Detecting Intersections of Functions: Is There a Foolproof Method?

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SUMMARY

The discussion focuses on algorithms for detecting intersections of functions, specifically addressing both finite and infinite points of intersection within defined ranges. The Newton-Raphson method is highlighted as a numerical approach for finding zeros of the difference between two functions, although it is noted that this method is effective only for well-behaved functions. The challenge of determining intersections when rotating plots around a third axis, such as in polygon edge graphs, is also mentioned, emphasizing the complexity of the problem without a universal solution.

PREREQUISITES
  • Understanding of numerical methods, specifically Newton-Raphson for root finding.
  • Familiarity with function analysis and properties of intersections.
  • Knowledge of graph theory, particularly in relation to polygon edges.
  • Basic concepts of calculus, including derivatives and limits.
NEXT STEPS
  • Research advanced numerical methods for root finding beyond Newton-Raphson.
  • Explore algorithms for detecting intersections in computational geometry.
  • Learn about function behavior analysis in calculus to identify conditions for intersections.
  • Investigate 3D graphing techniques and their implications for intersection detection.
USEFUL FOR

Mathematicians, computer scientists, and engineers involved in computational geometry, algorithm development, and those seeking to optimize function intersection detection methods.

Physt
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Does anyone know of an algorithm to detect the intersection of any two functions - both for individual points within a fixed range of x values and determining whether or not total points of intersection are finite or infinite over an infinite range of x values? Also, is this possible to do this when you rotate the plot around a third axis (such as using a graph for each edge of a polygon).
 
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Well, the simplest is probably to take the difference of the functions and find its zeros, by some numerical method such as Newton-Raphson. It works only for reasonably nice functions, though. There is certainly no general algorithm that always works.
 

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