Pub Date : 2025-12-19DOI: 10.1016/j.cpc.2025.110007
Cong-Zhang Gao , Jian-Wei Yin , Ying Cai , Xu Liu , Zheng-Feng Fan , Pei Wang , Shao-Ping Zhu
In recent decades, radiative transfer through the binary stochastic mixtures (i.e., a fraction of particulate high-Z materials are randomly dispersed into the low-Z background material, where the label Z means the atomic number) has received great attention in many scientific and engineering disciplines, accurate and efficient simulations in multidimensions are much in demand. In this work, we primarily focus on the efficient algorithms for accurately simulating radiative transfer in binary stochastic mixtures in two dimensions. Our computational model is to solve the radiation-material coupled equations for an ensemble of binary stochastic mixtures. In this context, a subgrid-based nearest-neighbor searching (SNNS) algorithm is introduced to explicitly model the binary stochastic mixture, resulting in an O(N) scaling with the number of particles, which is more flexible than the fast random sequential addition (RSA) algorithm. In order to accurately determine the grid-based parameters, a particle-resolved algorithm is developed by dividing the relationship between the particle’s location and the grid into four categories, reproducing analytical results exactly and efficiently. A parallel algorithm using the spatial domain decomposition with directed acylic graph (DAG) techniques is proposed to efficiently solve the radiation-material coupled equations. These algorithms are combined to enable accurate and efficient simulations in two dimensions, which is validated by reported benchmark results. We find that convergent results require a sufficiently high resolution of the particle and a high-order quadrature. Although results based on one physical realization are somewhat representative, the ensemble-averaged results are more meaningful to avoid the statistical anomalies in some cases. Moreover, case studies on the influence of particle size distribution, the validation of the effective opacity models, and the particle size effect are presented and analyzed. Our work provides efficient algorithms for routinely simulating radiative transfer in binary stochastic mixtures in multidimensions, which can yield the benchmark results for analytical homogenized models of relevance.
{"title":"Efficient algorithms for accurately simulating radiative transfer in binary stochastic mixtures in two dimensions","authors":"Cong-Zhang Gao , Jian-Wei Yin , Ying Cai , Xu Liu , Zheng-Feng Fan , Pei Wang , Shao-Ping Zhu","doi":"10.1016/j.cpc.2025.110007","DOIUrl":"10.1016/j.cpc.2025.110007","url":null,"abstract":"<div><div>In recent decades, radiative transfer through the binary stochastic mixtures (i.e., a fraction of particulate high-<em>Z</em> materials are randomly dispersed into the low-<em>Z</em> background material, where the label <em>Z</em> means the atomic number) has received great attention in many scientific and engineering disciplines, accurate and efficient simulations in multidimensions are much in demand. In this work, we primarily focus on the efficient algorithms for accurately simulating radiative transfer in binary stochastic mixtures in two dimensions. Our computational model is to solve the radiation-material coupled equations for an ensemble of binary stochastic mixtures. In this context, a subgrid-based nearest-neighbor searching (SNNS) algorithm is introduced to explicitly model the binary stochastic mixture, resulting in an <em>O</em>(<em>N</em>) scaling with the number of particles, which is more flexible than the fast random sequential addition (RSA) algorithm. In order to accurately determine the grid-based parameters, a particle-resolved algorithm is developed by dividing the relationship between the particle’s location and the grid into four categories, reproducing analytical results exactly and efficiently. A parallel algorithm using the spatial domain decomposition with directed acylic graph (DAG) techniques is proposed to efficiently solve the radiation-material coupled equations. These algorithms are combined to enable accurate and efficient simulations in two dimensions, which is validated by reported benchmark results. We find that convergent results require a sufficiently high resolution of the particle and a high-order quadrature. Although results based on one physical realization are somewhat representative, the ensemble-averaged results are more meaningful to avoid the statistical anomalies in some cases. Moreover, case studies on the influence of particle size distribution, the validation of the effective opacity models, and the particle size effect are presented and analyzed. Our work provides efficient algorithms for routinely simulating radiative transfer in binary stochastic mixtures in multidimensions, which can yield the benchmark results for analytical homogenized models of relevance.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"320 ","pages":"Article 110007"},"PeriodicalIF":3.4,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145836435","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 : 2025-12-18DOI: 10.1016/j.cpc.2025.110008
Julian Soltau , Arne Walter , Frank Duschek , Thomas Dekorsy
We present a new simulation framework for the detection of aerosol fluorescence with integration spheres. Utilizing a Monte Carlo based ray-tracing approach, aerosol fluorescence within integrating sphere setups is simulated from photon generation through laser excitation over interactions with the setup components to losses and finally detection. Through modular design, the position and number of openings, sensors, etc. can be freely configured. Therefore, potential experimental setups can be evaluated with regard to overall performance, bottlenecks can be identified and the impact of different component parameters determined.
