end_inset
,
\begin_inset Formula $\tilde{k}=k/k_{0}$
\end_inset
,
\begin_inset Formula $č=c/k_{0}$
\end_inset
\begin_inset Formula
\[
s_{q}(x)\equiv e^{ix}x^{-q}
\]
\end_inset
\begin_inset Formula
\[
\tilde{\rho}_{\kappa,č}(x)\equiv\left(1-e^{-čx}\right)^{\text{\kappa}}=\left(1-e^{-\frac{c}{k_{0}}k_{0}r}\right)^{\kappa}=\left(1-e^{-cr}\right)^{\kappa}=\rho_{\kappa,c}(r)
\]
\end_inset
\begin_inset Formula
\[
s_{q}^{\textup{L}}\left(x\right)\equiv s_{q}(x)\tilde{\rho}_{\kappa,č}(x)=e^{ix}x^{-q}\left(1-e^{-čx}\right)^{\text{\kappa}}
\]
\end_inset
\begin_inset Formula
\begin{eqnarray*}
\pht n{s_{q}^{\textup{L}}}\left(\tilde{k}\right) & = & \int_{0}^{\infty}s_{q}^{\textup{L}}\left(x\right)xJ_{n}\left(\tilde{k}x\right)\ud x=\int_{0}^{\infty}s_{q}\left(x\right)\tilde{\rho}_{\kappa,č}(x)xJ_{n}\left(\tilde{k}x\right)\ud x\\
& = & \int_{0}^{\infty}s_{k_{0},q}\left(r\right)\rho_{\kappa,c}(r)\left(k_{0}r\right)J_{n}\left(kr\right)\ud\left(k_{0}r\right)\\
& = & k_{0}^{2}\int_{0}^{\infty}s_{k_{0},q}\left(r\right)\rho_{\kappa,c}(r)rJ_{n}\left(kr\right)\ud r\\
& = & k_{0}^{2}\pht n{s_{k_{0},q}^{\textup{L}}}\left(k\right)
\end{eqnarray*}
\end_inset
\end_layout
\end_inset
\end_layout
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\begin_layout Plain Layout
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\begin_inset Note Note
status open
\begin_layout Plain Layout
Another analytically feasible possibility could be
\begin_inset Formula
\begin{equation}
\rho_{p}^{\textup{ig.}}\equiv e^{-p/x^{2}}.\label{eq:inverse gaussian regularisation function}
\end{equation}
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\end_inset
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\end_layout
\begin_layout Plain Layout
Nope, propably did not work.
\end_layout
\end_inset
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\end_layout
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\begin_layout Subsubsection
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Hankel transforms of the long-range parts, „binomial“ regularisation
\begin_inset CommandInset label
LatexCommand label
name "sub:Hankel-transforms-binom-reg"
\end_inset
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\end_layout
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\begin_layout Plain Layout
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Let
\begin_inset Note Note
status open
\begin_layout Plain Layout
\begin_inset Formula $\rho_{\kappa,c}$
\end_inset
from
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:binom regularisation function"
\end_inset
serve as the regularisation fuction and
\end_layout
\end_inset
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\end_layout
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\begin_layout Plain Layout
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\begin_inset Formula
\begin{eqnarray}
\pht n{s_{q,k_{0}}^{\textup{L}\kappa,c}}\left(k\right) & \equiv & \int_{0}^{\infty}\frac{e^{ik_{0}r}}{\left(k_{0}r\right)^{q}}J_{n}\left(kr\right)\left(1-e^{-cr}\right)^{\kappa}r\,\ud r\nonumber \\
& = & k_{0}^{-q}\int_{0}^{\infty}r^{1-q}J_{n}\left(kr\right)\sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}e^{-(\sigma c-ik_{0})r}\ud r\nonumber \\
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& \underset{\equiv}{\textup{form.}} & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\pht n{s_{q,k_{0}}^{\textup{L}1,\sigma c}}\left(k\right).\label{eq:2D Hankel transform of regularized outgoing wave, decomposition}
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\end{eqnarray}
\end_inset
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From
\begin_inset Note Note
status open
\begin_layout Plain Layout
[REF DLMF 10.22.49]
\end_layout
\end_inset
\begin_inset CommandInset citation
LatexCommand cite
after "10.22.49"
key "NIST:DLMF"
\end_inset
one digs
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\begin_inset Note Note
status open
\begin_layout Plain Layout
\begin_inset Formula
\begin{eqnarray*}
\mu & \leftarrow & 2-q\\
\nu & \leftarrow & n\\
b & \leftarrow & k\\
a & \leftarrow & c-ik_{0}
\end{eqnarray*}
\end_inset
\end_layout
\end_inset
\begin_inset Formula
\begin{multline}
\pht n{s_{q,k_{0}}^{\textup{L}1,c}}\left(k\right)=\frac{k^{n}Γ\left(2-q+n\right)}{2^{n}k_{0}^{q}\left(c-ik_{0}\right)^{2-q+n}}\hgfr\left(\frac{2-q+n}{2},\frac{3-q+n}{2};1+n;\frac{-k^{2}}{\left(c-ik_{0}\right)^{2}}\right),\\
\Re\left(2-q+n\right)>0,\Re(c-ik_{0}\pm k)\ge0,\label{eq:2D Hankel transform of exponentially suppressed outgoing wave as 2F1}
\end{multline}
\end_inset
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and using [REF DLMF 15.9.17] and
\begin_inset Note Note
status open
\begin_layout Plain Layout
\begin_inset Formula $P_{\nu}^{\mu}=P_{-\nu-1}^{\mu}$
\end_inset
\end_layout
\end_inset
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\begin_inset CommandInset citation
LatexCommand cite
after "14.9.5"
key "NIST:DLMF"
\end_inset
\begin_inset Note Note
status open
\begin_layout Plain Layout
[REF DLMF 14.9.5]
\end_layout
\end_inset
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\end_layout
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\begin_layout Plain Layout
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\begin_inset Note Note
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status collapsed
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\begin_layout Plain Layout
\begin_inset Formula
\begin{eqnarray*}
\pht n{s_{q,k_{0}}^{\textup{L}\kappa,c}}\left(k\right) & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{n}\text{Γ}\left(2-q+n\right)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{2-q+n}}\hgfr\left(\frac{2-q+n}{2},\frac{3-q+n}{2};1+n;\frac{-k^{2}}{\left(\sigma c-ik_{0}\right)^{2}}\right)\\
\mbox{(D15.2.2)} & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{n}Γ\left(2-q+n\right)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{2-q+n}}\sum_{s=0}^{\infty}\frac{\left(\frac{2-q+n}{2}\right)_{s}\left(\frac{3-q+n}{2}\right)_{s}}{Γ(1+n+s)s!}\left(\frac{-k^{2}}{\left(\sigma c-ik_{0}\right)^{2}}\right)^{s},\quad\left|\frac{-k^{2}}{\left(\sigma c-ik_{0}\right)^{2}}\right|<1\\
\end{eqnarray*}
\end_inset
\end_layout
\begin_layout Plain Layout
\begin_inset Formula
\begin{eqnarray*}
\pht n{s_{q,k_{0}}^{\textup{L}\kappa,c}}\left(k\right) & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{n}\text{Γ}\left(2-q+n\right)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{2-q+n}}\hgfr\left(\frac{2-q+n}{2},\frac{3-q+n}{2};1+n;\frac{-k^{2}}{\left(\sigma c-ik_{0}\right)^{2}}\right)\\
\mbox{(D15.8.2)} & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{n}\text{Γ}\left(2-q+n\right)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{2-q+n}}(\\
& & \pi\frac{\left(\frac{k^{2}}{\left(\sigma c-ik_{0}\right)^{2}}\right)^{-\frac{2-q+n}{2}}}{Γ\left(\frac{3-q+n}{2}\right)\text{Γ}\left(1+n-\frac{2-q+n}{2}\right)}\hgfr\left(\begin{array}{c}
\frac{2-q+n}{2},\frac{2-q+n}{2}-\left(1+n\right)+1\\
1/2
\end{array};-\frac{\left(\sigma c-ik_{0}\right)^{2}}{k^{2}}\right)\\
& - & \pi\frac{\left(\frac{k^{2}}{\left(\sigma c-ik_{0}\right)^{2}}\right)^{-\frac{3-q+n}{2}}}{\text{Γ}\left(\frac{2-q+n}{2}\right)\text{Γ}\left(1+n-\frac{3-q+n}{2}\right)}\hgfr\left(\begin{array}{c}
\frac{3-q+n}{2},\frac{3-q+n}{2}-\left(1+n\right)+1\\
3/2
\end{array};-\frac{\left(\sigma c-ik_{0}\right)^{2}}{k^{2}}\right))\\
& = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{n}\text{Γ}\left(2-q+n\right)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{2-q+n}}\pi(\\
& & \frac{\left(\frac{k^{2}}{\left(\sigma c-ik_{0}\right)^{2}}\right)^{-\frac{2-q+n}{2}}}{\text{Γ}\left(\frac{3-q+n}{2}\right)\text{Γ}\left(\frac{q+n}{2}\right)}\hgfr\left(\begin{array}{c}
\frac{2-q+n}{2},\frac{2-q-n}{2}\\
1/2
\end{array};-\frac{\left(\sigma c-ik_{0}\right)^{2}}{k^{2}}\right)\\
& - & \frac{\left(\frac{k^{2}}{\left(\sigma c-ik_{0}\right)^{2}}\right)^{-\frac{3-q+n}{2}}}{\text{Γ}\left(\frac{2-q+n}{2}\right)\text{Γ}\left(\frac{q+n-1}{2}\right)}\hgfr\left(\begin{array}{c}
\frac{3-q+n}{2},\frac{3-q-n}{2}\\
3/2
\end{array};-\frac{\left(\sigma c-ik_{0}\right)^{2}}{k^{2}}\right))\\
\mbox{(D15.2.2)} & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{n}\text{Γ}\left(2-q+n\right)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{2-q+n}}\pi\sum_{s=0}^{\infty}(\\
& & \frac{\left(\frac{k^{2}}{\left(\sigma c-ik_{0}\right)^{2}}\right)^{-\frac{2-q+n}{2}}}{\text{Γ}\left(\frac{3-q+n}{2}\right)\text{Γ}\left(\frac{q+n}{2}\right)}\frac{\left(\frac{2-q+n}{2}\right)_{s}\left(\frac{2-q-n}{2}\right)_{s}}{\text{Γ}\left(\frac{1}{2}+s\right)s!}\left(-\frac{\left(\sigma c-ik_{0}\right)^{2}}{k^{2}}\right)^{s}\\
& - & \frac{\left(\frac{k^{2}}{\left(\sigma c-ik_{0}\right)^{2}}\right)^{-\frac{3-q+n}{2}}}{\text{Γ}\left(\frac{2-q+n}{2}\right)\text{Γ}\left(\frac{q+n-1}{2}\right)}\frac{\left(\frac{3-q+n}{2}\right)_{s}\left(\frac{3-q-n}{2}\right)_{s}}{\text{Γ}\left(\frac{3}{2}+s\right)s!}\left(-\frac{\left(\sigma c-ik_{0}\right)^{2}}{k^{2}}\right)^{s})\\
& = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{\kor{k^{n}}\text{Γ}\left(2-q+n\right)}{2^{n}k_{0}^{q}\kor{\left(\sigma c-ik_{0}\right)^{2-q+n}}}\pi\sum_{s=0}^{\infty}\left(-1\right)^{s}(\\
& & \frac{\left(\frac{2-q+n}{2}\right)_{s}\left(\frac{2-q-n}{2}\right)_{s}}{\text{Γ}\left(\frac{3-q+n}{2}\right)\text{Γ}\left(\frac{q+n}{2}\right)\text{Γ}\left(\frac{1}{2}+s\right)s!}k^{-2+q\kor{-n}-2s}\left(\sigma c-ik_{0}\right)^{\kor{2-q+n}+2s}\\
& - & \frac{\left(\frac{3-q+n}{2}\right)_{s}\left(\frac{3-q-n}{2}\right)_{s}}{\text{Γ}\left(\frac{2-q+n}{2}\right)\text{Γ}\left(\frac{q+n-1}{2}\right)\text{Γ}\left(\frac{3}{2}+s\right)s!}k^{-3+q\kor{-n}-2s}\left(\sigma c-ik_{0}\right)^{\kor{3-q+n}+2s})\\
\mbox{} & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{\text{Γ}\left(2-q+n\right)}{2^{n}k_{0}^{q}}\pi\sum_{s=0}^{\infty}\left(-1\right)^{s}(\\
& & \frac{\left(\frac{2-q+n}{2}\right)_{s}\left(\frac{2-q-n}{2}\right)_{s}}{\text{Γ}\left(\frac{3-q+n}{2}\right)\text{Γ}\left(\frac{q+n}{2}\right)\text{Γ}\left(\frac{1}{2}+s\right)s!}\kor{k^{-2+q-2s}}\kor{\left(\sigma c-ik_{0}\right)^{2s}}\\
& - & \frac{\left(\frac{3-q+n}{2}\right)_{s}\left(\frac{3-q-n}{2}\right)_{s}}{\text{Γ}\left(\frac{2-q+n}{2}\right)\text{Γ}\left(\frac{q+n-1}{2}\right)\text{Γ}\left(\frac{3}{2}+s\right)s!}\kor{k^{-3+q-2s}}\kor{\left(\sigma c-ik_{0}\right)^{1+2s}})\\
& = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{\text{Γ}\left(2-q+n\right)}{2^{n}k_{0}^{q}}\pi\sum_{s=0}^{\infty}\left(-1\right)^{s}k^{-2+q-2s}\left(\sigma c-ik_{0}\right)^{2s}\\
& & \times\left(\underbrace{\frac{\left(\frac{2-q+n}{2}\right)_{s}\left(\frac{2-q-n}{2}\right)_{s}}{\text{Γ}\left(\frac{3-q+n}{2}\right)\text{Γ}\left(\frac{q+n}{2}\right)\text{Γ}\left(\frac{1}{2}+s\right)s!}}_{\equiv c_{q,n,s}}-\underbrace{\frac{\left(\frac{3-q+n}{2}\right)_{s}\left(\frac{3-q-n}{2}\right)_{s}}{\text{Γ}\left(\frac{2-q+n}{2}\right)\text{Γ}\left(\frac{q+n-1}{2}\right)\text{Γ}\left(\frac{3}{2}+s\right)s!}}_{č_{q,n,s}}\frac{\left(\sigma c-ik_{0}\right)}{k}\right)\\
& = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{\text{Γ}\left(2-q+n\right)}{2^{n}k_{0}^{q}}\pi\sum_{s=0}^{\infty}\left(-1\right)^{s}k^{-2+q-2s}\left(\kor{\left(\sigma c-ik_{0}\right)^{2s}}c_{q,n,s}-\frac{\left(\sigma c-ik_{0}\right)^{2s+1}}{k}č_{q,n,s}\right)\\
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\mbox{(binom.)} & = & \kor{\sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}}\frac{\text{Γ}\left(2-q+n\right)}{2^{n}k_{0}^{q}}\pi\sum_{s=0}^{\infty}\left(-1\right)^{s}k^{-2+q-2s}\left(c_{q,n,s}\sum_{t=0}^{2s}\binom{2s}{t}\left(\kor{\sigma}c\right)^{t}\left(-ik_{0}\right)^{2s-t}-č_{q,n,s}\sum_{t=0}^{2s+1}\binom{2s+1}{t}\left(\kor{\sigma}c\right)^{t}\left(-ik_{0}\right)^{2s+1-t}k^{-1}\right)\\
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\mbox{(conds?)} & = & \frac{\text{Γ}\left(2-q+n\right)}{2^{n}k_{0}^{q}}\pi\sum_{s=0}^{\infty}\left(-1\right)^{s}k^{-2+q-2s}\kappa!\left(-1\right)^{\kappa}\left(c_{q,n,s}\sum_{t=0}^{2s}\binom{2s}{t}\begin{Bmatrix}t\\
\kappa
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\end{Bmatrix}c^{t}\left(-ik_{0}\right)^{2s-t}-č_{q,n,s}\sum_{t=0}^{2s+1}\binom{2s+1}{t}\begin{Bmatrix}t\\
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\kappa
\end{Bmatrix}c^{t}\left(-ik_{0}\right)^{2s+1-t}k^{-1}\right)
\end{eqnarray*}
\end_inset
now the Stirling number of the 2nd kind
\begin_inset Formula $\begin{Bmatrix}t\\
\kappa
\end{Bmatrix}=0$
\end_inset
if
\begin_inset Formula $\kappa>t$
\end_inset
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.
