Polarizable atomic multipoles for learning long-range electrostatics

• URL: http://arxiv.org/abs/2605.05746v1
• Date: Thu, 07 May 2026 06:40:53 GMT
• Title: Polarizable atomic multipoles for learning long-range electrostatics
• Abstract summary: Long-range electrostatics and polarization remain central obstacles to extending machine learning interatomic potentials.<n>We introduce a semi-local framework for learning electrostatics from energies and forces using polarizable atomic multipoles.
• Score: 7.061065106576948
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Long-range electrostatics and polarization remain central obstacles to extending machine learning interatomic potentials (MLIPs) to ionic, polar, and interfacial systems. Here, we introduce a semi-local framework for learning electrostatics from energies and forces using polarizable atomic multipoles. Local equivariant descriptors predict environment-dependent latent monopoles, dipoles, and quadrupoles, while residual non-local charge transfer and polarization are captured by non-self-consistent linear response in induced charges and dipoles. Across four diverse benchmarks and four short-range MLIP architectures, the multipole hierarchy and response terms systematically improve potential energy surface accuracy, with the largest gains in systems where long-range effects are essential. More importantly, the learned latent variables recover physically meaningful electrical responses: accurate Born effective charge tensors, emergent polarizabilities, infrared spectra in close agreement with experiments, and semi-quantitative Raman spectra for bulk water and hybrid MAPbI$_3$ perovskite. This systematically improvable, physically transparent framework enables MLIPs trained on standard energy and force labels to predict polarization-sensitive observables.

Related papers

• An SO(3)-equivariant reciprocal-space neural potential for long-range interactions [84.08721947253646]
  Long-range electrostatic and polarization interactions play a central role in molecular and condensed-phase systems.<n>Modern SO(3)-equivariant neural potentials achieve high accuracy for short-range chemistry, but cannot represent the anisotropic, slowly decaying multipolar correlations governing realistic materials.<n>Here we introduce EquiEwald, a unified neural interatomic potential that embeds an Ewald-inspired reciprocal-space formulation within an irreducible SO(3)-equivariant framework.
  arXiv  Detail & Related papers  (2026-03-19T01:16:11Z)
• Quantum Bipolar Thermoelectricity [39.3098730337656]
  bipolar quantum thermoelectricity could provide a new route for spectroscopic sensing of electromagnetic modes.<n>Results suggest that bipolar quantum thermoelectricity could provide a new route for spectroscopic sensing of electromagnetic modes.
  arXiv  Detail & Related papers  (2025-08-05T08:46:39Z)
• A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials [8.414405667524889]
  Latent Ewald Summation (LES) method infers electrostatic interactions, polarization, and Born effective charges (BECs)<n>We present LES as a standalone library, compatible with any short-range MLIP, and demonstrate its integration with methods such as MACE, NequIP, CACE, and CHGNet.<n>We scale LES to large and chemically diverse data by training MACELES-OFF on the SPICE set containing molecules and clusters, making a universal MLIP with electrostatics for organic systems including biomolecules.
  arXiv  Detail & Related papers  (2025-07-18T18:21:45Z)
• Machine learning interatomic potential can infer electrical response [3.502816712907136]
  Machine learning interatomic potentials (MLIPs) offer an efficient and scalable alternative to quantum mechanical methods.<n>We show that polarization and Born effective charge (BEC) tensors can be directly extracted from long-range MLIPs.<n>This work extends the capability MLIPs to predict electrical response--without training on charges or polarization or BECs--and enables accurate modeling of electric-field-driven processes in diverse systems at scale.
  arXiv  Detail & Related papers  (2025-04-07T15:14:07Z)
• Learning charges and long-range interactions from energies and forces [3.502816712907136]
  We introduce the Latent Ewald Summation method, which captures long-range electrostatics without explicitly learning atomic charges or charge equilibration.<n>We benchmark LES on diverse and challenging systems, including charged molecules, ionic liquid, electrolyte solution, polar dipeptides, surface adsorber, electrolyte/solid interfaces, and solid-solid interfaces.<n>Our results show that LES can effectively infer physical partial charges, dipole and quadrupole moments, as well as achieve better accuracy compared to methods that explicitly learn charges.
  arXiv  Detail & Related papers  (2024-12-19T23:24:44Z)
• Spin Squeezing with Magnetic Dipoles [37.93140485169168]
  Entanglement can improve the measurement precision of quantum sensors beyond the shot noise limit.<n>We take advantage of the magnetic dipole-dipole interaction native to most neutral atoms to realize spin-squeezed states.<n>We achieve 7.1 dB of metrologically useful squeezing using the finite-range spin exchange interactions in an erbium quantum gas microscope.
  arXiv  Detail & Related papers  (2024-11-11T18:42:13Z)
• Long-range interactions in Weyl dense atomic arrays protected from dissipation and disorder [41.94295877935867]
  Long-range interactions are a key resource in many quantum phenomena and technologies. We show how to design the polaritonic bands of these atomic metamaterials to feature a pair of frequency-isolated Weyl points. These Weyl excitations can thus mediate interactions that are simultaneously long-range, due to their gapless nature; robust, due to the topological protection of Weyl points; and decoherence-free, due to their subradiant character.
  arXiv  Detail & Related papers  (2024-06-18T20:15:16Z)
• In-situ-tunable spin-spin interactions in a Penning trap with in-bore optomechanics [41.94295877935867]
  We present an optomechanical system for in-situ tuning of the coherent spin-motion and spin-spin interaction strength. We characterize the system using measurements of the induced mean-field spin precession. These experiments show approximately a $times2$ variation in the ratio of the coherent to incoherent interaction strength.
  arXiv  Detail & Related papers  (2024-01-31T11:00:39Z)
• Tailoring Near-Field-Mediated Photon Electron Interactions with Light Polarization [0.0]
  We investigate the effect of the polarization and the spatial profile of plasmonic near-field distributions on shaping free-electrons. We show that polarization of the exciting light can be used as a control knop for disseminating acceleration and deceleration path ways. We also demonstrate the possibility of tailoring the shape of localized plasmons by incorporating specific arrangements of nanorods.
  arXiv  Detail & Related papers  (2022-11-17T10:44:44Z)
• Complete Excitation of Discrete Quantum Systems by Single Free Electrons [0.0]
  We find a maximum achievable excitation probability of $100%$, which requires specific conditions relating to the coupling strength and the transition symmetry. Our work reveals the potential of free electrons to control localized excitations and delineates the boundaries of such control.
  arXiv  Detail & Related papers  (2022-02-21T10:22:17Z)
• A background-free optically levitated charge sensor [50.591267188664666]
  We introduce a new technique to model and eliminate dipole moment interactions limiting the performance of sensors employing levitated objects. As a demonstration, this is applied to the search for unknown charges of a magnitude much below that of an electron. As a by-product of the technique, the electromagnetic properties of the levitated objects can also be measured on an individual basis.
  arXiv  Detail & Related papers  (2021-12-20T08:16:28Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.