PROGRAM SUMMARY
Program Title: AFIS - Aerosol Fluorescence in Integrating Spheres
CPC Library link to program files:https://doi.org/10.17632/nj9dg3tr6d.1
Licensing provisions: BSD 3-clause
Programming language: Python
Nature of problem: Measuring (bio-)aerosol fluorescence is a complex task, especially for thin aerosols. In order to evaluate new experimental setups utilizing an integrating sphere, simulation data is essential to asses which system configurations yield promising results. Therefore, a simulation environment capable of calculating the different interactions within the setup is necessary, ideally providing a high level of customizability for the simulated setups.
Solution method: The AFIS simulation framework utilizes a ray-tracing approach based on a classical Monte Carlo description of the involved processes. Through batch-wise processing and penalization the computational efficiency is increased.
{"title":"AFIS - A simulation framework for detection of aerosol fluorescence with integrating spheres","authors":"Julian Soltau , Arne Walter , Frank Duschek , Thomas Dekorsy","doi":"10.1016/j.cpc.2025.110008","DOIUrl":"10.1016/j.cpc.2025.110008","url":null,"abstract":"<div><div>We present a new simulation framework for the detection of aerosol fluorescence with integration spheres. Utilizing a Monte Carlo based ray-tracing approach, aerosol fluorescence within integrating sphere setups is simulated from photon generation through laser excitation over interactions with the setup components to losses and finally detection. Through modular design, the position and number of openings, sensors, etc. can be freely configured. Therefore, potential experimental setups can be evaluated with regard to overall performance, bottlenecks can be identified and the impact of different component parameters determined.</div><div><strong>PROGRAM SUMMARY</strong></div><div><em>Program Title:</em> AFIS - <strong>A</strong>erosol <strong>F</strong>luorescence in <strong>I</strong>ntegrating <strong>S</strong>pheres</div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/nj9dg3tr6d.1</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> BSD 3-clause</div><div><em>Programming language:</em> Python</div><div><em>Nature of problem:</em> Measuring (bio-)aerosol fluorescence is a complex task, especially for thin aerosols. In order to evaluate new experimental setups utilizing an integrating sphere, simulation data is essential to asses which system configurations yield promising results. Therefore, a simulation environment capable of calculating the different interactions within the setup is necessary, ideally providing a high level of customizability for the simulated setups.</div><div><em>Solution method:</em> The AFIS simulation framework utilizes a ray-tracing approach based on a classical Monte Carlo description of the involved processes. Through batch-wise processing and penalization the computational efficiency is increased.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"321 ","pages":"Article 110008"},"PeriodicalIF":3.4,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145974179","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 : 2025-12-18DOI: 10.1016/j.cpc.2025.109993
A. Diaw, C.A. Johnson, E.A. Unterberg, J. Nichols
OpenEdge is a collaborative, open-source, object-oriented Direct Simulation Monte Carlo (DSMC) code, designed specifically for plasma simulations in magnetic fusion environments. The code features include advanced structures, robust capabilities, and an effective parallelization strategy, all of which significantly enhance performance. It includes specialized modules for managing complex particle interactions, including collisions, ionization/recombination, and reflection/sputtering. Benchmarks and performance analyses have confirmed its efficiency and scalability. Versatile and adaptable, OpenEdge is applied across a broad spectrum of plasma-material interaction studies and charged particle transport in various fusion research settings.
{"title":"OpenEdge: A collaborative, open-source, multi-purpose direct simulation Monte Carlo for plasma simulation in magnetic fusion environments","authors":"A. Diaw, C.A. Johnson, E.A. Unterberg, J. Nichols","doi":"10.1016/j.cpc.2025.109993","DOIUrl":"10.1016/j.cpc.2025.109993","url":null,"abstract":"<div><div>OpenEdge is a collaborative, open-source, object-oriented Direct Simulation Monte Carlo (DSMC) code, designed specifically for plasma simulations in magnetic fusion environments. The code features include advanced structures, robust capabilities, and an effective parallelization strategy, all of which significantly enhance performance. It includes specialized modules for managing complex particle interactions, including collisions, ionization/recombination, and reflection/sputtering. Benchmarks and performance analyses have confirmed its efficiency and scalability. Versatile and adaptable, OpenEdge is applied across a broad spectrum of plasma-material interaction studies and charged particle transport in various fusion research settings.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"320 ","pages":"Article 109993"},"PeriodicalIF":3.4,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145836437","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 : 2025-12-18DOI: 10.1016/j.cpc.2025.109995
Stephen E. Gant , Francesco Ricci , Guy Ohad , Ashwin Ramasubramaniam , Leeor Kronik , Jeffrey B. Neaton
We introduce an automated workflow for generating non-empirical Wannier-localized optimally-tuned screened range-separated hybrid (WOT-SRSH) functionals. WOT-SRSH functionals have been shown to yield highly accurate fundamental band gaps, band structures, and optical spectra for bulk and 2D semiconductors and insulators. Our workflow automatically and efficiently determines the WOT-SRSH functional parameters for a given crystal structure and composition, approximately enforcing the correct screened long-range Coulomb interaction and an ionization potential ansatz. In contrast to previous manual tuning approaches, our tuning procedure relies on a new search algorithm that only requires a few hybrid functional calculations with minimal user input. We demonstrate our workflow on 23 previously studied semiconductors and insulators, reporting the same high level of accuracy. By automating the tuning process and improving its computational efficiency, the approach outlined here enables applications of the WOT-SRSH functional to compute spectroscopic and optoelectronic properties for a wide range of materials.
