In the framework of the Geant4 toolkit, a new physics process is introduced for the Monte Carlo simulation of quasi-elastic charge exchange reactions of charged pions and kaons on nuclei. In these reactions, neutral mesons are produced. Such process is needed for the detailed simulation of both signal and background reactions in various experimental setups. One of the motivations of this work is a search for rare invisible decays of neutral mesons that could be possible due to interactions with particles of the hypothetical dark sector. In this article, we describe the implementation of the cross sections of charge exchange processes of pions and kaons, the final state generation algorithm and the ways of turning on the processes in the Geant4 application. The validation versus experimental data is discussed.
{"title":"Charge exchange process in Geant4","authors":"A.V. Bagulya , V.M. Grichine , V.N. Ivanchenko , M.M. Kirsanov","doi":"10.1016/j.cpc.2026.110033","DOIUrl":"10.1016/j.cpc.2026.110033","url":null,"abstract":"<div><div>In the framework of the Geant4 toolkit, a new physics process is introduced for the Monte Carlo simulation of quasi-elastic charge exchange reactions of charged pions and kaons on nuclei. In these reactions, neutral mesons are produced. Such process is needed for the detailed simulation of both signal and background reactions in various experimental setups. One of the motivations of this work is a search for rare invisible decays of neutral mesons that could be possible due to interactions with particles of the hypothetical dark sector. In this article, we describe the implementation of the cross sections of charge exchange processes of pions and kaons, the final state generation algorithm and the ways of turning on the processes in the Geant4 application. The validation versus experimental data is discussed.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"321 ","pages":"Article 110033"},"PeriodicalIF":3.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2025-12-30DOI: 10.1016/j.cpc.2025.110011
Ossiel Aguilar-Spíndola, Francisco Sánchez-Ochoa
<div><div>Many first-principles packages employ periodic and symmetry conditions to reduce the computational time and cost. The supercell (SC) method is useful to address periodic systems with different physical perturbations; however, the theoretical definition of a specific SC is a real challenge in Crystallography and Solid State Physics studies. In particular, whether the system is commensurable and made of several two-dimensional (2D) layers with different Bravais lattice, initial local stacking, and interlayer relative orientation. This work presents Nookiin (from the junction of Yucatec Maya words, Nook: ’<em>knit</em>’ or ’<em>wave</em>’; and iin: ’<em>me</em>’), an open-source Python code, designed for the efficient generation of commensurable SCs using geometric methods. Nookiin has an efficient algorithm that minimizes structural distortions at a geometric level, providing an optimized approach for representing 2D heterostructures with a reduced number of atoms. Its modular architecture facilitates adaptation to different problems. Its use through both an interactive console interface and programmatic implementation allows seamless integration into scientific workflows. Additionally, Nookiin offers tools for structural visualization and export of configurations compatible with first-principles codes such as the Vienna <em>ab initio</em> Simulation Package (VASP) code [17]. This report presents the theoretical foundations of the method, the computational implementation of the algorithm, and the results obtained that validate its effectiveness in generating commensurable SCs. With these characteristics, Nookiin establishes itself as a versatile and alternative resource for research in Solid State Physics and Materials Science. The software is openly available at <span><span>github.com/OssielAg/Nook-iin</span><svg><path></path></svg></span>, with a citable release archived at <span><span>doi.org/10.5281/zenodo.15706528</span><svg><path></path></svg></span>.</div><div><strong>Program Summary</strong></div><div><em>Program Title:</em> Nookiin</div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/yvxpwg8sx6.1</span><svg><path></path></svg></span></div><div><em>Developer’s repository link:</em> <span><span>https://github.com/OssielAg/Nook-iin</span><svg><path></path></svg></span>, <span><span>https://doi.org/10.5281/zenodo.14257396</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> GPL-3.0</div><div><em>Programming language:</em> Python</div><div><em>External routines/libraries:</em> numpy, matplotlib</div><div><em>Nature of problem:</em> Van der Waals heterostructures usually comprise many layers with different composition, initial local stacking, Bravais lattices and relative interlayer orientation due to weak dispersion forces. The definition of a periodic and commensurable common cell is a challenge, if physical properties are studied by first principles calculations within
