Published October 16, 2026
| Version v1.1.0
Software
Open
Hash-committed pre-registration and exact unlearning make belief revisions in autonomous SiGeC semiconductor campaigns checkable
Authors/Creators
- 1. Materials Science & Engineering, The University of Utah
Description
Code, data and figure scripts for the paper "Hash-committed pre-registration and exact unlearning make belief revisions in autonomous SiGeC semiconductor campaigns checkable" (Advanced Intelligent Discovery (Wiley)). Taylor D. Sparks acknowledges support from the Army Research Office Materials Design, under Contract No. W911NF-23-1-0333.
Notes
Code (Python, shell and SLURM scripts) is released under the MIT License (LICENSE). Data, result files and figures are released under the Creative Commons Attribution 4.0 International licence (LICENSE-CC-BY-4.0.txt). Archived third-party datasets keep their own terms; their sources are cited in the paper.
Files
Sparks-Ackolf-HOLAR-Autonomous-Labs/TurnstileSDL_Audit-v1.1.0.zip
Additional details
Related works
- Is supplement to
- Software: https://github.com/Sparks-Ackolf-HOLAR-Autonomous-Labs/TurnstileSDL_Audit/tree/v1.1.0 (URL)