Machine-Learned Phase Diagrams of Generalized Kitaev Honeycomb Magnets

Code

• gitlab.physik.uni-muenchen.de/tk-svm/tksvm-op
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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- (J-K-) 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 Z_3 phase, which emerges through the competition between the Kitaev and spin liquids, against Heisenberg interactions. The results imply that, in the restricted parameter space spanned by the three primary exchange interactions -- J, K, and , the representative Kitaev material - RuCl_3 lies close to the boundaries of several phases, including a simple ferromagnet, the unconventional S_3 Z_3 and nested zigzag-stripy magnets. A zigzag order is stabilized by a finite ^ and/or J_3 term, whereas the four magnetic orders may compete in particular if ^ is anti-ferromagnetic.

Reproductions