MOMENTS OF RANDOM MULTIPLICATIVE FUNCTIONS, I: LOW MOMENTS, BETTER THAN SQUAREROOT CANCELLATION, AND CRITICAL MULTIPLICATIVE CHAOS
Forum of Mathematics, Pi, Tome 8 (2020)

Voir la notice de l'article provenant de la source Cambridge University Press

We determine the order of magnitude of $\mathbb{E}|\sum _{n\leqslant x}f(n)|^{2q}$, where $f(n)$ is a Steinhaus or Rademacher random multiplicative function, and $0\leqslant q\leqslant 1$. In the Steinhaus case, this is equivalent to determining the order of $\lim _{T\rightarrow \infty }\frac{1}{T}\int _{0}^{T}|\sum _{n\leqslant x}n^{-it}|^{2q}\,dt$.In particular, we find that $\mathbb{E}|\sum _{n\leqslant x}f(n)|\asymp \sqrt{x}/(\log \log x)^{1/4}$. This proves a conjecture of Helson that one should have better than squareroot cancellation in the first moment and disproves counter-conjectures of various other authors. We deduce some consequences for the distribution and large deviations of $\sum _{n\leqslant x}f(n)$.The proofs develop a connection between $\mathbb{E}|\sum _{n\leqslant x}f(n)|^{2q}$ and the $q$th moment of a critical, approximately Gaussian, multiplicative chaos and then establish the required estimates for that. We include some general introductory discussion about critical multiplicative chaos to help readers unfamiliar with that area.
@article{10_1017_fmp_2019_7,
     author = {ADAM J. HARPER},
     title = {MOMENTS {OF} {RANDOM} {MULTIPLICATIVE} {FUNCTIONS,} {I:} {LOW} {MOMENTS,} {BETTER} {THAN} {SQUAREROOT} {CANCELLATION,} {AND} {CRITICAL} {MULTIPLICATIVE} {CHAOS}},
     journal = {Forum of Mathematics, Pi},
     publisher = {mathdoc},
     volume = {8},
     year = {2020},
     doi = {10.1017/fmp.2019.7},
     language = {en},
     url = {http://geodesic.mathdoc.fr/articles/10.1017/fmp.2019.7/}
}
TY  - JOUR
AU  - ADAM J. HARPER
TI  - MOMENTS OF RANDOM MULTIPLICATIVE FUNCTIONS, I: LOW MOMENTS, BETTER THAN SQUAREROOT CANCELLATION, AND CRITICAL MULTIPLICATIVE CHAOS
JO  - Forum of Mathematics, Pi
PY  - 2020
VL  - 8
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/articles/10.1017/fmp.2019.7/
DO  - 10.1017/fmp.2019.7
LA  - en
ID  - 10_1017_fmp_2019_7
ER  - 
%0 Journal Article
%A ADAM J. HARPER
%T MOMENTS OF RANDOM MULTIPLICATIVE FUNCTIONS, I: LOW MOMENTS, BETTER THAN SQUAREROOT CANCELLATION, AND CRITICAL MULTIPLICATIVE CHAOS
%J Forum of Mathematics, Pi
%D 2020
%V 8
%I mathdoc
%U http://geodesic.mathdoc.fr/articles/10.1017/fmp.2019.7/
%R 10.1017/fmp.2019.7
%G en
%F 10_1017_fmp_2019_7
ADAM J. HARPER. MOMENTS OF RANDOM MULTIPLICATIVE FUNCTIONS, I: LOW MOMENTS, BETTER THAN SQUAREROOT CANCELLATION, AND CRITICAL MULTIPLICATIVE CHAOS. Forum of Mathematics, Pi, Tome 8 (2020). doi: 10.1017/fmp.2019.7

[1] Arguin, L.-P., Belius, D. and Harper, A. J., ‘Maxima of a randomized Riemann zeta function, and branching random walks’, Ann. Appl. Probab. 27(1) (2017), 178–215.Google Scholar | DOI

[2] Barral, J., Kupiainen, A., Nikula, M., Saksman, E. and Webb, C., ‘Basic properties of critical lognormal multiplicative chaos’, Ann. Probab. 43(5) (2015), 2205–2249.Google Scholar | DOI

[3] Berestycki, N., ‘An elementary approach to Gaussian multiplicative chaos’, Electron. Commun. Probab. 22(Paper No. 27) (2017), 12 pp.Google Scholar | DOI

[4] Bondarenko, A. and Seip, K., ‘Helson’s problem for sums of a random multiplicative function’, Mathematika 62(1) (2016), 101–110.Google Scholar | DOI

[5] Chatterjee, S. and Soundararajan, K., ‘Random multiplicative functions in short intervals’, Int. Math. Res. Not. IMRN 2012 (2012), 479–492.Google Scholar | DOI

[6] Duplantier, B., Rhodes, R., Sheffield, S. and Vargas, V., ‘Renormalization of critical Gaussian multiplicative chaos and KPZ relation’, Comm. Math. Phys. 330(1) (2014), 283–330.Google Scholar | DOI

