Alternative Bound on a Double Geometric Series

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SUMMARY

The discussion centers on bounding a double power series using dominant functions derived from geometric series. The primary functions discussed are φ(x,y) = M / ((1 - x/x₀)(1 - y/y₀)) and ψ(x,y) = M / (1 - (x/x₀ + y/y₀)). The latter function is highlighted for its utility in proving the existence of analytic solutions to differential equations and integrable Pfaffians. The conversation emphasizes the need for a clearer understanding of why ψ is advantageous over φ, particularly in the context of Taylor series expansions.

PREREQUISITES
  • Understanding of double power series and their convergence
  • Familiarity with geometric series and their properties
  • Knowledge of Taylor series expansions
  • Basic concepts of analytic functions and differential equations
NEXT STEPS
  • Study the properties of double power series and their applications in analysis
  • Learn about the derivation and applications of geometric series in bounding functions
  • Explore Taylor series and their role in approximating functions
  • Investigate the theory behind Pfaffian forms and their integrability conditions
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Mathematicians, students of advanced calculus, and researchers in analysis who are interested in understanding the nuances of bounding functions in double power series and their implications in differential equations.

bolbteppa
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If |a_{mn}x_0^my_0^n| \leq M then a double power series f(x,y) = \sum a_{mn} x^m y^n can be 'bounded' by a dominant function of the form \phi(x,y) = \tfrac{M}{(1-\tfrac{x}{x_0})(1-\tfrac{y}{y_0})}, obviously derived from a geometric series argument. This is useful when proving that analytic solutions exist to y' = f(x,y) in the case that f is analytic.

A more useful dominant function when proving existence for an integrable pfaffian of the form dz = f_1dx_1 + f_2dx_2 is given by \psi(x,y) = \tfrac{M}{1-(\tfrac{x}{x_0}+\tfrac{y}{y_0})}. The coefficients of x^my^n in the taylor expansion of \psi is equal to the coefficients of x^my^n in the taylor expansion of M(\tfrac{x}{x_0}+\tfrac{y}{y_0})^{m+n}, and are at least equal to the coefficients of the taylor expansion of \phi.

My question is, how in the world does one gain any intuition for all of this? I can understand, derive & use \phi(x,y) = \tfrac{M}{(1-\tfrac{x}{x_0})(1-\tfrac{y}{y_0})} perfectly, however motivating, deriving & using the alternative function \psi(x,y) = \tfrac{M}{1-(\tfrac{x}{x_0}+\tfrac{y}{y_0})} is too arbitrary for me, is there a nice way to see the use of this second dominant function as obvious? Page 397 if needed
 
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The first thing that struck me is that

##\big(1 - \dfrac{x}{x_0})\big(1 - \dfrac{y}{y_0})## differs by only 1 term, ##xy/x_0y_0##, from ##1 - \big(\dfrac{x}{x_0} +\dfrac{y}{y_0})##. So your ##\phi## and ##\psi## are not that different.

I would guess that someone needed the second formulation, hoped it would work, and then found a convincing argument that it is okay (as per your notes re Taylor's series).

A lot of mathematics looks unintuitive in this way when it is presented as a fait accompli. The book would be more helpful if written to show you an example of why the second bound is useful in some cases, and then guided you through an explanation of why you can do it that way. Depending on x and ##x_0## the missing term could be either positive or negative, so you need some non-trivial explanation of why the second bound works.

Maybe there is a more intuitive explanation that I don't see. Maybe not.
 

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