Rigidity hierarchy in random point fields: random polynomials and determinantal processes
Subhro Ghosh, Manjunath Krishnapur

TL;DR
This paper systematically studies the concept of rigidity in point processes, introduces new classes with varying rigidity levels, and establishes conditions under which determinantal processes exhibit rigidity, including a novel family with arbitrarily high rigidity.
Contribution
It introduces a one-parameter family of point processes with adjustable rigidity levels and provides conditions for rigidity in determinantal point processes based on their kernels.
Findings
Determinantal processes are rigid iff their kernel is a projection.
A new family of point processes with arbitrarily high rigidity levels.
Connections between rigidity and zero sets of Gaussian functions.
Abstract
In certain point processes, the configuration of points outside a bounded domain determines, with probability 1, certain statistical features of the points within the domain. This notion, called rigidity, was introduced in a work of Ghosh and Peres. In this paper, rigidity and the related notion of tolerance are examined systematically and point processes with rigidity of various degrees are introduced. Natural classes of point processes such as determinantal point processes, zero sets of Gaussian entire functions and perturbed lattices are examined from the point of view of rigidity, and general conditions are provided for them to exhibit specified nature of spatially rigid behaviour. In particular, we examine the rigidity of determinantal point processes in terms of their kernel, and demonstrate that a necessary condition for determinantal processes to exhibit rigidity is that their…
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