Pub Date : 2025-04-11DOI: 10.1016/j.cpc.2025.109617
Emmanuel Lorin , Charlotte Noxon
This paper is devoted to the computation of atomic/molecular polarization (dipole moment) or acceleration in the context of attosecond science and with preliminary application to nonperturbative nonlinear optics. Specifically, dipole moments and dipole accelerations are efficiently learnt for continuous sets of physical parameters using neural networks trained from a finite number of solutions to parameterized Time Dependent Schrödinger equations computed with classical numerical methods. We then propose an application to a Maxwell-Schrödinger system modeling the macroscopic propagation of intense and short laser pulses in a gas, and show that polarization learning allows for an important improvement of the computational efficiency. Some experiments and analytical results illustrate the proposed strategy.
{"title":"Efficient data-driven polarization learning for attosecond science and nonperturbative nonlinear optics","authors":"Emmanuel Lorin , Charlotte Noxon","doi":"10.1016/j.cpc.2025.109617","DOIUrl":"10.1016/j.cpc.2025.109617","url":null,"abstract":"<div><div>This paper is devoted to the computation of atomic/molecular polarization (dipole moment) or acceleration in the context of attosecond science and with preliminary application to nonperturbative nonlinear optics. Specifically, dipole moments and dipole accelerations are efficiently learnt for <em>continuous</em> sets of physical parameters using neural networks trained from a finite number of solutions to parameterized Time Dependent Schrödinger equations computed with classical numerical methods. We then propose an application to a Maxwell-Schrödinger system modeling the macroscopic propagation of intense and short laser pulses in a gas, and show that polarization learning allows for an important improvement of the computational efficiency. Some experiments and analytical results illustrate the proposed strategy.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"313 ","pages":"Article 109617"},"PeriodicalIF":7.2,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143859112","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 : 2025-04-11DOI: 10.1016/j.cpc.2025.109615
Chenxi Zhao , Yongchuan Yu , Oskar J. Haidn , Xiangyu Hu
In the smoothed particle dynamics (SPH) method, the characteristics of a target particle are interpolated based on the information from its neighbor particles. Consequently, a uniform initial distribution of particles significantly enhances the accuracy of SPH calculations. This aspect is particularly critical in Eulerian SPH, where particles are stationary throughout the simulation. To address this, we introduce a physics-driven complex relaxation method for multi-body systems. Through a series of two-dimensional and three-dimensional case studies, we demonstrate that this method is capable of achieving a globally uniform particle distribution, especially at the interfaces between contacting bodies, and ensuring improved zero-order consistency. Moreover, the effectiveness and reliability of the complex relaxation method in enhancing the accuracy of physical simulations are further validated.
{"title":"Physics-driven complex relaxation for multi-body systems of SPH method","authors":"Chenxi Zhao , Yongchuan Yu , Oskar J. Haidn , Xiangyu Hu","doi":"10.1016/j.cpc.2025.109615","DOIUrl":"10.1016/j.cpc.2025.109615","url":null,"abstract":"<div><div>In the smoothed particle dynamics (SPH) method, the characteristics of a target particle are interpolated based on the information from its neighbor particles. Consequently, a uniform initial distribution of particles significantly enhances the accuracy of SPH calculations. This aspect is particularly critical in Eulerian SPH, where particles are stationary throughout the simulation. To address this, we introduce a physics-driven complex relaxation method for multi-body systems. Through a series of two-dimensional and three-dimensional case studies, we demonstrate that this method is capable of achieving a globally uniform particle distribution, especially at the interfaces between contacting bodies, and ensuring improved zero-order consistency. Moreover, the effectiveness and reliability of the complex relaxation method in enhancing the accuracy of physical simulations are further validated.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"313 ","pages":"Article 109615"},"PeriodicalIF":7.2,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143829555","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 : 2025-04-11DOI: 10.1016/j.cpc.2025.109609
Francesco Ricci , Renato Vacondio , José M. Domínguez , Angelantonio Tafuni
This study builds on our prior 2D variable-resolution framework for Smoothed Particle Hydrodynamics (SPH) using domain decomposition, extending it to the simulation of three-dimensional flows. We enhance the domain decomposition strategy to enable efficient mass transfer across subdomains with varying resolutions. Key improvements include a refined calculation of Eulerian fluxes at the interfaces between different subdomains, including the free surface, and the use of a first-order consistent approximation of the pressure gradient for a smooth transition of the physical variables across the different resolution zones.
The model is implemented in the SPH solver DualSPHysics and validated through several 3D test cases, including flow past a sphere, water entry of a wedge, and wave-induced motion of a floating box. Simulation results indicate that our 3D multi-resolution model can capture complex fluid-structure interactions effectively, and it can offer significant computational savings over traditional uniform resolution techniques. Our advancements provide a scalable and efficient solution for simulating a wide range of multi-scale engineering applications, especially those involving fluid-structure interaction.