{"title":"Nookiin: Python software to build commensurable multilayer heterostructures","authors":"Ossiel Aguilar-Spíndola, Francisco Sánchez-Ochoa","doi":"10.1016/j.cpc.2025.110011","DOIUrl":"10.1016/j.cpc.2025.110011","url":null,"abstract":"<div><div>Many first-principles packages employ periodic and symmetry conditions to reduce the computational time and cost. The supercell (SC) method is useful to address periodic systems with different physical perturbations; however, the theoretical definition of a specific SC is a real challenge in Crystallography and Solid State Physics studies. In particular, whether the system is commensurable and made of several two-dimensional (2D) layers with different Bravais lattice, initial local stacking, and interlayer relative orientation. This work presents Nookiin (from the junction of Yucatec Maya words, Nook: ’<em>knit</em>’ or ’<em>wave</em>’; and iin: ’<em>me</em>’), an open-source Python code, designed for the efficient generation of commensurable SCs using geometric methods. Nookiin has an efficient algorithm that minimizes structural distortions at a geometric level, providing an optimized approach for representing 2D heterostructures with a reduced number of atoms. Its modular architecture facilitates adaptation to different problems. Its use through both an interactive console interface and programmatic implementation allows seamless integration into scientific workflows. Additionally, Nookiin offers tools for structural visualization and export of configurations compatible with first-principles codes such as the Vienna <em>ab initio</em> Simulation Package (VASP) code [17]. This report presents the theoretical foundations of the method, the computational implementation of the algorithm, and the results obtained that validate its effectiveness in generating commensurable SCs. With these characteristics, Nookiin establishes itself as a versatile and alternative resource for research in Solid State Physics and Materials Science. The software is openly available at <span><span>github.com/OssielAg/Nook-iin</span><svg><path></path></svg></span>, with a citable release archived at <span><span>doi.org/10.5281/zenodo.15706528</span><svg><path></path></svg></span>.</div><div><strong>Program Summary</strong></div><div><em>Program Title:</em> Nookiin</div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/yvxpwg8sx6.1</span><svg><path></path></svg></span></div><div><em>Developer’s repository link:</em> <span><span>https://github.com/OssielAg/Nook-iin</span><svg><path></path></svg></span>, <span><span>https://doi.org/10.5281/zenodo.14257396</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> GPL-3.0</div><div><em>Programming language:</em> Python</div><div><em>External routines/libraries:</em> numpy, matplotlib</div><div><em>Nature of problem:</em> Van der Waals heterostructures usually comprise many layers with different composition, initial local stacking, Bravais lattices and relative interlayer orientation due to weak dispersion forces. The definition of a periodic and commensurable common cell is a challenge, if physical properties are studied by first principles calculations within ","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"321 ","pages":"Article 110011"},"PeriodicalIF":3.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145974178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2026-01-01DOI: 10.1016/j.cpc.2025.110017
M.H. Heraiz , E. Redouane-Salah
In this work, we developed an adaptive grid algorithm to integrate the splitting probability distribution in initial state radiation (ISR) for Large Hadrons Collider (LHC) collisions. By employing a dynamically refined grid, the method concentrates computational resources on regions of physical significance, while avoiding divergence-prone areas associated with collinear and soft emissions. A veto algorithm manages these regions effectively. This approach enhances the accuracy of Monte Carlo simulations, enabling robust phase space generation while minimizing computational cost.
{"title":"Exploring ISR phase space in proton-proton collision with adaptive grid and veto algorithms","authors":"M.H. Heraiz , E. Redouane-Salah","doi":"10.1016/j.cpc.2025.110017","DOIUrl":"10.1016/j.cpc.2025.110017","url":null,"abstract":"<div><div>In this work, we developed an adaptive grid algorithm to integrate the splitting probability distribution in initial state radiation (ISR) for Large Hadrons Collider (LHC) collisions. By employing a dynamically refined grid, the method concentrates computational resources on regions of physical significance, while avoiding divergence-prone areas associated with collinear and soft emissions. A veto algorithm manages these regions effectively. This approach enhances the accuracy of Monte Carlo simulations, enabling robust phase space generation while minimizing computational cost.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"321 ","pages":"Article 110017"},"PeriodicalIF":3.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145974297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Modern heterogeneous high-performance computing (HPC) systems powered by advanced graphics processing unit (GPU) architectures enable accelerating computing with unprecedented performance and scalability. Here, we present a GPU-accelerated solver for the three-dimensional (3D) time-dependent Dirac Equation optimized for distributed HPC systems. The solver named GaDE is designed to simulate the electron dynamics in atoms induced by electromagnetic fields in the relativistic regime. It combines MPI with CUDA/HIP to target both NVIDIA and AMD GPU architectures. We discuss our implementation strategies in which the majority of the computations are carried out on GPUs, taking advantage of the GPU-aware MPI feature to optimize communication performance. We evaluate GaDE on the pre-exascale supercomputer LUMI, powered by AMD MI250X GPU and the HPE’s Slingshot interconnect. Single GPU performance on NVIDIA A100, GH200 and AMD MI250X shows comparable performance between A100 and MI250X in compute and memory bandwidth, with GH200 delivering higher performance. Weak scaling on LUMI demonstrates excellent scalability, achieving 85% parallel efficiency across 2048 GPUs, while strong scaling delivers a 16× speedup on 32 GPUs - 50% efficiency for a communication-intensive, time-dependent Dirac equation solver. These results demonstrate GaDE’s high scalability, making it suitable for exascale systems and enabling predictive simulations for ultra-intense laser experiments probing relativistic quantum effects.