\end_layout
\begin_layout Plain Layout
What about the gamma fn on the left? Using DLMF 5.5.5, which says
\begin_inset Formula $Γ(2z)=\pi^{-1/2}2^{2z-1}\text{Γ}(z)\text{Γ}(z+\frac{1}{2})$
\end_inset
we have
\begin_inset Formula
\[
\text{Γ}\left(2-q+n\right)=\frac{2^{1-q+n}}{\sqrt{\pi}}\text{Γ}\left(\frac{2-q+n}{2}\right)\text{Γ}\left(\frac{3-q+n}{2}\right),
\]
\end_inset
so
\begin_inset Formula
\begin{eqnarray*}
\pht n{s_{q,k_{0}}^{\textup{L}\kappa,c}}\left(k\right) & = & \frac{\kor{\text{Γ}\left(2-q+n\right)}}{\kor{2^{n}}k_{0}^{q}}\kor{\pi}\sum_{s=0}^{\infty}\left(-1\right)^{s}k^{-2+q-2s}\kappa!\left(-1\right)^{\kappa}\left(\frac{\left(\frac{2-q+n}{2}\right)_{s}\left(\frac{2-q-n}{2}\right)_{s}}{\kor{\text{Γ}\left(\frac{3-q+n}{2}\right)}\text{Γ}\left(\frac{q+n}{2}\right)\text{Γ}\left(\frac{1}{2}+s\right)s!}\sum_{t=0}^{2s}\binom{2s}{t}\begin{Bmatrix}t\\
\kappa
\end{Bmatrix}c^{t}\left(-ik_{0}\right)^{2s-t}-\frac{\left(\frac{3-q+n}{2}\right)_{s}\left(\frac{3-q-n}{2}\right)_{s}}{\kor{\text{Γ}\left(\frac{2-q+n}{2}\right)}\text{Γ}\left(\frac{q+n-1}{2}\right)\text{Γ}\left(\frac{3}{2}+s\right)s!}\sum_{t=0}^{2s}\binom{2s+1}{t}\begin{Bmatrix}t\\
\kappa
\end{Bmatrix}c^{t}\left(-ik_{0}\right)^{2s+1-t}k^{-1}\right)\\
& = & \frac{2^{1-q}}{k_{0}^{q}}\sqrt{\pi}\sum_{s=0}^{\infty}\left(-1\right)^{s}k^{-2+q-2s}\kappa!\left(-1\right)^{\kappa}\left(\frac{\kor{\text{Γ}\left(\frac{2-q+n}{2}\right)\left(\frac{2-q+n}{2}\right)_{s}}\left(\frac{2-q-n}{2}\right)_{s}}{\text{Γ}\left(\frac{q+n}{2}\right)\text{Γ}\left(\frac{1}{2}+s\right)s!}\sum_{t=0}^{2s}\binom{2s}{t}\begin{Bmatrix}t\\
\kappa
\end{Bmatrix}c^{t}\left(-ik_{0}\right)^{2s-t}-\frac{\kor{\text{Γ}\left(\frac{3-q+n}{2}\right)\left(\frac{3-q+n}{2}\right)_{s}}\left(\frac{3-q-n}{2}\right)_{s}}{\text{Γ}\left(\frac{q+n-1}{2}\right)\text{Γ}\left(\frac{3}{2}+s\right)s!}\sum_{t=0}^{2s}\binom{2s+1}{t}\begin{Bmatrix}t\\
\kappa
\end{Bmatrix}c^{t}\left(-ik_{0}\right)^{2s+1-t}k^{-1}\right)\\
\mbox{(D5.2.5)} & = & \frac{2^{1-q}}{k_{0}^{q}}\sqrt{\pi}\sum_{s=0}^{\infty}\left(-1\right)^{s}k^{-2+q-2s}\kappa!\left(-1\right)^{\kappa}\left(\frac{\text{Γ}\left(\frac{2-q+n}{2}+s\right)\left(\frac{2-q-n}{2}\right)_{s}}{\text{Γ}\left(\frac{q+n}{2}\right)\text{Γ}\left(\frac{1}{2}+s\right)s!}\sum_{t=0}^{2s}\binom{2s}{t}\begin{Bmatrix}t\\
\kappa
\end{Bmatrix}c^{t}\left(-ik_{0}\right)^{2s-t}-\frac{\text{Γ}\left(\frac{3-q+n}{2}+s\right)\left(\frac{3-q-n}{2}\right)_{s}}{\text{Γ}\left(\frac{q+n-1}{2}\right)\text{Γ}\left(\frac{3}{2}+s\right)s!}\sum_{t=0}^{2s}\binom{2s+1}{t}\begin{Bmatrix}t\\
\kappa
\end{Bmatrix}c^{t}\left(-ik_{0}\right)^{2s+1-t}k^{-1}\right)
\end{eqnarray*}
\end_inset
The two terms have to be treated fifferently depending on whether q
\begin_inset Formula $q+n$
\end_inset
is even or odd.
\end_layout
\begin_layout Plain Layout
First, assume that
\begin_inset Formula $q+n$
\end_inset
is even, so the left term has gamma functions and pochhammer symbols with
integer arguments, while the right one has half-integer arguments.
As
\begin_inset Formula $n$
\end_inset
is non-negative and
\begin_inset Formula $q$
\end_inset
is positive,
\begin_inset Formula $\frac{q+n}{2}$
\end_inset
is positive, and the Pochhammer symbol
\begin_inset Formula $\left(\frac{2-q-n}{2}\right)_{s}=0$
\end_inset
if
\begin_inset Formula $s\ge\frac{q+n}{2}$
\end_inset
, which transforms the sum over
\begin_inset Formula $s$
\end_inset
to a finite sum for the left term.
However, there still remain divergent terms if
\begin_inset Formula $\frac{2-q+n}{2}+s\le0$
\end_inset
(let's handle this later; maybe D15.8.6– 7 may be then be useful)! Now we
need to perform some transformations of variables to make the other sum
finite as well
\end_layout
\begin_layout Plain Layout
Pár kroků zpět:
\begin_inset Formula
\begin{eqnarray*}
\pht n{s_{q,k_{0}}^{\textup{L}\kappa,c}}\left(k\right) & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{\kor{\text{Γ}\left(2-q+n\right)}}{\kor{2^{n}}k_{0}^{q}}\kor{\pi}\sum_{s=0}^{\infty}\left(-1\right)^{s}k^{-2+q-2s}\left(\sigma c-ik_{0}\right)^{2s}\times\left(\underbrace{\frac{\left(\frac{2-q+n}{2}\right)_{s}\left(\frac{2-q-n}{2}\right)_{s}}{\kor{\text{Γ}\left(\frac{3-q+n}{2}\right)}\text{Γ}\left(\frac{q+n}{2}\right)\text{Γ}\left(\frac{1}{2}+s\right)s!}}_{\equiv c_{q,n,s}}-\underbrace{\frac{\left(\frac{3-q+n}{2}\right)_{s}\left(\frac{3-q-n}{2}\right)_{s}}{\kor{\text{Γ}\left(\frac{2-q+n}{2}\right)}\text{Γ}\left(\frac{q+n-1}{2}\right)\text{Γ}\left(\frac{3}{2}+s\right)s!}}_{č_{q,n,s}}\frac{\left(\sigma c-ik_{0}\right)}{k}\right)\\
& = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{2^{1-q}}{k_{0}^{q}}\sqrt{\pi}\sum_{s=0}^{\infty}\left(-1\right)^{s}k^{-2+q-2s}\left(\sigma c-ik_{0}\right)^{2s}\times\left(\frac{\text{Γ}\left(\frac{2-q+n}{2}\right)\left(\frac{2-q+n}{2}\right)_{s}\left(\frac{2-q-n}{2}\right)_{s}}{\text{Γ}\left(\frac{q+n}{2}\right)\text{Γ}\left(\frac{1}{2}+s\right)s!}-\frac{\text{Γ}\left(\frac{3-q+n}{2}\right)\left(\frac{3-q+n}{2}\right)_{s}\left(\frac{3-q-n}{2}\right)_{s}}{\text{Γ}\left(\frac{q+n-1}{2}\right)\text{Γ}\left(\frac{3}{2}+s\right)s!}\frac{\left(\sigma c-ik_{0}\right)}{k}\right)
\end{eqnarray*}
\end_inset
2017-08-16 19:34:31 +03:00
2017-08-18 20:36:28 +03:00
\end_layout
\begin_layout Plain Layout
If
\begin_inset Formula $q+n$
\end_inset
is even and
\begin_inset Formula $2-q+n\le0$
\end_inset
\begin_inset Formula
\begin{eqnarray*}
\pht n{s_{q,k_{0}}^{\textup{L}\kappa,c}}\left(k\right) & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{n}\text{Γ}\left(2-q+n\right)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{2-q+n}}\kor{\hgfr}\left(\frac{2-q+n}{2},\frac{3-q+n}{2};1+n;\frac{-k^{2}}{\left(\sigma c-ik_{0}\right)^{2}}\right)\\
\mbox{(D15.1.2)} & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{n}\text{Γ}\left(2-q+n\right)\koru{\text{Γ}(1+n)}}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{2-q+n}}\koru{\hgf}\left(\frac{2-q+n}{2},\kor{\frac{3-q+n}{2};1+n;\frac{-k^{2}}{\left(\sigma c-ik_{0}\right)^{2}}}\right)\\
\mbox{(D15.8.6)} & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{\kor{k^{n}}\text{Γ}\left(2-q+n\right)\text{Γ}(1+n)}{2^{n}k_{0}^{q}\kor{\left(\sigma c-ik_{0}\right)^{2-q+n}}}\koru{\frac{\left(\frac{3-q+n}{2}\right)_{-\frac{2-q+n}{2}}}{\left(1+n\right)_{-\frac{2-q+n}{2}}}\kor{\left(\frac{k^{2}}{\left(\sigma c-ik_{0}\right)^{2}}\right)^{-\frac{2-q+n}{2}}}}\hgf\left(\begin{array}{c}
\frac{2-q+n}{2},\koru{\kor{1-\left(1+n\right)+\frac{2-q+n}{2}}}\\
\koru{\kor{1-\frac{3-q+n}{2}+\frac{2-q+n}{2}}}
\end{array};\koru{\frac{\left(\sigma c-ik_{0}\right)^{2}}{-k^{2}}}\right)\\
& = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{\koru{k^{q-2}}\text{Γ}\left(2-q+n\right)\text{Γ}(1+n)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{\koru{\frac{3}{2}\left(2-q+n\right)}}}\frac{\left(\frac{3-q+n}{2}\right)_{-\frac{2-q+n}{2}}}{\left(1+n\right)_{-\frac{2-q+n}{2}}}\kor{\hgf\left(\begin{array}{c}
\frac{2-q+n}{2},\koru{\frac{2-q-n}{2}}\\
\koru{1/2}
\end{array};\frac{\left(\sigma c-ik_{0}\right)^{2}}{-k^{2}}\right)}\\
\mbox{(D15.2.1)} & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\kor{\text{Γ}\left(2-q+n\right)}\text{Γ}(1+n)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{\frac{3}{2}\left(2-q+n\right)}}\frac{\left(\frac{3-q+n}{2}\right)_{-\frac{2-q+n}{2}}}{\left(1+n\right)_{-\frac{2-q+n}{2}}}\koru{\sum_{s=0}^{\infty}\frac{\left(\frac{2-q+n}{2}\right)_{s}\left(\frac{2-q-n}{2}\right)_{s}}{\left(\frac{1}{2}\right)_{s}s!}\left(\frac{\left(\sigma c-ik_{0}\right)^{2}}{-k^{2}}\right)^{s}}\\
\mbox{(D5.5.5)} & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\text{Γ}(1+n)}{\kor{2^{n}}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{\frac{3}{2}\left(2-q+n\right)}}\koru{\frac{2^{1-q\kor{+n}}}{\sqrt{\pi}}\kor{\text{Γ}\left(\frac{2-q+n}{2}\right)}\text{Γ}\left(\frac{3-q+n}{2}\right)}\frac{\left(\frac{3-q+n}{2}\right)_{-\frac{2-q+n}{2}}}{\left(1+n\right)_{-\frac{2-q+n}{2}}}\sum_{s=0}^{\infty}\frac{\kor{\left(\frac{2-q+n}{2}\right)_{s}}\left(\frac{2-q-n}{2}\right)_{s}}{\left(\frac{1}{2}\right)_{s}s!}\left(\frac{\left(\sigma c-ik_{0}\right)^{2}}{-k^{2}}\right)^{s}\\
\mbox{(D5.2.5)} & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\text{Γ}(1+n)}{k_{0}^{q}\left(\sigma c-ik_{0}\right)^{\frac{3}{2}\left(2-q+n\right)}}\frac{\koru{2^{1-q}}}{\sqrt{\pi}}\text{Γ}\left(\frac{3-q+n}{2}\right)\frac{\left(\frac{3-q+n}{2}\right)_{-\frac{2-q+n}{2}}}{\left(1+n\right)_{-\frac{2-q+n}{2}}}\sum_{s=0}^{\infty}\frac{\koru{\text{Γ}\left(\frac{2-q+n}{2}+s\right)}\left(\frac{2-q-n}{2}\right)_{s}}{\left(\frac{1}{2}\right)_{s}s!}\left(\frac{\left(\sigma c-ik_{0}\right)^{2}}{-k^{2}}\right)^{s}\\
& = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\text{Γ}(1+n)}{k_{0}^{q}\left(\sigma c-ik_{0}\right)^{\frac{3}{2}\left(2-q+n\right)}}\frac{2^{1-q}}{\sqrt{\pi}}\text{Γ}\left(\frac{3-q+n}{2}\right)\frac{\left(\frac{3-q+n}{2}\right)_{-\frac{2-q+n}{2}}}{\left(1+n\right)_{-\frac{2-q+n}{2}}}\sum_{s=0}^{\frac{q+n}{2}}\frac{\text{Γ}\left(\frac{2-q+n}{2}+s\right)\left(\frac{2-q-n}{2}\right)_{s}}{\left(\frac{1}{2}\right)_{s}s!}\left(\frac{\left(\sigma c-ik_{0}\right)^{2}}{-k^{2}}\right)^{s}\\
& = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\text{Γ}(1+n)}{k_{0}^{q}\left(\sigma c-ik_{0}\right)^{\frac{3}{2}\left(2-q+n\right)}}\frac{2^{1-q}}{\sqrt{\pi}}\text{Γ}\left(\frac{3-q+n}{2}\right)\frac{\left(\frac{3-q+n}{2}\right)_{-\frac{2-q+n}{2}}}{\left(1+n\right)_{-\frac{2-q+n}{2}}}\sum_{s=0}^{\frac{q+n}{2}}\frac{\text{Γ}\left(\frac{2-q+n}{2}+s\right)\left(\frac{2-q-n}{2}\right)_{s}}{\left(\frac{1}{2}\right)_{s}s!}\left(\frac{\left(\sigma c-ik_{0}\right)^{2}}{-k^{2}}\right)^{s}
\end{eqnarray*}
\end_inset
now
\begin_inset Formula $\left(\frac{2-q-n}{2}\right)_{s}=0$
\end_inset
whenever
\begin_inset Formula $s\ge\frac{q+n}{2}$
\end_inset
and
\begin_inset Formula $\text{Γ}\left(\frac{2-q+n}{2}+s\right)$
\end_inset
is singular whenever
\begin_inset Formula $s\le-\frac{2-q+n}{2}$
\end_inset
, so we are no less fucked than before.
