Arc search in graphs via Szegedy walks

TL;DR

This paper explores quantum arc search in graphs using Szegedy walks, analyzing symmetry effects, success probabilities, and performance across different graph types, providing theoretical insights into quantum edge search.

Contribution

It establishes conditions under which arc search success probability is graph-symmetry independent and analyzes the effectiveness of quantum search on various graph classes.

Findings

Success probability is independent of the marked arc in arc-transitive graphs.

Quantum search is ineffective on path and cycle graphs.

Quantum search performs well on complete bipartite graphs $K_{n,n}$.

Abstract

This paper studies the search for a single arc in a graph using the Szegedy walk. Arc search can be interpreted as finding a quantum particle not only in its position but also with a specific internal state. The quantum walk employed in this study is essentially the model proposed by Segawa and Yoshie for the purpose of edge search. First, we investigate how the symmetry of a graph is reflected in its time evolution matrix, and provide a sufficient condition under which the success probability of the search is independent of the marked arc. In particular, we prove that if a graph is arc-transitive, the success probability is independent of the choice of the marked arc. Next, we analyze path and cycle graphs and show that the quantum search is ineffective for these graphs, whereas it performs well for complete bipartite graphs $K_{n,n}$. These results provide a theoretical foundation for studying arc and edge searches on various graphs, while also suggesting new problems concerning the eigenvalue analysis of edge-signed graphs in spectral graph theory.