{"title":"Automated workflow for non-empirical Wannier-localized optimal tuning of range-separated hybrid functionals","authors":"Stephen E. Gant , Francesco Ricci , Guy Ohad , Ashwin Ramasubramaniam , Leeor Kronik , Jeffrey B. Neaton","doi":"10.1016/j.cpc.2025.109995","DOIUrl":"10.1016/j.cpc.2025.109995","url":null,"abstract":"<div><div>We introduce an automated workflow for generating non-empirical Wannier-localized optimally-tuned screened range-separated hybrid (WOT-SRSH) functionals. WOT-SRSH functionals have been shown to yield highly accurate fundamental band gaps, band structures, and optical spectra for bulk and 2D semiconductors and insulators. Our workflow automatically and efficiently determines the WOT-SRSH functional parameters for a given crystal structure and composition, approximately enforcing the correct screened long-range Coulomb interaction and an ionization potential ansatz. In contrast to previous manual tuning approaches, our tuning procedure relies on a new search algorithm that only requires a few hybrid functional calculations with minimal user input. We demonstrate our workflow on 23 previously studied semiconductors and insulators, reporting the same high level of accuracy. By automating the tuning process and improving its computational efficiency, the approach outlined here enables applications of the WOT-SRSH functional to compute spectroscopic and optoelectronic properties for a wide range of materials.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"320 ","pages":"Article 109995"},"PeriodicalIF":3.4,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145973029","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 : 2025-12-18DOI: 10.1016/j.cpc.2025.110004
Alberto Cuadra, César Huete, Marcos Vera
The Combustion Toolbox (CT) is a newly developed open-source thermochemical code designed to solve problems involving chemical equilibrium for both gas- and condensed-phase species. The kernel of the code is based on the theoretical framework set forth by NASA’s computer program CEA (Chemical Equilibrium with Applications) while incorporating new algorithms that significantly improve both convergence rate and robustness. The thermochemical properties are computed under the ideal gas approximation using an up-to-date version of NASA’s 9-coefficient polynomial fits. These fits use the Third Millennium database, which includes the available values from Active Thermochemical Tables. Combustion Toolbox is programmed in MATLAB with an object-oriented architecture composed of three main modules: CT-EQUIL, CT-SD, and CT-ROCKET. The kernel module, CT-EQUIL, minimizes the Gibbs/Helmholtz free energy of the system using the technique of Lagrange multipliers combined with a multidimensional Newton-Raphson method, upon the condition that two state functions are used to define the mixture properties (e.g., enthalpy and pressure). CT-SD solves processes involving strong changes in dynamic pressure, such as steady shock and detonation waves under normal and oblique incidence angles. Finally, CT-ROCKET estimates rocket engine performance under highly idealized conditions. The new tool is equipped with a versatile Graphical User Interface and has been successfully used for teaching and research activities over the last six years. Results are in excellent agreement with CEA, Cantera within Caltech’s Shock and Detonation Toolbox (SD-Toolbox), and the Thermochemical Equilibrium Abundances (TEA) code. CT is available under an open-source GPLv3 license via GitHub https://github.com/CombustionToolbox/combustion_toolbox, and its documentation can be found in https://combustion-toolbox-website.readthedocs.io.