Maybe let's try the other variable transformation.
Or what about (D15.8.27)?
\begin_inset Formula
\begin{eqnarray*}
\pht n{s_{q,k_{0}}^{\textup{L}\kappa,c}}\left(k\right) & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\text{Γ}\left(2-q+n\right)\text{Γ}(1+n)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{\frac{3}{2}\left(2-q+n\right)}}\frac{\left(\frac{3-q+n}{2}\right)_{-\frac{2-q+n}{2}}}{\left(1+n\right)_{-\frac{2-q+n}{2}}}\kor{\hgf\left(\begin{array}{c}
\frac{2-q+n}{2},\frac{2-q-n}{2}\\
1/2
\end{array};\frac{\left(\sigma c-ik_{0}\right)^{2}}{-k^{2}}\right)}\\
\mbox{(D15.8.27)} & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\text{Γ}\left(2-q+n\right)\text{Γ}(1+n)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{\frac{3}{2}\left(2-q+n\right)}}\frac{\kor{\left(\frac{3-q+n}{2}\right)_{-\frac{2-q+n}{2}}}}{\left(1+n\right)_{-\frac{2-q+n}{2}}}\koru{\frac{\kor{Γ\left(\frac{3-q+n}{2}\right)}Γ\left(\frac{3-q-n}{2}\right)}{2Γ\left(\frac{1}{2}\right)Γ\left(2-q+\frac{1}{2}\right)}\left(\hgf\left(\begin{array}{c}
2-q+n,2-q-n\\
2-q+\frac{1}{2}
\end{array};\frac{1}{2}-\frac{\sigma c-ik_{0}}{ik}\right)+\hgf\left(\begin{array}{c}
2-q+n,2-q-n\\
2-q+\frac{1}{2}
\end{array};\frac{1}{2}+\frac{\sigma c-ik_{0}}{ik}\right)\right)}\\
& = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\text{Γ}\left(2-q+n\right)\text{Γ}(1+n)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{\frac{3}{2}\left(2-q+n\right)}}\frac{\kor{\text{Γ}\koru{\left(\frac{3-q+n}{2}-\frac{2-q+n}{2}\right)}}\text{Γ}\left(\frac{3-q-n}{2}\right)}{\left(1+n\right)_{-\frac{2-q+n}{2}}2\kor{\text{Γ}\left(\frac{1}{2}\right)}\text{Γ}\left(2-q+\frac{1}{2}\right)}\left(\hgf\left(\begin{array}{c}
2-q+n,2-q-n\\
2-q+\frac{1}{2}
\end{array};\frac{1}{2}-\frac{\sigma c-ik_{0}}{ik}\right)+\hgf\left(\begin{array}{c}
2-q+n,2-q-n\\
2-q+\frac{1}{2}
\end{array};\frac{1}{2}+\frac{\sigma c-ik_{0}}{ik}\right)\right)\\
& = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\text{Γ}\left(2-q+n\right)\text{Γ}(1+n)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{\frac{3}{2}\left(2-q+n\right)}}\frac{\text{Γ}\left(\frac{3-q-n}{2}\right)}{\left(1+n\right)_{-\frac{2-q+n}{2}}2\text{Γ}\left(2-q+\frac{1}{2}\right)}\kor{\left(\hgf\left(\begin{array}{c}
2-q+n,2-q-n\\
2-q+\frac{1}{2}
\end{array};\frac{1}{2}-\frac{\sigma c-ik_{0}}{ik}\right)+\hgf\left(\begin{array}{c}
2-q+n,2-q-n\\
2-q+\frac{1}{2}
\end{array};\frac{1}{2}+\frac{\sigma c-ik_{0}}{ik}\right)\right)}\\
\mbox{(D15.2.1)} & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\text{Γ}\left(2-q+n\right)\text{Γ}(1+n)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{\frac{3}{2}\left(2-q+n\right)}}\frac{\text{Γ}\left(\frac{3-q-n}{2}\right)}{\left(1+n\right)_{-\frac{2-q+n}{2}}2\text{Γ}\left(2-q+\frac{1}{2}\right)}\koru{\sum_{s=0}^{\infty}\left(\frac{\left(2-q+n\right)_{s}\left(2-q-n\right)_{s}}{\left(2-q+\frac{1}{2}\right)_{s}s!}\kor{\left(\left(\frac{1}{2}-\frac{\sigma c-ik_{0}}{ik}\right)^{s}+\left(\frac{1}{2}+\frac{\sigma c-ik_{0}}{ik}\right)^{s}\right)}\right)}\\
\mbox{(binom)} & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\text{Γ}(1+n)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{\frac{3}{2}\left(2-q+n\right)}}\frac{\text{Γ}\left(\frac{3-q-n}{2}\right)}{\left(1+n\right)_{-\frac{2-q+n}{2}}2\text{Γ}\left(2-q+\frac{1}{2}\right)}\sum_{s=0}^{\infty}\frac{\kor{\left(2-q+n\right)_{s}}\left(2-q-n\right)_{s}}{\left(2-q+\frac{1}{2}\right)_{s}s!}\koru{\sum_{r=0}^{s}\binom{s}{r}\left(\frac{\sigma c-ik_{0}}{ik}\right)^{r}2^{r-s}\left(\left(-1\right)^{r}+1\right)}\\
& = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\text{Γ}(1+n)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{\frac{3}{2}\left(2-q+n\right)}}\frac{\text{Γ}\left(\frac{3-q-n}{2}\right)}{\kor{\left(1+n\right)_{-\frac{2-q+n}{2}}}2\text{Γ}\left(2-q+\frac{1}{2}\right)}\sum_{s=0}^{\infty}\frac{\koru{\text{Γ}\left(2-q+n+s\right)}\left(2-q-n\right)_{s}}{\left(2-q+\frac{1}{2}\right)_{s}s!}\sum_{r=0}^{s}\binom{s}{r}\left(\frac{\sigma c-ik_{0}}{ik}\right)^{r}2^{r-s}\left(\left(-1\right)^{r}+1\right)\\
& = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\text{Γ}(1+n)}{2^{n}k_{0}^{q}\kor{\left(\sigma c-ik_{0}\right)^{\frac{3}{2}\left(2-q+n\right)}}}\frac{\koru{\text{Γ}\left(1+n\right)}\text{Γ}\left(\frac{3-q-n}{2}\right)}{\koru{\text{Γ}\left(\frac{q+n}{2}\right)}2\text{Γ}\left(2-q+\frac{1}{2}\right)}\sum_{s=0}^{\infty}\frac{\text{Γ}\left(2-q+n+s\right)\left(2-q-n\right)_{s}}{\left(2-q+\frac{1}{2}\right)_{s}s!}\sum_{r=0}^{s}\binom{s}{r}\kor{\left(\frac{\sigma c-ik_{0}}{ik}\right)^{r}}2^{r-s}\left(\left(-1\right)^{r}+1\right)\\
& = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\text{Γ}(1+n)}{2^{n}k_{0}^{q}}\frac{\text{Γ}\left(1+n\right)\text{Γ}\left(\frac{3-q-n}{2}\right)}{Γ\left(\frac{q+n}{2}\right)2\text{Γ}\left(2-q+\frac{1}{2}\right)}\sum_{s=0}^{\infty}\frac{\text{Γ}\left(2-q+n+s\right)\left(2-q-n\right)_{s}}{\left(2-q+\frac{1}{2}\right)_{s}s!}\sum_{r=0}^{s}\binom{s}{r}\koru{\left(ik\right)^{-r}}\koru{\kor{\left(\sigma c-ik_{0}\right)^{r-\frac{3}{2}\left(2-q+n\right)}}}2^{r-s}\left(\left(-1\right)^{r}+1\right)\\
(bionm) & = & \kor{\sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}}\frac{k^{q-2}\text{Γ}(1+n)}{2^{n}k_{0}^{q}}\frac{\text{Γ}\left(1+n\right)\text{Γ}\left(\frac{3-q-n}{2}\right)}{\text{Γ}\left(\frac{q+n}{2}\right)2\text{Γ}\left(2-q+\frac{1}{2}\right)}\sum_{s=0}^{\infty}\frac{\text{Γ}\left(2-q+n+s\right)\left(2-q-n\right)_{s}}{\left(2-q+\frac{1}{2}\right)_{s}s!}\sum_{r=0}^{s}\binom{s}{r}\left(ik\right)^{-r}\koru{\sum_{w=0}^{\infty|r-\frac{3}{2}\left(2-q+n\right)}\binom{r-\frac{3}{2}\left(2-q+n\right)}{w}\kor{\sigma^{w}}c^{w}\left(-ik_{0}^{r-\frac{3}{2}\left(2-q+n\right)-w}\right)}2^{r-s}\left(\left(-1\right)^{r}+1\right)\\
& = & \koru{\kappa!\left(-1\right)^{\kappa}}\frac{k^{q-2}\text{Γ}(1+n)}{2^{n}k_{0}^{q}}\frac{\text{Γ}\left(1+n\right)\text{Γ}\left(\frac{3-q-n}{2}\right)}{\text{Γ}\left(\frac{q+n}{2}\right)2\text{Γ}\left(2-q+\frac{1}{2}\right)}\sum_{s=\kor 0}^{\infty}\frac{\text{Γ}\left(2-q+n+s\right)\left(2-q-n\right)_{s}}{\left(2-q+\frac{1}{2}\right)_{s}s!}\sum_{r=\kor 0}^{s}\binom{\kor s}{\kor r}\left(ik\right)^{-r}\sum_{w=\kor 0}^{\infty|r-\frac{3}{2}\left(2-q+n\right)}\binom{r-\frac{3}{2}\left(2-q+n\right)}{\kor w}\koru{\kor{\begin{Bmatrix}w\\
\kappa
\end{Bmatrix}}}c^{w}\left(-ik_{0}^{r-\frac{3}{2}\left(2-q+n\right)-w}\right)2^{r-s}\left(\left(-1\right)^{r}+1\right)\\
& = & \kappa!\left(-1\right)^{\kappa}\frac{k^{q-2}\text{Γ}(1+n)}{2^{n}k_{0}^{q}}\frac{\text{Γ}\left(1+n\right)\text{Γ}\left(\frac{3-q-n}{2}\right)}{\text{Γ}\left(\frac{q+n}{2}\right)2\text{Γ}\left(2-q+\frac{1}{2}\right)}\sum_{s=\koru{\kappa}}^{\infty}\frac{\text{Γ}\left(2-q+n+s\right)\left(2-q-n\right)_{s}}{\left(2-q+\frac{1}{2}\right)_{s}s!}\sum_{r=\koru{\kappa}}^{s}\binom{s}{r}\left(ik\right)^{-r}\sum_{w=\koru{\kappa}}^{\infty|r-\frac{3}{2}\left(2-q+n\right)}\binom{r-\frac{3}{2}\left(2-q+n\right)}{w}\begin{Bmatrix}w\\
\kappa
\end{Bmatrix}c^{w}\left(-ik_{0}^{r-\frac{3}{2}\left(2-q+n\right)-w}\right)2^{r-s}\left(\left(-1\right)^{r}+1\right)\\
& = & \kappa!\left(-1\right)^{\kappa}\frac{k^{q-2}\text{Γ}(1+n)}{2^{n}k_{0}^{q}}\frac{\text{Γ}\left(1+n\right)\text{Γ}\left(\frac{3-q-n}{2}\right)}{\text{Γ}\left(\frac{q+n}{2}\right)2\text{Γ}\left(2-q+\frac{1}{2}\right)}\sum_{s=\kappa}^{\infty}\frac{\text{Γ}\left(2-q+n+s\right)\left(2-q-n\right)_{s}}{\left(2-q+\frac{1}{2}\right)_{s}s!}\sum_{r=\kappa}^{s}\binom{s}{r}\left(ik\right)^{-r}\sum_{w=\kappa}^{\infty|r-\frac{3}{2}\left(2-q+n\right)}\binom{r-\frac{3}{2}\left(2-q+n\right)}{w}\begin{Bmatrix}w\\
\kappa
\end{Bmatrix}c^{w}\left(-ik_{0}^{r-\frac{3}{2}\left(2-q+n\right)-w}\right)2^{r-s}\left(\left(-1\right)^{r}+1\right)
\end{eqnarray*}
\end_inset
\end_layout
\begin_layout Plain Layout
The previous things are valid only if
\begin_inset Formula $q$
\end_inset
has a small non-integer part,
\begin_inset Formula $q=q'+\varepsilon$
\end_inset
.
They might still play a role in the series (especially in the infinite
ones) when taking the limit
\begin_inset Formula $\varepsilon\to0$
\end_inset
.
