fix pimd/langevin: An efficient implementation of path integral molecular dynamics in LAMMPS

Y Yifan Li A Axel Gomez (Department of Chemistry) K Kehan Cai (Department of Chemistry, Princeton University 1 , Princeton, New Jersey 08544,) C Chunyi Zhang (Department of Chemistry, Princeton University) L Li Fu (College of Materials and Environmental Engineering, Hangzhou Dianzi University, Hangzhou, China.) W Weile Jia (University of Chinese Academy of Sciences 4 , Beijing 101408,) Y Yotam M. Y. Feldman (School of Chemistry, Tel Aviv University 5 , Tel Aviv 6997801,) O Ofir Blumer (School of Chemistry, Tel Aviv University 5 , Tel Aviv 6997801,) J Jacob Higer (School of Physics, Tel Aviv University 6 , Tel Aviv 6997801,) B Barak Hirshberg (School of Chemistry, Tel Aviv University 5 , Tel Aviv 6997801,) S Shenzhen Xu (School of Materials Science and Engineering) A Axel Kohlmeyer (Institute for Computational Molecular Science, Temple University, Science Education and Research Center (035-07) 8 , Philadelphia, Pennsylvania 19122,) R Roberto Car (Department of Chemistry, Princeton University)

Abstract

Path integral molecular dynamics (PIMD), which maps a quantum particle onto a fictitious classical system of ring polymers and propagates the “beads” of this extended classical system using molecular dynamics, is widely used to capture nuclear quantum effects in molecular simulations. Accurate PIMD calculations typically require a large number of beads and are, therefore, computationally demanding. While software packages such as i-PI offer comprehensive PIMD functionality, the high efficiency of simulations driven by machine learning interatomic potentials, such as deep potential (DP), calls for more efficient PIMD implementations that fully exploit modern massively parallel supercomputers. Here, we present fix pimd/langevin, an efficient PIMD implementation in LAMMPS that supports commonly used features and leverages the Message Passing Interface architecture of LAMMPS to achieve high computational efficiency. We demonstrate the usage, validate the correctness of our code using liquid water as a representative example, and provide a comprehensive overview of the supported features. Then, we discuss several important technical aspects of the implementation. Using DP simulations of water as a benchmark, we show that our implementation achieves several-fold acceleration compared to i-PI. Finally, we report strong and weak scaling results that demonstrate the favorable parallel performance of our code.

Article Details

Volume / Issue Vol. 164, Issue 14
Published April 14, 2026
ISSN 0021-9606
Publisher American Institute of Physics

Journal Info

The Journal of Chemical Physics

American Institute of Physics

ISSN: 0021-9606 Physical Sciences

Authors (13)

Y

Yifan Li

A

Axel Gomez

Department of Chemistry

K

Kehan Cai

Department of Chemistry, Princeton University 1 , Princeton, New Jersey 08544,

C

Chunyi Zhang

Department of Chemistry, Princeton University

L

Li Fu

College of Materials and Environmental Engineering, Hangzhou Dianzi University, Hangzhou, China.

W

Weile Jia

University of Chinese Academy of Sciences 4 , Beijing 101408,

Y

Yotam M. Y. Feldman

School of Chemistry, Tel Aviv University 5 , Tel Aviv 6997801,

O

Ofir Blumer

School of Chemistry, Tel Aviv University 5 , Tel Aviv 6997801,

J

Jacob Higer

School of Physics, Tel Aviv University 6 , Tel Aviv 6997801,

B

Barak Hirshberg

School of Chemistry, Tel Aviv University 5 , Tel Aviv 6997801,

S

Shenzhen Xu

School of Materials Science and Engineering

A

Axel Kohlmeyer

Institute for Computational Molecular Science, Temple University, Science Education and Research Center (035-07) 8 , Philadelphia, Pennsylvania 19122,

R

Roberto Car

Department of Chemistry, Princeton University