{"title":"Combustion Toolbox: An open-source thermochemical code for gas- and condensed-phase problems involving chemical equilibrium","authors":"Alberto Cuadra, César Huete, Marcos Vera","doi":"10.1016/j.cpc.2025.110004","DOIUrl":"10.1016/j.cpc.2025.110004","url":null,"abstract":"<div><div>The Combustion Toolbox (CT) is a newly developed open-source thermochemical code designed to solve problems involving chemical equilibrium for both gas- and condensed-phase species. The kernel of the code is based on the theoretical framework set forth by NASA’s computer program CEA (Chemical Equilibrium with Applications) while incorporating new algorithms that significantly improve both convergence rate and robustness. The thermochemical properties are computed under the ideal gas approximation using an up-to-date version of NASA’s 9-coefficient polynomial fits. These fits use the Third Millennium database, which includes the available values from Active Thermochemical Tables. Combustion Toolbox is programmed in MATLAB with an object-oriented architecture composed of three main modules: CT-EQUIL, CT-SD, and CT-ROCKET. The kernel module, CT-EQUIL, minimizes the Gibbs/Helmholtz free energy of the system using the technique of Lagrange multipliers combined with a multidimensional Newton-Raphson method, upon the condition that two state functions are used to define the mixture properties (e.g., enthalpy and pressure). CT-SD solves processes involving strong changes in dynamic pressure, such as steady shock and detonation waves under normal and oblique incidence angles. Finally, CT-ROCKET estimates rocket engine performance under highly idealized conditions. The new tool is equipped with a versatile Graphical User Interface and has been successfully used for teaching and research activities over the last six years. Results are in excellent agreement with CEA, Cantera within Caltech’s Shock and Detonation Toolbox (SD-Toolbox), and the Thermochemical Equilibrium Abundances (TEA) code. CT is available under an open-source GPLv3 license via GitHub <span><span>https://github.com/CombustionToolbox/combustion_toolbox</span><svg><path></path></svg></span>, and its documentation can be found in <span><span>https://combustion-toolbox-website.readthedocs.io</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"320 ","pages":"Article 110004"},"PeriodicalIF":3.4,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145880067","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 : 2025-12-18DOI: 10.1016/j.cpc.2025.110002
Josiah Roberts , Biswas Rijal , Simon Divilov , Jon-Paul Maria , William G. Fahrenholtz , Douglas E. Wolfe , Donald W. Brenner , Stefano Curtarolo , Eva Zurek
<div><div>We present the Plan for Robust and Accurate Potentials (PRAPs), a software package for training and using moment tensor potentials (MTPs) in concert with the Machine Learned Interatomic Potentials (MLIP) software package. PRAPs provides an automated workflow to train MTPs using active learning procedures, and a variety of utilities to ease and improve workflows when utilizing the MLIP software. PRAPs was originally developed in the context of crystal structure prediction, in which one calculates convex hulls and predicts low energy metastable and thermodynamically stable structures, but the potentials PRAPs develops are not limited to such applications. PRAPs produces two potentials, one capable of rough estimates of the energies, forces and stresses of almost any chemical structure in the specified compositional space – the Robust Potential – and a second potential intended to provide more accurate descriptions of ground state and metastable structures – the Accurate Potential. We also present a Python library, <em>mliputils</em>, designed to assist users in working with the chemical structural files used by the MLIP package.</div></div><div><h3>PROGRAM SUMMARY</h3><div><em>Program Title:</em> The Plan for Robust and Accurate Potentials (PRAPs)</div><div><em>CPC Library link to program files:</em> (to be added by Technical Editor)</div><div><em>Developer’s repository link:</em> <span><span>https://github.com/Dryctarth/PRAPs.git</span><svg><path></path></svg></span></div><div><em>Code Ocean capsule:</em> (to be added by Technical Editor)</div><div><em>Licensing provisions(please choose one):</em> BSD 3-clause</div><div><em>Programming language:</em> Bash, Python</div><div><em>Supplementary material:</em> User manual</div><div><em>Nature of problem:</em> Keeping track of all the steps involved in training moment tensor potentials across several systems has proven to be a challenge in need of project management. For every large step, like training, there are several small, mundane commands that need to be handled, and these must all be repeated identically across any chemical system users may care about (while tracking variations). Finally, communication must be made between the AFLOW, MLIP, and VASP programs.</div><div><em>Solution method:</em> The PRAPs package incorporates a degree of automation, handling the different job submissions and tasks needed to train multiple moment tensor potentials, file management, identifying and removing unphysical chemical structures, and performing some analytical tasks. The package also includes some simple utility functions to allow users to better read, write, and manipulate MLIP’s chemical structure file format.</div><div><em>Additional comments including restrictions and unusual features:</em> Requires a local installation of Automatic FLOW (AFLOW) v3.10+, the Vienna <em>ab initio</em> Software Package (VASP) v5+, and the Machine Learning for Interatomic Potentials (MLIP) v2+ program packages.</di