{"title":"GaDE - GPU-acceleration of time-dependent Dirac equation for exascale","authors":"Johanne Elise Vembe , Marcin Krotkiewski , Magnar Bjørgve , Morten Førre , Hicham Agueny","doi":"10.1016/j.cpc.2025.110015","DOIUrl":"10.1016/j.cpc.2025.110015","url":null,"abstract":"<div><div>Modern heterogeneous high-performance computing (HPC) systems powered by advanced graphics processing unit (GPU) architectures enable accelerating computing with unprecedented performance and scalability. Here, we present a GPU-accelerated solver for the three-dimensional (3D) time-dependent Dirac Equation optimized for distributed HPC systems. The solver named GaDE is designed to simulate the electron dynamics in atoms induced by electromagnetic fields in the relativistic regime. It combines MPI with CUDA/HIP to target both NVIDIA and AMD GPU architectures. We discuss our implementation strategies in which the majority of the computations are carried out on GPUs, taking advantage of the GPU-aware MPI feature to optimize communication performance. We evaluate GaDE on the pre-exascale supercomputer LUMI, powered by AMD MI250X GPU and the HPE’s Slingshot interconnect. Single GPU performance on NVIDIA A100, GH200 and AMD MI250X shows comparable performance between A100 and MI250X in compute and memory bandwidth, with GH200 delivering higher performance. Weak scaling on LUMI demonstrates excellent scalability, achieving 85% parallel efficiency across 2048 GPUs, while strong scaling delivers a 16× speedup on 32 GPUs - 50% efficiency for a communication-intensive, time-dependent Dirac equation solver. These results demonstrate GaDE’s high scalability, making it suitable for exascale systems and enabling predictive simulations for ultra-intense laser experiments probing relativistic quantum effects.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"321 ","pages":"Article 110015"},"PeriodicalIF":3.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2025-12-30DOI: 10.1016/j.cpc.2025.110018
Chirag Rathi , Alexander Voinov , Kyle Godbey , Zach Meisel , Kristen Leibensperger
We introduce a new open-access, web-based database (http://nld.ascsn.net), Current Archive of Nuclear Density of Levels (CANDL), that hosts experimental nuclear level density (NLD) datasets from a variety of techniques and energy ranges. Built using the Dash framework in Python, the database is designed to be interactive and user-friendly, allowing researchers to search, visualize, fit, and export NLD data with minimal effort. This resource includes data extracted from evaporation spectra, Oslo method variants, and other experimental techniques that cover excitation energies beyond the neutron resonance region. The database supports on-the-fly fitting with two widely-used phenomenological models—the Constant Temperature (CT) model and the Back-Shifted Fermi Gas (BSFG) model—selected for their simplicity and computational efficiency. Future versions aim to include additional datasets and model types, as well as easy-to-use interfaces to data science techniques. This platform offers a vital tool for the nuclear physics, astrophysics, medicine, and reactor design communities.