{"title":"Three-dimensional variable resolution for multi-scale modeling in Smoothed Particle Hydrodynamics","authors":"Francesco Ricci , Renato Vacondio , José M. Domínguez , Angelantonio Tafuni","doi":"10.1016/j.cpc.2025.109609","DOIUrl":"10.1016/j.cpc.2025.109609","url":null,"abstract":"<div><div>This study builds on our prior 2D variable-resolution framework for Smoothed Particle Hydrodynamics (SPH) using domain decomposition, extending it to the simulation of three-dimensional flows. We enhance the domain decomposition strategy to enable efficient mass transfer across subdomains with varying resolutions. Key improvements include a refined calculation of Eulerian fluxes at the interfaces between different subdomains, including the free surface, and the use of a first-order consistent approximation of the pressure gradient for a smooth transition of the physical variables across the different resolution zones.</div><div>The model is implemented in the SPH solver DualSPHysics and validated through several 3D test cases, including flow past a sphere, water entry of a wedge, and wave-induced motion of a floating box. Simulation results indicate that our 3D multi-resolution model can capture complex fluid-structure interactions effectively, and it can offer significant computational savings over traditional uniform resolution techniques. Our advancements provide a scalable and efficient solution for simulating a wide range of multi-scale engineering applications, especially those involving fluid-structure interaction.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"313 ","pages":"Article 109609"},"PeriodicalIF":7.2,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143837971","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 : 2025-04-11DOI: 10.1016/j.cpc.2025.109612
M.F. Huq , V.V. Srinivasaragavan , O. Sahni , D. Curreli
In this work we discuss a block-structured nonuniform meshing technique for multi-scale plasma simulations of plasma sheaths and scrape-off layers, suitable to implementation in hybrid Particle-in-Cell (PIC) schemes that consider kinetic ions and Boltzmann electrons. The meshing scheme is designed to support large-scale fusion plasma domains (spanning tens of meters) with a substantially reduced number of degrees-of-freedom (DOF) compared to simulations employing a uniform mesh. We show that the solution derived at low DOFs maintains the same level of accuracy as solutions obtained from highly refined uniform meshes, still maintaining particle noise under control. The meshing scheme can be equally applied to both 1D and 2D plasma domains. This reduction in DOFs leads to a significant reduction in computational cost while keeping total count of computational particles the same for corresponding cases, making it a valuable tool for cost-effective, multi-scale fusion plasma simulations.
{"title":"A block-structured nonuniform meshing technique for reducing the degrees-of-freedom in hybrid particle-in-cell plasma simulations","authors":"M.F. Huq , V.V. Srinivasaragavan , O. Sahni , D. Curreli","doi":"10.1016/j.cpc.2025.109612","DOIUrl":"10.1016/j.cpc.2025.109612","url":null,"abstract":"<div><div>In this work we discuss a block-structured nonuniform meshing technique for multi-scale plasma simulations of plasma sheaths and scrape-off layers, suitable to implementation in hybrid Particle-in-Cell (PIC) schemes that consider kinetic ions and Boltzmann electrons. The meshing scheme is designed to support large-scale fusion plasma domains (spanning tens of meters) with a substantially reduced number of degrees-of-freedom (DOF) compared to simulations employing a uniform mesh. We show that the solution derived at low DOFs maintains the same level of accuracy as solutions obtained from highly refined uniform meshes, still maintaining particle noise under control. The meshing scheme can be equally applied to both 1D and 2D plasma domains. This reduction in DOFs leads to a significant reduction in computational cost while keeping total count of computational particles the same for corresponding cases, making it a valuable tool for cost-effective, multi-scale fusion plasma simulations.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"313 ","pages":"Article 109612"},"PeriodicalIF":7.2,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868725","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 : 2025-04-10DOI: 10.1016/j.cpc.2025.109601
Zihan Wang , Ziyue Hu , Mingwei Yang , Yalin Dong , Wenlong Huang , Haijun Ren
Physics-Informed Neural Network (PINN) is a deep learning framework that has been widely employed to solve spatial-temporal partial differential equations (PDEs) across various fields. However, recent numerical experiments indicate that the vanilla-PINN often struggles with PDEs featuring high-frequency solutions or strong nonlinearity. To enhance PINN's performance, we propose a novel strategy called the Preconditioning-Pretraining Physics-Informed Neural Network (PP-PINN). This approach involves transforming the original task into a new system characterized by low frequency and weak nonlinearity over an extended time scale. The transformed PDEs are then solved using a pretraining approach. Additionally, we introduce a new constraint termed “fixed point”, which is beneficial for scenarios with extremely high frequency or strong nonlinearity. To demonstrate the efficacy of our method, we apply the newly developed strategy to three different equations, achieving improved accuracy and reduced computational costs compared to previous approaches which incorporate the pretraining technique. The effectiveness and interpretability of our PP-PINN are also discussed, emphasizing its advantages in tackling high-frequency solutions and strong nonlinearity, thereby offering insights into its broader applicability in complex mathematical modeling.
