English

Moments of polynomials with random multiplicative coefficients

Number Theory 2023-11-23 v3 Probability

Abstract

For X(n)X(n) a Rademacher or Steinhaus random multiplicative function, we consider the random polynomials PN(θ)=1NnNX(n)e(nθ), P_N(\theta) = \frac1{\sqrt{N}} \sum_{n\leq N} X(n) e(n\theta), and show that the 2k2k-th moments on the unit circle 01PN(θ)2kdθ \int_0^1 \big| P_N(\theta) \big|^{2k}\, d\theta tend to Gaussian moments in the sense of mean-square convergence, uniformly for k(logN/loglogN)1/3k \ll (\log N / \log \log N)^{1/3}, but that in contrast to the case of i.i.d. coefficients, this behavior does not persist for kk much larger. We use these estimates to (i) give a proof of an almost sure Salem-Zygmund type central limit theorem for PN(θ)P_N(\theta), previously obtained in unpublished work of Harper by different methods, and (ii) show that asymptotically almost surely (logN)1/6εmaxθPN(θ)exp((logN)1/2+ε), (\log N)^{1/6 - \varepsilon} \ll \max_\theta |P_N(\theta)| \ll \exp((\log N)^{1/2+\varepsilon}), for all ε>0\varepsilon > 0.

Keywords

Cite

@article{arxiv.2012.15507,
  title  = {Moments of polynomials with random multiplicative coefficients},
  author = {Jacques Benatar and Alon Nishry and Brad Rodgers},
  journal= {arXiv preprint arXiv:2012.15507},
  year   = {2023}
}

Comments

Minor changes in Theorem 1.4