{"title":"A new database website for nuclear level densities","authors":"Chirag Rathi , Alexander Voinov , Kyle Godbey , Zach Meisel , Kristen Leibensperger","doi":"10.1016/j.cpc.2025.110018","DOIUrl":"10.1016/j.cpc.2025.110018","url":null,"abstract":"<div><div>We introduce a new open-access, web-based database (<span><span>http://nld.ascsn.net</span><svg><path></path></svg></span>), Current Archive of Nuclear Density of Levels (CANDL), that hosts experimental nuclear level density (NLD) datasets from a variety of techniques and energy ranges. Built using the Dash framework in Python, the database is designed to be interactive and user-friendly, allowing researchers to search, visualize, fit, and export NLD data with minimal effort. This resource includes data extracted from evaporation spectra, Oslo method variants, and other experimental techniques that cover excitation energies beyond the neutron resonance region. The database supports on-the-fly fitting with two widely-used phenomenological models—the Constant Temperature (CT) model and the Back-Shifted Fermi Gas (BSFG) model—selected for their simplicity and computational efficiency. Future versions aim to include additional datasets and model types, as well as easy-to-use interfaces to data science techniques. This platform offers a vital tool for the nuclear physics, astrophysics, medicine, and reactor design communities.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"321 ","pages":"Article 110018"},"PeriodicalIF":3.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper introduces PolyDiM, an open-source C++ library tailored for the development and implementation of polytopal discretization methods for partial differential equations. The library provides robust and modular tools to support advanced numerical techniques, with a focus on the Virtual Element Method in both 2D and 3D settings. PolyDiM is designed to address a wide range of challenging problems, including those involving non-convex geometries, domain decomposition and mixed-dimensional coupling applications. It is integrated with the geometry library GeDiM, and offers interfaces for MATLAB and Python to enhance accessibility. Distinguishing features include support for multiple polynomial bases, advanced stabilization strategies, and efficient local-to-global assembly procedures. PolyDiM aims to serve both as a research tool and a foundation for scalable scientific computing in complex geometrical settings.
{"title":"POLYDIM: A C++ library for POLYtopal DIscretization Methods","authors":"Stefano Berrone , Andrea Borio , Gioana Teora , Fabio Vicini","doi":"10.1016/j.cpc.2025.109937","DOIUrl":"10.1016/j.cpc.2025.109937","url":null,"abstract":"<div><div>This paper introduces PolyDiM, an open-source C++ library tailored for the development and implementation of polytopal discretization methods for partial differential equations. The library provides robust and modular tools to support advanced numerical techniques, with a focus on the Virtual Element Method in both 2D and 3D settings. PolyDiM is designed to address a wide range of challenging problems, including those involving non-convex geometries, domain decomposition and mixed-dimensional coupling applications. It is integrated with the geometry library GeDiM, and offers interfaces for MATLAB and Python to enhance accessibility. Distinguishing features include support for multiple polynomial bases, advanced stabilization strategies, and efficient local-to-global assembly procedures. PolyDiM aims to serve both as a research tool and a foundation for scalable scientific computing in complex geometrical settings.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"320 ","pages":"Article 109937"},"PeriodicalIF":3.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145681670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2025-11-11DOI: 10.1016/j.cpc.2025.109943
Liang Wan , Qingsong Mei , Haowen Liu , Huafeng Zhang , Jun-Ping Du , Shigenobu Ogata , Wen Tong Geng
Despite its widespread use in materials science, conventional molecular dynamics (MD) simulations are severely constrained by timescale limitations. To address this shortcoming, we propose an empirical formulation of accelerated MD method, adapted from a collective-variable-based extended system dynamics framework. While this framework is originally developed for efficient free energy sampling and reaction pathway determination of specific rare events in condensed matter, we have modified it to enable accelerated MD simulation and prediction of microstructure evolution of materials across a broad range of scenarios. In essence, the nearest neighbor off-centering absolute displacement (NNOAD), which quantifies the deviation of an atom from the geometric center of its nearest neighbors in materials, is introduced. We propose that the collection of NNOADs of all atoms can serve as a generalized reaction coordinate for various structural transitions in materials. The NNOAD of each atom, represented by its three components, is coupled with three additional dynamic variables assigned to the atom. Time evolution of the additional dynamic variables follows Langevin equation, while Nosé-Hoover dynamics is employed to thermostat the system. Through careful analysis and benchmark simulations, we established appropriate parameter ranges for the equations in our method. Application of this method to several test cases demonstrates its capability to accelerate MD simulations by several orders of magnitude while maintaining kinetic consistency and good accuracy in predicting long timescale microstructure evolutions of materials. We also provide some preliminary thoughts on theoretical justification of the method, offering insights into its underlying principles.
