Vertex Weight Reconstruction in the Gel'fand's Inverse Problem on Connected Weighted Graphs

TL;DR

This paper develops a two-stage method to reconstruct interior vertex weights in weighted graphs from boundary spectral data, utilizing boundary control techniques and validated through numerical experiments.

Contribution

It introduces a novel reconstruction procedure for vertex weights in weighted graphs using boundary spectral data and adapts the boundary control method to this setting.

Findings

Successful reconstruction of interior vertex weights demonstrated.

The method is validated with numerical examples showing quantitative accuracy.

Identifies classes of graphs where unique continuation holds for the wave equation.

Abstract

We consider the reconstruction of the vertex weight in the discrete Gel'fand's inverse boundary spectral problem for the graph Laplacian. Given the boundary vertex weight and the edge weight of the graph, we develop reconstruction procedures to recover the interior vertex weight from the Neumann boundary spectral data on a class of finite, connected and weighted graphs. The procedures are divided into two stages: the first stage reconstructs the Neumann-to-Dirichlet map for the graph wave equation from the Neumann boundary spectral data, and the second stage reconstructs the interior vertex weight from the Neumann-to-Dirichlet map using the boundary control method adapted to weighted graphs. For the second stage, we identify a class of weighted graphs where the unique continuation principle holds for the graph wave equation. The reconstruction procedures are further turned into an algorithm, which is implemented and validated on several numerical examples with quantitative performance reported.