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arxiv: 1604.08378 · v1 · pith:QP3XHT5Hnew · submitted 2016-04-28 · 🧮 math.PR · math.NT

Multiplicative chaos measures for a random model of the Riemann zeta function

classification 🧮 math.PR math.NT
keywords chaosmeasurerandomapproximationfunctionmultiplicativeproveriemann
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We prove convergence of a stochastic approximation of powers of the Riemann $\zeta$ function to a non-Gaussian multiplicative chaos measure, and prove that this measure is a non-trivial multifractal random measure. The results cover both the subcritical and critical chaos. A basic ingredient of the proof is a 'good' Gaussian approximation of the induced random fields that is potentially of independent interest.

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  1. High points of a random model of the Riemann-zeta function and Gaussian multiplicative chaos

    math.PR 2019-06 unverdicted novelty 5.0

    In a random model of the Riemann zeta function, the normalized total mass of high points a linear order below the maximum converges almost surely to Gaussian multiplicative chaos of an approximating process times a ra...