Google AI Quantum and collaborators produced experimental quantum data from superconducting processor experiments. The data likely contains results from quantum approximate optimization runs on non-planar graph problems. The dataset is associated with an Open Access paper published on arXiv.
Use Cases
- Benchmarking quantum optimization algorithms based on experimental results
- Analyzing the performance of superconducting processors on non-planar graph problems
- Comparing theoretical QAOA predictions with experimental data
- Studying quantum hardware limitations for combinatorial optimization
Strengths
- Data originates from a published experiment by Google AI Quantum, a leading research group
- Associated with a specific, peer-reviewed arXiv paper providing context
Limitations
- Column-level documentation is absent; field semantics must be inferred after download
- Row count is unknown, which may limit suitability assessment
- Last update date is unknown; freshness unverified
Provenance
- Source
- Google AI Quantum And Collaborators
- Collection Method
- Experimental data from superconducting processor runs