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In [[numerical analysis]], '''Chebyshev nodes''' are the roots of the [[Chebyshev polynomials|Chebyshev polynomial of the first kind]], which are [[algebraic number]]s. They are often used as nodes in [[polynomial interpolation]] because the resulting interpolation polynomial minimizes the effect of [[Runge's phenomenon]].{{fact|date=December 2013}}
 
==Definition==
 
For a given natural number ''n'', '''Chebyshev nodes''' in the interval [&minus;1, 1] are
 
:<math>x_i = \cos\left(\frac{2i-1}{2n}\pi\right) \mbox{ , } i=1,\ldots,n.</math>  
 
These are the roots of the [[Chebyshev polynomial of the first kind]] of degree n. For nodes over an arbitrary interval [''a'', ''b''] an [[affine transformation]] can be used:
 
:<math>{x}_i = \frac{1}{2} (a+b) - \frac{1}{2} (b-a) \cos\left(\frac{2i-1}{2n}\pi\right). </math>
 
==Approximation using Chebyshev nodes==
 
The Chebyshev nodes are important in [[approximation theory]] because they form a particularly good set of nodes for [[polynomial interpolation]]. Given a function ƒ on the interval <math>[-1,+1]</math> and <math>n</math> points <math>x_1,  x_2, \ldots , x_n,</math> in that interval, the interpolation polynomial is that unique polynomial <math>P_{n-1}</math> of degree <math>n-1</math> which has value <math>f(x_i)</math> at each point <math>x_i</math>.   The interpolation error at <math>x</math> is
 
:<math>f(x) - P_{n-1}(x) = \frac{f^{(n)}(\xi)}{n!} \prod_{i=1}^n (x-x_i) </math>
 
for some <math>\xi</math> in [&minus;1,&nbsp;1].<ref>{{harvtxt|Stewart|1996}}, (20.3)</ref> So it is logical to try to minimize
 
:<math>\max_{x \in [-1,1]} \left| \prod_{i=1}^n (x-x_i) \right|. </math>
 
This product Π is a ''[[monic polynomial|monic]]'' polynomial of degree ''n''. It may be shown that the maximum absolute value of any such polynomial is bounded below by 2<sup>1&minus;''n''</sup>. This bound is attained by the scaled Chebyshev polynomials 2<sup>1&minus;''n''</sup> ''T''<sub>''n''</sub>, which are also monic.  (Recall that |''T''<sub>''n''</sub>(''x'')|&nbsp;≤&nbsp;1 for ''x''&nbsp;∈&nbsp;[&minus;1,&nbsp;1].<ref>{{harvtxt|Stewart|1996}}, Lecture 20, &sect;14</ref>).   When interpolation nodes ''x''<sub>''i''</sub> are the roots of the ''T''<sub>''n''</sub>, the interpolation error satisfies
therefore
:<math>|f(x) - P_{n-1}(x)| \le \frac{1}{2^{n-1}n!} \max_{\xi \in [-1,1]} |f^{(n)} (\xi)|.</math>
<!-- To do: write about Lebesgue constant and connection with Fourier series -->
 
==Notes==
<references/>
 
==References==
*Burden, Richard L.; Faires, J. Douglas: ''Numerical Analysis'', 8th ed., pages 503–512, ISBN 0-534-39200-8.
*{{Citation | last1=Stewart | first1=Gilbert W. | title=Afternotes on Numerical Analysis | publisher=[[Society for Industrial and Applied Mathematics|SIAM]] | isbn=978-0-89871-362-6 | year=1996}}.
 
[[Category:Numerical analysis]]
[[Category:Algebraic numbers]]

Revision as of 20:40, 19 January 2014

In numerical analysis, Chebyshev nodes are the roots of the Chebyshev polynomial of the first kind, which are algebraic numbers. They are often used as nodes in polynomial interpolation because the resulting interpolation polynomial minimizes the effect of Runge's phenomenon.Template:Fact

Definition

For a given natural number n, Chebyshev nodes in the interval [−1, 1] are

These are the roots of the Chebyshev polynomial of the first kind of degree n. For nodes over an arbitrary interval [a, b] an affine transformation can be used:

Approximation using Chebyshev nodes

The Chebyshev nodes are important in approximation theory because they form a particularly good set of nodes for polynomial interpolation. Given a function ƒ on the interval and points in that interval, the interpolation polynomial is that unique polynomial of degree which has value at each point . The interpolation error at is

for some in [−1, 1].[1] So it is logical to try to minimize

This product Π is a monic polynomial of degree n. It may be shown that the maximum absolute value of any such polynomial is bounded below by 21−n. This bound is attained by the scaled Chebyshev polynomials 21−n Tn, which are also monic. (Recall that |Tn(x)| ≤ 1 for x ∈ [−1, 1].[2]). When interpolation nodes xi are the roots of the Tn, the interpolation error satisfies therefore

Notes

  1. Template:Harvtxt, (20.3)
  2. Template:Harvtxt, Lecture 20, §14

References

  • Burden, Richard L.; Faires, J. Douglas: Numerical Analysis, 8th ed., pages 503–512, ISBN 0-534-39200-8.
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