We present a multiscale computational approach that combines atomistic spin models with the cluster multipole (CMP) method. The CMP method enables a systematic and accurate generation of complex noncollinear magnetic structures using symmetry-adapted representations. The parameters of the spin model are derived from density functional theory using the magnetic force theorem, with the paramagnetic state as a reference. The energy landscape of CMP-generated structures is inspected at the model Hamiltonian level and sets of low-energy magnetic structures are identified for each material candidate. The inclusion of relativistic antisymmetric and anisotropic pair interactions lifts partially the degeneracy among these most stable structures. To demonstrate the applicability and predictive capability of the method, we apply it to the noncollinear ${\mathrm{Mn}}_{3}X$ and collinear ${\mathrm{Fe}}_{3}X$ $(X=\mathrm{Ga},\mathrm{Ge}, \text{and} \mathrm{Sn})$ kagome compounds. The computational efficiency of the method in identifying low-energy structures among multiple CMP configurations highlights its potential for high-throughput screening of complex magnets with unknown magnetic order.

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• Antiferromagnetism
• Exchange interaction
• Ferromagnetism
• Coherent potential approximation
• Density functional theory
• Materials modeling