Chebyshev Polynomials
Connect Chebyshev recurrence, roots and equal-height extrema with the least maximum size of a monic polynomial.
By Riano · Published · Updated · Report a correction
Chebyshev Polynomials
For -1 ≤ x ≤ 1, Tn(x) = cos(n arccos x). For n ≥ 1 the n roots are cos((2k-1)π/(2n)), k=1,…,n, and the n+1 alternating extrema occur at cos(kπ/n), k=0,…,n. The constant T0=1 has no roots. Endpoint derivatives come from the polynomial recurrence, so no division by √(1-x2) is needed.
Worked Example: The Cubic Case
Let's find the explicit form of the Chebyshev polynomial of degree 3, T3(x).
Using the recurrence relation Tn+1(x) = 2xTn(x) - Tn-1(x) with T0(x) = 1 and T1(x) = x:
- T2(x) = 2x(x) - 1 = 2x2 - 1
- T3(x) = 2x(2x2 - 1) - x = 4x3 - 3x
The leading coefficient is 4, which is 23-1. The monic polynomial is obtained by dividing by 4, giving x3 - (3/4)x. The supremum norm of this monic polynomial on [-1, 1] is 1/4.
Interactive Experiment
You can interactively change the degree of the Chebyshev polynomial and the probe point in the module.
- Set the Degree n control to 3.
- Set the Probe x control to 0.5.
You will observe that the polynomial evaluation result T3(x) gives -1, which matches the calculation T3(0.5) = 4(0.5)3 - 3(0.5) = 4(0.125) - 1.5 = 0.5 - 1.5 = -1. Also note that at this point the derivative result shows 0, indicating an extremum.
Try exploring other combinations in the interactive experiment.
Limitations
This visualization only plots Chebyshev polynomials of the first kind up to degree 8. Higher degrees have more densely spaced roots (Chebyshev nodes) and extrema, which become harder to distinguish on a small screen. Additionally, this module restricts the domain to the standard interval [-1, 1]; it does not demonstrate the exponential growth of the polynomials outside this interval.
References
For more detailed mathematical properties, refer to the following sources from the NIST Digital Library of Mathematical Functions:
Experience it interactively
Adjust parameters, observe in real time, and build deep intuition with Riano’s interactive Chebyshev Polynomials module.
Try Chebyshev Polynomials on Riano →