aiqbench analysis
Error bars on IBM quantum hardware, as currently estimated, can understate real calculation errors by 12 to 32 times on oxygen and beryllium hydride VQE runs, so reported uncertainties should not be taken at face value. Error mitigation techniques such as zero-noise extrapolation help but do not close the gap, and some mitigated results fall outside physically plausible ranges. For researchers using quantum hardware for chemistry, independent validation before relying on any result matters more than the stated precision.
Residuals Exceed Uncertainty by Factors up to 32 in IBM VQE Quantum Evaluation
Reported accuracy in quantum calculations can be deeply misleading: molecular energies from IBM’s processors showed residuals exceeding stated uncertainties by up to thirtytwofold. While zero-noise extrapolation reduced oxygen calculation errors on one processor by nearly eightyfour per cent, twirled readout error extinction offered further gains, up to 80 millihartree per job, but with unpredictable variability. This work demonstrates that current uncertainty quantification may not reflect actual computational flaws.
Statistical error bars on quantum computer calculations have been unreliable indicators of accuracy. Calculations for oxygen and beryllium hydride molecules show raw results can exceed reported uncertainties by a factor up to thirty-two; this highlights limitations in current methods used to quantify calculation errors. The Fraunhofer Institute has revealed that standard methods of assessing accuracy in quantum computer calculations can be sharply misleading. Analyses on oxygen and beryllium hydride molecules showed actual calculation errors were between…
Excerpt shown under the publisher's RSS terms · 76 words · full text and figures are on the publisher's site
Related coverage
Uncertainty Evaluation: Bridging Machine Learning and Measurement Science
arXiv · Oct 15, 2026
How Reliable are AMR Parser Outputs? Uncertainty Estimation for AMR Parsing
arXiv · Oct 12, 2026
Robust Conformal Consensus: Multi-Agent LLM-as-a-Judge Interval Evaluation with Conformal Prediction
arXiv · Sep 9, 2026
A Unified Risk View of Uncertainty: Posterior Risk for Disentanglement and Evaluation Beyond Proxies
arXiv · Aug 7, 2026