{"title":"An empirical formulation of accelerated molecular dynamics for simulating and predicting microstructure evolution in materials","authors":"Liang Wan , Qingsong Mei , Haowen Liu , Huafeng Zhang , Jun-Ping Du , Shigenobu Ogata , Wen Tong Geng","doi":"10.1016/j.cpc.2025.109943","DOIUrl":"10.1016/j.cpc.2025.109943","url":null,"abstract":"<div><div>Despite its widespread use in materials science, conventional molecular dynamics (MD) simulations are severely constrained by timescale limitations. To address this shortcoming, we propose an empirical formulation of accelerated MD method, adapted from a collective-variable-based extended system dynamics framework. While this framework is originally developed for efficient free energy sampling and reaction pathway determination of specific rare events in condensed matter, we have modified it to enable accelerated MD simulation and prediction of microstructure evolution of materials across a broad range of scenarios. In essence, the nearest neighbor off-centering absolute displacement (NNOAD), which quantifies the deviation of an atom from the geometric center of its nearest neighbors in materials, is introduced. We propose that the collection of NNOADs of all atoms can serve as a generalized reaction coordinate for various structural transitions in materials. The NNOAD of each atom, represented by its three components, is coupled with three additional dynamic variables assigned to the atom. Time evolution of the additional dynamic variables follows Langevin equation, while Nosé-Hoover dynamics is employed to thermostat the system. Through careful analysis and benchmark simulations, we established appropriate parameter ranges for the equations in our method. Application of this method to several test cases demonstrates its capability to accelerate MD simulations by several orders of magnitude while maintaining kinetic consistency and good accuracy in predicting long timescale microstructure evolutions of materials. We also provide some preliminary thoughts on theoretical justification of the method, offering insights into its underlying principles.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"320 ","pages":"Article 109943"},"PeriodicalIF":3.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145681708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2025-11-19DOI: 10.1016/j.cpc.2025.109942
Roman Vetter
This article introduces TinyDEM, a lightweight implementation of a full-fledged discrete element method (DEM) solver in 3D. Newton’s damped equations of motion are solved explicitly for translations and rotations of a polydisperse ensemble of dry, soft, granular spherical particles, using quaternions to represent their orientation in space without gimbal lock. Particle collisions are modeled as inelastic and frictional, including full exchange of torque. With a general particle-mesh collision routine, complex rigid geometries can be simulated. TinyDEM is designed to be a compact standalone program written in simple C++11, devoid of explicit pointer arithmetics and advanced concepts such as manual memory management or polymorphism. It is parallelized with OpenMP and published freely under the 3-clause BSD license. TinyDEM can serve as an entry point into classical DEM simulations or as a foundation for more complex models of particle dynamics.
PROGRAM SUMMARY
Program Title: TinyDEM
CPC Library link to program files: (to be added by Technical Editor)
Developer’s repository link: —
Licensing provisions: BSD 3-clause
Programming language: C++11
Supplementary material: Videos 1–6
Nature of problem:
Dynamics and statics of polydisperse ensembles of visco-elastic, frictional, non-adhesive spherical particles (such as in granular media) in 1D, 2D and 3D. All three modes of torque exchange (sliding, rolling and twisting) are modeled with slip-stick Coulomb friction.
Solution method:
The discrete element method is used to solve Newton’s damped equations of motion for particle translations and rotations with the semi-implicit Euler scheme. Quaternions are used to represent particle orientations. For efficient collision detection, a linked cell list is used. A static geometrical environment can be defined with a discrete mesh. The program is parallelized with OpenMP for shared-memory systems.
Additional comments including restrictions and unusual features:
The source code is exceptionally compact, consisting of only about 600 commented lines in two files—a header and a source file. With no dependencies, it is highly portable and accessible, making it also suited for educational purposes.
