Grassmann–Wilson Invariant Normal Form for Acoustic-Subspace Geometry in Crystalline Solids: Reproducibility Archive
Description
This dataset provides the complete reproducibility archive supporting the Grassmann–Wilson invariant normal form for acoustic-subspace geometry in crystalline solids. It contains the analysis and figure-generation code, the complete canonical numerical output archives, statistical and external-validation results, normal-form coefficients, perturbative and analytic derivation records, Wilson-loop reconstruction and covariance audits, figure-level numerical data, execution provenance, software-environment information, and SHA-256 integrity manifests. The third-party PBEsol and Alexandria PBE source datasets are not redistributed. Instead, the archive provides exact source-population manifests, cryptographic identities, official acquisition information, and verification tools enabling reconstruction of the source snapshots used in the study. The included workflow records the analysis sequence and dependencies required for end-to-end numerical reproduction.
Files
Steps to reproduce
1. Extract the reproducibility archive to a local directory. 2. Use Python 3.12.0. Create a clean virtual environment, install pip 25.1.1, and install the exact package versions listed in environment/requirements_exact.txt. The original execution environment is recorded in environment/python_environment.json and environment/installed_packages.csv. 3. Verify the integrity of the extracted archive by running: python tools/verify_archive.py 4. Choose a clean working directory <WORK_ROOT>. Reconstruct the exact PBEsol and Alexandria PBE source snapshots from the official source by running: python tools/download_source_snapshots.py –destination <WORK_ROOT> –dataset all –include-displacements The download utility uses the source manifests distributed with this archive and accepts files only when their byte size and SHA-256 identity match the recorded source snapshot. 5. Independently verify the reconstructed source populations by running: python tools/verify_source_snapshots.py –data-root <WORK_ROOT> –verify-displacements The expected material populations are 10,028 PBEsol files and 9,958 Alexandria PBE files. 6. Execute the complete analysis sequence by running: python tools/run_workflow.py –work-root <WORK_ROOT> The runner reconstructs the exact execution filenames of the archived code revisions and follows the recorded 75-step workflow. The corresponding canonical numerical outputs are provided in results/complete_output_archives for independent comparison. Workflow provenance, declared dependencies, code identities, source identities, normal-form derivations, analytic traceability records, and figure-level numerical data are included in the archive. Third-party raw source datasets are not redistributed.