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1\section[Ion Scattering]{Ion Scattering}
2
3The necessity of accurately computing the characteristics of interatomic
4scattering arises in many disciplines in which energetic ions pass
5through materials. Traditionally, solutions to this problem not involving
6hadronic interactions have been dominated by the multiple scattering,
7which
8is reasonably successful, but not very flexible. In particular, it
9is relatively difficult to introduce into such a system a particular
10screening function which has been measured for a specific atomic pair,
11rather than the universal functions which are applied.
12 In many problems
13of current interest, such as the behavior of semiconductor device
14physics in a space environment, nuclear reactions, particle showers,
15and other effects are critically important in modeling the full details
16of ion transport. The process $G4ScreenedNuclearRecoil$ provides
17simulation of ion elastic scattering \cite{ion_scat_model}.
18
19\subsection{Method}
20
21The method used in this computation is a variant of a subset of the
22method described in Ref.\cite{MendenhallWellerXSection}.
23A very short recap of the basic material is included here. The scattering
24of two atoms from each other is assumed to be a completely classical
25process, subject to an interatomic potential described by a potential
26function\begin{equation}
27V(r)=\frac{Z_{1}Z_{2}e^{2}}{r}\phi\left(\frac{r}{a}\right)\label{VR_eqn}\end{equation}
28where $Z_{1}$ and $Z_{2}$ are the nuclear proton numbers, $e^{2}$
29is the electromagnetic coupling constant ($q_{e}^{2}/4\pi\epsilon_{0}$
30in SI units), $r$ is the inter-nuclear separation, $\phi$ is the
31screening function describing the effect of electronic screening of
32the bare nuclear charges, and $a$ is a characteristic length scale
33for this screening. In most cases, $\phi$ is a universal function
34used for all ion pairs, and the value of $a$ is an appropriately
35adjusted length to give reasonably accurate scattering behavior. In
36the method described here, there is no particular need for a universal
37function $\phi$, since the method is capable of directly solving
38the problem for most physically plausible screening functions. It
39is still useful to define a typical screening length $a$ in the calculation
40described below, to keep the equations in a form directly comparable
41with our previous work even though, in the end, the actual value is
42irrelevant as long as the final function $\phi(r)$ is correct. From
43this potential $V(r)$ one can then compute the classical scattering
44angle from the reduced center-of-mass energy $\varepsilon\equiv E_{c}a/Z_{1}Z_{2}e^{2}$
45(where $E_{c}$ is the kinetic energy in the center-of-mass frame)
46and reduced impact parameter $\beta\equiv b/a$\begin{equation}
47\theta_{c}=\pi-2\beta\int_{x_{{\scriptscriptstyle 0}}}^{\infty}f(z)\, dz/z^{2}\label{theta_eqn}\end{equation}
48where\begin{equation}
49f(z)=\left(1-\frac{\phi(z)}{z\,\varepsilon}-\frac{\beta^{2}}{z^{2}}\right)^{-1/2}\label{fz_eqn}\end{equation}
50and $x_{{\scriptscriptstyle 0}}$ is the reduced classical turning
51radius for the given $\varepsilon$ and $\beta$.
52
53The problem, then, is reduced to the efficient computation of this
54scattering integral. In our previous work, a great deal of analytical
55effort was included to proceed from the scattering integral to a full
56differential cross section calculation, but for application in a Monte-Carlo
57code, the scattering integral $\theta_{c}(Z_{1},\, Z_{2},\, E_{c},\, b)$
58and an estimated total cross section $\sigma_{{\scriptscriptstyle 0}}(Z_{1},\, Z_{2},\, E_{c})$
59are all that is needed. Thus, we can skip algorithmically forward
60in the original paper to equations 15-18 and the surrounding discussion
61to compute the reduced distance of closest approach $x_{{\scriptscriptstyle 0}}$.
62This computation follows that in the previous work exactly, and will
63not be reintroduced here.
64
65For the sake of ultimate accuracy in this algorithm, and due to the
66relatively low computational cost of so doing, we compute the actual
67scattering integral (as described in equations 19-21 of \cite{MendenhallWellerXSection})
68using a Lobatto quadrature of order 6, instead of the 4th order method
69previously described. This results in the integration accuracy exceeding
70that of any available interatomic potentials in the range of energies
71above those at which molecular structure effects dominate, and should
72allow for future improvements in that area. The integral $\alpha$
73then becomes (following the notation of the previous paper)
74\begin{equation}
75\alpha\approx\frac{1+\lambda_{{\scriptscriptstyle 0}}}{30}+\sum_{i=1}^{4}w'_{i}\, f\left(\frac{x_{{\scriptscriptstyle 0}}}{q_{i}}\right)\label{alpha_eq}\end{equation}
76where
77\begin{equation}
78\lambda_{{\scriptscriptstyle 0}}=\left(\frac{1}{2}+\frac{\beta^{2}}{2\, x_{{\scriptscriptstyle 0}}^{2}}-\frac{\phi'(x_{{\scriptscriptstyle 0}})}{2\,\varepsilon}\right)^{-1/2}\label{lambda_eqn}\end{equation}
79\\
80$w'_{i}\in${[}0.03472124, 0.1476903, 0.23485003, 0.1860249] \\
81$q_{i}\in${[}0.9830235, 0.8465224, 0.5323531, 0.18347974]\\
82Then \\
83\begin{equation}
84\theta_{c}=\pi-\frac{\pi\beta\alpha}{x_{{\scriptscriptstyle 0}}}\label{thetac_alpha_eq}\end{equation}
85
86
87The other quantity required to implement a scattering process
88is the total scattering cross section $\sigma_{{\scriptscriptstyle 0}}$
89for a given incident ion and a material through which the ion is propagating.
