QED-C Application-Specific Benchmark Profiles
Extension of the QED-C benchmark framework focused on application-specific benchmark profiles that measure quantum hardware capability across problem-relevant circuit shapes and depths. The volumetric benchmarking methodology plots result quality against circuit width and depth to produce capability maps, enabling comparison across different quantum platforms for specific application domains such as optimization, chemistry, and machine learning.[1]
- Algorithm: Volumetric benchmarking framework
- Category: other
- Framework: Qiskit, Cirq, Braket
- Reproducible: Yes
- Published:
- QED-C
- volumetric
- application-oriented
- benchmark-suite
- standardization
What algorithm does QED-C Application-Specific Benchmark Profiles use?
QED-C Application-Specific Benchmark Profiles uses the Volumetric benchmarking framework algorithm, categorized under other.
Frequently Asked Questions
What is the QED-C Application-Specific Benchmark Profiles benchmark?
Extension of the QED-C benchmark framework focused on application-specific benchmark profiles that measure quantum hardware capability across problem-relevant circuit shapes and depths. The volumetric benchmarking methodology plots result quality against circuit width and depth to produce capability maps, enabling comparison across different quantum platforms for specific application domains such as optimization, chemistry, and machine learning.
Is QED-C Application-Specific Benchmark Profiles reproducible?
Yes, this benchmark is reproducible.
Sources
- "Scalable Full-Stack Benchmarks for Quantum Computers", accessed 2026-03-19 — arXiv
- "QED-C Application-Oriented Benchmarks GitHub Repository", accessed 2026-03-19 — github.com