{"title":"A software package for generating robust and accurate potentials using the moment tensor potential framework","authors":"Josiah Roberts , Biswas Rijal , Simon Divilov , Jon-Paul Maria , William G. Fahrenholtz , Douglas E. Wolfe , Donald W. Brenner , Stefano Curtarolo , Eva Zurek","doi":"10.1016/j.cpc.2025.110002","DOIUrl":"10.1016/j.cpc.2025.110002","url":null,"abstract":"<div><div>We present the Plan for Robust and Accurate Potentials (PRAPs), a software package for training and using moment tensor potentials (MTPs) in concert with the Machine Learned Interatomic Potentials (MLIP) software package. PRAPs provides an automated workflow to train MTPs using active learning procedures, and a variety of utilities to ease and improve workflows when utilizing the MLIP software. PRAPs was originally developed in the context of crystal structure prediction, in which one calculates convex hulls and predicts low energy metastable and thermodynamically stable structures, but the potentials PRAPs develops are not limited to such applications. PRAPs produces two potentials, one capable of rough estimates of the energies, forces and stresses of almost any chemical structure in the specified compositional space – the Robust Potential – and a second potential intended to provide more accurate descriptions of ground state and metastable structures – the Accurate Potential. We also present a Python library, <em>mliputils</em>, designed to assist users in working with the chemical structural files used by the MLIP package.</div></div><div><h3>PROGRAM SUMMARY</h3><div><em>Program Title:</em> The Plan for Robust and Accurate Potentials (PRAPs)</div><div><em>CPC Library link to program files:</em> (to be added by Technical Editor)</div><div><em>Developer’s repository link:</em> <span><span>https://github.com/Dryctarth/PRAPs.git</span><svg><path></path></svg></span></div><div><em>Code Ocean capsule:</em> (to be added by Technical Editor)</div><div><em>Licensing provisions(please choose one):</em> BSD 3-clause</div><div><em>Programming language:</em> Bash, Python</div><div><em>Supplementary material:</em> User manual</div><div><em>Nature of problem:</em> Keeping track of all the steps involved in training moment tensor potentials across several systems has proven to be a challenge in need of project management. For every large step, like training, there are several small, mundane commands that need to be handled, and these must all be repeated identically across any chemical system users may care about (while tracking variations). Finally, communication must be made between the AFLOW, MLIP, and VASP programs.</div><div><em>Solution method:</em> The PRAPs package incorporates a degree of automation, handling the different job submissions and tasks needed to train multiple moment tensor potentials, file management, identifying and removing unphysical chemical structures, and performing some analytical tasks. The package also includes some simple utility functions to allow users to better read, write, and manipulate MLIP’s chemical structure file format.</div><div><em>Additional comments including restrictions and unusual features:</em> Requires a local installation of Automatic FLOW (AFLOW) v3.10+, the Vienna <em>ab initio</em> Software Package (VASP) v5+, and the Machine Learning for Interatomic Potentials (MLIP) v2+ program packages.</di","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"320 ","pages":"Article 110002"},"PeriodicalIF":3.4,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145920954","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 : 2025-12-17DOI: 10.1016/j.cpc.2025.109996
Nils Wittemeier , Nick Papior , Mads Brandbyge , Zeila Zanolli , Pablo Ordejon
We present the implementation of spinor quantum transport within the non-equilibrium Green’s function (NEGF) code TranSIESTA based on Density Functional Theory (DFT). First-principles methods play an essential role in molecular and material modelling, and the DFT+NEGF approach has become a widely-used tool for quantum transport simulation. Existing (open-source) DFT-based quantum transport codes either model non-equilibrium/finite-bias cases in an approximate way or rely on the collinear spin approximation. Our new implementation closes this gap and enables the TranSIESTA code to use full spinor-wave functions. Thereby it provides a method for transport simulation of topological materials and devices based on spin-orbit coupling (SOC) or non-collinear spins. These materials hold enormous potential for the development of ultra-low-energy electronics urgently needed for the design of sustainable technology. The new feature is tested on relevant systems determining magnetoresistance in iron nanostructures and transport properties of a lateral transition metal dichalcogenide heterojunction.