However, we got rid of the singularities in
\begin_inset Formula $\text{Γ}\left(2-q+n+s\right)$
\end_inset
if
\begin_inset Formula $\kappa$
\end_inset
is large enough.
\end_layout
\begin_layout Plain Layout
and we get same shit as before due to the singular
\begin_inset Formula $\text{Γ}\left(2-q+n+s\right)$
\end_inset
.
However,
\begin_inset Formula
\begin{eqnarray*}
(...) & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\text{Γ}(1+n)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{\frac{3}{2}\left(2-q+n\right)}}\frac{\text{Γ}\left(\frac{3-q-n}{2}\right)}{\left(1+n\right)_{-\frac{2-q+n}{2}}2\text{Γ}\left(2-q+\frac{1}{2}\right)}\sum_{s=0}^{\infty}\frac{\text{Γ}\left(2-q+n+s\right)\left(2-q-n\right)_{s}}{\left(2-q+\frac{1}{2}\right)_{s}s!}\sum_{r=0}^{s}\binom{s}{r}\left(\frac{\sigma c-ik_{0}}{ik}\right)^{r}2^{r-s}\kor{\left(\left(-1\right)^{r}+1\right)}\\
& = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\text{Γ}(1+n)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{\frac{3}{2}\left(2-q+n\right)}}\frac{\text{Γ}\left(\frac{3-q-n}{2}\right)}{\left(1+n\right)_{-\frac{2-q+n}{2}}2\text{Γ}\left(2-q+\frac{1}{2}\right)}\sum_{s=0}^{\infty}\frac{\text{Γ}\left(2-q+n+s\right)\left(2-q-n\right)_{s}}{\left(2-q+\frac{1}{2}\right)_{s}s!}\sum_{r=0}^{\koru{floor(s/2)}}\binom{s}{\koru{2r}}\left(\frac{\sigma c-ik_{0}}{ik}\right)^{\koru{2r}}2^{\koru{2r}-s}\left(\left(-1\right)^{\koru{2r}}+1\right)
\end{eqnarray*}
\end_inset
\begin_inset Formula
\begin{eqnarray*}
(...) & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\text{Γ}(1+n)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{\frac{3}{2}\left(2-q+n\right)}}\frac{\text{Γ}\left(\frac{3-q-n}{2}\right)}{\left(1+n\right)_{-\frac{2-q+n}{2}}2\text{Γ}\left(2-q+\frac{1}{2}\right)}\sum_{s=0}^{\infty}\frac{\text{Γ}\left(2-q+n+s\right)\left(2-q-n\right)_{s}}{\left(2-q+\frac{1}{2}\right)_{s}s!}\sum_{r=0}^{s}\binom{s}{r}\kor{\left(\frac{\sigma c-ik_{0}}{ik}\right)^{r}}2^{r-s}\left(\left(-1\right)^{r}+1\right)\\
binom & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\text{Γ}(1+n)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{\frac{3}{2}\left(2-q+n\right)}}\frac{\text{Γ}\left(\frac{3-q-n}{2}\right)}{\left(1+n\right)_{-\frac{2-q+n}{2}}2\text{Γ}\left(2-q+\frac{1}{2}\right)}\sum_{s=0}^{\infty}\frac{\text{Γ}\left(2-q+n+s\right)\left(2-q-n\right)_{s}}{\left(2-q+\frac{1}{2}\right)_{s}s!}\sum_{r=0}^{s}\binom{s}{r}\koru{\left(ik\right)^{-r}\sum_{b=0}^{r}\binom{r}{b}\sigma^{b}c^{b}\left(-ik_{0}\right)^{r-b}}2^{r-s}\left(\left(-1\right)^{r}+1\right)\\
& =
\end{eqnarray*}
\end_inset
\end_layout
\begin_layout Plain Layout
aaah.
Let's assume that
\begin_inset Formula $q$
\end_inset
is not exactly
\begin_inset Formula
\begin{eqnarray*}
& = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\kor{\text{Γ}\left(2-q+n\right)}\text{Γ}(1+n)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{\frac{3}{2}\left(2-q+n\right)}}\frac{\left(\frac{3-q+n}{2}\right)_{-\frac{2-q+n}{2}}}{\left(1+n\right)_{-\frac{2-q+n}{2}}}\sum_{s=0}^{\infty}\frac{\left(\frac{2-q+n}{2}\right)_{s}\left(\frac{2-q-n}{2}\right)_{s}}{\left(\frac{1}{2}\right)_{s}s!}\left(\frac{\left(\sigma c-ik_{0}\right)^{2}}{-k^{2}}\right)^{s}\\
& = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{q-2}\text{Γ}\left(2-q+n\right)\text{Γ}(1+n)}{2^{n}k_{0}^{q}\left(\sigma c-ik_{0}\right)^{\frac{3}{2}\left(2-q+n\right)}}\frac{\left(\frac{3-q+n}{2}\right)_{-\frac{2-q+n}{2}}}{\left(1+n\right)_{-\frac{2-q+n}{2}}}\sum_{s=0}^{\infty}k^{-2s}\frac{\left(\frac{2-q+n}{2}\right)_{s}\left(\frac{2-q-n}{2}\right)_{s}}{\left(\frac{1}{2}\right)_{s}s!}\left(\frac{\left(\sigma c-ik_{0}\right)^{2}}{-k^{2}}\right)^{s}
\end{eqnarray*}
\end_inset
zpět
\end_layout
\begin_layout Plain Layout
\begin_inset Formula
\begin{eqnarray*}
& = & \frac{2^{1-q}}{k_{0}^{q}}\sqrt{\pi}\sum_{s=0}^{\infty}\left(-1\right)^{s}k^{-2+q-2s}\kappa!\left(-1\right)^{\kappa}\left(\frac{\text{Γ}\left(\frac{2-q+n}{2}\right)\left(\frac{2-q+n}{2}\right)_{s}\left(\frac{2-q-n}{2}\right)_{s}}{\text{Γ}\left(\frac{q+n}{2}\right)\text{Γ}\left(\frac{1}{2}+s\right)s!}\sum_{t=0}^{2s}\binom{2s}{t}\begin{Bmatrix}t\\
\kappa
\end{Bmatrix}c^{t}\left(-ik_{0}\right)^{2s-t}-\frac{\text{Γ}\left(\frac{3-q+n}{2}\right)\left(\frac{3-q+n}{2}\right)_{s}\left(\frac{3-q-n}{2}\right)_{s}}{\text{Γ}\left(\frac{q+n-1}{2}\right)\text{Γ}\left(\frac{3}{2}+s\right)s!}\sum_{t=0}^{2s+1}\binom{2s+1}{t}\begin{Bmatrix}t\\
\kappa
\end{Bmatrix}c^{t}\left(-ik_{0}\right)^{2s+1-t}k^{-1}\right)\\
& = & \frac{2^{1-q}}{k_{0}^{q}}\sqrt{\pi}\sum_{s=0}^{\infty}\left(-1\right)^{s}k^{-2+q-2s}\kappa!\left(-1\right)^{\kappa}\left(\frac{\text{Γ}\left(\frac{2-q+n}{2}\right)\left(\frac{2-q+n}{2}\right)_{s}\left(\frac{2-q-n}{2}\right)_{s}}{\text{Γ}\left(\frac{q+n}{2}\right)\text{Γ}\left(\frac{1}{2}+s\right)\text{Γ}\left(1+s\right)}\sum_{t=0}^{2s}\binom{2s}{t}\begin{Bmatrix}t\\
\kappa
\end{Bmatrix}c^{t}\left(-ik_{0}\right)^{2s-t}-\frac{\text{Γ}\left(\frac{3-q+n}{2}\right)\left(\frac{3-q+n}{2}\right)_{s}\left(\frac{3-q-n}{2}\right)_{s}}{\text{Γ}\left(\frac{q+n-1}{2}\right)\text{Γ}\left(\frac{3}{2}+s\right)\text{Γ}\left(1+s\right)}\sum_{t=0}^{2s+1}\binom{2s+1}{t}\begin{Bmatrix}t\\
\kappa
\end{Bmatrix}c^{t}\left(-ik_{0}\right)^{2s+1-t}k^{-1}\right)
\end{eqnarray*}
\end_inset
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\end_layout
\end_inset
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\begin_inset Note Note
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status collapsed
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\begin_layout Plain Layout
\begin_inset Formula
\begin{eqnarray*}
a & \leftarrow & \frac{2-q+n}{2}\\
c & \leftarrow & 1+n\\
z & \leftarrow & \frac{-k^{2}}{\left(c-ik_{0}\right)^{2}}
\end{eqnarray*}
\end_inset
\begin_inset Formula
\begin{eqnarray*}
\pht n{s_{q,k_{0}}^{\textup{L}1,c}}\left(k\right) & = & \frac{k^{n}Γ\left(2-q+n\right)}{2^{n}k_{0}^{q}\left(c-ik_{0}\right)^{2-q+n}}2^{n}\left(\frac{-k^{2}}{\left(c-ik_{0}\right)^{2}}\right)^{-\frac{n}{2}}\left(1-\left(\frac{-k^{2}}{\left(c-ik_{0}\right)^{2}}\right)\right)^{-\frac{2-q+n}{2}+\frac{n}{2}}P_{2-q+n-(1+n)}^{1-(1+n)}\left(\frac{1}{\sqrt{1-\left(\frac{-k^{2}}{\left(c-ik_{0}\right)^{2}}\right)}}\right)\\
& = & \frac{k^{n}Γ\left(2-q+n\right)}{k_{0}^{q}\left(c-ik_{0}\right)^{2-q+n}}\left(\frac{-k^{2}}{\left(c-ik_{0}\right)^{2}}\right)^{-\frac{n}{2}}\left(1+\frac{k^{2}}{\left(c-ik_{0}\right)^{2}}\right)^{\frac{q}{2}-1}P_{1-q}^{-n}\left(\frac{1}{\sqrt{1+\frac{k^{2}}{\left(c-ik_{0}\right)^{2}}}}\right)
\end{eqnarray*}
\end_inset
\begin_inset Formula
\[
\left|\ph\frac{-k^{2}}{\left(c-ik_{0}\right)^{2}}\right|<\pi,\quad\left|\ph\left(1+\frac{k^{2}}{\left(c-ik_{0}\right)^{2}}\right)\right|<\pi
\]
\end_inset
in other words, neither
\begin_inset Formula $-k^{2}/\left(c-ik_{0}\right)^{2}$
\end_inset
nor
\begin_inset Formula $1+k^{2}/\left(c-ik_{0}\right)^{2}$
\end_inset
can be non-positive real number.
For assumed positive
\begin_inset Formula $k_{0}$
\end_inset
and non-negative
\begin_inset Formula $c$
\end_inset
and
\begin_inset Formula $k$
\end_inset
, the former case can happen only if
\begin_inset Formula $k=0$
\end_inset
and the latter only if
\begin_inset Formula $c=0\wedge k_{0}=k$
\end_inset
.
\begin_inset Formula
\begin{eqnarray*}
\left|\ph\frac{-k^{2}}{\left(c-ik_{0}\right)^{2}}\right|<\pi & \Leftrightarrow & \left|\ph\frac{-k^{2}}{\left(c-ik_{0}\right)^{2}}\right|\neq\pi\\
\varphi & \equiv & \ph\left(c-ik_{0}\right)<0,\\
\ph k & \equiv & 0\\
\ph\frac{-k^{2}}{\left(c-ik_{0}\right)^{2}} & = & 2\varphi\\
\rightsquigarrow\left|\varphi\right| & \neq & \pi/2\\
\rightsquigarrow c & \neq & k_{0}\\
\left|\ph\left(1+\frac{k^{2}}{\left(c-ik_{0}\right)^{2}}\right)\right| & = & \left|-2\varphi+\ph\left(\left(c-ik_{0}\right)^{2}+k^{2}\right)\right|
\end{eqnarray*}
\end_inset
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Finally, swapping the first two arguments of
\begin_inset Formula $\hgfr$
\end_inset
in the hypergeometric represenation [REF DLMF 14.3.6] (note [REF DLMF §14.21(iii)]
that this also holds for complex arguments) of Legendre functions gives
\begin_inset Formula $P_{\nu}^{\mu}=P_{-\nu-1}^{\mu}$
\end_inset
, so the above result can be written
\begin_inset Formula
\[
\pht n{s_{q,k_{0}}^{\textup{L}1,c}}\left(k\right)=\frac{k^{n}\text{Γ}\left(2-q+n\right)}{k_{0}^{q}\left(c-ik_{0}\right)^{2-q+n}}\left(\frac{-k^{2}}{\left(c-ik_{0}\right)^{2}}\right)^{-\frac{n}{2}}\left(1+\frac{k^{2}}{\left(c-ik_{0}\right)^{2}}\right)^{\frac{q}{2}-1}P_{q}^{-n}\left(\frac{1}{\sqrt{1+\frac{k^{2}}{\left(c-ik_{0}\right)^{2}}}}\right).
\]
\end_inset
Let's polish it a bit more
\begin_inset Formula
\begin{eqnarray*}
\pht n{s_{q,k_{0}}^{\textup{L}1,c}}\left(k\right) & = & \frac{Γ\left(2-q+n\right)}{k_{0}^{q}\left(c-ik_{0}\right)^{2-q}}\left(-1\right)^{-\frac{n}{2}}\left(1+\frac{k^{2}}{\left(c-ik_{0}\right)^{2}}\right)^{\frac{q}{2}-1}P_{q}^{-n}\left(\frac{1}{\sqrt{1+\frac{k^{2}}{\left(c-ik_{0}\right)^{2}}}}\right)\\
& = & \frac{\text{Γ}\left(2-q+n\right)}{k_{0}^{q}}\left(-1\right)^{-\frac{n}{2}}\left(\left(c-ik_{0}\right)^{2}+k^{2}\right)^{\frac{q}{2}-1}P_{q}^{-n}\left(\frac{1}{\sqrt{1+\frac{k^{2}}{\left(c-ik_{0}\right)^{2}}}}\right).
\end{eqnarray*}
\end_inset
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\end_layout
\end_inset
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\size footnotesize
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\begin_inset Formula
\begin{multline}
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\pht n{s_{q,k_{0}}^{\textup{L}1,c}}\left(k\right)=\frac{k^{n}Γ\left(2-q+n\right)}{k_{0}^{q}\left(c-ik_{0}\right)^{2-q+n}}\left(\frac{-k^{2}}{\left(c-ik_{0}\right)^{2}}\right)^{-\frac{n}{2}}\left(1+\frac{k^{2}}{\left(c-ik_{0}\right)^{2}}\right)^{\frac{q}{2}-1}P_{q}^{-n}\left(\frac{1}{\sqrt{1+\frac{k^{2}}{\left(c-ik_{0}\right)^{2}}}}\right),\\
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k>0\wedge k_{0}>0\wedge c\ge0\wedge\lnot\left(c=0\wedge k_{0}=k\right)\label{eq:2D Hankel transform of exponentially suppressed outgoing wave expanded}
\end{multline}
\end_inset
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\size default
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with principal branches of the hypergeometric functions, associated Legendre
functions, and fractional powers.
