libMobility: A Python library for hydrodynamics at the Smoluchowski level

Effective hydrodynamic modeling is crucial for accurately predicting fluid-particle interactions in diverse fields such as biophysics and materials science. Developing and implementing hydrodynamic algorithms is challenging due to the complexity of fluid dynamics, necessitating efficient management of large-scale computations and sophisticated boundary conditions. Furthermore, adapting these algorithms for use on massively parallel architectures such as GPUs adds an additional layer of complexity. This paper presents the libMobility software library, which offers a suite of CUDA-enabled solvers for simulating hydrodynamic interactions in particulate systems at the Rotne-Prager-Yamakawa level. The library facilitates precise simulations of particle displacements influenced by external forces and torques, including both the deterministic and stochastic components. Notable features of libMobility include its ability to handle linear and angular displacements, thermal fluctuations, and various domain geometries effectively. With an interface in Python, libMobility provides comprehensive tools for researchers in computational fluid dynamics and related fields to simulate particle mobility efficiently. This article details the technical architecture, functionality, and wide-ranging applications of libMobility. libMobility is available at https://github.com/stochasticHydroTools/libMobility.

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Publication Details

Journal
The Journal of Chemical Physics
Published
2026-01-27
DOI
https://doi.org/10.1063/5.0304943
Citations
1
Primary Topic
Lattice Boltzmann Simulation Studies
Type
article
Field-Weighted Citation Impact
41.77
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article

libMobility: A Python library for hydrodynamics at the Smoluchowski level

Raul P. Pelaez, Ryker Fish, Pablo Diez-Silva, Adam Carter et al.
1 citations
The Journal of Chemical Physics
Lattice Boltzmann Simulation Studies
41.77
article

libMobility: A Python library for hydrodynamics at the Smoluchowski level

Raul P. Pelaez, Ryker Fish, Pablo Diez-Silva, Adam Carter, Brennan Sprinkle, Rafael Delgado-Buscalioni
article en
1 citations

Abstract

Effective hydrodynamic modeling is crucial for accurately predicting fluid-particle interactions in diverse fields such as biophysics and materials science. Developing and implementing hydrodynamic algorithms is challenging due to the complexity of fluid dynamics, necessitating efficient management of large-scale computations and sophisticated boundary conditions. Furthermore, adapting these algorithms for use on massively parallel architectures such as GPUs adds an additional layer of complexity. This paper presents the libMobility software library, which offers a suite of CUDA-enabled solvers for simulating hydrodynamic interactions in particulate systems at the Rotne-Prager-Yamakawa level. The library facilitates precise simulations of particle displacements influenced by external forces and torques, including both the deterministic and stochastic components. Notable features of libMobility include its ability to handle linear and angular displacements, thermal fluctuations, and various domain geometries effectively. With an interface in Python, libMobility provides comprehensive tools for researchers in computational fluid dynamics and related fields to simulate particle mobility efficiently. This article details the technical architecture, functionality, and wide-ranging applications of libMobility. libMobility is available at https://github.com/stochasticHydroTools/libMobility.

The Journal of Chemical PhysicsVol. 164(4)
Centre National de la Recherche Scientifique (FR), Colorado School of Mines (US), Sorbonne Université (FR), PHENIX laboratory (FR), Universidad Autónoma de Madrid (ES)
Industry, innovation and infrastructure
Openalex Percentile: Top 1%
Lattice Boltzmann Simulation Studies
41.77
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libMobility: A Python library for hydrodynamics at the Smoluchowski level — Raul P. Pelaez, Ryker Fish, et al. · The Journal of Chemical Physics (2026) | TGRS Research Map | TGRS