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Accelerating molecular dynamics simulations using fast Ewald summation with prolates
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  • Published: 21 May 2026

Accelerating molecular dynamics simulations using fast Ewald summation with prolates

  • Jiuyang Liang  ORCID: orcid.org/0000-0003-0247-41491,2,
  • Libin Lu  ORCID: orcid.org/0000-0003-0745-94311,
  • Alex Barnett  ORCID: orcid.org/0009-0004-9732-24241,
  • Leslie Greengard  ORCID: orcid.org/0000-0003-2895-87151,3 &
  • …
  • Shidong Jiang  ORCID: orcid.org/0000-0001-7482-81671 

Nature Communications (2026) Cite this article

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Subjects

  • Computational chemistry
  • Computational methods
  • Computational science

Abstract

The evaluation of long-range Coulomb interactions is a significant cost in molecular dynamics (MD), even when using Particle Mesh Ewald (PME) or Particle-Particle-Particle-Mesh (PPPM) methods, which rely on Ewald splitting and the fast Fourier transform to achieve near-linear scaling. We introduce ESP—Ewald summation with prolate spheroidal wave functions (PSWFs)—which leads to a more efficient Fourier representation and a reduction in the required grid size, global communication, and particle-grid operations, without loss of accuracy. We have integrated the ESP method into two widely-used open-source MD packages, LAMMPS and GROMACS, enabling rapid comparison and adoption. Relative to PME/PPPM baselines at error tolerances 10−3 to 10−4, ESP gives roughly a 3-fold acceleration of electrostatic interactions, and a 2.5-fold speed-up in the MD simulation when using about 103 compute cores. At high accuracy (10−5), these increase to 10-fold for the far-field electrostatics and 5-fold for MD simulation. Furthermore, we show that the accelerated codes have improved strong scaling with core count, and validate them in realistic long-time biological and material simulations. ESP thus offers a practical, drop-in path to reduce the time-to-solution and energy footprint of MD workflows.

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Acknowledgements

The authors are grateful for discussions with Pilar Cossio and Berk Hess. They thank the Scientific Computing Core at the Flatiron Institute for support and for providing computational resources. The Flatiron Institute is a division of the Simons Foundation. J.L. discloses support for the research of this work from the National Natural Science Foundation of China (Grant No. 12401570) and the China Postdoctoral Science Foundation (Grant No. 2024M751948). All other authors declare no relevant funding.

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Authors and Affiliations

  1. Center for Computational Mathematics, Flatiron Institute, Simons Foundation, New York, NY, USA

    Jiuyang Liang, Libin Lu, Alex Barnett, Leslie Greengard & Shidong Jiang

  2. School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai, China

    Jiuyang Liang

  3. Courant Institute of Mathematical Sciences, New York University, New York, NY, USA

    Leslie Greengard

Authors
  1. Jiuyang Liang
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  2. Libin Lu
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  5. Shidong Jiang
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Corresponding authors

Correspondence to Alex Barnett, Leslie Greengard or Shidong Jiang.

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Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

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Cite this article

Liang, J., Lu, L., Barnett, A. et al. Accelerating molecular dynamics simulations using fast Ewald summation with prolates. Nat Commun (2026). https://doi.org/10.1038/s41467-026-73232-8

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  • Received: 16 December 2025

  • Accepted: 07 May 2026

  • Published: 21 May 2026

  • DOI: https://doi.org/10.1038/s41467-026-73232-8

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