The conditions from
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:2D Hankel transform of exponentially suppressed outgoing wave as 2F1"
\end_inset
should hold, but we will use
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:2D Hankel transform of exponentially suppressed outgoing wave expanded"
\end_inset
formally even if they are violated, with the hope that the divergences
eventually cancel in
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:2D Hankel transform of regularized outgoing wave, decomposition"
\end_inset
.
\end_layout
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\begin_layout Plain Layout
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\begin_inset Note Note
status collapsed
\begin_layout Plain Layout
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Let's do it.
\begin_inset Formula
\begin{eqnarray*}
\pht n{s_{q,k_{0}}^{\textup{L}\kappa,c}}\left(k\right) & = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{n}\text{Γ}\left(2-q+n\right)}{k_{0}^{q}\left(\sigma c-ik_{0}\right)^{2-q+n}}\left(\frac{-k^{2}}{\left(\sigma c-ik_{0}\right)^{2}}\right)^{-\frac{n}{2}}\left(1+\frac{k^{2}}{\left(\sigma c-ik_{0}\right)^{2}}\right)^{\frac{q}{2}-1}P_{q}^{-n}\left(\frac{1}{\sqrt{1+\frac{k^{2}}{\left(\sigma c-ik_{0}\right)^{2}}}}\right)\\
& = & \sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k^{n}\text{Γ}\left(2-q+n\right)}{k_{0}^{q}\left(\sigma c-ik_{0}\right)^{2-q+n}}\left(\frac{-k^{2}}{\left(\sigma c-ik_{0}\right)^{2}}\right)^{-\frac{n}{2}}\left(1+\frac{k^{2}}{\left(\sigma c-ik_{0}\right)^{2}}\right)^{\frac{q}{2}-1}P_{q}^{-n}\left(\frac{1}{\sqrt{1+\frac{k^{2}}{\left(\sigma c-ik_{0}\right)^{2}}}}\right)
\end{eqnarray*}
\end_inset
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\end_layout
\end_inset
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One problematic element here is the gamma function
\begin_inset Formula $\text{Γ}\left(2-q+n\right)$
\end_inset
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which is singular if the argument is zero or negative integer, i.e.
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if
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\begin_inset Formula $q-n\ge2$
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\end_inset
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; which is painful especially because of the case
\begin_inset Formula $q=2,n=0$
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\end_inset
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.
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The associated Legendre function can be expressed as a finite
\begin_inset Quotes eld
\end_inset
polynomial
\begin_inset Quotes erd
\end_inset
if
\begin_inset Formula $q\ge n$
\end_inset
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.
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In other cases, different expressions can be obtained from
\begin_inset CommandInset ref
LatexCommand ref
reference "eq:2D Hankel transform of exponentially suppressed outgoing wave as 2F1"
\end_inset
using various transformation formulae from either DLMF or
\begin_inset ERT
status open
\begin_layout Plain Layout
\backslash
begin{russian}
\end_layout
\end_inset
Прудников
\begin_inset ERT
status open
\begin_layout Plain Layout
\backslash
end{russian}
\end_layout
\end_inset
.
\end_layout
2018-11-14 08:37:59 +02:00
\begin_layout Plain Layout
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In fact, Mathematica is usually able to calculate the transforms for specific
values of
\begin_inset Formula $\kappa,q,n$
\end_inset
, but it did not find any general formula for me.
The resulting expressions are finite sums of algebraic functions, Table
\begin_inset CommandInset ref
LatexCommand ref
reference "tab:Asymptotical-behaviour-Mathematica"
\end_inset
shows how fast they decay with growing
\begin_inset Formula $k$
\end_inset
for some parameters.
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One particular case where Mathematica did not help at all is
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\begin_inset Formula $q=2,n=0$
\end_inset
, which is unfortunately important.
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\end_layout
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\begin_layout Plain Layout
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\begin_inset Float table
wide false
sideways false
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status open
\begin_layout Plain Layout
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\align center
\size footnotesize
\begin_inset Tabular
<lyxtabular version="3" rows="4" columns="5">
<features rotate="0" tabularvalignment="middle">
<column alignment="center" valignment="top">
<column alignment="center" valignment="top">
<column alignment="center" valignment="top">
<column alignment="center" valignment="top">
<column alignment="center" valignment="top">
<row>
<cell multicolumn="1" alignment="center" valignment="top" rightline="true" usebox="none">
\begin_inset Text
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\begin_layout Plain Layout
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\size footnotesize
\begin_inset Formula $\kappa=0$
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\end_inset
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\end_layout
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\end_inset
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</cell>
<cell multicolumn="2" alignment="center" valignment="top" rightline="true" usebox="none">
\begin_inset Text
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\begin_layout Plain Layout
\end_layout
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\end_inset
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</cell>
<cell alignment="center" valignment="top" usebox="none">
\begin_inset Text
\begin_layout Plain Layout
\end_layout
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\end_inset
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</cell>
<cell alignment="center" valignment="top" usebox="none">
\begin_inset Text
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\begin_layout Plain Layout
\size footnotesize
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\begin_inset Formula $n$
\end_inset
\end_layout
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\end_inset
</cell>
<cell alignment="center" valignment="top" usebox="none">
\begin_inset Text
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\begin_layout Plain Layout
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\end_layout
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\end_inset
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</cell>
</row>
<row>
<cell multicolumn="1" alignment="center" valignment="top" bottomline="true" usebox="none">
\begin_inset Text
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\begin_layout Plain Layout
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\end_layout
\end_inset
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</cell>
<cell alignment="center" valignment="top" bottomline="true" rightline="true" usebox="none">
\begin_inset Text
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\begin_layout Plain Layout
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\end_layout
\end_inset
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</cell>
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\begin_layout Plain Layout
\begin_inset Caption Standard
\begin_layout Plain Layout
Asymptotical behaviour of some
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:2D Hankel transform of regularized outgoing wave, decomposition"
\end_inset
obtained by Mathematica for
\begin_inset Formula $k\to\infty$
\end_inset
.
The table entries are the
\begin_inset Formula $N$
\end_inset
of
\begin_inset Formula $\pht n{s_{q,k_{0}}^{\textup{L}\kappa,c}}\left(k\right)=o\left(1/k^{N}\right)$
\end_inset
.
The special entry
\begin_inset Quotes eld
\end_inset
x
\begin_inset Quotes erd
\end_inset
means that Mathematica was not able to calculate the integral, and
\begin_inset Quotes eld
\end_inset
w
\begin_inset Quotes erd
\end_inset
denotes that the first returned term was not simply of the kind
\begin_inset Formula $(\ldots)k^{-N-1}$
\end_inset
.
\begin_inset CommandInset label
LatexCommand label
name "tab:Asymptotical-behaviour-Mathematica"
\end_inset
\end_layout
\end_inset
\end_layout
\end_inset
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\begin_inset Note Note
status open
\begin_layout Plain Layout
\begin_inset ERT
status open
\begin_layout Plain Layout
\backslash
begin{russian}
\end_layout
\end_inset
Градштейн и Рыжик
\begin_inset ERT
status open
\begin_layout Plain Layout
\backslash
end{russian}
\end_layout
\end_inset
6.512.1 has expression for
\begin_inset Formula $\int_{0}^{\infty}J_{\mu}\left(ax\right)J_{\nu}\left(bx\right)\ud x$
\end_inset
,
\begin_inset Formula $\Re\left(\mu+\nu\right)>-1$
\end_inset
in terms of hypergeometric function.
Unfortunately, no corresponding and general enough expression for
\begin_inset Formula $\int_{0}^{\infty}J_{\mu}\left(ax\right)Y_{\nu}\left(bx\right)\ud x$
\end_inset
.
\end_layout
\end_inset
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\end_layout
\begin_layout Paragraph
Case
\begin_inset Formula $n=0,q=2$
\end_inset
\end_layout
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\begin_layout Plain Layout
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As shown in a separate note,
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\end_layout
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\begin_layout Plain Layout
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\begin_inset Formula
\[
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\pht 0{s_{2,k_{0}}^{\textup{L}\kappa,c}}\left(k\right)=-\sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{1}{k_{0}^{2}}\sinh^{-1}\left(\frac{\sigma c-ik_{0}}{k}\right)
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\]
\end_inset
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for
\begin_inset Formula $\kappa\ge?$
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\end_inset
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,
\begin_inset Formula $k>k_{0}?$
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\end_inset
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\end_layout
\begin_layout Paragraph
Case
\begin_inset Formula $n=1,q=3$
\end_inset
\end_layout
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\begin_layout Plain Layout
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As shown in separate note (check whether copied correctly)
\begin_inset Formula
\[
\pht 1{s_{3,k_{0}}^{\textup{L}\kappa>3,c}}\left(k\right)=-\sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{\left(-ik_{0}+c\sigma\right)\sqrt{1-\left(\frac{k_{0}+ic\sigma}{k}\right)^{2}}-ik\sin^{-1}\left(\frac{k_{0}+ic\sigma}{k}\right)}{2k_{0}^{3}}
\]
\end_inset
for
\begin_inset Formula $\kappa\ge3$
\end_inset
,
\begin_inset Formula $k>k_{0}?$
\end_inset
\end_layout
\begin_layout Paragraph
Case
\begin_inset Formula $n=0,q=3$
\end_inset
\end_layout
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\begin_layout Plain Layout
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As shown in separate note (check whether copied correctly)
\lang finnish
\begin_inset Note Note
status collapsed
\begin_layout Plain Layout
\lang finnish
Sum[((-1)^(1 + sig)*(k*Sqrt[(k^2 - (k0 + I*c*sig)^2)/k^2] + (k0 + I*c*sig)*ArcSi
n[(k0 + I*c*sig)/k])*Binomial[kap, sig])/k0^3, {sig, 0, kap}]
\end_layout
\end_inset
\begin_inset Formula
\begin{eqnarray*}
\pht 0{s_{3,k_{0}}^{\textup{L}\kappa>3,c}}\left(k\right) & = & -\sum_{\sigma=0}^{\kappa}\left(-1\right)^{\sigma}\binom{\kappa}{\sigma}\frac{k\sqrt{1-\left(\frac{k_{0}+ic\sigma}{k}\right)^{2}}+\left(k_{0}+ic\sigma\right)\sin^{-1}\left(\frac{k_{0}+ic\sigma}{k}\right)}{k_{0}^{3}}
\end{eqnarray*}
\end_inset
\lang english
for
\begin_inset Formula $\kappa\ge2$
\end_inset
,
\begin_inset Formula $k>k_{0}?$
\end_inset
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\end_layout
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\begin_layout Plain Layout
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\begin_inset Note Note
status open
\begin_layout Plain Layout
From Wikipedia page on binomial coefficient, eq.
(10) and around:
\end_layout
\begin_layout Plain Layout
When
\begin_inset Formula $P(x)$
\end_inset
is of degree less than or equal to
\begin_inset Formula $n$
\end_inset
,
\begin_inset Formula
\[
\sum_{j=0}^{n}(-1)^{j}\binom{n}{j}P(n-j)=n!a_{n}
\]
\end_inset
where
\begin_inset Formula $a_{n}$
\end_inset
is the coefficient of degree
\begin_inset Formula $n$
\end_inset
in
\begin_inset Formula $P(x)$
\end_inset
.
\end_layout
\begin_layout Plain Layout
More generally,
\begin_inset Formula
\[
\sum_{j=0}^{n}(-1)^{j}\binom{n}{j}P(m+(n-j)d)=d^{n}n!a_{n}
\]
\end_inset
where
\begin_inset Formula $m$
\end_inset
and
\begin_inset Formula $d$
\end_inset
are complex numbers.
\end_layout
\end_inset
\begin_inset Note Note
status open
\begin_layout Subsubsection
Hankel transforms of the long-range parts, alternative regularisation with
\begin_inset Formula $e^{-p/x^{2}}$
\end_inset
\begin_inset CommandInset label
LatexCommand label
name "sub:Hankel-transforms-ig-reg"
\end_inset
\end_layout
\begin_layout Plain Layout
From [REF
\begin_inset ERT
status open
\begin_layout Plain Layout
\backslash
begin{russian}
\end_layout
\end_inset
Прудников, том 2
\begin_inset ERT
status open
\begin_layout Plain Layout
\backslash
end{russian}
\end_layout
\end_inset
, 2.12.9.14]
\begin_inset Formula
\begin{multline}
\int_{0}^{\infty}x^{\alpha-1}e^{-p/x^{2}}J_{\nu}\left(cx\right)\,\ud x=\frac{2^{\alpha-1}}{c^{\alpha}}Γ\begin{bmatrix}\left(\alpha+\nu\right)/2\\
1+\left(\nu-\alpha\right)/2
\end{bmatrix}{}_{0}F_{2}\left(1-\frac{\nu+\alpha}{2},1+\frac{\nu-\alpha}{2};\frac{c^{2}p}{4}\right)\\
+\frac{c^{\nu}p^{\left(\alpha+\nu\right)/2}}{2^{\nu+1}}\text{Γ}\begin{bmatrix}\left(\alpha+\nu\right)/2\\
\nu+1
\end{bmatrix}{}_{0}F_{2}\left(1+\frac{\nu+\alpha}{2},\nu+1;\frac{c^{2}p}{4}\right),\qquad[c,\Re p>0;\Re\alpha<3/2].\label{eq:prudnikov2 eq 2.12.9.14}
\end{multline}
\end_inset
Let now
\begin_inset Formula $\rho_{p}^{\textup{ig.}}$
\end_inset
from
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:inverse gaussian regularisation function"
\end_inset
serve as the regularisation fuction and
\begin_inset Formula
\[
\pht n{s_{q,k_{0}}^{\textup{L}'p}}\left(k\right)\equiv\int_{0}^{\infty}\frac{e^{ik_{0}r}}{\left(k_{0}r\right)^{q}}J_{n}\left(kr\right)e^{-p/r^{2}}r\,\ud r.
\]
\end_inset
And it seems that this is a dead-end, because
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:prudnikov2 eq 2.12.9.14"
\end_inset
cannot deal with the
\begin_inset Formula $e^{ik_{0}r}$
\end_inset
part.
Damn.
\end_layout
\end_inset
\end_layout
\begin_layout Subsection
3d (TODO)
\end_layout
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\begin_layout Plain Layout
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\begin_inset Formula
\begin{multline*}
\uaft{S_{l',m',t'\leftarrow l,m,t}\left(\vect{\bullet}\leftarrow\vect 0\right)}(\vect k)=\\
\sum_{p}c_{p}^{l',m',t'\leftarrow l,m,t}\ush p{m'-m}\left(\theta_{\vect k},\phi_{\vect k}\right)\left(-i\right)^{p}\usht p{z_{p}^{(J)}}\left(\left|\vect k\right|\right)
\end{multline*}
\end_inset
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\end_layout
\end_inset
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\end_layout
\begin_layout Section
Exponentially converging decompositions
\end_layout
\begin_layout Standard
(As in Linton, Thompson, Journal of Computational Physics 228 (2009) 1815– 1829
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[LT]
\begin_inset CommandInset citation
LatexCommand cite
key "linton_one-_2009"
\end_inset
.)
