Predicting QAOA Parameters for MAX-CUT from Infinite-Size Limit

Raw data used to generate figures for a research paper on predicting parameters for the Quantum Approximate Optimization Algorithm (QAOA) for the MAX-CUT problem. The data was created by Sami Boulebnane of University College London. The associated code for figure generation is hosted in a separate GitHub repository.

Use Cases

• Validate parameter prediction methods for QAOA based on data from the infinite-size limit.
• Reproduce or extend the analysis of QAOA performance for the MAX-CUT problem.
• Benchmark new quantum optimization algorithms against the parameter data.
• Study the relationship between theoretical infinite-size limits and finite-size system performance in QAOA.

Strengths

• Data is directly linked to a specific research paper, providing traceability.
• Associated code for figure generation is publicly available, supporting reproducibility.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and data scale are unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Sami Boulebnane, University College London

Collection Method

Likely generated via computational simulations or theoretical calculations for the associated research paper.