{"title":"Quantum transport with spin-orbit coupling: New developments in TranSIESTA","authors":"Nils Wittemeier , Nick Papior , Mads Brandbyge , Zeila Zanolli , Pablo Ordejon","doi":"10.1016/j.cpc.2025.109996","DOIUrl":"10.1016/j.cpc.2025.109996","url":null,"abstract":"<div><div>We present the implementation of spinor quantum transport within the non-equilibrium Green’s function (NEGF) code TranSIESTA based on Density Functional Theory (DFT). First-principles methods play an essential role in molecular and material modelling, and the DFT+NEGF approach has become a widely-used tool for quantum transport simulation. Existing (open-source) DFT-based quantum transport codes either model non-equilibrium/finite-bias cases in an approximate way or rely on the collinear spin approximation. Our new implementation closes this gap and enables the TranSIESTA code to use full spinor-wave functions. Thereby it provides a method for transport simulation of topological materials and devices based on spin-orbit coupling (SOC) or non-collinear spins. These materials hold enormous potential for the development of ultra-low-energy electronics urgently needed for the design of sustainable technology. The new feature is tested on relevant systems determining magnetoresistance in iron nanostructures and transport properties of a lateral transition metal dichalcogenide heterojunction.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"320 ","pages":"Article 109996"},"PeriodicalIF":3.4,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145836436","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 : 2025-12-17DOI: 10.1016/j.cpc.2025.110000
Chang-Min Lee , Sung-Joon Ye
<div><div>We developed a GPU-accelerated nucleus-nucleus fragmentation event generator. The Quantum Molecular Dynamics (QMD) model was implemented on GPU architecture. A corresponding evaporation model was also integrated to handle de-excitation. The developed models, RT2QMD, can handle nuclear collisions where the projectiles including oxygen isotopes and lighter nuclei, covering most of the situations in carbon-ion radiotherapy. The intended energy range of this package is 100 MeV/u to 500 MeV/u. This package was compared against the corresponding Geant4 models and experimental data. The RT2QMD showed good agreement with Geant4 and experimental data for neutron double-differential cross-section in the 290 MeV/u <span><math><mrow><msup><mrow></mrow><mn>12</mn></msup><msup><mrow><mi>C</mi><mo>(</mo></mrow><mn>12</mn></msup><mi>C</mi></mrow></math></span>,xn), <span><math><mrow><msup><mrow></mrow><mn>12</mn></msup><msup><mrow><mi>C</mi><mo>(</mo></mrow><mn>16</mn></msup><mi>O</mi></mrow></math></span>,xn) reactions, and the 230 MeV/u Cu(<span><math><mrow><msup><mrow></mrow><mn>4</mn></msup><mtext>He</mtext></mrow></math></span>,xn) reaction. The fragment production cross-section from <span><math><mrow><msup><mrow></mrow><mn>12</mn></msup><mi>C</mi><mspace></mspace><mo>−</mo><msup><mspace></mspace><mn>12</mn></msup><mi>C</mi></mrow></math></span> reactions showed relatively large differences compared to Geant4 and experimental data, due to the simplified evaporation model. The RT2QMD ran on an NVIDIA RTX 4090 GPU, while the Geant4 models ran on an Intel Xeon Gold 6342 node using all 48 available threads. The computing speeds of RT2QMD were about 30 times faster than those of Geant4 for all reactions. This package is part of the GPU-based Monte Carlo code, RT<sup>2</sup>, to handle dose calculation in heavy-ion therapy. <strong>PROGRAM SUMMARY</strong> <em>Program Title:</em> RT2QMD <em>CPC Library link to program files:</em> (to be added by Technical Editor) <em>Developer’s repository link:</em> <span><span>https://github.com/dlc2048/RT2QMD</span><svg><path></path></svg></span> <em>Licensing provisions:</em> Apache-2.0 <em>Programming language:</em> C++/CUDA (core implementation), Python (for phase-space and QMD field dump analysis) <em>Nature of problem:</em> The RT2QMD package generates phase-space distributions of secondary particles (photons, neutrons, protons, and heavier nuclei) resulting from nucleus-nucleus collision events. This package does not consider the production of pions or delta baryons. The intended energy range of this package is 100 MeV/u to 500 MeV/u. While calculations outside this energy range are possible, valid results are not guaranteed in those cases. This package runs on NVIDIA GPUs and provides sampling performance that is orders of magnitude faster than CPU-based event generators on hardware of the same generation and cost. <em>Solution method:</em> The nucleus-nucleus reaction Quantum Molecular Dynamics algorithm and
{"title":"RT2QMD: GPU-Accelerated nucleus-nucleus fragmentation event generator","authors":"Chang-Min Lee , Sung-Joon Ye","doi":"10.1016/j.cpc.2025.110000","DOIUrl":"10.1016/j.cpc.2025.110000","url":null,"abstract":"<div><div>We developed a GPU-accelerated nucleus-nucleus fragmentation event generator. The Quantum Molecular Dynamics (QMD) model was implemented on GPU architecture. A corresponding evaporation model was also integrated to handle de-excitation. The developed models, RT2QMD, can handle nuclear collisions where the projectiles including oxygen isotopes and lighter nuclei, covering most of the situations in carbon-ion radiotherapy. The intended energy range of this package is 100 MeV/u to 500 MeV/u. This package was compared against the corresponding Geant4 models and experimental data. The RT2QMD showed good agreement with Geant4 and experimental data for neutron double-differential cross-section in the 290 MeV/u <span><math><mrow><msup><mrow></mrow><mn>12</mn></msup><msup><mrow><mi>C</mi><mo>(</mo></mrow><mn>12</mn></msup><mi>C</mi></mrow></math></span>,xn), <span><math><mrow><msup><mrow></mrow><mn>12</mn></msup><msup><mrow><mi>C</mi><mo>(</mo></mrow><mn>16</mn></msup><mi>O</mi></mrow></math></span>,xn) reactions, and the 230 MeV/u Cu(<span><math><mrow><msup><mrow></mrow><mn>4</mn></msup><mtext>He</mtext></mrow></math></span>,xn) reaction. The fragment production cross-section from <span><math><mrow><msup><mrow></mrow><mn>12</mn></msup><mi>C</mi><mspace></mspace><mo>−</mo><msup><mspace></mspace><mn>12</mn></msup><mi>C</mi></mrow></math></span> reactions showed relatively large differences compared to Geant4 and experimental data, due to the simplified evaporation model. The RT2QMD ran on an NVIDIA