{"title":"Solving partial differential equations based on preconditioning-pretraining physics-informed neural network","authors":"Zihan Wang , Ziyue Hu , Mingwei Yang , Yalin Dong , Wenlong Huang , Haijun Ren","doi":"10.1016/j.cpc.2025.109601","DOIUrl":"10.1016/j.cpc.2025.109601","url":null,"abstract":"<div><div>Physics-Informed Neural Network (PINN) is a deep learning framework that has been widely employed to solve spatial-temporal partial differential equations (PDEs) across various fields. However, recent numerical experiments indicate that the vanilla-PINN often struggles with PDEs featuring high-frequency solutions or strong nonlinearity. To enhance PINN's performance, we propose a novel strategy called the Preconditioning-Pretraining Physics-Informed Neural Network (PP-PINN). This approach involves transforming the original task into a new system characterized by low frequency and weak nonlinearity over an extended time scale. The transformed PDEs are then solved using a pretraining approach. Additionally, we introduce a new constraint termed “fixed point”, which is beneficial for scenarios with extremely high frequency or strong nonlinearity. To demonstrate the efficacy of our method, we apply the newly developed strategy to three different equations, achieving improved accuracy and reduced computational costs compared to previous approaches which incorporate the pretraining technique. The effectiveness and interpretability of our PP-PINN are also discussed, emphasizing its advantages in tackling high-frequency solutions and strong nonlinearity, thereby offering insights into its broader applicability in complex mathematical modeling.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"312 ","pages":"Article 109601"},"PeriodicalIF":7.2,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143826155","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 : 2025-04-10DOI: 10.1016/j.cpc.2025.109621
Dong-sheng Cai, Ping-yang Wang
The particle merging algorithm enables particle-in-cell codes to simulate the process of rapidly increasing particle numbers. Dividing particles that are close in phase space into a subset for merging is beneficial for preserving the particle distribution function (PDF). However, larger subsets can cause particles with significant differences to be grouped together. To address this issue, we proposed a conservative constrained clustering-merging algorithm which employs the constrained k-means method to keep the number of particles within each subset at a low level while meeting the requirement of conserving physical quantities. Subsequently, the particles in each subset are merged by probabilistically adjusting their weights. The impact of subset size on the merging results and computational performance is also discussed.
{"title":"A conservative constrained clustering-merging algorithm for particle-in-cell codes","authors":"Dong-sheng Cai, Ping-yang Wang","doi":"10.1016/j.cpc.2025.109621","DOIUrl":"10.1016/j.cpc.2025.109621","url":null,"abstract":"<div><div>The particle merging algorithm enables particle-in-cell codes to simulate the process of rapidly increasing particle numbers. Dividing particles that are close in phase space into a subset for merging is beneficial for preserving the particle distribution function (PDF). However, larger subsets can cause particles with significant differences to be grouped together. To address this issue, we proposed a conservative constrained clustering-merging algorithm which employs the constrained k-means method to keep the number of particles within each subset at a low level while meeting the requirement of conserving physical quantities. Subsequently, the particles in each subset are merged by probabilistically adjusting their weights. The impact of subset size on the merging results and computational performance is also discussed.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"313 ","pages":"Article 109621"},"PeriodicalIF":7.2,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143875038","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 : 2025-04-10DOI: 10.1016/j.cpc.2025.109618
Qian Zhang , Jinlong Yang , Wei Hu
Two-dimensional (2D) van der Waals (vdWs) structures are the subject of extensive research in materials science, celebrated for their unique physical properties and potential technological applications. However, the diversity of stacking modes in 2D vdWs structures poses a challenge for research. In response to the complexity of the stacking process for these layered structures, we have developed a Python package, PyHTStack2D, specifically designed to support High-Throughput Stacking of 2D materials research. The package provides two primary functionalities: Firstly, it facilitates the batch stacking of homo- and heterostructures, with careful consideration of specific sequences and patterns, such as those observed in the 1T/2H phase transitions of transition metal dichalcogenides; Secondly, it aids in the efficient creation of computational directories and the generation of requisite shell scripts for the batch computation submissions of the stacked structures. By employing this package, we performed high-throughput computational simulations of properties such as electronic energy band structures and magnetic ground states of bilayers composed of 2H-TMDHs. These results have enabled us to identify the types of electronic band structures within these systems, providing critical insights into their potential applications in optoelectronics and photocatalysis. Furthermore, preliminary findings indicate the potential feasibility of generating bipolar magnetic semiconductors via the stacking of magnetic monolayers. The PyHTStack2D package provides an opportunity to perform efficient high-throughput calculations of 2D vdWs homo/heterostructures.
