Non-convergent power series but good approximation?

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Discussion Overview

The discussion centers on the phenomenon of using non-convergent power series in quantum mechanics (QM) to achieve good approximations by considering only lower-order terms. Participants explore the mathematical implications and the nature of such approximations.

Discussion Character

  • Exploratory, Technical explanation, Conceptual clarification

Main Points Raised

  • One participant questions the mathematical basis for using non-convergent power series and seeks to understand whether this is a recognized area of mathematics.
  • Another participant suggests that power series can be viewed as polynomials, implying that approximating with low-order polynomials may justify the approach taken in QM.
  • A third participant proposes examining specific series, like Stirling's approximation, to illustrate how divergent series can still yield useful approximations by analyzing the behavior of terms.
  • It is noted that such approximations are referred to as "asymptotic expansions," which may provide a framework for understanding the phenomenon.

Areas of Agreement / Disagreement

Participants express varying levels of understanding and interpretation of the phenomenon, with no consensus on the generality or implications of using non-convergent power series in this context.

Contextual Notes

Some assumptions about the behavior of divergent series and their approximations remain unexamined, and the discussion does not resolve the broader mathematical implications of these approximations.

nonequilibrium
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Hello,

In my QM class we're using power series which don't converge but apparently still give a good approximation if one only takes the lower-order terms.

Is there any way to understand such a phenomenon? Is it a genuine area of mathematics? Or is it impossible to say something general on this phenomenon?
 
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^ Power series are just polynomials, right? So essentially you're approximating using low-order polynomials. I don't know anything about QM but that'd be my guess as to why what you're doing is reasonable.
 
It might help to look at the math for a particular series to see what is going on. For example http://en.wikipedia.org/wiki/Stirling's_approximation

Usually, the terms of the divergent series reduce in size to a minimum and then increase. If you take the sum up to the smallest term in the series, the relatve error, | approximate value - exact value | / exact value, may converge to 0, even though the absolute error | approximate value - exact value | diverges.
 

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