Determinantal point processes conditioned on randomly incomplete configurations

TL;DR

This paper introduces a framework for analyzing point processes, especially determinantal ones, conditioned on incomplete configurations, revealing new rigidity properties and linking to random matrix theory and integrable systems.

Contribution

It constructs conditional ensembles for point processes, including determinantal processes, and demonstrates their applications in proving number rigidity and interpreting analytical methods.

Findings

Determinantal processes induced by orthogonal projections satisfy stronger number rigidity.

The construction provides a probabilistic interpretation of the Its-Izergin-Korepin-Slavnov method.

Special cases relate to unitary invariant random matrix ensembles.

Abstract

For a broad class of point processes, including determinantal point processes, we construct associated marked and conditional ensembles, which allow to study a random configuration in the point process, based on information about a randomly incomplete part of the configuration. We show that our construction yields a well behaving transformation of sufficiently regular point processes. In the case of determinantal point processes, we explain that special cases of the conditional ensembles already appear implicitly in the literature, namely in the study of unitary invariant random matrix ensembles, in the Its-Izergin-Korepin-Slavnov method to analyze Fredholm determinants, and in the study of number rigidity. As applications of our construction, we show that a class of determinantal point processes induced by orthogonal projection operators, including the sine, Airy, and Bessel point processes, satisfy a strengthened notion of number rigidity, and we give a probabilistic interpretation of the Its-Izergin-Korepin-Slavnov method.