Confused about computing Laurent series

In summary: However, in summary, we can write a Laurent series for each pole of an analytic function and use a Taylor series expansion to get the coefficients.
  • #1
quasar_4
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I am very confused about how to actually compute a Laurent series. Given an analytic function, we can write down its poles. Then, if I understand correctly, we have to write a Laurent series for each pole. What I'm confused about is the actual mechanics of writing one down. I know that for f(z) with pole at f(z0) that we can write

f(z) = (a_p)/(z-z0)^p + ...+ a_1/(z-z0) + a0 + a1(z-z0) + ...

what I don't understand is how to get the a[tex]^{n}[/tex] coefficients. I know we have the formula a[tex]_{n}[/tex] = (1/2*[tex]\pi[/tex]*i) * [tex]\oint[/tex][tex]\frac{f(z)}{(z-z0)^{n+1}}[/tex] dz, but all the examples I have just pop out the series (no one is doing any integrals). I must be missing something obvious!

If I can put it into the form f(z) = 1/(1+z) then I can use a geometric series to write this out...

but what if it's something like 1/z?
 
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  • #2
?? 1/z is already of that form! 1/z = z-1 so a-1= 1 and all the other ans are 0.
 
  • #3
oh no, then I am really confused about what's going on. In general, how is a Taylor series used in a Laurent series? Maybe that will help me get started. In the meantime, I guess I'm going to go read through that chapter again... :(
 
  • #4
A function is "analytic" at a point if and only if its Taylor's series at that point exists and converges to the function in some neighborhood of that point. A function, f(z), has a "pole of order n at z0" if and only if (z- z0)nf(z) is analytic at z0 but no lower power of z is. Write znf(z) as a Taylor's series and divide each term by zn to get the Laurent series for f(z).

For example, if f(z)= z-1, then zf(z)= 1 is analytic (and that IS its "Taylor's series: 1+ 0z+ 0z2+ ...) so f(z) has a pole of order 1 at 0 and the Laurent series for f(z) is 1/z+ 0+ 0z+...
 
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  • #5
oh, I see. Then when I am starting a problem of this type, it should perhaps be necessary tp start by checking analycity of the function. Once I've found the poles, I should be able to use a Taylor series exp. to write the Laurent series, then find the residue...

I think it is beginning to make sense, at least computationally. It might take a few days of computing these things before the theory part all sinks in.
 

Related to Confused about computing Laurent series

1. What is a Laurent series?

A Laurent series is a type of mathematical series that represents a function as an infinite sum of terms with positive and negative powers of a variable. It is a generalization of a Taylor series and is useful for representing functions with poles or branch points.

2. How is a Laurent series different from a Taylor series?

A Taylor series represents a function as an infinite sum of terms with only positive powers of a variable, while a Laurent series includes both positive and negative powers. Additionally, a Taylor series is centered around a point, while a Laurent series can be centered around a point or a discontinuity of the function.

3. When is it necessary to use a Laurent series?

A Laurent series is necessary when a function has singularities, such as poles or branch points, that cannot be represented by a Taylor series. It is also useful for representing functions with infinitely many zeros, such as the Riemann zeta function.

4. How can I compute a Laurent series?

To compute a Laurent series, you can use the formula for the coefficients of a Laurent series, which involves taking derivatives and evaluating the function at the center point. Alternatively, you can use software programs such as Mathematica or Wolfram Alpha, which have built-in functions for computing Laurent series.

5. What are some real-world applications of Laurent series?

Laurent series are used in various fields of science and engineering, such as physics, chemistry, and electrical engineering. They are particularly useful in analyzing systems with resonance, such as electrical circuits and mechanical oscillators. They are also used in signal processing and image processing to represent signals and images as a sum of different frequencies.

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