mscroggs.co.uk
mscroggs.co.uk

subscribe

Blog

 2018-09-13 
This is a post I wrote for round 2 of The Aperiodical's Big Internet Math-Off 2018. As I went out in round 1 of the Big Math-Off, you got to read about the real projective plane instead of this.
Polynomials are very nice functions: they're easy to integrate and differentiate, it's quick to calculate their value at points, and they're generally friendly to deal with. Because of this, it can often be useful to find a polynomial that closely approximates a more complicated function.
Imagine a function defined for \(x\) between -1 and 1. Pick \(n-1\) points that lie on the function. There is a unique degree \(n\) polynomial (a polynomial whose highest power of \(x\) is \(x^n\)) that passes through these points. This polynomial is called an interpolating polynomial, and it sounds like it ought to be a pretty good approximation of the function.
So let's try taking points on a function at equally spaced values of \(x\), and try to approximate the function:
$$f(x)=\frac1{1+25x^2}$$
Polynomial interpolations of \(\displaystyle f(x)=\frac1{1+25x^2}\) using equally spaced points
I'm sure you'll agree that these approximations are pretty terrible, and they get worse as more points are added. The high error towards 1 and -1 is called Runge's phenomenon, and was discovered in 1901 by Carl David Tolmé Runge.
All hope of finding a good polynomial approximation is not lost, however: by choosing the points more carefully, it's possible to avoid Runge's phenomenon. Chebyshev points (named after Pafnuty Chebyshev) are defined by taking the \(x\) co-ordinate of equally spaced points on a circle.
Eight Chebyshev points
The following GIF shows interpolating polynomials of the same function as before using Chebyshev points.
Nice, we've found a polynomial that closely approximates the function... But I guess you're now wondering how well the Chebyshev interpolation will approximate other functions. To find out, let's try it out on the votes over time of my first round Big Internet Math-Off match.
Scroggs vs Parker, 6-8 July 2018
The graphs below show the results of the match over time interpolated using 16 uniform points (left) and 16 Chebyshev points (right). You can see that the uniform interpolation is all over the place, but the Chebyshev interpolation is very close the the actual results.
Scroggs vs Parker, 6-8 July 2018, approximated using uniform points (left) and Chebyshev points (right)
But maybe you still want to see how good Chebyshev interpolation is for a function of your choice... To help you find out, I've written @RungeBot, a Twitter bot that can compare interpolations with equispaced and Chebyshev points. Just tweet it a function, and it'll show you how bad Runge's phenomenon is for that function, and how much better Chebysheb points are.
A list of constants and functions that RungeBot understands can be found here.

Similar posts

A surprising fact about quadrilaterals
Interesting tautologies
Big Internet Math-Off stickers 2019
Mathsteroids

Comments

Comments in green were written by me. Comments in blue were not written by me.
 Add a Comment 


I will only use your email address to reply to your comment (if a reply is needed).

Allowed HTML tags: <br> <a> <small> <b> <i> <s> <sup> <sub> <u> <spoiler> <ul> <ol> <li>
To prove you are not a spam bot, please type "oitar" backwards in the box below (case sensitive):

Archive

Show me a random blog post
 2020 

May 2020

A surprising fact about quadrilaterals
Interesting tautologies

Mar 2020

Log-scaled axes

Feb 2020

PhD thesis, chapter ∞
PhD thesis, chapter 5
PhD thesis, chapter 4
PhD thesis, chapter 3
Inverting a matrix
PhD thesis, chapter 2

Jan 2020

PhD thesis, chapter 1
Gaussian elimination
Matrix multiplication
Christmas (2019) is over
 2019 
▼ show ▼
 2018 
▼ show ▼
 2017 
▼ show ▼
 2016 
▼ show ▼
 2015 
▼ show ▼
 2014 
▼ show ▼
 2013 
▼ show ▼
 2012 
▼ show ▼

Tags

mathsteroids ucl royal institution phd graphs sport braiding chebyshev logs nine men's morris weather station pac-man programming people maths fractals raspberry pi chalkdust magazine bubble bobble weak imposition gaussian elimination cross stitch boundary element methods squares numerical analysis estimation video games exponential growth game show probability sobolev spaces hannah fry harriss spiral game of life arithmetic bempp tennis logic dragon curves captain scarlet oeis mathsjam manchester determinants the aperiodical php a gamut of games quadrilaterals news preconditioning draughts inline code matrix of cofactors london talking maths in public wool machine learning christmas javascript plastic ratio twitter binary puzzles mathslogicbot signorini conditions trigonometry asteroids dataset hexapawn computational complexity electromagnetic field misleading statistics royal baby tmip triangles books bodmas wave scattering frobel matrix of minors simultaneous equations palindromes python polynomials inverse matrices convergence dates cambridge golden ratio go ternary folding paper games golden spiral data light national lottery map projections matrices chess speed interpolation reuleaux polygons countdown world cup realhats pizza cutting hats martin gardner noughts and crosses sorting error bars geometry propositional calculus pythagoras rhombicuboctahedron data visualisation flexagons matrix multiplication gerry anderson probability menace advent calendar statistics approximation curvature reddit accuracy coins craft radio 4 sound folding tube maps big internet math-off european cup matt parker london underground graph theory platonic solids latex finite element method geogebra football final fantasy stickers rugby manchester science festival christmas card

Archive

Show me a random blog post
▼ show ▼
© Matthew Scroggs 2012–2020