Math 2.0

Harmonic analysis on Euclidean spaces Trigonometric polynomials and extremal problems Example

Rudin–Shapiro polynomials

Builds on Littlewood polynomial

Example

Define polynomials PmP_m and QmQ_m by P0(z)=Q0(z)=1P_0(z) = Q_0(z) = 1 and, for m≥0m \ge 0, Pm+1(z)=Pm(z)+z2mQm(z),Qm+1(z)=Pm(z)−z2mQm(z).P_{m+1}(z) = P_m(z) + z^{2^m} Q_m(z), \qquad Q_{m+1}(z) = P_m(z) - z^{2^m} Q_m(z). These are the Rudin–Shapiro polynomials. By induction, PmP_m and QmQ_m have degree 2m−12^m - 1, and all 2m2^m of their coefficients are +1+1 or −1-1. Indeed PmP_m fills the coefficients of 1,…,z2m−11, \ldots, z^{2^m - 1} and z2mQmz^{2^m} Q_m fills those of z2m,…,z2m+1−1z^{2^m}, \ldots, z^{2^{m+1} - 1}. So they are Littlewood polynomials. The first ones are P1(z)=1+zP_1(z) = 1 + z, Q1(z)=1−zQ_1(z) = 1 - z and P2(z)=1+z+z2−z3P_2(z) = 1 + z + z^2 - z^3.

For ∣z∣=1\abs{z} = 1, the parallelogram law ∣u+v∣2+∣u−v∣2=2∣u∣2+2∣v∣2\abs{u + v}^2 + \abs{u - v}^2 = 2\abs{u}^2 + 2\abs{v}^2 with ∣z2m∣=1\abs{z^{2^m}} = 1 gives ∣Pm+1(z)∣2+∣Qm+1(z)∣2=2(∣Pm(z)∣2+∣Qm(z)∣2).\abs{P_{m+1}(z)}^2 + \abs{Q_{m+1}(z)}^2 = 2 \left( \abs{P_m(z)}^2 + \abs{Q_m(z)}^2 \right). Hence ∣Pm(z)∣2+∣Qm(z)∣2=2m+1\abs{P_m(z)}^2 + \abs{Q_m(z)}^2 = 2^{m+1}, and max⁡∣z∣=1∣Pm(z)∣≤2⋅2m.\max_{\abs{z} = 1} \abs{P_m(z)} \le \sqrt{2} \cdot \sqrt{2^m}.

Remarks

Since the mean square of ∣Pm∣\abs{P_m} on the circle is 2m2^m, the maximum is at most 2\sqrt 2 times the root mean square. For a polynomial with NN coefficients ±1\pm 1, the maximum on the circle is always at least N\sqrt N, so this is optimal up to the factor 2\sqrt 2. A random choice of signs typically gives a maximum of order Nlog⁡N\sqrt{N \log N}, so the Rudin–Shapiro signs are much better than random. The coefficients of the PmP_m form the Rudin–Shapiro sequence, an automatic sequence.

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To understand this page from the ground up, read these 2 pages in order. The foundations come first.

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Further reading

  1. Web https://en.wikipedia.org/wiki/Rudin%E2%80%93Shapiro_sequence
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Instance ofLittlewood polynomial
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