On the supremum of random Dirichlet polynomials
Studia Mathematica, Tome 182 (2007) no. 1, pp. 41-65

Voir la notice de l'article provenant de la source Institute of Mathematics Polish Academy of Sciences

We study the supremum of some random Dirichlet polynomials $D_N(t)=\sum_{n=2}^N\varepsilon_n d_n n^{-\sigma - it}$, where $(\varepsilon_n)$ is a sequence of independent Rademacher random variables, the weights $(d_n)$ are multiplicative and $0\le \sigma 1/2$. Particular attention is given to the polynomials $\sum_{n\in {\cal E}_\tau}\varepsilon_n n^{-\sigma - it}$, ${\cal E}_\tau=\{2\le n\le N\!: \! P^+(n)\le p_\tau\}$, $P^+(n)$ being the largest prime divisor of $n$. We obtain sharp upper and lower bounds for the supremum expectation that extend the optimal estimate of Halász–Queffélec, $$ {\mathbb E}\, \sup_{t \in \mathbb R} \Big|\sum_{n=2}^N \varepsilon_n n^{-\sigma - it}\Big| \approx {N^{1-\sigma }\over \log N}. $$ The proofs are entirely based on methods of stochastic processes, in particular the metric entropy method.
DOI : 10.4064/sm182-1-3
Keywords: study supremum random dirichlet polynomials sum varepsilon n sigma where varepsilon sequence independent rademacher random variables weights multiplicative sigma particular attention given polynomials sum cal tau varepsilon sigma cal tau tau being largest prime divisor obtain sharp upper lower bounds supremum expectation extend optimal estimate hal queff lec mathbb sup mathbb sum varepsilon sigma approx sigma log proofs entirely based methods stochastic processes particular metric entropy method

Mikhail Lifshits 1 ; Michel Weber 2

1 Department of Mathematics and Mechanics St. Petersburg State University Bibliotechnaya pl. 2 198504, Stary Peterhof, Russia
2 Mathématique (IRMA) Université Louis-Pasteur et C.N.R.S. 7 rue René Descartes 67084 Strasbourg Cedex, France
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Mikhail Lifshits; Michel Weber. On the supremum of random Dirichlet polynomials. Studia Mathematica, Tome 182 (2007) no. 1, pp. 41-65. doi: 10.4064/sm182-1-3

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