[7] Grimmett, G. R. and Stirzaker, D. R., Probability and Random Processes, 3rd edn, (Oxford University Press, New York, 2001).Google Scholar

[8] Gut, A., Probability: A Graduate Course, 2nd edn, (Springer Texts in Statistics, New York, 2013).Google Scholar | DOI

[9] Halász, G., ‘On random multiplicative functions’, inHubert Delange Colloquium, (Orsay, 1982), Publications Mathématiques d’Orsay, 83 (Univ. Paris XI, Orsay, 1983), 74–96.Google Scholar

[10] Harper, A. J., ‘Bounds on the suprema of Gaussian processes, and omega results for the sum of a random multiplicative function’, Ann. Appl. Probab. 23(2) (2013), 584–616.Google Scholar | DOI

[11] Harper, A. J., ‘On the limit distributions of some sums of a random multiplicative function’, J. reine angew. Math. 678 (2013), 95–124.Google Scholar

[12] Harper, A. J., ‘Moments of random multiplicative functions, II: High moments’, Algebra Number Theory, to appear.Google Scholar

[13] Harper, A. J., Nikeghbali, A. and Radziwiłł, M., ‘A note on Helson’s conjecture on moments of random multiplicative functions’, inAnalytic Number Theory (Springer, Cham, 2015), 145–169.Google Scholar | DOI

[14] Heap, W. and Lindqvist, S., ‘Moments of random multiplicative functions and truncated characteristic polynomials’, Q. J. Math. 67(4) (2016), 683–714.Google Scholar

[15] Helson, H., ‘Hankel forms’, Studia Math. 198(1) (2010), 79–84.Google Scholar | DOI

[16] Hough, B., ‘Summation of a random multiplicative function on numbers having few prime factors’, Math. Proc. Cambridge Philos. Soc. 150 (2011), 193–214.Google Scholar | DOI

[17] Hu, Y. and Shi, Z., ‘Minimal position and critical martingale convergence in branching random walks, and directed polymers on disordered trees’, Ann. Probab. 37(2) (2009), 742–789.Google Scholar | DOI

[18] Lau, Y.-K., Tenenbaum, G. and Wu, J., ‘On mean values of random multiplicative functions’, Proc. Amer. Math. Soc. 141 (2013), 409–420. Also see for some corrections to the published version.Google Scholar | DOI

[19] Lawler, G. F. and Limic, V., Random Walk: a Modern Introduction, 1st edn, (Cambridge University Press, Cambridge, 2010).Google Scholar | DOI

[20] Montgomery, H. L. and Vaughan, R. C., Multiplicative Number Theory I: Classical Theory, 1st edn, (Cambridge University Press, Cambridge, 2007).Google Scholar

[21] Ng, N., ‘The distribution of the summatory function of the Möbius function’, Proc. Lond. Math. Soc. (3) 89(3) (2004), 361–389.Google Scholar | DOI

[22] Reinert, G. and Röllin, A., ‘Multivariate normal approximation with Stein’s method of exchangeable pairs under a general linearity condition’, Ann. Probab. 37(6) (2009), 2150–2173.Google Scholar | DOI

[23] Rhodes, R. and Vargas, V., ‘Gaussian multiplicative chaos and applications: A review’, Probab. Surv. 11 (2014), 315–392.Google Scholar | DOI

[24] Sadikova, S. M., ‘Two-dimensional analogues of an inequality of Esseen with applications to the Central Limit Theorem’, Theory Probab. Appl. 11 (1966), 325–335.Google Scholar | DOI

[25] Saksman, E. and Seip, K., ‘Integral means and boundary limits of Dirichlet series’, Bull. Lond. Math. Soc. 41(3) (2009), 411–422.Google Scholar | DOI

[26] Saksman, E. and Seip, K., ‘Some open questions in analysis for Dirichlet series’, inRecent Progress on Operator Theory and Approximation in Spaces of Analytic Functions, Contemp. Mathematics, 679 (American Mathematical Society, Providence, RI, 2016), 179–191.Google Scholar | DOI

[27] Saksman, E. and Webb, C., ‘Multiplicative chaos measures for a random model of the Riemann zeta function’, Preprint available online at .Google Scholar

[28] Saksman, E. and Webb, C., ‘The Riemann zeta function and Gaussian multiplicative chaos: statistics on the critical line’, Preprint available online at .Google Scholar

[29] Soundararajan, K., ‘Moments of the Riemann zeta function’, Ann. of Math. 170 (2009), 981–993.Google Scholar | DOI

[30] Weber, M. J. G., ‘L 1 -Norm of Steinhaus chaos on the polydisc’, Monatsh. Math. 181(2) (2016), 473–483.Google Scholar | DOI

[31] Wintner, A., ‘Random factorizations and Riemann’s hypothesis’, Duke Math. J. 11 (1944), 267–275.Google Scholar | DOI

Cité par Sources :