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We describe a local surrogate model for use in conjunction with globalstructure search methods. The model follows the Gaussian approximationpotential (GAP) formalism and is based on a the smooth overlap of atomicpositions descriptor with sparsification in terms of a reduced number of localenvironments using mini-batch $k$-means. The model is implemented in theAtomistic Global Optimization X framework and used as a partial replacement ofthe local relaxations in basin hopping structure search. The approach is shownto be robust for a wide range of atomistic system including molecules,nano-particles, surface supported clusters and surface thin films. The benefitsin a structure search context of a local surrogate model are demonstrated. Thisincludes the ability to transfer learning from smaller systems as well as thepossibility to perform concurrent multi-stoichiometry searches.

Atomistic structure search using local surrogate mode