{"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/an-efficient-algorithm-for-computing-the","title":"An efficient algorithm for computing the Baker-Campbell-Hausdorff series and some of its applications","arxiv_id":"0810.2656","date":"2008-10-15","proceeding":null,"authors":["Fernando Casas","Ander Murua"],"abstract":"We provide a new algorithm for generating the Baker--Campbell--Hausdorff (BCH) series $Z = \\log(\\e^X \\e^Y)$ in an arbitrary generalized Hall basis of the free Lie algebra $\\mathcal{L}(X,Y)$ generated by $X$ and $Y$. It is based on the close relationship of $\\mathcal{L}(X,Y)$ with a Lie algebraic structure of labeled rooted trees. With this algorithm, the computation of the BCH series up to degree 20 (111013 independent elements in $\\mathcal{L}(X,Y)$) takes less than 15 minutes on a personal computer and requires 1.5 GBytes of memory. We also address the issue of the convergence of the series, providing an optimal convergence domain when $X$ and $Y$ are real or complex matrices.","url_abs":"http://arxiv.org/abs/0810.2656v1","url_pdf":"http://arxiv.org/pdf/0810.2656v1.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":"an-efficient-algorithm-for-computing-the","repo_url":"https://github.com/bottler/iisignature","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"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}