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\end_layout
\begin_layout Standard
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\begin_inset Note Note
status open
\begin_layout Plain Layout
[LT]
\end_layout
\end_inset
\begin_inset CommandInset citation
LatexCommand cite
key "linton_one-_2009"
\end_inset
offers an exponentially convergent decomposition.
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Let
\begin_inset Formula
\begin{eqnarray*}
\sigma_{n}^{m}\left(\vect{\beta}\right) & = & \sum_{\vect R\in\Lambda}^{'}e^{i\vect{\beta}\cdot\vect R}\swv_{n}^{m}\left(\vect R\right),\\
\swv_{n}^{m}\left(\vect r\right) & = & Y_{n}^{m}\left(\hat{\vect r}\right)h_{n}\left(\left|\vect r\right|\right).
\end{eqnarray*}
\end_inset
Then, we have a decomposition
\begin_inset Formula $\sigma_{n}^{m}=\sigma_{n}^{m(0)}+\sigma_{n}^{m(1)}+\sigma_{n}^{m(2)}$
\end_inset
.
The real-space sum part
\begin_inset Formula $\sigma_{n}^{m(2)}$
\end_inset
is already
\begin_inset Quotes eld
\end_inset
convention independent
\begin_inset Quotes erd
\end_inset
in [LT(4.5)] (i.e.
the result is also expressed in terms of
\begin_inset Formula $Y_{n}^{m}$
\end_inset
, so it is valid regardless of normalisation or CS-phase convention used
inside
\begin_inset Formula $Y_{n}^{m}$
\end_inset
):
\begin_inset Formula
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\begin{equation}
\sigma_{n}^{m(2)}=-\frac{2^{n+1}i}{k^{n+1}\sqrt{\pi}}\sum_{\vect R\in\Lambda}^{'}\left|\vect R\right|^{n}e^{i\vect{\beta}\cdot\vect R}Y_{n}^{m}\left(\vect R\right)\int_{\eta}^{\infty}e^{-\left|\vect R\right|^{2}\xi^{2}}e^{-k/4\xi^{2}}\xi^{2n}\ud\xi.\label{eq:Ewald in 3D short-range part}
\end{equation}
\end_inset
However the other parts in
\begin_inset CommandInset citation
LatexCommand cite
key "linton_one-_2009"
\end_inset
\begin_inset Note Note
status open
\begin_layout Plain Layout
[LT]
\end_layout
\end_inset
are convention dependend, so let me fix it here.
\begin_inset Note Note
status open
\begin_layout Plain Layout
[LT]
\end_layout
\end_inset
\begin_inset CommandInset citation
LatexCommand cite
key "linton_one-_2009"
\end_inset
use the convention
\begin_inset CommandInset citation
LatexCommand cite
after "(A.7)"
key "linton_one-_2009"
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\end_inset
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\begin_inset Note Note
status open
\begin_layout Plain Layout
[LT(A.7)]
\end_layout
\end_inset
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\begin_inset Formula
\begin{eqnarray*}
P_{n}^{m}\left(0\right) & = & \frac{\left(-1\right)^{\left(n-m\right)/2}\left(n+m\right)!}{2^{n}\left(\left(n-m\right)/2\right)!\left(\left(n+m\right)/2\right)!}\qquad n+m\mbox{ even,}\\
Y_{n}^{m}\left(\theta,\phi\right) & = & \left(-1\right)^{m}\sqrt{\frac{\left(2n+1\right)\left(n-m\right)!}{4\pi\left(n+m\right)!}}P_{n}^{m}\left(\cos\theta\right)e^{im\phi},
\end{eqnarray*}
\end_inset
noting that the former formula is valid also for negative
\begin_inset Formula $m$
\end_inset
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(as can be checked by substituting
\begin_inset CommandInset citation
LatexCommand cite
after "(A.4)"
key "linton_one-_2009"
\end_inset
\begin_inset Note Note
status open
\begin_layout Plain Layout
[LT(A.4)]
\end_layout
\end_inset
).
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Therefore
\begin_inset Formula
\begin{eqnarray*}
Y_{n}^{m}\left(\frac{\pi}{2},\phi\right) & = & \left(-1\right)^{m}\sqrt{\frac{\left(2n+1\right)\left(n-m\right)!}{4\pi\left(n+m\right)!}}\frac{\left(-1\right)^{\left(n-m\right)/2}\left(n+m\right)!}{2^{n}\left(\left(n-m\right)/2\right)!\left(\left(n+m\right)/2\right)!}e^{im\phi}\\
& = & \frac{\left(-1\right)^{\left(n+m\right)/2}\sqrt{\left(2n+1\right)\left(n-m\right)!\left(n+m\right)!}}{\sqrt{\pi}2^{n+1}\left(\left(n-m\right)/2\right)!\left(\left(n+m\right)/2\right)!}e^{im\phi}
\end{eqnarray*}
\end_inset
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Let us substitute this into
\begin_inset Note Note
status open
\begin_layout Plain Layout
[LT(4.5)]
\end_layout
\end_inset
\begin_inset CommandInset citation
LatexCommand cite
after "(4.5)"
key "linton_one-_2009"
\end_inset
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\begin_inset Formula
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\begin{eqnarray}
\sigma_{n}^{m(1)} & = & -\frac{i^{n+1}}{2k^{2}\mathscr{A}}\left(-1\right)^{\left(n+m\right)/2}\sqrt{\left(2n+1\right)\left(n-m\right)!\left(n+m\right)!}\times\nonumber \\
& & \times\sum_{\vect K_{pq}\in\Lambda^{*}}^{'}\sum_{j=0}^{\left[\left(n-\left|m\right|/2\right)\right]}\frac{\left(-1\right)^{j}\left(\beta_{pq}/2k\right)^{n-2j}e^{im\phi_{\vect{\beta}_{pq}}}\Gamma_{j,pq}}{j!\left(\frac{1}{2}\left(n-m\right)-j\right)!\left(\frac{1}{2}\left(n+m\right)-j\right)!}\left(\frac{\gamma_{pq}}{2}\right)^{2j-1}\nonumber \\
& = & -\frac{i^{n+1}}{2k^{2}\mathscr{A}}\sqrt{\pi}2^{n+1}\left(\left(n-m\right)/2\right)!\left(\left(n+m\right)/2\right)!\times\nonumber \\
& & \times\sum_{\vect K_{pq}\in\Lambda^{*}}^{'}Y_{n}^{m}\left(\frac{\pi}{2},\phi_{\vect{\beta}_{pq}}\right)\sum_{j=0}^{\left[\left(n-\left|m\right|/2\right)\right]}\frac{\left(-1\right)^{j}\left(\beta_{pq}/2k\right)^{n-2j}\Gamma_{j,pq}}{j!\left(\frac{1}{2}\left(n-m\right)-j\right)!\left(\frac{1}{2}\left(n+m\right)-j\right)!}\left(\frac{\gamma_{pq}}{2}\right)^{2j-1}\nonumber \\
& = & -\frac{i^{n+1}}{k\mathscr{A}}\sqrt{\pi}2\left(\left(n-m\right)/2\right)!\left(\left(n+m\right)/2\right)!\times\nonumber \\
& & \times\sum_{\vect K_{pq}\in\Lambda^{*}}^{'}Y_{n}^{m}\left(\frac{\pi}{2},\phi_{\vect{\beta}_{pq}}\right)\sum_{j=0}^{\left[\left(n-\left|m\right|/2\right)\right]}\frac{\left(-1\right)^{j}\left(\beta_{pq}/k\right)^{n-2j}\Gamma_{j,pq}}{j!\left(\frac{1}{2}\left(n-m\right)-j\right)!\left(\frac{1}{2}\left(n+m\right)-j\right)!}\left(\gamma_{pq}\right)^{2j-1}\label{eq:2D Ewald in 3D long-range part}
\end{eqnarray}
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\end_inset
which basically replaces an ugly prefactor with another, similarly ugly
one.
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See
\begin_inset CommandInset citation
LatexCommand cite
key "linton_one-_2009"
\end_inset
\begin_inset Note Note
status open
\begin_layout Plain Layout
[LT]
\end_layout
\end_inset
for the meanings of the
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\begin_inset Formula $pq$
\end_inset
-indexed symbols.
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Note that the latter version does not depend on the sign of
\begin_inset Formula $m$
\end_inset
(except for that which is already included in
\begin_inset Formula $Y_{n}^{m}$
\end_inset
).
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\end_layout
\begin_layout Standard
To have it complete,
\begin_inset Formula
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\begin{equation}
\sigma_{n}^{m(0)}=\frac{\delta_{n0}\delta_{m0}}{4\pi}\Gamma\left(-\frac{1}{2},-\frac{k}{4\eta^{2}}\right)=\frac{\delta_{n0}\delta_{m0}}{\sqrt{4\pi}}\Gamma\left(-\frac{1}{2},-\frac{k}{4\eta^{2}}\right)Y_{n}^{m}.\label{eq:Ewald in 3D origin part}
\end{equation}
\end_inset
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\end_layout
\begin_layout Standard
N.B.
Apparently, the formulae might be valid regardless of coordinate system
orientation (then the spherical harmonic arguments would be of course general
\begin_inset Formula $Y_{n}^{m}\left(\theta,\phi\right)$
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\end_inset
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,
\begin_inset Formula $Y_{n}^{m}\left(\theta_{b_{pq}},\phi_{\vect{\beta}_{pq}}\right)$
\end_inset
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accordingly; but CHECK).
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\end_layout
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\begin_layout Subsection
Error estimates
\end_layout
\begin_layout Standard
For the part of a 2D lattice sum that lies outside of a circle with radius
\begin_inset Formula $R$
\end_inset
and
\begin_inset Formula $f(r)$
\end_inset
positive, radial, monotonically decreasing, we have
\end_layout
\begin_layout Standard
\begin_inset Formula
\begin{equation}
\mathscr{A}_{\Lambda}\sum_{\begin{array}{c}
\vect R_{i}\in\Lambda\\
\left|\vect R_{i}\right|\ge R
\end{array}}f\left(\left|\vect R_{i}\right|\right)\le2\pi\underbrace{\int_{R_{\mathrm{s}}\left(R,\Lambda\right)}^{\infty}rf(r)\,\ud r}_{\equiv B_{R_{\mathrm{s}}}\left[f\right]},\label{eq:lsum_bound}
\end{equation}
\end_inset
where the largest
\begin_inset Quotes eld
\end_inset
safe radius
\begin_inset Quotes erd
\end_inset
\begin_inset Formula $R_{\mathrm{s}}\left(R,\Lambda\right)$
\end_inset
is probably something like
\begin_inset Formula $R-\left|\vect u_{\mathrm{L}}\right|$
\end_inset
where
\begin_inset Formula $\vect u_{\mathrm{L}}$
\end_inset
is the longer primitive lattice vector of
\begin_inset Formula $\Lambda$
\end_inset
.
\end_layout
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\begin_layout Subsubsection
Short-range (real-space) sum
\end_layout
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\begin_layout Standard
For the short-range part
\begin_inset Formula $\sigma_{n}^{m(2)}$
\end_inset
, the radially varying part reads
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\begin_inset Formula $f_{\eta}^{\mathrm{S}}\left(R_{pq}\right)\equiv R_{pq}^{n}\int_{\eta}^{\infty}e^{-R_{pq}^{2}\xi^{2}}e^{k^{2}/4\xi^{2}}\xi^{2n}\ud\xi$
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\end_inset
and for its integral as in
\begin_inset CommandInset ref
LatexCommand ref
reference "eq:lsum_bound"
\end_inset
we have
\begin_inset Formula
\begin{eqnarray*}
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B_{R_{\mathrm{s}}}\left[f_{\eta}^{\mathrm{S}}\right] & = & \int_{R_{\mathrm{s}}}^{\infty}r^{n+1}\int_{\eta}^{\infty}e^{-r^{2}\xi^{2}}e^{k^{2}/4\xi^{2}}\xi^{2n}\ud\xi\,\ud r\\
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& \le & e^{k^{2}/4\eta^{2}}\int_{R_{\mathrm{s}}}^{\infty}\int_{\eta}^{\infty}r^{n+1}e^{-r^{2}\xi^{2}}\xi^{2n}\ud\xi\,\ud r\\
& = & e^{k^{2}/4\eta^{2}}\frac{\eta^{2n+1}R_{\mathrm{s}}^{2+n}\left(E_{\frac{1}{2}-n}\left(\eta^{2}R_{\mathrm{s}}^{2}\right)-E_{-\frac{n}{2}}\left(\eta^{2}R_{\mathrm{s}}^{2}\right)\right)}{2\left(n-1\right)}\\
& = & e^{k^{2}/4\eta^{2}}\frac{\eta^{2n+1}R_{\mathrm{s}}^{2+n}\left(\left(\eta R_{\mathrm{s}}\right)^{-2n-1}\Gamma\left(n+\frac{1}{2},\eta^{2}R_{\mathrm{s}}^{2}\right)-\left(\eta R_{\mathrm{s}}\right)^{-n-2}\Gamma\left(\frac{n}{2}+1,\eta^{2}R_{\mathrm{s}}^{2}\right)\right)}{2\left(n-1\right)}\\
& = & \frac{e^{k^{2}/4\eta^{2}}}{2\left(n-1\right)}\left(R_{\mathrm{s}}^{1-n}\Gamma\left(n+\frac{1}{2},\eta^{2}R_{\mathrm{s}}^{2}\right)-\eta^{n-1}\Gamma\left(\frac{n}{2}+1,\eta^{2}R_{\mathrm{s}}^{2}\right)\right),
\end{eqnarray*}
\end_inset
where the integral is according to mathematica and the error functions were
transformed to incomplete gammas using the relation
\begin_inset Formula $\Gamma\left(s,x\right)=x^{s}E_{1-s}\left(x\right)$
\end_inset
from Wikipedia or equivalently
\begin_inset Formula $\Gamma\left(1-n,z\right)=z^{1-n}E_{n}\left(z\right)$
\end_inset
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from
\begin_inset CommandInset citation
LatexCommand cite
after "8.4.13"
key "NIST:DLMF"
\end_inset
\begin_inset Note Note
status open
\begin_layout Plain Layout
[DLMF(8.4.13)]
\end_layout
\end_inset
.
