Physics-inspired Equivariant Descriptors of Non-bonded Interactions

• URL: http://arxiv.org/abs/2308.13208v2
• Date: Tue, 3 Oct 2023 18:18:23 GMT
• Title: Physics-inspired Equivariant Descriptors of Non-bonded Interactions
• Authors: Kevin K. Huguenin-Dumittan, Philip Loche, Ni Haoran and Michele Ceriotti
• Abstract summary: We present an extension of the long distance equivariant (LODE) framework that can handle diverse LR interactions in a consistent way. We provide a direct physical interpretation of these using the multipole expansion which allows for simpler and more efficient implementations.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: One essential ingredient in many machine learning (ML) based methods for atomistic modeling of materials and molecules is the use of locality. While allowing better system-size scaling, this systematically neglects long-range (LR) effects, such as electrostatics or dispersion interaction. We present an extension of the long distance equivariant (LODE) framework that can handle diverse LR interactions in a consistent way, and seamlessly integrates with preexisting methods by building new sets of atom centered features. We provide a direct physical interpretation of these using the multipole expansion, which allows for simpler and more efficient implementations. The framework is applied to simple toy systems as proof of concept, and a heterogeneous set of molecular dimers to push the method to its limits. By generalizing LODE to arbitrary asymptotic behaviors, we provide a coherent approach to treat arbitrary two- and many-body non-bonded interactions in the data-driven modeling of matter.

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