English

Weighted $L_p$ Markov factors with doubling weights on the ball

Classical Analysis and ODEs 2022-01-19 v1

Abstract

Let Lp,w, 1p<,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 Pp,wPp,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 (1p<)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)=(1x2)μ1/2, μ0w_\mu(x)=(1-|x|^2)^{\mu-1/2}, \ \mu\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, \sigma^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.

Keywords

Cite

@article{arxiv.2201.06711,
  title  = {Weighted $L_p$ Markov factors with doubling weights on the ball},
  author = {Jiansong Li and Heping Wang and Kai Wang},
  journal= {arXiv preprint arXiv:2201.06711},
  year   = {2022}
}

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17 pages