New scoring system aims to measure quantum computers' real-world utility
Researchers at Sandia National Laboratories have introduced a metric called QUOPS to quantify how useful a quantum computer is for practical computations. The score compares a machine's operational capacity against the requirements of specific algorithms, such as simulating the FeMoco molecule or breaking cryptography. Tests on leading quantum computers from Google, IBM, and Quantinuum show they currently fall far short of the scores needed for these tasks.
The QUOPS metric works by having a quantum computer execute a standardized set of circuits, from which researchers derive a numerical score reflecting both qubit count and operational speed. That figure can then be matched against the score required by a target algorithm, such as simulating FeMoco or defeating RSA encryption. If the machine's score falls short, the computation is expected to fail.
Testing on systems from Google, IBM, and Quantinuum revealed scores below 2000, while useful algorithms demand scores exceeding 200,000. Even Quantinuum's fault-tolerant Helios-1 configuration managed only about 40. Researchers view fault-tolerant machines as the likely path forward, with logical qubits needing to surpass ordinary qubits in QUOPS before practical utility becomes achievable.
The QUOPS framework could give researchers, funders, and industry observers a common yardstick for comparing quantum machines, potentially steering investment toward designs that score higher. If widely adopted, it may accelerate progress toward practical applications in chemistry and cryptography, but it could also oversimplify what makes a quantum computer genuinely powerful. Policymakers and businesses tracking quantum readiness may find the metric useful for planning, though its long-term relevance remains uncertain as the technology evolves.