Question about weights using Chebyshev polynomials as quadrature

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Discussion Overview

The discussion revolves around the use of Chebyshev polynomials in the Clenshaw–Curtis quadrature scheme for optimizing integrals, specifically addressing the calculation of weights when the number of collocation points is even. Participants explore the implications of the equations presented in the article regarding the weights assigned to collocation points.

Discussion Character

  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant questions the calculation of weights for even N, noting that the element corresponding to s=3 appears to be calculated twice, leading to confusion about the intended method in the article.
  • Another participant responds by asserting that the weights are defined correctly, emphasizing that the formula for w3 depends solely on N and s, and does not imply duplication.
  • A later reply clarifies that the notation used in the article is simply a way to avoid redundancy in writing, suggesting that ωN/2 is defined only once for even N.

Areas of Agreement / Disagreement

Participants express differing interpretations of the weight calculations, with some asserting clarity in the definitions while others remain uncertain about the implications of the notation used in the article. The discussion does not reach a consensus on the initial participant's concerns.

Contextual Notes

The discussion highlights potential ambiguities in the notation and definitions used in the article, particularly regarding the treatment of weights for collocation points when N is even. There are unresolved aspects concerning how these weights are derived and their implications for the optimization process.

confused_engineer
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Hello everyone.

I am studying this article since I am interested in optimization. The article makes use of Clenshaw–Curtis quadrature scheme to discretize the integral part of the cost function to a finite sum using Chebyshev polynomials.

The article differentiates between the case of odd and even number of collocation points. In equation 27 and 28 (fourth page), the case of N even is discussed. If N is even, then the N+1 collocation points, including 0, form a vector of odd length.

Then weights are calculated as ws=wN-s=... for s=1, 2, ..., N/2. Meanwhile, w0 and wN are calculated on a different way.

This in turn means that one of the elements is calculated twice, as shown in the following example:

N=6; N+1=7; N/2=3; s=1, 2, 3; N-s=6-1=5, 6-2=4, 6-3=3.

As you can see, the fourth element of the vector, number 3, appears two times. I find this weird. Can someone please tell me if I am understanding the article wrong or if this is intended to happen?

Thanks for reading.
Regards.
 
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I do not see where the problem is. For ##N=6## we have ##w_0=w_6=1/35## and then formulas for ##w_1=w_5##, ##w_2=w_4##, and ##w_3##. Since ##s=3= N-s=6-3## and the formula for ##w_3## only depends on the given number ##N## and ##s=3##, where is it defined twice?
 
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fresh_42 said:
I do not see where the problem is. For ##N=6## we have ##w_0=w_6=1/35## and then formulas for ##w_1=w_5##, ##w_2=w_4##, and ##w_3##. Since ##s=3= N-s=6-3## and the formula for ##w_3## only depends on the given number ##N## and ##s=3##, where is it defined twice?
First of all, thanks for answering my question.

I am confused because the article tallks about ωs and ωN-s and I find extrange that following the paper one arrives to ω33=4/N*... for this particular example.

Therefore, I understand from your answer that ω33=4/N*... is the weight of the fourth element of the vector. I thought that since I had ω33, the middle element might have twice the weight.

Sorry if I haven't expressed myself clearly.
Thanks again for your answer.
 
No, it was only a way to avoid writing an extra line for ##\omega_{N/2}##. ##N/2 = N-N/2## for even ##N## so it is only defined once.
 
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fresh_42 said:
No, it was only a way to avoid writing an extra line for ##\omega_{N/2}##. ##N/2 = N-N/2## for even ##N## so it is only defined once.
Then is all clear. Thank you very much.
 

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