How Do You Find the Maclaurin Polynomials for cos(πx)?

In summary, the Maclaurin polynomials of order n = 0, 1, 2, 3, and 4 for the function cos(∏x) are 1, 1, 1, 1, and 1, respectively. The pattern for the nth polynomial is that the odd values for k are 0. The general form for the nth polynomial is fk(x) = (∏)kcos(∏x)' and fk(0) = (∏)k(-1)k. The sigma notation for the nth polynomial is ##\sum_{k=0}^n\frac{(-1)^k\pi^{2k}x^{2k}}{(
  • #1
Mosaness
92
0
1. Find the Maclaurin polynomials of order n = 0, 1, 2, 3, and 4, and then find the nth MacLaurin polynomials for the function in sigma notation.

cos(∏x)





2. Here is what I did:
p0x = cos (0∏) = 1
p1x = cos(0∏) - ∏sin(0∏)x = 1
p2x = cos(0∏) - ∏sin(0∏)x -[itex]\frac{∏2(cos∏x)(x2)}{2!}[/itex](

and so on...

And the pattern that forms are that the odd values for k are 0.

So p0x = p1x
and p2x = p3x

etc etc.

fk(x) = (∏)kcos(∏x)'
and fk(0) = (∏)k(-1)k

As for the sigma notation:

Here is what I obtained:
Ʃnk = 0([itex]\frac{(∏2k(-1)k}{k!}[/itex](x)2k

According to the solution manual however, there is a n/2 on top of the sigma notation instead of a n.

I don't understand .
 
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  • #2
Mosaness said:
1. Find the Maclaurin polynomials of order n = 0, 1, 2, 3, and 4, and then find the nth MacLaurin polynomials for the function in sigma notation.

cos(∏x)





2. Here is what I did:
p0x = cos (0∏) = 1
p1x = cos(0∏) - ∏sin(0∏)x = 1
p2x = cos(0∏) - ∏sin(0∏)x -[itex]\frac{∏2(cos∏x)(x2)}{2!}[/itex](

and so on...

And the pattern that forms are that the odd values for k are 0.

So p0x = p1x
and p2x = p3x

etc etc.

fk(x) = (∏)kcos(∏x)'
and fk(0) = (∏)k(-1)k

No. That isn't right if k is odd.

As for the sigma notation:

Here is what I obtained:
##\sum_{k=0}^n\frac{(-1)^k\pi^{2k}x^{2k}}{k!}##
[Fixed your latex. Don't mix other symbols with tex]
According to the solution manual however, there is a n/2 on top of the sigma notation instead of a n.

I don't understand .

I think the only thing wrong with your final answer is you should have a ##(2k)!## in the denominator. Then note that your general sum gives only the even powers, which are the only non-zero terms. Your book's answer probably has something to do with indexing it differently. Hard to say without seeing it.
 

1. What are Maclaurin Polynomials?

Maclaurin Polynomials are a type of polynomial approximation used in calculus. They are named after Scottish mathematician Colin Maclaurin and are derived from the Taylor series, a mathematical tool used to express functions as an infinite sum of terms. Maclaurin Polynomials are often used to approximate a function at a specific point by using a finite number of terms from its Taylor series.

2. How are Maclaurin Polynomials calculated?

To calculate a Maclaurin Polynomial, you first need to find the derivatives of the function at the point of interest. Then, the coefficients of the polynomial are determined by plugging these derivatives into the formula for the Taylor series. The resulting polynomial will be an approximation of the original function at the point of interest.

3. What is the purpose of using Maclaurin Polynomials?

Maclaurin Polynomials are useful for approximating complicated functions that are difficult to evaluate directly. They allow us to find the value of a function at a specific point without having to evaluate an infinite series. They are also used in many areas of physics and engineering to model and analyze real-world systems.

4. Can Maclaurin Polynomials be used for any function?

Yes, Maclaurin Polynomials can be used for any differentiable function. However, the accuracy of the approximation depends on the smoothness of the function and the number of terms used in the polynomial. In some cases, using a larger number of terms may result in a more accurate approximation.

5. How do Maclaurin Polynomials relate to the concept of a Taylor series?

A Maclaurin Polynomial is a specific type of Taylor series, where the point of interest is set to be 0. This makes the calculation of the polynomial simpler, as the derivatives at 0 are often easier to find. However, as the number of terms used in the polynomial increases, it becomes a better approximation for the original function, just like a Taylor series.

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