Online Resource 2
Shot saturation and evidence limits in quantum-AI hardware benchmarks
Discover Quantum Science

Author: Vikram Lex
Affiliation: KarLex AI, Newark, DE, USA
Email: vikram@karlexai.com
ORCID: https://orcid.org/0009-0009-8364-244X

Historical numerical summaries and source snapshots, analysis code, dependency versions, complete result records, editable manuscript materials, and instructions for reproducing the numerical analyses and figures.

Extract the complete archive into an empty directory. The original code/ and paper/ directory layout is preserved. Start with paper/hardware_benchmarks/REPRODUCE.md and code/hardware_benchmark/README.md. Both editable manuscript sources and numerical inputs are included, so the generated figures and tables can be reinserted by compiling those original sources. The separately supplied manuscript_source.zip contains the same submitted main text in the flat layout used by the journal's submission system.

The reproduction instructions use local CPU computation. Historical quantum/GPU workloads are not rerun by the hardware reanalysis commands; the theory experiment uses simulated independent measurements and frozen model traces. Archived scripts are evidence of the earlier workflow, not instructions to purchase new cloud executions.

Licensing and attribution: code/LICENSE records the project-code license. Third-party model and dataset terms remain those of their respective sources; this notice does not relicense them. Raw text corpora and pretrained model weights are not included. The earlier QHM project preprint is cited at https://doi.org/10.21203/rs.3.rs-9825475/v1 (Research Square, CC BY 4.0).

SHA256SUMS.txt covers every other archive member. Original source and data archive checksum lists are retained as well. RESOURCE_METADATA.json records their archive hashes and this resource's bibliographic identity.
