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| Main Authors: | , , |
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| Format: | Recurso digital |
| Language: | |
| Published: |
Zenodo
2025
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| Subjects: | |
| Online Access: | https://doi.org/10.5281/zenodo.17684948 |
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Table of Contents:
- <p>This dataset and code repository accompanies the publication introducing BA-QEC, the first quantum-error-correction decoder explicitly inspired by biological immune-system architecture. BA-QEC integrates a Bayesian prior derived from human TCRβ CDR3 length distributions and an adaptive clonal-expansion memory mechanism to improve decoding performance in topological quantum codes. Simulations of a distance-7 rotated surface code demonstrate 22% threshold improvement from the biological prior alone, and up to 61% enhancement when combined with clonal memory under temporally correlated (1/f-type) noise. All code is open-source (MIT license) and fully reproducible in <10 minutes on Google Colab.</p> <p>The repository includes:</p> <p>Python notebooks for Stim-based and PyMatching-based simulations,</p> <p>Clonal-expansion cache implementation,</p> <p>Scripts for reproducing figures and pseudothreshold plots,</p> <p>Documentation on integrating the biological prior into MWPM decoding.</p> <p>This work establishes a novel link between adaptive immunity and quantum error correction, offering a new paradigm for biologically inspired, efficient, and adaptive decoders.</p>