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Abstract
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The complex Gaussian multiplicative chaos (or complex GMC) is informally defined as a random
distribution
where
is a
-correlated
Gaussian field on
and
is a complex parameter. The correlation function of
is of
the form
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where
is a continuous function. We consider the cases
and
where
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and
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We prove that if
is replaced
by an approximation
obtained
via mollification, then
, when
properly rescaled, converges when
.
The limit does not depend on the mollification kernel. When
, the convergence holds
in probability and in
for some value of
.
When
,
the convergence holds only in law. In this latter case, the limit can be described as a
complex Gaussian white noise with a random intensity given by a critical real GMC. The
regions
and
correspond to the phase boundary between the three different regions of the complex
GMC phase diagram. These results complete previous results obtained for the GMC
in phases I and III and only leave as an open problem the question of convergence in
phase II.
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Keywords
random distributions, $\log$-correlated fields, Gaussian
multiplicative chaos
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Mathematical Subject Classification
Primary: 60F99, 60G15, 82B99
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Milestones
Received: 18 January 2023
Revised: 13 November 2023
Accepted: 8 January 2024
Published: 26 May 2024
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© 2024 MSP (Mathematical Sciences
Publishers). |
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