Benchmarking the computational power of quantum computers
Abstract
Quantum computing hardware is advancing rapidly toward utility-scale machines that will enable scientific breakthroughs. Many teams are pursuing distinct and difficult-to-compare routes to this goal, using different qubit technologies and logical architectures. Tracking progress toward quantum utility therefore requires rigorous benchmarks that measure computational capability relative to utility-scale challenge problems and enable fair comparison across disparate platforms. Here we demonstrate direct, cross-platform measurement of quantum computational capability using a new benchmark that quantifies the size of the largest computationally relevant quantum circuits that a machine can execute successfully and the speed at which it can execute them. We apply this quantum universal operation performance system (QUOPS) experimentally to leading processors from Quantinuum, Google, and IBM, computing directly on physical qubits. Translating state-of-the-art resource requirements for recognized challenge problems that represent useful quantum computation into effective QUOPS circuit sizes shows that computational capability must grow by 5 orders of magnitude, motivating fault-tolerant approaches. We use the same benchmark to assess the performance of a simple fault-tolerant logical-qubit processor implemented on up to eight [[7,1,3]]-encoded logical qubits using Quantinuum Helios-1, and project the growth of capability across successive generations of fault-tolerant quantum computers to show how QUOPS can track progress toward quantum scientific utility.
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BibTeX
@misc{proctor2026benchmarking,
title = {{Benchmarking the computational power of quantum computers}},
author = {Timothy Proctor and Oliver Hart and Oliver Widzowski Maupin and Matthew Girling and Daniel Hothem and Daniel Mills and Jordan Hines and Karl Mayer and Jacob S. Nelson and Tyler LeBlond and Zohim Chandani and Diego Forlivesi and Piper C. Wysocki and Boldizsár Poór and Joan M. Dreiling and Annie Park and Adam P. Reed and Brian Estey and Cameron Foltz and Akhil Isanaka and M. S. Allman and Michael Mills and Maxwell D. Urmey and Peter E. Siegfried and Audrey Faricy and Jin-Sung Kim and Cristina Cîrstoiu and Andrew D. Baczewski and Charles H. Baldwin and Robin Blume-Kohout},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.12146},
eprint = {2609.12146},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.12146},
}
RIS
TY - UNPB
TI - Benchmarking the computational power of quantum computers
AU - Timothy Proctor
AU - Oliver Hart
AU - Oliver Widzowski Maupin
AU - Matthew Girling
AU - Daniel Hothem
AU - Daniel Mills
AU - Jordan Hines
AU - Karl Mayer
AU - Jacob S. Nelson
AU - Tyler LeBlond
AU - Zohim Chandani
AU - Diego Forlivesi
AU - Piper C. Wysocki
AU - Boldizsár Poór
AU - Joan M. Dreiling
AU - Annie Park
AU - Adam P. Reed
AU - Brian Estey
AU - Cameron Foltz
AU - Akhil Isanaka
AU - M. S. Allman
AU - Michael Mills
AU - Maxwell D. Urmey
AU - Peter E. Siegfried
AU - Audrey Faricy
AU - Jin-Sung Kim
AU - Cristina Cîrstoiu
AU - Andrew D. Baczewski
AU - Charles H. Baldwin
AU - Robin Blume-Kohout
PY - 2026
DA - 2026/09/10
PB - arXiv
DO - 10.48550/arxiv.2609.12146
UR - https://arxiv.org/abs/2609.12146
AB - Quantum computing hardware is advancing rapidly toward utility-scale machines that will enable scientific breakthroughs. Many teams are pursuing distinct and difficult-to-compare routes to this goal, using different qubit technologies and logical architectures. Tracking progress toward quantum utility therefore requires rigorous benchmarks that measure computational capability relative to utility-scale challenge problems and enable fair comparison across disparate platforms. Here we demonstrate direct, cross-platform measurement of quantum computational capability using a new benchmark that quantifies the size of the largest computationally relevant quantum circuits that a machine can execute successfully and the speed at which it can execute them. We apply this quantum universal operation performance system (QUOPS) experimentally to leading processors from Quantinuum, Google, and IBM, computing directly on physical qubits. Translating state-of-the-art resource requirements for recognized challenge problems that represent useful quantum computation into effective QUOPS circuit sizes shows that computational capability must grow by 5 orders of magnitude, motivating fault-tolerant approaches. We use the same benchmark to assess the performance of a simple fault-tolerant logical-qubit processor implemented on up to eight [[7,1,3]]-encoded logical qubits using Quantinuum Helios-1, and project the growth of capability across successive generations of fault-tolerant quantum computers to show how QUOPS can track progress toward quantum scientific utility.
ER -