Quantum WalkScore: Benchmarking Quantum Computers on the Graph Nodefinding Problem

Abstract

Recent advances in quantum computing hardware toward fault-tolerance have increased interest in evaluating near-term quantum platforms on application-relevant quantum algorithms. In this work, we introduce Quantum WalkScore (QWS), a scalable application-oriented benchmark designed to assess the performance of NISQ and future fault-tolerant quantum computers in executing essential quantum routines --discrete-time quantum walks and quantum amplitude amplification-- to solve the graph nodefinding problem (marked-vertex search). QWS quantifies performance by scoring the largest problem size for which a designated target node can be found with success probability above a defined threshold. In addition to the complete protocol description, we provide example parameter-selection scenarios designed from noiseless simulation results and demonstrate QWS evaluation through experimental runs on multiple generations of IBM real quantum processors.