RTX 4090 GPU, while the Geant4 models ran on an Intel Xeon Gold 6342 node using all 48 available threads. The computing speeds of RT2QMD were about 30 times faster than those of Geant4 for all reactions. This package is part of the GPU-based Monte Carlo code, RT<sup>2</sup>, to handle dose calculation in heavy-ion therapy. <strong>PROGRAM SUMMARY</strong> <em>Program Title:</em> RT2QMD <em>CPC Library link to program files:</em> (to be added by Technical Editor) <em>Developer’s repository link:</em> <span><span>https://github.com/dlc2048/RT2QMD</span><svg><path></path></svg></span> <em>Licensing provisions:</em> Apache-2.0 <em>Programming language:</em> C++/CUDA (core implementation), Python (for phase-space and QMD field dump analysis) <em>Nature of problem:</em> The RT2QMD package generates phase-space distributions of secondary particles (photons, neutrons, protons, and heavier nuclei) resulting from nucleus-nucleus collision events. This package does not consider the production of pions or delta baryons. The intended energy range of this package is 100 MeV/u to 500 MeV/u. While calculations outside this energy range are possible, valid results are not guaranteed in those cases. This package runs on NVIDIA GPUs and provides sampling performance that is orders of magnitude faster than CPU-based event generators on hardware of the same generation and cost. <em>Solution method:</em> The nucleus-nucleus reaction Quantum Molecular Dynamics algorithm and ","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"320 ","pages":"Article 110000"},"PeriodicalIF":3.4,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145836431","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}
<div><div>The Discrete Element Method (DEM) is widely used to simulate the mechanical behavior of granular materials across a broad range of applications and industrial domains. Particle shape is a key feature playing a crucial role for physics-fidelity of DEM simulations. However, accurately representing complex particle shapes within DEM frameworks presents significant challenges such as defining unambiguous contact normals or managing geometric singularities. Rigid particles are often modeled as convex polyhedra, which inherently suffer from ill-defined outward normal vectors at sharp edges and vertices. To represent non-convex geometries, these polyhedra must typically be combined, further increasing the computational and geometric complexity. In this work, we adopt an efficient and robust strategy to overcome these limitations by using <em>R</em>-shapes, defined as rounded-edge shapes, also known as sphero-polyhedra, obtained by sweeping a sphere of radius <em>R</em> along the edges and faces of a base polyhedral shape. This construction results in smooth surface transitions and circumvents common issues associated with traditional polygonal representations. This paper provides a detailed presentation of the implementation, structure, and advantages of <em>R</em>-shapes in DEM simulations. The proposed solutions are implemented in a fully open-source software package called <span>Rockable</span>, developed in <span>C++</span>, which integrates state-of-the-art numerical techniques and shared-memory parallelization for enhanced performance. Beyond the geometric modeling aspects, we also address several methodological challenges, including the treatment of contact elasticity and the numerical integration scheme. The combined contributions of this work offer a practical and efficient framework for simulating complex particle shapes in DEM with high physics fidelity and computational efficiency.<strong>Program summary</strong></div><div><em>Program Title:</em><span>Rockable</span></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><span><span>https://github.com/richefeu/rockable</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> CeCILL-B</div><div><em>Programming language:</em>C<span>++</span>11</div><div><em>Supplementary material:</em></div><div><em>Nature of problem(approx. 50–250 words):</em></div><div>The open-source software <span>Rockable</span> addresses key challenges in simulating the mechanical behavior of granular materials using the Discrete Element Method (DEM), widely applied in both industrial applications and academic studies particularly where particle shape plays a critical role. Accurate modeling of the diversity of particle shapes in DEM remains non-trivial, due in part to ambiguities in defining contact normals. Rigid particles are often represented as convex polyhedra, which suffer from poorly defined
{"title":"Advanced strategies for discrete simulations with three-dimensional R-shapes in rockable framework","authors":"Vincent Richefeu , Gaël Combe , Lhassan Amarsid , Raphaël Prat , Jean-Mathieu Vanson , Saied Nezamabadi , Patrick Mutabaruka , Jean-Yves Delenne , Farhang Radjaï","doi":"10.1016/j.cpc.2025.109997","DOIUrl":"10.1016/j.cpc.2025.109997","url":null,"abstract":"<div><div>The Discrete Element Method (DEM) is widely used to simulate the mechanical behavior of granular materials across a broad range of applications and industrial domains. Particle shape is a key feature playing a crucial role for physics-fidelity of DEM simulations. However, accurately representing complex particle shapes within DEM frameworks presents significant challenges such as defining unambiguous contact normals or managing geometric singularities. Rigid particles are often modeled as convex polyhedra, which inherently suffer from ill-defined outward normal vectors at sharp edges and vertices. To represent non-convex geometries, these polyhedra must typically be