QEMScore: How Much Does the Measurement Add to Learned Quantum Error Mitigation?

arXiv:2609.17896 · quant-ph, cs.LG · Submitted 2026-09-15 · Read on arXiv

quant-ph, cs.LG

Submitted: 2026-09-15

Updated: 2026-09-15

Comments: 55 pages, including references and appendices

Code: https://github.com/yzhao062/QEMScore

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 47× in this paper · explained in 2 episodes
• Ablation — 42× in this paper · explained in 1 episode
• Calibration — 28× in this paper · explained in 7 episodes
• Accuracy — 24× in this paper · explained in 1 episode
• Aggregation — 8× in this paper · explained in 1 episode
• Benchmarking — 8× in this paper · explained in 4 episodes
• Distribution Shift — 4× in this paper · explained in 6 episodes
• Verification — 4× in this paper · explained in 2 episodes
• Allocator — 3× in this paper · explained in 1 episode
• Amortization — 3× in this paper · explained in 1 episode
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Addressability — 2× in this paper · explained in 1 episode
• Generalization — 2× in this paper · explained in 13 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Abstention — 1× in this paper · explained in 1 episode
• Conformal Prediction — 1× in this paper · explained in 5 episodes
• Core — 1× in this paper · explained in 2 episodes
• EMMA — 1× in this paper · explained in 2 episodes
• International Conference on Quantum Computing and Engineering — 1× in this paper
• Quantum Circuits — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Zero-Shot Transfer — 1× in this paper · explained in 4 episodes

Sources

• Better than classical? The subtle art of benchmarking quantum machine learning models
• A Quantum Approximate Optimization Algorithm

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