{"title":"TinyDEM: Minimal open granular DEM code with sliding, rolling and twisting friction","authors":"Roman Vetter","doi":"10.1016/j.cpc.2025.109942","DOIUrl":"10.1016/j.cpc.2025.109942","url":null,"abstract":"<div><div>This article introduces TinyDEM, a lightweight implementation of a full-fledged discrete element method (DEM) solver in 3D. Newton’s damped equations of motion are solved explicitly for translations and rotations of a polydisperse ensemble of dry, soft, granular spherical particles, using quaternions to represent their orientation in space without gimbal lock. Particle collisions are modeled as inelastic and frictional, including full exchange of torque. With a general particle-mesh collision routine, complex rigid geometries can be simulated. TinyDEM is designed to be a compact standalone program written in simple C++11, devoid of explicit pointer arithmetics and advanced concepts such as manual memory management or polymorphism. It is parallelized with OpenMP and published freely under the 3-clause BSD license. TinyDEM can serve as an entry point into classical DEM simulations or as a foundation for more complex models of particle dynamics.</div><div><strong>PROGRAM SUMMARY</strong></div><div><em>Program Title:</em> TinyDEM</div><div><em>CPC Library link to program files:</em> (to be added by Technical Editor)</div><div><em>Developer’s repository link:</em> —</div><div><em>Licensing provisions:</em> BSD 3-clause</div><div><em>Programming language:</em> C++11</div><div><em>Supplementary material:</em> Videos 1–6</div><div><strong>Nature of problem:</strong></div><div>Dynamics and statics of polydisperse ensembles of visco-elastic, frictional, non-adhesive spherical particles (such as in granular media) in 1D, 2D and 3D. All three modes of torque exchange (sliding, rolling and twisting) are modeled with slip-stick Coulomb friction.</div><div><strong>Solution method:</strong></div><div>The discrete element method is used to solve Newton’s damped equations of motion for particle translations and rotations with the semi-implicit Euler scheme. Quaternions are used to represent particle orientations. For efficient collision detection, a linked cell list is used. A static geometrical environment can be defined with a discrete mesh. The program is parallelized with OpenMP for shared-memory systems.</div><div><strong>Additional comments including restrictions and unusual features:</strong></div><div>The source code is exceptionally compact, consisting of only about 600 commented lines in two files—a header and a source file. With no dependencies, it is highly portable and accessible, making it also suited for educational purposes.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"320 ","pages":"Article 109942"},"PeriodicalIF":3.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145616218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2025-12-09DOI: 10.1016/j.cpc.2025.109986
Feng Han , Jianguo Wang , Guoliang Peng , Xueting Shi
In this paper, a physics-informed multiresolution wavelet neural network (PIMWNN) method is proposed for solving partial differential equations (PDEs). This method uses the multiresolution wavelet neural network (MWNN) to approximate unknown functions, then substituting the MWNN into PDEs and training the MWNN by least-squares algorithm. We apply the proposed method to various problems, including stationary/nonstationary advection, diffusion and advection-diffusion problems, and linear/nonlinear time-dependent problems. Numerical experiments show that the PIMWNN method can achieve higher accuracy and faster speed than Physics Informed Neural Networks (PINNs). Moreover, the PIMWNN method can handle different boundary conditions easily and solve the time-dependent problems efficiently. The proposed method is expected to solve the spectral bias problem in network training. These characteristics show the great potential of the PIMWNN method used in the field of numerical solving methods for PDEs.
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Pub Date : 2026-03-01Epub Date: 2025-12-06DOI: 10.1016/j.cpc.2025.109982
Mayanak K Gupta
Machine learning and computing advancements have made it possible to carry out simulations over longer lengths and timescales. This has opened up new opportunities for understanding materials in different thermodynamic conditions. These large-scale simulations help analyze experimental measurements such as inelastic scattering and study diffusion in solid electrolytes for potential use in future batteries. However, analyzing these large datasets presents challenges in extracting useful thermodynamic and transport properties. To address these challenges, the Fortran-based code MDLAB has been developed. This code processes large-scale molecular dynamics simulation trajectories from various software and computes important quantities like mean squared displacements, phonon spectra, pair-distribution functions, simulated neutron/X-ray spectra and more. This comprehensive approach allows for a deeper understanding of material behavior, ultimately enhancing our overall grasp of condensed matter physics.
{"title":"A molecular dynamics postprocessing tool for analyzing the structure and dynamics of materials","authors":"Mayanak K Gupta","doi":"10.1016/j.cpc.2025.109982","DOIUrl":"10.1016/j.cpc.2025.109982","url":null,"abstract":"<div><div>Machine learning and computing advancements have made it possible to carry out simulations over longer lengths and timescales. This has opened up new opportunities for understanding materials in different thermodynamic conditions. These large-scale simulations help analyze experimental measurements such as inelastic scattering and study diffusion in solid electrolytes for potential use in future batteries. However, analyzing these large datasets presents challenges in extracting useful thermodynamic and transport properties. To address these challenges, the Fortran-based code MDLAB has been developed. This code processes large-scale molecular dynamics simulation trajectories from various software and computes important quantities like mean squared displacements, phonon spectra, pair-distribution functions, simulated neutron/X-ray spectra and more. This comprehensive approach allows for a deeper understanding of material behavior, ultimately enhancing our overall grasp of condensed matter physics.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"320 ","pages":"Article 109982"},"PeriodicalIF":3.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145880069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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