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Packet separation and the Gibbs phenomenon

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E11 Packet separation and the Gibbs phenomenon

A Fourier partial sum is global. When the target has a jump, the partial sum must approximate that jump using continuous trigonometric polynomials. This creates the classical Gibbs oscillation. Standard accounts and recovery methods appear in [Zygmund2002], [GottliebShu1997].

Standard fact E11.1: Classical square-wave Gibbs behavior

Let \(q(x)=\tfrac12\operatorname{sign}(\sin x)\), whose jump at zero has size one. For \(n\geq1\), its partial sum through the first \(n\) positive odd frequencies is

\[ Q_n(x)=\frac{2}{\pi}\sum_{k=0}^{n-1}\frac{\sin((2k+1)x)}{2k+1}. \]

At \(x_n=\pi/(2n)\),

\[ x_n\longrightarrow0,\qquad Q_n(x_n)\longrightarrow\frac{\operatorname{Si}(\pi)}{\pi} =\frac12+G,\qquad G\approx0.089489872236, \]

where \(\operatorname{Si}(z)=\int_0^z\sin(t)/t\,dt\) and \(G=\operatorname{Si}(\pi)/\pi-1/2>0\). Thus a nonzero overshoot persists along points approaching the jump. Scaling by a real amplitude \(a\) gives an overshoot or undershoot of magnitude \(|a|G\).

For the limit, put \(u_k=(k+\tfrac12)/n\). The identity

\[ Q_n(x_n)=\frac{1}{\pi n}\sum_{k=0}^{n-1}\frac{\sin(\pi u_k)}{u_k} \longrightarrow\frac1\pi\int_0^1\frac{\sin(\pi u)}u\,du =\frac{\operatorname{Si}(\pi)}{\pi} \]

is a midpoint Riemann sum, since the integrand has continuous value \(\pi\) at zero. This is the normalized classical example in [DLMFGibbs], Section 6.16(i), equations 6.16.1–6.16.4.

The square-wave example supplies a classical comparison. The following retained-packet identities do not require a general overshoot theorem. They change the approximation problem because the discontinuity is no longer represented by the Fourier partial sum.

Theorem E11.2: Uniform convergence with exact jump packets

Let \(f=s+j\) on a compact domain, where \(j\) is any bounded singular packet. Suppose \(Q_ms\to s\) uniformly. Then

\[ \widetilde f_m=Q_ms+j \]

converges uniformly to \(f\), even when \(f\) is discontinuous:

\[ \|f-\widetilde f_m\|_\infty = \|s-Q_ms\|_\infty \longrightarrow0. \]

There is no error proportional to the jump size because the jump is shared exactly by \(f\) and \(\widetilde f_m\).

Proof of Theorem E11.2

Apply Theorem E7.5 in the supremum norm.

Theorem E11.3: Estimated packet Gibbs bound

Let \(Q_m\) be linear and uniformly bounded on \(L^p\), with

\[ \sup_m\|Q_m\|\leq C_Q. \]

For \(f=s+j\) and an estimated packet \(\widehat j_m\), define

\[ \widehat f_m =Q_m(f-\widehat j_m)+\widehat j_m. \]

Then

\[ \|f-\widehat f_m\|_p \leq \|s-Q_ms\|_p +(1+C_Q)\|j-\widehat j_m\|_p. \]

Consequently, smooth approximation and packet recovery may be improved independently. No claim of Gibbs removal is justified unless both terms are controlled in the norm under consideration.

Proof of Theorem E11.3

This is Theorem E7.8 with the uniform operator bound.

Corollary E11.4: Boundary band error

Let \(\Gamma\) be the singular boundary and assume

\[ \mu(N_\delta(\Gamma))\leq C_\Gamma\delta \]

for small \(\delta\). For finite \(p\),

\[ \|f-\widetilde f_m\|_{L^p(N_\delta(\Gamma))} \leq (C_\Gamma\delta)^{1/p} \|s-Q_ms\|_\infty. \]

Proof of Corollary E11.4

The error equals \(s-Q_ms\). Bound it by its supremum and multiply by the measure of the boundary tube.

Example E11.5: Square wave Fourier tail

Let

\[ j(t)={\mathbf 1}_{[-a,a]}(t) \]

on the circle and let \(s\) be smooth. If \(Q_m\) is a Fourier partial sum, then \(Q_m(s+j)\) has the ordinary oscillatory boundary layer. In contrast,

\[ Q_ms+j \]

has error exactly \(s-Q_ms\). The visual comparison in Figure illustrates this change in approximation target. It is not a new Fourier summability theorem.

Fourier approximation of a whole jump signal compared with approximation of the smooth component alone.
Global Fourier truncation represents the jump and exhibits an oscillatory boundary layer. Packet separation retains the jump and approximates only the smooth component.

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