## From Gaussian Quadrature to Chebyshev Quadrature

Hi,

I dont know if Gauss-Chebyshev Quadrature is the same of Chebyshev Quadrature.
The only good information that i found was from Wolfram:

And there is write Chebyshev Quadrature is a simplification of Gaussian quadrature. So here is my question: How can i simplify from Gaussian Quadrature to Chebyshev Quadrature?
 PhysOrg.com science news on PhysOrg.com >> Galaxies fed by funnels of fuel>> The better to see you with: Scientists build record-setting metamaterial flat lens>> Google eyes emerging markets networks

Recognitions:
You ask an interesting question about terminology. I don't know the answer, but I think it would help to state the question explicitly rather than expecting readers to follow links.

The Wikipedia article on Gaussian Quadrature states:

 An n-point Gaussian quadrature rule, named after Carl Friedrich Gauss, is a quadrature rule constructed to yield an exact result for polynomials of degree 2n − 1 or less by a suitable choice of the points $x_i$ and weights $w_i$ for i = 1,...,n. The domain of integration for such a rule is conventionally taken as [−1, 1], so the rule is stated as $\int_{-1}^{1} f(x) dx \approx \sum_{i=1}^n w_i f(x_i)$
 ...if the integrated function can be written as $f(x) = W(x) g(x)$, where $g(x)$ is approximately polynomial, and $W(x)$ is known, then there are alternative weights ${w'}_i$ such that $\int_{-1}^1 f(x)\,dx = \int_{-1}^1 W(x) g(x)\,dx \approx \sum_{i=1}^n w_i' g(x_i)$ Common weighting functions include $W(x)=(1-x^2)^{-1/2}$ (Chebyshev–Gauss)....

The question is whether that definition is equivalent to the one on the Wolfram site which defines Chebyshev Quadrature as:

 A Gaussian quadrature-like formula for numerical estimation of integrals. It uses weighting function W(x)=1 in the interval [-1,1] and forces all the weights to be equal. The general formula is $\int_{-1}^1 f(x)dx=\frac{2}{n} \sum_{i=1}^n f(x_i)$ where the abscissas x_i are found by taking terms up to $y^n$ in the Maclaurin series of $s_n(y)=exp(1/2n[-2+ln(1-y)(1-\frac{1}{y})+ln(1+y)(1+\frac{1}{y})])$ and then defining $G_n(x)=x^n s_n(\frac{1}{x})$ The roots of $G_n(x)$ then give the abscissas.
I had to do the LaTex manually instead of a straight cut-and-past. I hope I haven't introduced any typos.
 Recognitions: Science Advisor The most plausible definition I found for Chebyshev quadrature is on page 2 of this PDF of lecture notes: http://www.google.com/url?sa=t&rct=j...ZdaFdA&cad=rja It says Chebyshev quadrature is based on using Chebyshev polynomials.

## From Gaussian Quadrature to Chebyshev Quadrature

Thanks Stephen Tashi.

Finally i found the proof. Chebyshev quadrature is really hard to find because always when you google it other similar topics appears. So the book i found this information is: Introduction to Numerical Analysis - F. B. Hildebrand