{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/sensitivity-of-a-chaotic-logic-gate","title":"Sensitivity of a Chaotic Logic Gate","arxiv_id":"2202.07617","date":"2022-02-15","proceeding":null,"authors":["Noeloikeau Charlot","Daniel J. Gauthier"],"abstract":"Chaotic logic gates or `chaogates' are a promising mixed-signal approach to designing universal computers. However, chaotic systems are exponentially sensitive to small perturbations, and the effects of noise can cause chaotic computers to fail. Here, we examine the sensitivity of a simulated chaogate to noise and other parameter variations (such as differences in supply voltage). We find that the regions in parameter space corresponding to chaotic dynamics coincide with the regions of maximum error in the computation. Further, this error grows exponentially within 4-10 iterations of the chaotic map. As such, we discuss the fundamental limitations of chaotic computing, and suggest potential improvements. Our Python simulation methods are open-source and available at https://github.com/Noeloikeau/chaogate.","url_abs":"https://arxiv.org/abs/2202.07617v1","url_pdf":"https://arxiv.org/pdf/2202.07617v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"sensitivity-of-a-chaotic-logic-gate","repo_url":"https://github.com/noeloikeau/chaogate","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}