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 random function.
A note on the maximum of the Riemann zeta function, and log-correlated random variables
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
In recent work, Fyodorov and Keating conjectured the maximum size of $|\zeta(1/2+it)|$ in a typical interval of length O(1) on the critical line. They did this by modelling the zeta function by the characteristic polynomial of a random matrix; relating the random matrix problem to another problem from statistical mechanics; and applying a heuristic analysis of that problem. In this note we recover a conjecture like that of Fyodorov and Keating, but using a different model for $|\zeta(1/2+it)|$ in terms of a random Euler product. In this case the probabilistic model reduces to studying the supremum of Gaussian random variables with logarithmic correlations, and can be analysed rigorously.
fields
math.PR 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
High points of a random model of the Riemann-zeta function and Gaussian multiplicative chaos
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 random function.