Kac-Rice formula for transverse intersections
Michele Stecconi

TL;DR
This paper generalizes the Kac-Rice formula to compute expected counts of intersections and preimages of submanifolds by random maps, with applications to Gaussian sections and geometric probability.
Contribution
It introduces a new measure-theoretic proof of the generalized Kac-Rice formula and extends it to intersection degrees and various types of counting measures.
Findings
Derived a measure-theoretic proof of the generalized Kac-Rice formula.
Extended the formula to intersection degrees and other counting measures.
Applied the results to Gaussian sections, homogeneous spaces, and isotropic fields.
Abstract
We prove a generalized Kac-Rice formula that, in a well defined regular setting, computes the expected cardinality of the preimage of a submanifold via a random map, by expressing it as the integral of a density. Our proof starts from scratch and although it follows the guidelines of the standard proofs of Kac-Rice formula, it contains some new ideas coming from the point of view of measure theory. Generalizing further, we extend this formula to any other type of counting measure, such as the intersection degree. We discuss in depth the specialization to smooth Gaussian random sections of a vector bundle. Here, the formula computes the expected number of points where the section meets a given submanifold of the total space, it holds under natural non-degeneracy conditions and can be simplified by using appropriate connections. Moreover, we point out a class of submanifolds, that we…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
