How to Integrate a Function with Steep Rise for Small x?

Click For Summary

Discussion Overview

The discussion revolves around the numerical integration of a function that exhibits a steep rise for small values of x, specifically from 0 to infinity. The function is characterized by different behaviors in the small and large x limits, with a focus on how to effectively handle the steep rise in the integration process.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant proposes using standard adaptive quadrature routines available in software like Maple, Mathematica, or MATLAB, suggesting that these can handle the integration effectively by adjusting mesh widths based on the behavior of the function.
  • Another participant expresses concern that adaptive quadrature may be too slow for their needs, considering the necessity to evaluate the integral many thousands of times, and suggests splitting the integral at x=1 and using a change of variable for x<1.
  • A later reply introduces a seemingly unrelated comment about the concept of steepness in integration, referencing a specific document, which may indicate a differing perspective on the topic.

Areas of Agreement / Disagreement

Participants do not appear to reach a consensus on the best method for integration, with differing opinions on the efficiency of adaptive quadrature versus alternative approaches such as splitting the integral.

Contextual Notes

There are assumptions regarding the behavior of the function at small and large x, as well as the effectiveness of various numerical integration techniques, which remain unresolved. The discussion does not clarify the implications of the steep rise on the choice of integration method.

Who May Find This Useful

This discussion may be useful for researchers or practitioners involved in numerical analysis, particularly those dealing with integrals of functions that exhibit steep behavior in certain regions.

DrDu
Science Advisor
Messages
6,423
Reaction score
1,004
I want to integrate a function numerically from 0 to infinity where for small x ##f(x)\sim x^{-5/2} \exp(-a/x)## and for large x ##f(x) \sim \exp(-bx)##.
How do I best treat the steep rise for small x?
 
Physics news on Phys.org
The integrand is not singular at ##x = 0## so you could use a standard routine for adaptive quadrature, as implemented in the standard software (Maple, Mathematica, MATLAB, Octave, etc.). This will select a smaller mesh width near ##x = 0## and allow for a larger mesh width for large ##x##.

If you insist on doing it yourself, it is not so hard to implement one of the usual rules (e.g. trapezoidal or Simpson's) adaptively through recursion. Most NA books discuss this. If you need references, let me know. To deal with the limit at infinity, just restrict to a large but finite interval. Because of your behavior for large ##x##, it will be easy to get a bound on the contribution to the error.
 
Thank you for your answer Krylov!
Adaptive quadrature is too slow for my purposes as I will have to evaluate integrals of this kind many thousand times. I think now about splitting the integral e.g. at x=1, use y=-a/x as new integration variable for x<1 and use Gauss-Laguerre integration on both regions.
 
  • Like
Likes   Reactions: S.G. Janssens
Steep is associated with googling "http://web.engr.illinois.edu/~rnandwa2/Reports/ECE521_Gear.pdfof integration" in my perception.
 

Similar threads

  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 11 ·
Replies
11
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 6 ·
Replies
6
Views
3K
  • · Replies 20 ·
Replies
20
Views
4K
  • · Replies 27 ·
Replies
27
Views
3K
  • · Replies 8 ·
Replies
8
Views
3K