Generalized Resistance Geometry from Kron Reduction and Effective Resistance

TL;DR

This paper introduces a generalized resistance geometry for directed graphs using Kron reduction and effective resistance, establishing new identities and metrics that extend classical undirected graph theory.

Contribution

It develops a unified resistance geometry framework for directed graphs, including identities, metrics, and embeddings that parallel and extend classical undirected graph concepts.

Findings

Proves a Fiedler--Bapat identity linking resistance matrix and Laplacian for strongly connected directed graphs.

Defines a generalized resistance metric that coincides with strict negative type metrics.

Characterizes properties of resistance curvature, radius, and resistive embeddings in the new framework.

Abstract

We develop a generalized resistance geometry based on Kron reduction and effective resistance for directed graphs, paralleling classical undirected graph theory. For strongly connected directed graphs, we prove a Fiedler--Bapat identity that links the resistance matrix and the Laplacian through the symmetrized pseudoinverse. This identity provides a canonical definition of the resistance curvature and resistance radius in the strongly connected directed setting. In the strongly connected weight-balanced case, it also implies that the operation of associating an undirected Laplacian with a directed Laplacian via the pseudoinverse of the symmetrized pseudoinverse commutes with Kron reduction. We further introduce a class of signed undirected Laplacians for which effective resistance defines a distance between nodes. We call this distance the generalized resistance metric and prove that it coincides with the class of strict negative type metrics. Within this framework, we investigate analytical and geometric properties of resistance curvature and resistance radius, characterize the maximum graph-variance problem, and generalize resistive embeddings. These results place signed undirected resistance geometry on a footing parallel to the classical unsigned undirected theory and provide a unified perspective on model reduction, graph variance, and resistance-based embedding.