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Therefore, the upper estimate for the short-range sum error is
\begin_inset Formula
\begin{eqnarray*}
\left|\sigma_{n}^{m(2)}|_{R_{pq}>R}\right| & \le & \frac{2^{n+1}}{k^{n+1}\sqrt{\pi}}\left|P_{n}^{m}\left(0\right)\right|\frac{2\pi}{\mathscr{A}_{\Lambda}}\frac{e^{k^{2}/4\eta^{2}}}{2\left(n-1\right)}\left(R_{\mathrm{s}}^{1-n}\Gamma\left(n+\frac{1}{2},\eta^{2}R_{\mathrm{s}}^{2}\right)-\eta^{n-1}\Gamma\left(\frac{n}{2}+1,\eta^{2}R_{\mathrm{s}}^{2}\right)\right)\\
& = & \frac{2^{n+1}}{k^{n+1}}\left|P_{n}^{m}\left(0\right)\right|\frac{\sqrt{\pi}}{\mathscr{A}_{\Lambda}}\frac{e^{k^{2}/4\eta^{2}}}{n-1}\left(R_{\mathrm{s}}^{1-n}\Gamma\left(n+\frac{1}{2},\eta^{2}R_{\mathrm{s}}^{2}\right)-\eta^{n-1}\Gamma\left(\frac{n}{2}+1,\eta^{2}R_{\mathrm{s}}^{2}\right)\right).
\end{eqnarray*}
\end_inset
Apparently, this expression is problematic for
\begin_inset Formula $n=1$
\end_inset
; Mathematica gives for that case some ugly expression with
\begin_inset Formula $_{2}F_{2}$
\end_inset
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, resulting in:
\begin_inset Formula
\[
B_{R_{\mathrm{s}}}\left[f_{\eta}^{\mathrm{S}}\right]\le e^{k^{2}/4\eta^{2}}\left(\frac{\eta R}{2}{}_{2}F_{2}\left(\begin{array}{cc}
\frac{1}{2}, & \frac{1}{2}\\
\frac{3}{2}, & \frac{3}{2}
\end{array};-\eta^{2}R_{\mathrm{s}}^{2}\right)-\frac{\sqrt{\pi}}{8}\left(\gamma_{\mathrm{E}}-2\mathrm{erfc}\left(\eta R_{\mathrm{s}}\right)+2\log\left(2\eta R_{\mathrm{s}}\right)\right)\right).
\]
\end_inset
The problem is that evaluation of the
\begin_inset Formula $_{2}F_{2}$
\end_inset
for large argument is very problematic.
However, Mathematica says that the value of the right parenthesis drops
below DBL_EPSILON for
\begin_inset Formula $\eta R_{\mathrm{s}}>6$
\end_inset
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.
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\end_layout
\begin_layout Standard
Also the expression for
\begin_inset Formula $n\ne1$
\end_inset
decreases very fast, so as long as the value of
\begin_inset Formula $e^{k^{2}/4\eta^{2}}$
\end_inset
is reasonably low, there should not be much trouble.
\end_layout
\begin_layout Standard
\begin_inset Note Note
status open
\begin_layout Plain Layout
Maybe it might make sense to take a rougher estimate using (for
2018-09-11 01:01:26 +03:00
\begin_inset Formula $n=1$
\end_inset
)
\begin_inset Formula
\begin{eqnarray*}
B_{R_{\mathrm{s}}}\left[f_{\eta}^{\mathrm{L}}\right] & = & \int_{R_{\mathrm{s}}}^{\infty}r^{2}\int_{\eta}^{\infty}e^{-r^{2}\xi^{2}}e^{k^{2}/4\xi^{2}}\xi^{2}\ud\xi\,\ud r\\
& \le & e^{k^{2}/4\eta^{2}}\int_{R_{\mathrm{s}}}^{\infty}\int_{\eta}^{\infty}e^{-r^{2}\xi^{2}}r^{2}\xi^{2}\ud\xi\,\ud r,
\end{eqnarray*}
\end_inset
now the integration on the last line is
\begin_inset Quotes eld
\end_inset
symmetric
\begin_inset Quotes erd
\end_inset
w.r.t.
\begin_inset Formula $R_{\mathrm{s}}\leftrightarrow\eta$
\end_inset
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, so we can write either
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\begin_inset Formula
\[
B_{R_{\mathrm{s}}}\left[f_{\eta}^{\mathrm{L}}\right]\le e^{k^{2}/4\eta^{2}}\int_{R_{\mathrm{s}}}^{\infty}\int_{\eta}^{\infty}e^{-r^{2}\xi^{2}}r^{2}\xi^{2}\ud\xi\,\ud r
\]
\end_inset
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\end_layout
\end_inset
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\end_layout
\begin_layout Subsubsection
Long-range (
\begin_inset Formula $k$
\end_inset
-space) sum
\end_layout
\begin_layout Standard
For
\begin_inset Formula $\beta_{pq}>k$
\end_inset
, we have
\begin_inset Formula $\gamma_{pq}=\frac{\beta_{pq}}{k}\sqrt{1-\left(k/\beta_{pq}\right)^{2}}\le\frac{\beta_{pq}}{k}$
\end_inset
, hence
\begin_inset Formula $\Gamma_{j,pq}=\Gamma\left(\frac{1}{2}-j,\frac{\beta_{pq}^{2}-k^{2}}{4\eta^{2}}\right)$
\end_inset
and the
\begin_inset Formula $\beta_{pq}$
\end_inset
-dependent part of
\begin_inset Formula $\sigma_{n}^{m(1)}$
\end_inset
is
\end_layout
\begin_layout Standard
\begin_inset Formula
\begin{eqnarray*}
\left(\beta_{pq}/k\right)^{n-2j}\Gamma_{j,pq}\left(\gamma_{pq}\right)^{2j-1} & = & \left(\beta_{pq}/k\right)^{n-2j}\Gamma\left(\frac{1}{2}-j,\frac{\beta_{pq}^{2}-k^{2}}{4\eta^{2}}\right)\left(\frac{\beta_{pq}^{2}}{k^{2}}-1\right)^{j-\frac{1}{2}}\\
& \le & \left(\beta_{pq}/k\right)^{n-2j}\left(\frac{\beta_{pq}^{2}-k^{2}}{4\eta^{2}}\right)^{-j-\frac{1}{2}}e^{-\frac{\beta_{pq}^{2}-k^{2}}{4\eta^{2}}}\left(\frac{\beta_{pq}^{2}}{k^{2}}-1\right)^{j-\frac{1}{2}}\\
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& = & \left(2\eta\right)^{2j+1}e^{-\frac{\beta_{pq}^{2}-k^{2}}{4\eta^{2}}}k^{-n-1}\beta_{pq}^{n-2j}\left(\frac{\beta_{pq}^{2}}{k^{2}}-1\right)^{-1}\\
& = & e^{-\frac{\beta_{pq}^{2}-k^{2}}{4\eta^{2}}}\left(\frac{\beta_{pq}}{k}\right)^{n}\frac{2\eta}{k}\left(\frac{2\eta}{\beta_{pq}}\right)^{2j}\left(\frac{\beta_{pq}^{2}}{k^{2}}-1\right)^{-1}.
\end{eqnarray*}
\end_inset
The only diverging factor here is apparently
\begin_inset Formula $\left(\beta_{pq}/k\right)^{n}$
\end_inset
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; Mathematica and
\begin_inset CommandInset citation
LatexCommand cite
key "NIST:DLMF"
\end_inset
\begin_inset Note Note
status open
\begin_layout Plain Layout
[DMLF]
\end_layout
\end_inset
say
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\begin_inset Formula
\begin{eqnarray*}
\int_{B_{\mathrm{s}}}^{\infty}e^{-\frac{\beta^{2}}{4\eta^{2}}}\beta^{n}\beta\ud\beta & = & \frac{B_{\mathrm{s}}^{n+2}}{2}E_{-\frac{n}{2}}\left(\frac{B_{\mathrm{s}}^{2}}{4\eta^{2}}\right)\\
& = & \frac{B_{\mathrm{s}}^{n+2}}{2}\left(\frac{B_{\mathrm{s}}^{2}}{4\eta^{2}}\right)^{-1-\frac{n}{2}}\Gamma\left(1+\frac{n}{2},\frac{B_{\mathrm{s}}^{2}}{4\eta^{2}}\right)\\
& = & \frac{\left(2\eta\right)^{n+2}}{2}\Gamma\left(1+\frac{n}{2},\frac{B_{\mathrm{s}}^{2}}{4\eta^{2}}\right).
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\end{eqnarray*}
\end_inset
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\end_layout
\begin_layout Subsection
1D
\end_layout
\begin_layout Standard
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For 1D chains, one can use almost the same formulae as above – the main
difference is that there are different exponents in some terms of the long-rang
e part so that
\begin_inset Formula $\sigma_{n[1\mathrm{d}]}^{m(1)}/\sigma_{n[2\mathrm{d}]}^{m(1)}=k\gamma_{pq}/2\sqrt{\pi}$
\end_inset
(see
\begin_inset CommandInset citation
LatexCommand cite
after "(4.62)"
key "linton_lattice_2010"
\end_inset
), so
\end_layout
\begin_layout Standard
\begin_inset Formula
\begin{eqnarray}
\sigma_{n}^{m(1)} & = & -\frac{i^{n+1}}{2k\sqrt{\pi}\mathscr{A}}\left(-1\right)^{\left(n+m\right)/2}\sqrt{\left(2n+1\right)\left(n-m\right)!\left(n+m\right)!}\times\nonumber \\
& & \times\sum_{\vect K_{pq}\in\Lambda^{*}}^{'}\sum_{j=0}^{\left[\left(n-\left|m\right|/2\right)\right]}\frac{\left(-1\right)^{j}\left(\beta_{pq}/2k\right)^{n-2j}e^{im\phi_{\vect{\beta}_{pq}}}\Gamma_{j,pq}}{j!\left(\frac{1}{2}\left(n-m\right)-j\right)!\left(\frac{1}{2}\left(n+m\right)-j\right)!}\left(\frac{\gamma_{pq}}{2}\right)^{2j}\nonumber \\
& = & -\frac{i^{n+1}}{2k\mathscr{A}}2^{n+1}\left(\left(n-m\right)/2\right)!\left(\left(n+m\right)/2\right)!\times\nonumber \\
& & \times\sum_{\vect K_{pq}\in\Lambda^{*}}^{'}Y_{n}^{m}\left(\frac{\pi}{2},\phi_{\vect{\beta}_{pq}}\right)\sum_{j=0}^{\left[\left(n-\left|m\right|/2\right)\right]}\frac{\left(-1\right)^{j}\left(\beta_{pq}/2k\right)^{n-2j}\Gamma_{j,pq}}{j!\left(\frac{1}{2}\left(n-m\right)-j\right)!\left(\frac{1}{2}\left(n+m\right)-j\right)!}\left(\frac{\gamma_{pq}}{2}\right)^{2j}\nonumber \\
& = & -\frac{i^{n+1}}{\mathscr{A}}\left(\left(n-m\right)/2\right)!\left(\left(n+m\right)/2\right)!\times\nonumber \\
& & \times\sum_{\vect K_{pq}\in\Lambda^{*}}^{'}Y_{n}^{m}\left(\frac{\pi}{2},\phi_{\vect{\beta}_{pq}}\right)\sum_{j=0}^{\left[\left(n-\left|m\right|/2\right)\right]}\frac{\left(-1\right)^{j}\left(\beta_{pq}/k\right)^{n-2j}\Gamma_{j,pq}}{j!\left(\frac{1}{2}\left(n-m\right)-j\right)!\left(\frac{1}{2}\left(n+m\right)-j\right)!}\left(\gamma_{pq}\right)^{2j}\label{eq:1D Ewald in 3D long-range part}
\end{eqnarray}
\end_inset
and of course, in this case the unit cell
\begin_inset Quotes eld
\end_inset
volume
\begin_inset Quotes erd
\end_inset
\begin_inset Formula $\mathscr{A}$
\end_inset
has the dimension of length instead of
\begin_inset Formula $\mbox{length}^{2}$
\end_inset
.
Eqs.
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:Ewald in 3D short-range part"
\end_inset
,
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:Ewald in 3D origin part"
\end_inset
for
\begin_inset Formula $\sigma_{n}^{m(2)},\sigma_{n}^{m(0)}$
\end_inset
can be used directly without modifications.
\end_layout
\begin_layout Standard
\begin_inset Note Note
status open
\begin_layout Plain Layout
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One-dimensional lattice sums are provided in [REF LT, sect.
3].
However, these are the
\begin_inset Quotes eld
\end_inset
non-shifted
\begin_inset Quotes erd
\end_inset
sums,
\begin_inset Formula
\begin{eqnarray*}
\ell_{n}\left(\beta\right) & = & \sum_{j\in\ints}^{'}e^{i\beta aj}\mathcal{H}_{n}^{0}\left(aj\hat{\vect z}\right)\\
& = & \sum_{j\in\ints}^{'}e^{i\beta aj}h_{n}\left(\left|aj\right|\right)Y_{n}^{0}\\
& = & \sqrt{\frac{2n+1}{4\pi}}\sum_{j\in\ints}^{'}P_{n}^{0}\left(\sgn j\right)h_{n}\left(\left|aj\right|\right)e^{i\beta aj}\\
& = & \sqrt{\frac{2n+1}{4\pi}}\sum_{j\in\ints}^{'}\left(\sgn j\right)^{n}h_{n}\left(\left|aj\right|\right)e^{i\beta aj},
\end{eqnarray*}
\end_inset
where we used
\begin_inset Formula $P_{n}^{m}\left(\pm1\right)=\left(\pm1\right)^{n}\delta_{m0}$
\end_inset
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.
\end_layout
\end_inset
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2018-09-10 23:01:49 +03:00
\end_layout
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\begin_layout Section
Major TODOs and open questions
\end_layout
\begin_layout Itemize
Check if
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:2D Hankel transform of exponentially suppressed outgoing wave expanded"
\end_inset
gives a satisfactory result for the case
\begin_inset Formula $q=2,n=0$
\end_inset
.
\end_layout
\begin_layout Itemize
Analyse the behaviour
\begin_inset Formula $k\to k_{0}$
\end_inset
.
\end_layout
\begin_layout Itemize
Find a general algorithm for generating the expressions of the Hankel transforms.
\end_layout
\begin_layout Itemize
Three-dimensional case.
\end_layout
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\begin_layout Section
(Appendix) Fourier vs.
Hankel transform
\end_layout
\begin_layout Subsection
Three dimensions
\end_layout
\begin_layout Standard
Given a nice enough function
\begin_inset Formula $f$
\end_inset
of a real 3d variable, assume its factorisation into radial and angular
parts
\begin_inset Formula
\[
f(\vect r)=\sum_{l,m}f_{l,m}(\left|\vect r\right|)\ush lm\left(\theta_{\vect r},\phi_{\vect r}\right).
\]
\end_inset
Acording to (REF Baddour 2010, eqs.
