analysis / Harmonic analysis; pointwise convergence of Fourier series
Almost everywhere convergence of Fourier series in L log L
Theorem 1.1: for every complex-valued f∈LlogL(T) there is a null set Nf with limN→∞SNf(x)=f(x) for x∈/Nf, along the full sequence. The key estimate is a good-set bound ∫{Mρ≤e4h}supN∣SNρ∣≤Cd for bounded densities of height ed, summed over height layers. The paper also deduces a weak-L1 maximal inequality in Luxemburg norm. It does not address spaces strictly between LlogL and L1 (where Konyagin's divergence results apply below LlogL), nor lacunary or higher-dimensional analogues.
Theorem 1.1: for every complex-valued f∈LlogL(T) there is a null set Nf with limN→∞SNf(x)=f(x) for x∈/Nf, along the full sequence. The key estimate is a good-set bound ∫{Mρ≤e4h}supN∣SNρ∣≤Cd for bounded densities of height ed, summed over height layers. The paper also deduces a weak-L1 maximal inequality in Luxemburg norm. It does not address s…
Theorem 1.1: for every complex-valued f∈LlogL(T) there is a null set Nf with limN→∞SNf(x)=f(x) for x∈/Nf, along the full sequence. The key estimate is a good-set bound ∫{Mρ≤e4h}supN∣SNρ∣≤Cd for bounded densities of height ed, summed over height layers. The paper also deduces a weak-L1 maximal inequality in Luxemburg norm. It does not address spaces strictly between LlogL and L1 (where Konyagin's divergence results apply below LlogL), nor lacunary or higher-dimensional analogues.
Theorem 1.1: for every complex-valued f∈LlogL(T) there is a null set Nf with limN→∞SNf(x)=f(x) for x∈/Nf, along the full sequence. The key estimate is a good-set bound ∫{Mρ≤e4h}supN∣SNρ∣≤Cd for bounded densities of height ed, summed over height layers. The paper also deduces a weak-L1 maximal inequality in Luxemburg norm. It does not address spaces strictly between LlogL and L1 (where Konyagin's divergence results apply below LlogL), nor lacunary or higher-dimensional analogues.