A1.3

Functional Analysis
Part II, 2002

(i) Let Pr(eiθ)P_{r}\left(e^{i \theta}\right) be the real part of 1+reiθ1reiθ\frac{1+r e^{i \theta}}{1-r e^{i \theta}}. Establish the following properties of PrP_{r} for 0r<10 \leqslant r<1 : (a) 0<Pr(eiθ)=Pr(eiθ)1+r1r0<P_{r}\left(e^{i \theta}\right)=P_{r}\left(e^{-i \theta}\right) \leqslant \frac{1+r}{1-r}; (b) Pr(eiθ)Pr(eiδ)P_{r}\left(e^{i \theta}\right) \leqslant P_{r}\left(e^{i \delta}\right) for 0<δθπ0<\delta \leqslant|\theta| \leqslant \pi; (c) Pr(eiθ)0P_{r}\left(e^{i \theta}\right) \rightarrow 0, uniformly on 0<δθπ0<\delta \leqslant|\theta| \leqslant \pi, as rr increases to 1 .

(ii) Suppose that fL1(T)f \in L^{1}(\mathbf{T}), where T\mathbf{T} is the unit circle {eiθ:πθπ}\left\{e^{i \theta}:-\pi \leqslant \theta \leqslant \pi\right\}. By definition, f1=12πππf(eiθ)dθ\|f\|_{1}=\frac{1}{2 \pi} \int_{-\pi}^{\pi}\left|f\left(e^{i \theta}\right)\right| d \theta. Let

Pr(f)(eiθ)=12πππPr(ei(θt))f(eit)dtP_{r}(f)\left(e^{i \theta}\right)=\frac{1}{2 \pi} \int_{-\pi}^{\pi} P_{r}\left(e^{i(\theta-t)}\right) f\left(e^{i t}\right) d t

Show that Pr(f)P_{r}(f) is a continuous function on T\mathbf{T}, and that Pr(f)1f1\left\|P_{r}(f)\right\|_{1} \leqslant\|f\|_{1}.

[You may assume without proof that 12πππPr(eiθ)dθ=1\frac{1}{2 \pi} \int_{-\pi}^{\pi} P_{r}\left(e^{i \theta}\right) d \theta=1.]

Show that Pr(f)fP_{r}(f) \rightarrow f, uniformly on T\mathbf{T} as rr increases to 1 , if and only if ff is a continuous function on T\mathbf{T}.

Show that Pr(f)f10\left\|P_{r}(f)-f\right\|_{1} \rightarrow 0 as rr increases to 1 .