90This value requires special consideration for a process such as screened
91scattering. In the limiting case that the screening function is unity,
92which corresponds to Rutherford scattering, the total cross section
93is infinite. For various screening functions, the total cross section
94may or may not be finite. However, one must ask what the intent of
95defining a total cross section is, and determine from that how to
96define it.
97
98In Geant4, the total cross section is used to determine a mean-free-path
99$l_{\mu}$ which is used in turn to generate random transport distances
100between discrete scattering events for a particle. In reality, where
101an ion is propagating through, for example, a solid material, scattering
102is not a discrete process but is continuous. However, it is a useful,
103and highly accurate, simplification to reduce such scattering to a
104series of discrete events, by defining some minimum energy transfer
105of interest, and setting the mean free path to be the path over which
106statistically one such minimal transfer has occurred. This approach
107is identical to the approach developed for the original TRIM code
108\cite{TRIM1980}. As long as the minimal interesting energy transfer
109is set small enough that the cumulative effect of all transfers smaller
110than that is negligible, the approximation is valid. As long as the
111impact parameter selection is adjusted to be consistent with the selected
112value of $l_{\mu}$, the physical result isn't particularly sensitive
113to the value chosen.
114
115Noting, then, that the actual physical result isn't very sensitive
116to the selection of $l_{\mu},$ one can be relatively free about defining
117the cross section $\sigma_{{\scriptscriptstyle 0}}$ from which $l_{\mu}$
118is computed. The choice used for this implementation is fairly simple.
119Define a physical cutoff energy $E_{min}$ which is the smallest energy
120transfer to be included in the calculation. Then, for a given incident
121particle with atomic number $Z_{1}$, mass $m_{1}$, and lab energy
122$E_{inc}$, and a target atom with atomic number $Z_{2}$ and mass
123$m_{2}$, compute the scattering angle $\theta_{c}$ which will transfer
124this much energy to the target from the solution of\begin{equation}
125E_{min}=E_{inc}\,\frac{4\, m_{1}\, m_{2}}{(m_{1}+m_{2})^{2}}\,\sin^{2}\frac{\theta_{c}}{2}\label{recoil_kinematics}\end{equation}.
126Then, noting that $\alpha$ from eq. \ref{alpha_eq} is a number very close to unity, one can solve for an approximate
127impact parameter $b$ with a single root-finding operation to find the classical turning point.
128Then, define the total cross section to be $\sigma_{{\scriptscriptstyle 0}}=\pi b^{2}$,
129the area of the disk inside of which the passage of an ion will cause
130at least the minimum interesting energy transfer. Because this process
131is relatively expensive, and the result is needed extremely frequently,
132the values of $\sigma_{{\scriptscriptstyle 0}}(E_{inc})$ are precomputed
133for each pairing of incident ion and target atom, and the results
134cached in a cubic-spline interpolation table. However, since the actual result isn't very critical, the
135cached results can be stored in a very coarsely sampled table without
136degrading the calculation at all, as long as the values of the $l_{\mu}$
137used in the impact parameter selection are rigorously consistent with
138this table.
139
140The final necessary piece of the scattering integral calculation is
141the statistical selection of the impact parameter $b$ to be used
142in each scattering event. This selection is done following the original
143algorithm from TRIM, where the cumulative probability distribution
144for impact parameters is \begin{equation}
145P(b)=1-\exp\left(\frac{-\pi\, b^{2}}{\sigma_{{\scriptscriptstyle 0}}}\right)\label{cum_prob}\end{equation}
146where $N\,\sigma_{{\scriptscriptstyle 0}}\equiv1/l_{\mu}$ where $N$
147is the total number density of scattering centers in the target material
148and $l_{\mu}$ is the mean free path computed in the conventional
149way. To produce this distribution from a uniform random variate $r$
150on (0,1], the necessary function is\begin{equation}
151b=\sqrt{\frac{-\log r}{\pi\, N\, l_{\mu}}}\label{sampling_func}\end{equation}
152This choice of sampling function does have the one peculiarity that
153it can produce values of the impact parameter which are larger than
154the impact parameter which results in the cutoff energy transfer,
155as discussed above in the section on the total cross section, with
156probability $1/e$. When this occurs, the scattering event is not
157processed further, since the energy transfer is below threshold. For
158this reason, impact parameter selection is carried out very early
159in the algorithm, so the effort spent on uninteresting events is minimized.
