Bilinear Hilbert Transforms and (Sub)Bilinear Maximal Functions along Convex Curves

preprint2020arXivOpen access

Abstract

In this paper, we determine the Lp(R)×Lq(R)→Lr(R)L^p(\mathbb{R})\times L^q(\mathbb{R})\rightarrow L^r(\mathbb{R}) boundedness of the bilinear Hilbert transform Hγ(f,g)H_γ(f,g) along a convex curve γγ Hγ(f,g)(x):=p. v.∫−∞∞f(x−t)g(x−γ(t)) dtt,H_γ(f,g)(x):=\mathrm{p.\,v.}\int_{-\infty}^{\infty}f(x-t)g(x-γ(t)) \,\frac{\textrm{d}t}{t}, where pp, qq, and rr satisfy 1p+1q=1r\frac{1}{p}+\frac{1}{q}=\frac{1}{r}, and r>12r>\frac{1}{2}, p>1p>1, and q>1q>1. Moreover, the same Lp(R)×Lq(R)→Lr(R)L^p(\mathbb{R})\times L^q(\mathbb{R})\rightarrow L^r(\mathbb{R}) boundedness property holds for the corresponding (sub)bilinear maximal function Mγ(f,g)M_γ(f,g) along a convex curve γγ Mγ(f,g)(x):=sup⁡ε>012ε∫−εε∣f(x−t)g(x−γ(t))∣ dt.M_γ(f,g)(x):=\sup_{\varepsilon>0}\frac{1}{2\varepsilon}\int_{-\varepsilon}^{\varepsilon}|f(x-t)g(x-γ(t))| \,\textrm{d}t.

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