13, 16), its Fourier transform can then be expressed in terms of Hankel
transforms (CHECK normalisation of
\begin_inset Formula $j_{n}$
\end_inset
, REF Baddour (1))
\begin_inset Formula
\[
\uaft f(\vect k)=\frac{4\pi}{\left(2\pi\right)^{\frac{3}{2}}}\sum_{l,m}\left(-i\right)^{l}\left(\bsht{f_{l,m}}{}\right)\left(\left|\vect k\right|\right)\ush lm\left(\theta_{\vect k},\phi_{\vect k}\right)
\]
\end_inset
where the spherical Hankel transform
\begin_inset Formula $\bsht l{}$
\end_inset
of degree
\begin_inset Formula $l$
\end_inset
is defined as (REF Baddour eq.
2)
\begin_inset Formula
\[
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\bsht lg(k)\equiv\int_{0}^{\infty}\ud r\, r^{2}g(r)j_{l}\left(kr\right).
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\]
\end_inset
Using this convention, the inverse spherical Hankel transform is given by
(REF Baddour eq.
3)
\begin_inset Formula
\[
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g(r)=\frac{2}{\pi}\int_{0}^{\infty}\ud k\, k^{2}\bsht lg(k)j_{l}(k),
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\]
\end_inset
so it is not unitary.
\end_layout
\begin_layout Standard
An unitary convention would look like this:
\begin_inset Formula
\begin{equation}
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\usht lg(k)\equiv\sqrt{\frac{2}{\pi}}\int_{0}^{\infty}\ud r\, r^{2}g(r)j_{l}\left(kr\right).\label{eq:unitary 3d Hankel tf definition}
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\end{equation}
\end_inset
Then
\begin_inset Formula $\usht l{}^{-1}=\usht l{}$
\end_inset
and the unitary, angular-momentum Fourier transform reads
\begin_inset Formula
\begin{eqnarray}
\uaft f(\vect k) & = & \frac{4\pi}{\left(2\pi\right)^{\frac{3}{2}}}\sqrt{\frac{\pi}{2}}\sum_{l,m}\left(-i\right)^{l}\left(\usht l{f_{l,m}}\right)\left(\left|\vect k\right|\right)\ush lm\left(\theta_{\vect k},\phi_{\vect k}\right)\nonumber \\
& = & \sum_{l,m}\left(-i\right)^{l}\left(\usht l{f_{l,m}}\right)\left(\left|\vect k\right|\right)\ush lm\left(\theta_{\vect k},\phi_{\vect k}\right).\label{eq:Fourier v. Hankel tf 3d}
\end{eqnarray}
\end_inset
Cool.
\end_layout
\begin_layout Subsection
Two dimensions
\end_layout
\begin_layout Standard
Similarly in 2d, let the expansion of
\begin_inset Formula $f$
\end_inset
be
\begin_inset Formula
\[
f\left(\vect r\right)=\sum_{m}f_{m}\left(\left|\vect r\right|\right)e^{im\phi_{\vect r}},
\]
\end_inset
its Fourier transform is then (CHECK this, it is taken from the Wikipedia
article on Hankel transform)
\begin_inset Formula
\begin{equation}
\uaft f\left(\vect k\right)=\sum_{m}i^{m}e^{im\phi_{\vect k}}\pht mf_{m}\left(\left|\vect k\right|\right)\label{eq:Fourier v. Hankel tf 2d}
\end{equation}
\end_inset
where the Hankel transform of order
\begin_inset Formula $m$
\end_inset
is defined as
\begin_inset Formula
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\begin{eqnarray}
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\pht mg\left(k\right) & = & \int_{0}^{\infty}\ud r\, g(r)J_{m}(kr)r\label{eq:unitary 2d Hankel tf definition}\\
& = & \left(-1\right)^{m}\int_{0}^{\infty}\ud r\, g(r)J_{-m}(kr)r
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\end{eqnarray}
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\end_inset
which is already self-inverse,
\begin_inset Formula $\pht m{}^{-1}=\pht m{}$
\end_inset
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(hence also unitary).
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\end_layout
\begin_layout Section
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(Appendix) Multidimensional Dirac comb
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\end_layout
\begin_layout Subsection
1D
\end_layout
\begin_layout Standard
This is all from Wikipedia
\end_layout
\begin_layout Subsubsection
Definitions
\end_layout
\begin_layout Standard
\begin_inset Formula
\begin{eqnarray*}
Ш(t) & \equiv & \sum_{k=-\infty}^{\infty}\delta(t-k)\\
Ш_{T}(t) & \equiv & \sum_{k=-\infty}^{\infty}\delta(t-kT)=\frac{1}{T}Ш\left(\frac{t}{T}\right)
\end{eqnarray*}
\end_inset
\end_layout
\begin_layout Subsubsection
Fourier series representation
\end_layout
\begin_layout Standard
\begin_inset Formula
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\begin{equation}
Ш_{T}(t)=\sum_{n=-\infty}^{\infty}e^{2\pi int/T}\label{eq:1D Dirac comb Fourier series}
\end{equation}
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\end_inset
\end_layout
\begin_layout Subsubsection
Fourier transform
\end_layout
\begin_layout Standard
With unitary ordinary frequency Ft., i.e.
\end_layout
\begin_layout Standard
\begin_inset Formula
\[
\uoft f(\vect{\xi})\equiv\int_{\mathbb{R}^{n}}f(\vect x)e^{-2\pi i\vect x\cdot\vect{\xi}}\ud^{n}\vect x
\]
\end_inset
we have
\begin_inset Formula
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\begin{equation}
\uoft{Ш_{T}}(f)=\frac{1}{T}Ш_{\frac{1}{T}}(f)=\sum_{n=-\infty}^{\infty}e^{-i2\pi fnT}\label{eq:1D Dirac comb Ft ordinary freq}
\end{equation}
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\end_inset
and with unitary angular frequency Ft., i.e.
\begin_inset Formula
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\begin{equation}
\uaft f(\vect k)\equiv\frac{1}{\left(2\pi\right)^{n/2}}\int_{\mathbb{R}^{n}}f(\vect x)e^{-i\vect x\cdot\vect k}\ud^{n}\vect x\label{eq:Ft unitary angular frequency}
\end{equation}
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\end_inset
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we have (CHECK)
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\begin_inset Formula
\[
\uaft{Ш_{T}}(\omega)=\frac{\sqrt{2\pi}}{T}Ш_{\frac{2\pi}{T}}(\omega)=\frac{1}{\sqrt{2\pi}}\sum_{n=-\infty}^{\infty}e^{-i\omega nT}
\]
\end_inset
\end_layout
\begin_layout Subsection
Dirac comb for multidimensional lattices
\end_layout
\begin_layout Subsubsection
Definitions
\end_layout
\begin_layout Standard
Let
\begin_inset Formula $d$
\end_inset
be the dimensionality of the real vector space in question, and let
\begin_inset Formula $\basis u\equiv\left\{ \vect u_{i}\right\} _{i=1}^{d}$
\end_inset
denote a basis for some lattice in that space.
Let the corresponding lattice delta comb be
\begin_inset Formula
\[
\dc{\basis u}\left(\vect x\right)\equiv\sum_{n_{1}=-\infty}^{\infty}\ldots\sum_{n_{d}=-\infty}^{\infty}\delta\left(\vect x-\sum_{i=1}^{d}n_{i}\vect u_{i}\right).
\]
\end_inset
\end_layout
\begin_layout Standard
Furthemore, let
\begin_inset Formula $\rec{\basis u}\equiv\left\{ \rec{\vect u}_{i}\right\} _{i=1}^{d}$
\end_inset
be the reciprocal lattice basis, that is the basis satisfying
\begin_inset Formula $\vect u_{i}\cdot\rec{\vect u_{j}}=\delta_{ij}$
\end_inset
.
This slightly differs from the usual definition of a reciprocal basis,
here denoted
\begin_inset Formula $\recb{\basis u}\equiv\left\{ \recb{\vect u_{i}}\right\} _{i=1}^{d}$
\end_inset
, which satisfies
\begin_inset Formula $\vect u_{i}\cdot\recb{\vect u_{j}}=2\pi\delta_{ij}$
\end_inset
instead.
\end_layout
\begin_layout Subsubsection
Factorisation of a multidimensional lattice delta comb
\end_layout
\begin_layout Standard
By simple drawing, it can be seen that
\begin_inset Formula
\[
\dc{\basis u}(\vect x)=c_{\basis u}\prod_{i=1}^{d}\dc{}\left(\vect x\cdot\rec{\vect u_{i}}\right)
\]
\end_inset
where
\begin_inset Formula $c_{\basis u}$
\end_inset
is some numerical volume factor.
In order to determine
\begin_inset Formula $c_{\basis u}$
\end_inset
, let us consider only the
\begin_inset Quotes eld
\end_inset
zero tooth
\begin_inset Quotes erd
\end_inset
of the comb, leading to
\begin_inset Formula
\[
\delta^{d}(\vect x)=c_{\basis u}\prod_{i=1}^{d}\delta\left(\vect x\cdot\rec{\vect u_{i}}\right).
\]
\end_inset
From the scaling property of delta function,
\begin_inset Formula $\delta(ax)=\left|a\right|^{-1}\delta(x)$
\end_inset
, we get
\begin_inset Formula
\[
\delta^{d}(\vect x)=c_{\basis u}\prod_{i=1}^{d}\left\Vert \rec{\vect u_{i}}\right\Vert ^{-1}\delta\left(\vect x\cdot\frac{\rec{\vect u_{i}}}{\left\Vert \rec{\vect u_{i}}\right\Vert }\right).
\]
\end_inset
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\end_layout
\begin_layout Standard
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From the Osgood's book (p.
375):
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\end_layout
\begin_layout Standard
\begin_inset Formula
\[
\dc A(\vect x)=\frac{1}{\left|\det A\right|}\dc{}^{(d)}\left(A^{-1}\vect x\right)
\]
\end_inset
\begin_inset Note Note
status open
\begin_layout Plain Layout
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Applying both sides to a test function that is one at the origin, we get
\begin_inset Formula $c_{\basis u}=\prod_{i=1}^{d}\left\Vert \rec{\vect u_{i}}\right\Vert $
\end_inset
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SRSLY?, and hence
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\begin_inset Formula
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\begin{equation}
\dc{\basis u}(\vect x)=\prod_{i=1}^{d}\left\Vert \rec{\vect u_{i}}\right\Vert \dc{}\left(\vect x\cdot\rec{\vect u_{i}}\right).\label{eq:Dirac comb factorisation}
\end{equation}
\end_inset
\end_layout
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\end_inset
\end_layout
\begin_layout Subsubsection
Fourier series representation
\end_layout
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\begin_layout Standard
\begin_inset Note Note
status open
\begin_layout Plain Layout
Utilising the Fourier series for 1D Dirac comb
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:1D Dirac comb Fourier series"
\end_inset
and the factorisation
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:Dirac comb factorisation"
\end_inset
, we get
\begin_inset Formula
\begin{eqnarray*}
\dc{\basis u}(\vect x) & = & \prod_{j=1}^{d}\left\Vert \rec{\vect u_{j}}\right\Vert \sum_{n_{j}=-\infty}^{\infty}e^{2\pi in_{i}\vect x\cdot\rec{\vect u_{i}}}\\
& = & \left(\prod_{j=1}^{d}\left\Vert \rec{\vect u_{j}}\right\Vert \right)\sum_{\vect n\in\mathbb{Z}^{d}}e^{2\pi i\vect x\cdot\sum_{k=1}^{d}n_{k}\rec{\vect u_{k}}}.
\end{eqnarray*}
\end_inset
\end_layout
\end_inset
\end_layout
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\begin_layout Subsubsection
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Fourier transform (OK)
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\end_layout
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\begin_layout Standard
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From the Osgood's book https://see.stanford.edu/materials/lsoftaee261/chap8.pdf,
p.
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379
\end_layout
\begin_layout Standard
\begin_inset Formula
\[
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\uoft{\dc{\basis u}}\left(\vect{\xi}\right)=\left|\det\rec{\basis u}\right|\dc{\rec{\basis u}}^{(d)}\left(\vect{\xi}\right).
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\]
\end_inset
And consequently, for unitary/angular frequency it is
\end_layout
\begin_layout Standard
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\begin_inset Formula
\begin{eqnarray}
\uaft{\dc{\basis u}}\left(\vect k\right) & = & \frac{1}{\left(2\pi\right)^{\frac{d}{2}}}\uoft{\dc{\basis u}}\left(\frac{\vect k}{2\pi}\right)\nonumber \\
& = & \frac{\left|\det\rec{\basis u}\right|}{\left(2\pi\right)^{\frac{d}{2}}}\dc{\rec{\basis u}}^{(d)}\left(\frac{\vect k}{2\pi}\right)\nonumber \\
& = & \left(2\pi\right)^{\frac{d}{2}}\left|\det\rec{\basis u}\right|\dc{\recb{\basis u}}\left(\vect k\right)\nonumber \\
& = & \frac{\left|\det\recb{\basis u}\right|}{\left(2\pi\right)^{\frac{d}{2}}}\dc{\recb{\basis u}}\left(\vect k\right).\label{eq:Dirac comb uaFt}
\end{eqnarray}
\end_inset
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\end_layout
\begin_layout Standard
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\begin_inset Note Note
status open
\begin_layout Plain Layout
On the third line, we used the stretch theorem, getting
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\begin_inset Formula
\[
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\dc{\recb{\basis u}}\left(\vect k\right)=\dc{2\pi\rec{\basis u}}\left(\vect k\right)=\left(2\pi\right)^{-d}\dc{\rec{\basis u}}\left(\frac{\vect k}{2\pi}\right)
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\]
\end_inset
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\end_layout
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\end_inset
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\end_layout
\begin_layout Subsubsection
Convolution
\end_layout
\begin_layout Standard
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\begin_inset Formula
\[
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\left(f\ast\dc{\basis u}\right)(\vect x)=\sum_{\vect t\in\basis u\ints^{d}}f(\vect x-\vect t)
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\]
\end_inset
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\end_layout
\begin_layout Standard
\begin_inset Note Note
status open
\begin_layout Plain Layout
So, from the stretch theorem
\begin_inset Formula $\uoft{(f(A\vect x))}=\frac{1}{\left|\det A\right|}\uoft{f\left(A^{-T}\vect{\xi}\right)}=\left|\det A^{-T}\right|\uoft{f\left(A^{-T}\vect{\xi}\right)}$
\end_inset
\end_layout
\begin_layout Plain Layout
From
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:Dirac comb factorisation"
\end_inset
and
\begin_inset CommandInset ref
LatexCommand eqref
reference "eq:1D Dirac comb Ft ordinary freq"
\end_inset
\begin_inset Formula
\[
\uoft{\dc{\basis u}}(\vect{\xi})=\prod_{i=1}^{d}\left\Vert \rec{\vect u_{i}}\right\Vert \dc{}\left(\vect x\cdot\rec{\vect u_{i}}\right).
\]
\end_inset
\end_layout
\end_inset
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\end_layout
\begin_layout Standard
\begin_inset CommandInset bibtex
LatexCommand bibtex
bibfiles "Ewald summation,Tables"
options "plain"
\end_inset
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\end_layout
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\end_body
\end_document