Multiplying and dividing macularin question

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SUMMARY

The discussion focuses on the multiplication and division of macularin series to derive polynomial terms. It establishes that for exact values, all terms of the series must be included, while for approximations, truncation is permissible based on desired accuracy. The product of two series is defined through the convolution of their coefficients, while division requires careful handling of coefficients to avoid singularities, particularly ensuring that the leading coefficient of the denominator is non-zero. The discussion also highlights the implications of series starting at different powers and the resulting behavior of the quotient series.

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When you multiply or divide macularin series to find, let's say, the first 3 nonzero terms of the polynomial, how many terms of each series should be included in the multipication/division?
 
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All of them if you want an exact value.

If you are looking for an approximation, then you can truncate numerator and/or denominator. But how many terms you need to keep depends upon what accuracy you want.
 
Suppose you have the two series
[tex]f(x)=\sum_{k=0}^{\infty} a_k x^k, \quad g(x)=\sum_{k=0}^{\infty} b_k x^k.[/tex]
Then the product is
[tex]f(x) g(x)=\sum_{j,k=0}^{\infty} a_j b_k x^{j+k}.[/tex]
Now within the common range of convergence you are allowed to interchange the terms as you like. So we can reorder the zeros in powers [itex]n=j+k[/itex]. At fixed [itex]n[/itex], given [itex]j \in \{0,1,\ldots n\}[/itex][/tex], [itex]k=n-j[/itex]. This means that
[tex]f(x) g(x)=\sum_{n=0}^{\infty} x^n \sum_{j=0}^{n} a_j b_{n-j}.[/tex]
That means to get the expansion of [itex]f g[/itex] to order [itex]n[/itex] you need the coefficients of the original functions to the same order, [itex]n[/itex].

For division you set
[tex]\frac{f(x)}{g(x)}=\sum_{k=0}^{\infty} c_k x^k.[/tex]
Then you have
[tex]f(x)=\sum_{n=0}^{\infty} a_n x^n=g(x) \sum_{k=0}^{\infty} c_k x^k=\sum_{j=0}^{\infty} b_j x^k \sum_{k=0}^{\infty} c_k x^k=\sum_{n=0}^{\infty} x^n \sum_{j=0}^{n} b_j c_{n-j}.[/tex]
Comparing coefficients you get the set of equations
[tex]a_n=\sum_{j=0}^{n} b_j c_{n-j},[/tex]
from which you can recursively determine the [itex]c_k[/itex].

Starting from [itex]n=0[/itex] you get
[tex]a_0=b_0 c_0 \; \Rightarrow c_0=\frac{a_0}{b_0},[/tex]
then for [itex]n=1[/itex]
[tex]a_1=b_0 c_1+b_1 c_0 \; \Rightarrow c_1=\frac{a_1-b_1 c_0}{b_0}[/tex]
or generally
[tex]a_n=\sum_{j=0}^{n} b_j c_{n-j} \; \Rightarrow \; c_n=\frac{a_n-\sum_{j=1}^{n} b_j c_{n-j}}{b_0}.[/tex]
As you see, you must have [itex]b_0 \neq 0[/itex] in order to have a well-defined power series for the fraction [itex]f/g[/itex]. That's clear, because if [itex]b_0=0[/itex] then [itex]g(0)=0[/itex], and the function [itex]f/g[/itex] has a singularity at [itex]x=0[/itex].

If the power series of [itex]g[/itex] starts at the power [itex]n_0[/itex], i.e., if [itex]c_k=0[/itex] for [itex]0 \leq k<n_0[/itex] and [itex]c_{n_0} \neq 0[/itex], then you can write
[tex]g(x)=x^{n_0} \sum_{k=0}^{\infty} \tilde{b}_{k} x^k=x^{n_0} \tilde{g}(x), \quad \tilde{b}_k=b_{n_0+k}[/tex]
and use the above considerations for
[tex]\frac{f(x)}{\tilde{g}(x)}=\sum_{k=0}^{\infty} \tilde{c}_k x^k.[/tex]
Then you get recursively the [itex]\tilde{c}_n[/itex] as explained above and then you finally find
[tex]\frac{f(x)}{g(x)}=\frac{1}{x^{n_0}} \sum_{k=0}^{\infty} \tilde{c}_k x^k.[/tex]
That means that in this case [itex]f/g[/itex] has a pole of order [itex]n_0[/itex]. The convergence radius of the corresponding Laurent series is still given by the smaller of the convergence radii [itex]r_{<}[/itex] of the power series expansion of [itex]f[/itex] and [itex]g[/itex] around 0, i.e., the Laurent series is convergent for [itex]0<|x|<r_{<}[/itex].
 

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