160
161The above choice of impact sampling is modified when the mean-free-path
162is very short. If $\sigma_{{\scriptscriptstyle 0}}>\pi\left(\frac{l}{2}\right)^{2}$
163where $l$ is the approximate lattice constant of the material, as
164defined by $l=N^{-1/3}$, the sampling is replaced by uniform sampling
165on a disk of radius $l/2$, so that\begin{equation}
166b=\frac{l}{2}\sqrt{r}\label{flat_sampling}\end{equation}
167This takes into account that impact parameters larger than half the
168lattice spacing do not occur, since then one is closer to the adjacent
169atom. This also derives from TRIM.
170
171One extra feature is included in our model, to accelerate the production
172of relatively rare events such as high-angle scattering. This feature
173is a cross-section scaling algorithm, which allows the user access
174to an unphysical control of the algorithm which arbitrarily scales
175the cross-sections for a selected fraction of interactions. This is
176implemented as a two-parameter adjustment to the central algorithm.
177The first parameter is a selection frequency $f_{h}$ which sets what
178fraction of the interactions will be modified. The second parameter
179is the scaling factor for the cross-section. This is implemented by,
180for a fraction $f_{h}$ of interactions, scaling the impact parameter
181by $b'=b/\sqrt{scale}$. This feature, if used with care so that it
182does not provide excess multiple-scattering, can provide between 10
183and 100-fold improvements to event rates. If used without checking
184the validity by comparing to un-adjusted scattering computations,
185it can also provide utter nonsense.
186
187
188\subsection{Implementation Details}
189
190\label{Lobatto}The coefficients for the summation to approximate
191the integral for $\alpha$ in eq.(\ref{alpha_eq}) are derived from
192the values in Abramowitz \& Stegun \cite{AbramowitzStegunLobatto},
193altered to make the change-of-variable used for this integral. There
194are two basic steps to the transformation. First, since the provided
195abscissas $x_{i}$ and weights $w_{i}$ are for integration on {[}-1,1],
196with only one half of the values provided, and in this work the integration
197is being carried out on {[}0,1], the abscissas are transformed as:\begin{equation}
198y_{i}\in\left\{ \frac{1\mp x_{i}}{2}\right\} \label{as_yxform}\end{equation}
199 Then, the primary change-of-variable is applied resulting in:\begin{eqnarray}
200q_{i} & = & \cos\frac{\pi\, y_{i}}{2}\label{q_xform}\\
201w'_{i} & = & \frac{w_{i}}{2}\sin\frac{\pi\, y_{i}}{2}\label{wprime_xform}\end{eqnarray}
202 except for the first coefficient $w'_{1}$where the $\sin()$ part
203of the weight is taken into the limit of $\lambda_{{\scriptscriptstyle 0}}$
204as described in eq.(\ref{lambda_eqn}). This value is just $w'_{1}=w_{1}/2$.
205
206\subsection{Status of this document}
207 06.12.07  created by V. Ivanchenko from paper of M.H.~Mendenhall and R.A.~Weller\\
20806.12.07  further edited by M. Mendenhall to bring contents of paper up-to-date with current implementation.
209
210\begin{latexonly}
211
212\begin{thebibliography}{99}
213
214\bibitem{ion_scat_model}
215M.H.~Mendenhall, R.A.~Weller, An algorithm for computing screened Coulomb
216scattering in Geant4, {\em Nucl. Instr. Meth. B 227 (2005) 420.}
217
218\bibitem{MendenhallWellerXSection}
219M.H.~Mendenhall, R.A.~Weller, Algorithms for the rapid computation of
220  classical cross sections for screened coulomb collisions,
221{\em Nucl. Instr. Meth. in Physics Res. B58 (1991) 11.}
222
223\bibitem{TRIM1980}
224J.P.~Biersack, L.G.~Haggmark, A Monte Carlo computer program for the
225  transport of energetic ions in amorphous targets,
226{\em Nucl. Instr. Meth. in Physics Res. 174 (1980) 257.}
227
228\bibitem{AbramowitzStegunLobatto}
229M.~Abramowitz, I.~Stegun (Eds.), Handbook of Mathematical Functions,
230{\em Dover, New York, 1965, pp. 888, 920.}
231
232\end{thebibliography}
233
234\end{latexonly}
235
236\begin{htmlonly}
237
238\subsection{Bibliography}
239
240\begin{enumerate}
241
242\item
243M.H.~Mendenhall, R.A.~Weller, An algorithm for computing screened Coulomb
244scattering in Geant4, {\em Nucl. Instr. Meth. B 227 (2005) 420.}
245
246\item
247M.H.~Mendenhall, R.A.~Weller, Algorithms for the rapid computation of
248  classical cross sections for screened coulomb collisions,
249{\em Nucl. Instr. Meth. in Physics Res. B58 (1991) 11.}
250
251\item
252J.P.~Biersack, L.G.~Haggmark, A Monte Carlo computer program for the
253  transport of energetic ions in amorphous targets,
254{\em Nucl. Instr. Meth. in Physics Res. 174 (1980) 257.}
255
256\item
257M.~Abramowitz, I.~Stegun (Eds.), Handbook of Mathematical Functions,
258{\em Dover, New York, 1965, pp. 888, 920.}
259
260\end{enumerate}
261
262\end{htmlonly}
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