combined, further increasing the computational and geometric complexity. In this work, we adopt an efficient and robust strategy to overcome these limitations by using <em>R</em>-shapes, defined as rounded-edge shapes, also known as sphero-polyhedra, obtained by sweeping a sphere of radius <em>R</em> along the edges and faces of a base polyhedral shape. This construction results in smooth surface transitions and circumvents common issues associated with traditional polygonal representations. This paper provides a detailed presentation of the implementation, structure, and advantages of <em>R</em>-shapes in DEM simulations. The proposed solutions are implemented in a fully open-source software package called <span>Rockable</span>, developed in <span>C++</span>, which integrates state-of-the-art numerical techniques and shared-memory parallelization for enhanced performance. Beyond the geometric modeling aspects, we also address several methodological challenges, including the treatment of contact elasticity and the numerical integration scheme. The combined contributions of this work offer a practical and efficient framework for simulating complex particle shapes in DEM with high physics fidelity and computational efficiency.<strong>Program summary</strong></div><div><em>Program Title:</em><span>Rockable</span></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><span><span>https://github.com/richefeu/rockable</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> CeCILL-B</div><div><em>Programming language:</em>C<span>++</span>11</div><div><em>Supplementary material:</em></div><div><em>Nature of problem(approx. 50–250 words):</em></div><div>The open-source software <span>Rockable</span> addresses key challenges in simulating the mechanical behavior of granular materials using the Discrete Element Method (DEM), widely applied in both industrial applications and academic studies particularly where particle shape plays a critical role. Accurate modeling of the diversity of particle shapes in DEM remains non-trivial, due in part to ambiguities in defining contact normals. Rigid particles are often represented as convex polyhedra, which suffer from poorly defined ","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"320 ","pages":"Article 109997"},"PeriodicalIF":3.4,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145836598","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}
We introduce an out-of-equilibrium replica exchange Monte Carlo (REMC) scheme designed to accelerate the equilibration of hard body systems under high-pressure conditions. The method deliberately violates balance by significantly increasing the swap acceptance probability, thereby forcing replicas to explore the entire range of sampling pressures. As a result, replicas undergo abrupt pressure changes analogous to annealing processes that help reduce defects. We demonstrate the efficacy of the approach on systems of N hard disks confined within a circular cavity (with 400 ≤ N ≤ 450), where it consistently achieves higher maximal packing fractions than standard REMC within the same number of cycles. Furthermore, we establish new maximal packing records for cases where the best known maximal packings fall below Cantrell’s low-density limit and for N ≤ 1000. Similar improvements are observed for disks confined within a square cavity. Finally, we discuss the potential of alternating cycles of out-of-equilibrium and equilibrium REMC to further approach the equilibrium equation of state of hard body systems at very high densities.
我们介绍了一种非平衡复制交换蒙特卡罗（REMC）方案，旨在加速高压条件下硬体系统的平衡。该方法故意通过显著增加交换接受概率来破坏平衡，从而迫使副本探索采样压力的整个范围。因此，仿制品会经历类似于退火过程的突然压力变化，从而有助于减少缺陷。我们证明了该方法在圆形腔内（400 ≤ N ≤ 450）的N个硬盘系统上的有效性，在相同次数的循环内，它始终比标准REMC获得更高的最大填充分数。此外，我们建立了新的最大包装的情况下，最知名的最大包装低于Cantrell的低密度极限和N ≤ 1000。类似的改进被观察到圆盘限制在一个方形腔内。最后，我们讨论了非平衡和平衡REMC交替循环的潜力，以进一步接近非常高密度下硬体系统的状态平衡方程。
{"title":"Densest packings and accelerated equilibration of hard body systems via out-of-equilibrium replica exchange Monte Carlo! method","authors":"Eduardo Basurto , Peter Gurin , Szabolcs Varga , Gerardo Odriozola","doi":"10.1016/j.cpc.2025.109990","DOIUrl":"10.1016/j.cpc.2025.109990","url":null,"abstract":"<div><div>We introduce an out-of-equilibrium replica exchange Monte Carlo (REMC) scheme designed to accelerate the equilibration of hard body systems under high-pressure conditions. The method deliberately violates balance by significantly increasing the swap acceptance probability, thereby forcing replicas to explore the entire range of sampling pressures. As a result, replicas undergo abrupt pressure changes analogous to annealing processes that help reduce defects. We demonstrate the efficacy of the approach on systems of <em>N</em> hard disks confined within a circular cavity (with 400 ≤ <em>N</em> ≤ 450), where it consistently achieves higher maximal packing fractions than standard REMC within the same number of cycles. Furthermore, we establish new maximal packing records for cases where the best known maximal packings fall below Cantrell’s low-density limit and for <em>N</em> ≤ 1000. Similar improvements are observed for disks confined within a square cavity. Finally, we discuss the potential of alternating cycles of out-of-equilibrium and equilibrium REMC to further approach the equilibrium equation of state of hard body systems at very high densities.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"320 ","pages":"Article 109990"},"PeriodicalIF":3.4,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145836600","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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