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In mathematics, '''Lentz's algorithm''' is an [[algorithm]] to evaluate [[generalized continued fraction|continued fraction]]s, and was originally devised to compute tables of spherical [[Bessel function]]s.<ref name=":0">{{Cite
The version usually employed now is due to Thompson and Barnett.<ref name="
== History ==
The idea was introduced in 1973 by William J. Lentz<ref name=":0" /> and was simplified by him in 1982.<ref>{{Cite book|last=J.|first=Lentz, W.|url=http://worldcat.org/oclc/227549426|title=A Simplification of Lentz's Algorithm.|date=August 1982|publisher=Defense Technical Information Center|oclc=227549426}}</ref> Lentz suggested that calculating ratios of spherical Bessel functions of complex arguments can be difficult. He developed a new continued fraction technique for calculating the ratios of spherical Bessel functions of consecutive order. This method was an improvement compared to other methods because it started from the beginning of the continued fraction rather than the tail, had a built-in check for convergence, and was numerically stable. The original algorithm uses algebra to bypass a zero in either the numerator or denominator.
== Initial work ==
This theory was initially motivated by Lentz's need for accurate calculation of ratios of spherical Bessel function necessary for [[Mie scattering]]. He created a new continued fraction algorithm that starts from the beginning of the continued fraction and not at the tail-end. This eliminates guessing how many terms of the continued fraction are needed for convergence. In addition, continued fraction representations for both ratios of Bessel functions and spherical Bessel functions of consecutive order themselves can be computed with Lentz's algorithm.<ref
== Algorithm ==
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:<math>{f}_{3} = {b}_{0} + \frac{{a}_{1}}{{b}_{1} + \frac{{a}_{2}}{{b}_{2} + \frac{{a}_{3}}{{b}_{3}}}}</math>
etc., or using the [[
:<math>{f}_{n} = {b}_{0} + \underset{j = 1}\overset{n}\operatorname{K}\frac{{a}_{j}}{{b}_{j}
is the <math>n</math>th convergent to <math>f</math> then
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where <math>{A}_{n}</math> and <math>{B}_{n}</math> are given by the Wallis-Euler recurrence relations
:<
\begin{align}
{A}_{-1} & = 1 & {B}_{-1} & = 0\\
{A}_{0} & = {b}_{0} & {B}_{0} & = 1\\
\end{align}
</math>
▲:<math>{A}_{n} = {b}_{n} {A}_{n - 1} + {a}_{n} {A}_{n - 2}</math>
▲Lenz's method defines
:<math>{C}_{n} = \frac{{A}_{n}}{{A}_{n - 1}}</math>
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:<math>{D}_{n} = \frac{{B}_{n - 1}}{{B}_{n}}</math>
so that the <math>n</math>th convergent is <math>{f}_{n} = {C}_{n} {D}_{n} {f}_{n - 1}</math> with <math>{f}_{0} = \frac{{A}_{0}}{{B}_{0}} = {b}_{0}</math> and uses the recurrence relations
:<math>
\begin{align}
\end{align}
</math>
When the product <math>{C}_{n} {D}_{n}</math> approaches unity with increasing <math>n</math>, it is hoped that <math>{f}_{n}</math> has converged to <math>f</math>.<ref name="Numerical-Recipes">{{Cite book |last1=Press |first1=W.H. |title=Numerical Recipes: The Art of Scientific Computing |last2=Teukolsky |first2=S.A. |last3=Vetterling |first3=W.T. |last4=Flannery |first4=B. P. |publisher=Cambridge University Press |year=2007 |edition=3rd |pages=207–208}}</ref>▼
▲:<math>{C}_{0} = \frac{{A}_{0}}{{A}_{- 1}} = {b}_{0}</math>
Lentz's algorithm has the advantage of side-stepping an inconvenience of the Wallis-Euler relations, namely that the numerators <math>A_n</math> and denominators <math>B_n</math> are prone to grow or diminish very rapidly with increasing <math>n</math>. In direct numerical application of the Wallis-Euler relations, this means that <math>A_{n-1}</math>, <math>A_{n-2}</math>, <math>B_{n-1}</math>, <math>B_{n-2}</math> must be periodically checked and rescaled to avoid floating-point overflow or underflow.<ref name="Numerical-Recipes" />
== Thompson and Barnett modification ==
▲:<math>{D}_{n} = \frac{1}{{b}_{n} + {a}_{n} {D}_{n - 1}}</math>
In Lentz's original algorithm, it can happen that <math>{C}_{n} = 0</math>, resulting in division by zero at the next step. The problem can be remedied simply by setting <math>{C}_{n} = \varepsilon</math> for some sufficiently small <math>\varepsilon</math>. This gives <math>{C}_{n + 1} = {b}_{n + 1} + \frac{{a}_{n + 1}}{\varepsilon} = \frac{{a}_{n + 1}}{\varepsilon}</math> to within floating-point precision, and the product <math>{C}_{n} {C}_{n + 1} = {a}_{n + 1}</math> irrespective of the precise value of ε. Accordingly, the value of <math>{f}_{0} = {C}_{0} = {b}_{0}</math> is also set to <math>\varepsilon</math> in the case of <math>{b}_{0} = 0</math>.
Similarly, if the denominator in <math>{D}_{n} = \frac{1}{{b}_{n} + {a}_{n} {D}_{n - 1}}</math> is zero, then setting <math>{D}_{n} = \frac{1}{\varepsilon}</math> for small enough <math>\varepsilon</math> gives <math>{D}_{n} {D}_{n + 1} = \frac{1}{{a}_{n + 1}}</math> irrespective of the value of <math>\varepsilon</math>.<ref name="Thompson-and-Barnett" /><ref name="Numerical-Recipes" />
▲When the product <math>{C}_{n} {D}_{n}</math> approaches unity with increasing <math>n</math>, it is hoped that <math>{f}_{n}</math> has converged to <math>f</math>.<ref>{{Cite book |last1=Press |first1=W.H. |title=Numerical Recipes: The Art of Scientific Computing |last2=Teukolsky |first2=S.A. |last3=Vetterling |first3=W.T. |last4=Flannery |first4=B. P. |publisher=Cambridge University Press |year=2007 |edition=3rd |pages=207–208}}</ref>
== Applications ==
Lentz's algorithm was used widely in the late twentieth century. It was suggested that it doesn't have any rigorous analysis of error propagation. However, a few empirical tests suggest that it's at least as good as the other methods.
==References==
{{reflist}}
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