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Subcritical Multiplicative Chaos for Regularized Counting Statistics from Random Matrix Theory

Lambert, Gaultier
•
Ostrovsky, Dmitry
•
Simm, Nick
2018
  • journal article

Periodico
COMMUNICATIONS IN MATHEMATICAL PHYSICS
Abstract
For an N× N Haar distributed random unitary matrix UN, we consider the random field defined by counting the number of eigenvalues of UN in a mesoscopic arc centered at the point u on the unit circle. We prove that after regularizing at a small scale εN> 0 , the renormalized exponential of this field converges as N→ ∞ to a Gaussian multiplicative chaos measure in the whole subcritical phase. We discuss implications of this result for obtaining a lower bound on the maximum of the field. We also show that the moments of the total mass converge to a Selberg-like integral and by taking a further limit as the size of the arc diverges, we establish part of the conjectures in Ostrovsky (Nonlinearity 29(2):426–464, 2016). By an analogous construction, we prove that the multiplicative chaos measure coming from the sine process has the same distribution, which strongly suggests that this limiting object should be universal. Our approach to the L1-phase is based on a generalization of the construction in Berestycki (Electron Commun Probab 22(27):12, 2017) to random fields which are only asymptotically Gaussian. In particular, our method could have applications to other random fields coming from either random matrix theory or a different context.
DOI
10.1007/s00220-018-3130-z
WOS
WOS:000431030400001
Archivio
https://hdl.handle.net/20.500.11767/152112
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85045451426
https://arxiv.org/abs/1612.02367
https://ricerca.unityfvg.it/handle/20.500.11767/152112
Diritti
open access
license:creative commons
license uri:http://creativecommons.org/licenses/by/4.0/
Soggetti
  • Settore MATH-03/B - P...

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