Answer:Newton-Cotes Formula: Proving $\omega_j=\omega_{n-j}$ & $(b-a)$ Sum

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In summary, the question is asking to prove that for a given set of weights, it holds that $\omega_j=\omega_{n-j}$ and $\sum_j{\omega_j}=(b-a)$. The first proof involves considering odd functions in the interval from -1 to 1, while the second proof involves using a quadrature formula based on the constant function 1. The first proof uses the fact that the Lagrange polynomials are symmetric, while the second proof uses the fact that the Lagrange interpolation is a perfect interpolation.
  • #1
akerman
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I have been given this question and I have no idea how to answer it. I know that the answer will contain two small proofs where one of them uses quadrature formulae.
So I have been ask to show Show it holds that $\omega_j=\omega_{n-j}$ and that $\sum_j{\omega_j}=(b-a)$. Knowing that Newton cotes formulae is in the equi spaced points $x_i=a+ih$ with $h=(b-a)/n$ and $i=0,\dots,n$

Any idea how to properly solve this?
 
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  • #2
First proof should consider odd functions in the interval from -1 to 1, and I would like to show that ωj=ωn−j The second one should consider the quadrature formulae (constant funciton 1) based on that I would like to prove ∑jωj=(b−a) where ω is the weights. However I don't know how...
 
  • #3
I haven't answered before because I don't quite know what to make of your question.

Which formulae do you mean?
What do you mean by $\omega_j$?
 
  • #4
So in this context ωj are weights, actually I think its called a quadrature weight. So I would like to show that for corresponding weights it is true or it holds that ωj = ωj-1. I am sure for this proof odd functions need to be considered in the interval of -1 to 1. Does that explain it any better?
 
  • #5
I like Serena said:
I haven't answered before because I don't quite know what to make of your question.

Which formulae do you mean?
What do you mean by $\omega_j$?

We interpolate $f$ using a Lagrange interpolation polynomial of the form

$$
p_n(x)=\sum_{k=0}^nL_k(x)f(x_k).
$$

We obtain

$$
\int_a^bf(x)dx\approx \int_a^b\sum_{k=0}^nL_k(x)f(x_k)=\sum_{k=0}^nf(x_k)\int_a^bL_k(x)dx:=\sum_{k=0}^nf(x_k)\omega_k,
$$
where the $\omega_k:=\int_a^bL_k(x)dx$ are called integration weights.

So based on that I would like to prove that $ω_j=ω_{n−j}$ and the second proof should be proving that $\sum\limits_j ω_j=(b−a)$.

I like Serena do you know how it can be achieved?
 
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  • #6
akerman said:
We interpolate $f$ using a Lagrange interpolation polynomial of the form

$$
p_n(x)=\sum_{k=0}^nL_k(x)f(x_k).
$$

We obtain

$$
\int_a^bf(x)dx\approx \int_a^b\sum_{k=0}^nL_k(x)f(x_k)=\sum_{k=0}^nf(x_k)\int_a^bL_k(x)dx:=\sum_{k=0}^nf(x_k)\omega_k,
$$
where the $\omega_k:=\int_a^bL_k(x)dx$ are called integration weights.

So based on that I would like to prove that $ω_j=ω_{n−j}$ and the second proof should be proving that $\sum\limits_j ω_j=(b−a)$.

I like Serena do you know how it can be achieved?

The Lagrange polynomials $L_k(x)$ are completely independent of $f(x)$.
Since the interval has been split in equal subintervals, the construction of $L_k(x)$ is completely symmetric.
Therefore $L_k(x) = L_{n-k}(x)$, which in turn implies that $ω_j=ω_{n−j}$.
 
  • #7
I like Serena said:
The Lagrange polynomials $L_k(x)$ are completely independent of $f(x)$.
Since the interval has been split in equal subintervals, the construction of $L_k(x)$ is completely symmetric.
Therefore $L_k(x) = L_{n-k}(x)$, which in turn implies that $ω_j=ω_{n−j}$.

OK that makes sense.
What about the second proof which is ∑jωj=(b−a). I need to prove it considering the quadrature formulae (constant function 1)
 
  • #8
akerman said:
OK that makes sense.
What about the second proof which is ∑jωj=(b−a). I need to prove it considering the quadrature formulae (constant function 1)

If we fill in $f(x)=1$, we get in the left hand side:
$$\int_a^b 1\ dx = b-a$$
and on the right hand side:
$$\sum_{k=0}^n 1 \cdot \omega_k = \sum_j \omega_j$$

In other words:
$$b-a \approx \sum_j \omega_j$$

Furthermore, with $f(x)=1$ the Lagrange interpolation is a perfect interpolation.
That is:
$$f(x) = p_n(x)$$
So the approximation will actually be an equality.

So:
$$b-a = \sum_j \omega_j$$
which concludes the proof.
 

FAQ: Answer:Newton-Cotes Formula: Proving $\omega_j=\omega_{n-j}$ & $(b-a)$ Sum

What is the Newton-Cotes formula?

The Newton-Cotes formula is a method used for numerical integration, which is a way to approximate the area under a curve by dividing it into smaller, simpler shapes. It is named after mathematicians Isaac Newton and Roger Cotes, who developed the formula in the 18th century.

How does the Newton-Cotes formula work?

The formula works by dividing the interval of integration into several smaller subintervals and approximating the function over each subinterval using a polynomial. The area under the curve is then calculated by summing the areas of these approximating polynomials.

What is the significance of proving ωj = ωn-j in the Newton-Cotes formula?

This proof shows that the weights used in the formula are symmetrical, meaning that the same weight is used for both the left and right endpoints of each subinterval. This leads to a more accurate approximation of the area under the curve.

How is (b-a) sum used in the Newton-Cotes formula?

The (b-a) sum is used as a scaling factor in the Newton-Cotes formula. It is multiplied by the sum of the weights and function values to adjust for the size of the interval being integrated over.

What are some applications of the Newton-Cotes formula?

The Newton-Cotes formula is commonly used in numerical analysis and scientific computing to approximate integrals. It is also used in fields such as physics, engineering, and economics to solve various problems involving areas under curves.

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