SQuASH Surrogate Benchmark Dataset for Quantum Architecture Search (QAS)

This dataset supports the SQuASH benchmark for Quantum Architecture Search (QAS), as presented in our paper. It includes training and evaluation data used for surrogate model learning, structured into multiple problem instances. Each subdirectory contains a database file with information extracted from .pkl files, such as initial PQC, optimal PQC and target evaluation metric, e.g., fidelity or train/test accuracy.

The dataset is organized for direct integration with the SQuASH GitHub repository and is designed to accelerate QAS research and support reproducible benchmarking.