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 "vector" in the box below (case sensitive):

Archive

Show me a random blog post
 2021 

Jan 2021

Christmas (2020) is over
 2020 
▼ show ▼
 2019 
▼ show ▼
 2018 
▼ show ▼
 2017 
▼ show ▼
 2016 
▼ show ▼
 2015 
▼ show ▼
 2014 
▼ show ▼
 2013 
▼ show ▼
 2012 
▼ show ▼

Tags

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

Archive

Show me a random blog post
▼ show ▼
© Matthew Scroggs 2012–2021