Nodal count for a random signing of a graph with disjoint cycles

TL;DR

This paper investigates the distribution of nodal surplus in eigenvectors of random signings of matrices supported on graphs with disjoint cycles, showing it follows a binomial distribution under certain conditions.

Contribution

It introduces a probabilistic model for nodal surplus in signed graph matrices and proves a binomial distribution result for generic cases.

Findings

Nodal surplus follows a binomial distribution for random signings.

The result applies to matrices supported on graphs with disjoint cycles.

Part of the proof adapts ideas from quantum graph theory.

Abstract

Let $G$ be a simple, connected graph on $n$ vertices, and further assume that $G$ has disjoint cycles. Let $h$ be a real symmetric matrix supported on $G$ (for example, a discrete Schr\"odinger operator). The eigenvalues of $h$ are ordered increasingly, $\lambda_1 \le \cdots \le \lambda_n$, and if $\phi$ is the eigenvector corresponding to $\lambda_k$, the nodal (edge) count $\nu(h,k)$ is the number of edges $(rs)$ such that $ h_{rs}\phi_{r}\phi_{s}>0$. The nodal surplus is $\sigma(h,k)= \nu(h,k) - (k-1)$. Let $h'$ be a random signing of $h$, that is a real symmetric matrix obtained from $h$ by changing the sign of some of its off-diagonal elements. If $h$ satisfies a certain generic condition, we show for each $k$ that the nodal surplus has a binomial distribution $\sigma(h',k)\sim Bin(\beta,\frac{1}{2})$. Part of the proof follows ideas developed by the first author together with Ram Band and Gregory Berkolaiko in a joint unpublished project studying a similar question on quantum graphs.