Benchmarking quantum computers with any quantum algorithm

• URL: http://arxiv.org/abs/2508.05754v1
• Date: Thu, 07 Aug 2025 18:11:22 GMT
• Title: Benchmarking quantum computers with any quantum algorithm
• Authors: Stefan K. Seritan, Aditya Dhumuntarao, Aidan Q. Wilber-Gauthier, Kenneth M. Rudinger, Antonio E. Russo, Robin Blume-Kohout, Andrew D. Baczewski, Timothy Proctor,
• Abstract summary: Application-based benchmarks are increasingly used to quantify and compare quantum computers' performance.<n>We present a method for creating scalable and efficient benchmarks from any quantum algorithm or application.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Application-based benchmarks are increasingly used to quantify and compare quantum computers' performance. However, because contemporary quantum computers cannot run utility-scale computations, these benchmarks currently test this hardware's performance on ``small'' problem instances that are not necessarily representative of utility-scale problems. Furthermore, these benchmarks often employ methods that are unscalable, limiting their ability to track progress towards utility-scale applications. In this work, we present a method for creating scalable and efficient benchmarks from any quantum algorithm or application. Our subcircuit volumetric benchmarking (SVB) method runs subcircuits of varied shape that are ``snipped out'' from some target circuit, which could implement a utility-scale algorithm. SVB is scalable and it enables estimating a capability coefficient that concisely summarizes progress towards implementing the target circuit. We demonstrate SVB with experiments on IBM Q systems using a Hamiltonian block-encoding subroutine from quantum chemistry algorithms.

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