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Published April 16, 2025 | Version 1.0.0
Dataset Open

SQuASH Surrogate Benchmark Dataset for Quantum Architecture Search (QAS)

Creators

  • 1. ROR icon Fraunhofer Society

Description

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.

Table of contents (English)

  • Top-level folder: raw_ghz_a.zip/

    • raw_test_ghz_a.zip/ – contains  the test subset for the ghz_a search space and includes

      • raw_test_ghz_a_data.zip with  .pckl files storing each PQC along with its metadata and 
      • test_ghz_a.db file - circuits metadata  as DB

    • raw_train_ghz_a.zip/ – contains  the train subset without augmentation for the ghz_a search space and includes

      • raw_train_ghz_a_data.zip with  .pckl files storing each PQC along with its metadata and 
      • train_ghz_a.db file - circuits metadata as DB

    • raw_train_ghz_a_augmented.zip/ – contains  the train subset incl. augmented PQCs for the ghz_a search space and includes

      • raw_train_ghz_a_augmented_data.zip with  .pckl files storing each PQC along with its metadata and 
      • train_ghz_a_augmented.db file -circuits metadata as DV
  • Top-level folders: raw_ghz_b.zip/ has the same structure but data for the search space ghz_b

  • Top-level folders: ls_a.zip/

      • raw_ls_a_data.zip/ – contains  .pckl files storing each PQC along with its metadata for the search space l

      • ls_a.db file - circuits metadata  as DB

        Note that for train/test splitting, ls_a space uses the automatical split specified in gen_dataset.py with random seed `42`.
  • Top-level folders: graph_data_ghz_a.zip/,  graph_data_ghz_b.zip/,graph_data_ls_a.zip/ – contain  .pt files, i.e., all data subsets for particular search spaces, with circuits converted into directed acyclic graph respresentation (DAG). This representation can be directly used to tran a GCN. 

Files

graph_data_ghz_a.zip

Files (6.2 GB)

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Additional details

Dates

Available
2025-04-16

Software

Repository URL
https://github.com/SQuASH-bench/SQuASH
Programming language
Python
Development Status
Active