{"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/machine-learned-phase-diagrams-of-generalized","title":"Machine-Learned Phase Diagrams of Generalized Kitaev Honeycomb Magnets","arxiv_id":"2102.01103","date":"2021-02-01","proceeding":null,"authors":["Nihal Rao","Ke Liu","Marc Machaczek","Lode Pollet"],"abstract":"We use a recently developed interpretable and unsupervised machine-learning method, the tensorial kernel support vector machine (TK-SVM), to investigate the low-temperature classical phase diagram of a generalized Heisenberg-Kitaev-$\\Gamma$ ($J$-$K$-$\\Gamma$) model on a honeycomb lattice. Aside from reproducing phases reported by previous quantum and classical studies, our machine finds a hitherto missed nested zigzag-stripy order and establishes the robustness of a recently identified modulated $S_3 \\times Z_3$ phase, which emerges through the competition between the Kitaev and $\\Gamma$ spin liquids, against Heisenberg interactions. The results imply that, in the restricted parameter space spanned by the three primary exchange interactions -- $J$, $K$, and $\\Gamma$, the representative Kitaev material $\\alpha$-${\\rm RuCl}_3$ lies close to the boundaries of several phases, including a simple ferromagnet, the unconventional $S_3 \\times Z_3$ and nested zigzag-stripy magnets. A zigzag order is stabilized by a finite $\\Gamma^{\\prime}$ and/or $J_3$ term, whereas the four magnetic orders may compete in particular if $\\Gamma^{\\prime}$ is anti-ferromagnetic.","url_abs":"https://arxiv.org/abs/2102.01103v2","url_pdf":"https://arxiv.org/pdf/2102.01103v2.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":"abstracts"},"code_links":[{"paper_slug":"machine-learned-phase-diagrams-of-generalized","repo_url":"https://gitlab.physik.uni-muenchen.de/tk-svm/tksvm-op","is_official":1,"mentioned_in_paper":0,"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}