Reciprocal Space Attention for Learning Long-Range Interactions

• URL: http://arxiv.org/abs/2510.13055v1
• Date: Wed, 15 Oct 2025 00:35:47 GMT
• Title: Reciprocal Space Attention for Learning Long-Range Interactions
• Authors: Hariharan Ramasubramanian, Alvaro Vazquez-Mayagoitia, Ganesh Sivaraman, Atul C. Thakur,
• Abstract summary: We introduce Reciprocal-Space Attention (RSA), a framework designed to capture long-range interactions in the Fourier domain.<n> RSA can be integrated with any existing local or semi-local MLIP framework.<n>We show that RSA consistently captures long-range physics across a broad range of chemical and materials systems.
• Score: 2.5432391525687748
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Machine learning interatomic potentials (MLIPs) have revolutionized the modeling of materials and molecules by directly fitting to ab initio data. However, while these models excel at capturing local and semi-local interactions, they often prove insufficient when an explicit and efficient treatment of long-range interactions is required. To address this limitation, we introduce Reciprocal-Space Attention (RSA), a framework designed to capture long-range interactions in the Fourier domain. RSA can be integrated with any existing local or semi-local MLIP framework. The central contribution of this work is the mapping of a linear-scaling attention mechanism into Fourier space, enabling the explicit modeling of long-range interactions such as electrostatics and dispersion without relying on predefined charges or other empirical assumptions. We demonstrate the effectiveness of our method as a long-range correction to the MACE backbone across diverse benchmarks, including dimer binding curves, dispersion-dominated layered phosphorene exfoliation, and the molecular dipole density of bulk water. Our results show that RSA consistently captures long-range physics across a broad range of chemical and materials systems. The code and datasets for this work is available at https://github.com/rfhari/reciprocal_space_attention

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