LATTE: an atomic environment descriptor based on Cartesian tensor contractions

• URL: http://arxiv.org/abs/2405.08137v1
• Date: Mon, 13 May 2024 19:31:00 GMT
• Title: LATTE: an atomic environment descriptor based on Cartesian tensor contractions
• Abstract summary: We propose a new descriptor for local atomic environments, to be used in combination with machine learning models for the construction of interatomic potentials. The Local Atomics Trainable Expansion (LATTE) allows for the efficient construction of a variable number of many-body terms with learnable parameters. We compare this new descriptor to existing ones on several systems, showing it to be competitive with very fast potentials at one end of the spectrum, and to an accuracy close to the state of the art.
• Score: 3.2771631221674333
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We propose a new descriptor for local atomic environments, to be used in combination with machine learning models for the construction of interatomic potentials. The Local Atomic Tensors Trainable Expansion (LATTE) allows for the efficient construction of a variable number of many-body terms with learnable parameters, resulting in a descriptor that is efficient, expressive, and can be scaled to suit different accuracy and computational cost requirements. We compare this new descriptor to existing ones on several systems, showing it to be competitive with very fast potentials at one end of the spectrum, and extensible to an accuracy close to the state of the art.

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