Weighted LpL_p Markov factors with doubling weights on the ball

preprint2022arXivOpen access

Abstract

Let Lp,w, 1≤p<∞,L_{p,w},\ 1 \le p<\infty, denote the weighted LpL_p space of functions on the unit ball Bd\Bbb B^d with a doubling weight ww on Bd\Bbb B^d. The Markov factor for Lp,wL_{p,w} on a polynomial PP is defined by ∥ ∣∇P∣ ∥p,w∥P∥p,w\frac{\|\, |\nabla P|\,\|_{p,w}}{\|P\|_{p,w}}, where ∇P\nabla P is the gradient of PP. We investigate the worst case Markov factors for Lp,w (1≤p<∞)L_{p,w}\ (1\le p<\infty) and obtain that the degree of these factors are at most 22. In particular, for the Jacobi weight wμ(x)=(1−∣x∣2)μ−1/2, μ≥0w_μ(x)=(1-|x|^2)^{μ-1/2}, \ μ\ge0, the exponent 22 is sharp. We also study the average case Markov factor for L2,wL_{2,w} on random polynomials with independent N(0,σ2)N(0, σ^2) coefficients and obtain that the upper bound of the average (expected) Markov factor is order degree to the 3/23/2, as compared to the degree squared worst case upper bound.

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