Freezing and decorated Poisson point processes

Abstract

The limiting extremal processes of the branching Brownian motion (BBM), the two-speed BBM, and the branching random walk are known to be randomly shifted decorated Poisson point processes (SDPPP). In the proofs of those results, the Laplace functional of the limiting extremal process is shown to satisfy $L[{\theta }_{y}f]=g(y-{\tau }_f)$ for any nonzero, nonnegative, compactly supported, continuous function $f$, where ${\theta }_y$ is the shift operator, ${\tau }_f$ is a real number that depends on $f$, and $g$ is a real function that is independent of $f$. We show that, under some assumptions, this property characterizes the structure of SDPPP. Moreover, when it holds, we show that $g$ has to be a convolution of the Gumbel distribution with some measure. The above property of the Laplace functional is closely related to a `freezing phenomenon' that is expected by physicists to occur in a wide class of log-correlated fields, and which has played an important role in the analysis of various models. Our results shed light on this intriguing phenomenon and provide a natural tool for proving an SDPPP structure in these and other models.

35 pages

References in corpus (2)

• Freezing and extreme value statistics in a Random Energy Model with logarithmically correlated potential
• Variable speed branching Brownian motion 1. Extremal processes in the weak correlation regime

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