{"title":"PyHTStack2D: A Python package for high-throughput homo/hetero stacking of 2D materials","authors":"Qian Zhang , Jinlong Yang , Wei Hu","doi":"10.1016/j.cpc.2025.109618","DOIUrl":"10.1016/j.cpc.2025.109618","url":null,"abstract":"<div><div>Two-dimensional (2D) van der Waals (vdWs) structures are the subject of extensive research in materials science, celebrated for their unique physical properties and potential technological applications. However, the diversity of stacking modes in 2D vdWs structures poses a challenge for research. In response to the complexity of the stacking process for these layered structures, we have developed a Python package, PyHTStack2D, specifically designed to support High-Throughput Stacking of 2D materials research. The package provides two primary functionalities: Firstly, it facilitates the batch stacking of homo- and heterostructures, with careful consideration of specific sequences and patterns, such as those observed in the 1T/2H phase transitions of transition metal dichalcogenides; Secondly, it aids in the efficient creation of computational directories and the generation of requisite shell scripts for the batch computation submissions of the stacked structures. By employing this package, we performed high-throughput computational simulations of properties such as electronic energy band structures and magnetic ground states of bilayers composed of 2H-TMDHs. These results have enabled us to identify the types of electronic band structures within these systems, providing critical insights into their potential applications in optoelectronics and photocatalysis. Furthermore, preliminary findings indicate the potential feasibility of generating bipolar magnetic semiconductors via the stacking of magnetic monolayers. The PyHTStack2D package provides an opportunity to perform efficient high-throughput calculations of 2D vdWs homo/heterostructures.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"312 ","pages":"Article 109618"},"PeriodicalIF":7.2,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816790","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 : 2025-04-09DOI: 10.1016/j.cpc.2025.109611
A.Y. Pankin , J. Breslau , M. Gorelenkova , R. Andre , B. Grierson , J. Sachdev , M. Goliyad , G. Perumpilly
This paper provides a comprehensive review of the TRANSP code, a sophisticated tool for interpretive and predictive analysis of tokamak plasmas, detailing its major capabilities and features. It describes the equations for particle, power, and momentum balance analysis, as well as the poloidal field diffusion equations. The paper outlines the spatial and time grids used in TRANSP and details the equilibrium assumptions and solvers. Various models for heating and current drive and radiation, including updates to the NUBEAM model, are discussed. The handling of large-scale events such as sawtooth crashes and pellet injections is examined, along with the predictive capabilities for advancing plasma profiles. The integration of TRANSP with the ITER Integrated Modeling and Analysis Suite (IMAS) is highlighted, demonstrating enhanced data access and analysis capabilities. Additionally, the paper discusses best practices and continuous integration techniques to enhance TRANSP's robustness. The suite of TRANSP tools, designed for efficient data analysis and simulation, further supports the optimization of tokamak operations and coupling with other tokamak codes. Continuous development and support ensure that TRANSP remains a major code for the analysis of experimental data for controlled thermonuclear fusion, maintaining its critical role in supporting the optimization of tokamak operations and advancing fusion research.
{"title":"TRANSP integrated modeling code for interpretive and predictive analysis of tokamak plasmas","authors":"A.Y. Pankin , J. Breslau , M. Gorelenkova , R. Andre , B. Grierson , J. Sachdev , M. Goliyad , G. Perumpilly","doi":"10.1016/j.cpc.2025.109611","DOIUrl":"10.1016/j.cpc.2025.109611","url":null,"abstract":"<div><div>This paper provides a comprehensive review of the TRANSP code, a sophisticated tool for interpretive and predictive analysis of tokamak plasmas, detailing its major capabilities and features. It describes the equations for particle, power, and momentum balance analysis, as well as the poloidal field diffusion equations. The paper outlines the spatial and time grids used in TRANSP and details the equilibrium assumptions and solvers. Various models for heating and current drive and radiation, including updates to the NUBEAM model, are discussed. The handling of large-scale events such as sawtooth crashes and pellet injections is examined, along with the predictive capabilities for advancing plasma profiles. The integration of TRANSP with the ITER Integrated Modeling and Analysis Suite (IMAS) is highlighted, demonstrating enhanced data access and analysis capabilities. Additionally, the paper discusses best practices and continuous integration techniques to enhance TRANSP's robustness. The suite of TRANSP tools, designed for efficient data analysis and simulation, further supports the optimization of tokamak operations and coupling with other tokamak codes. Continuous development and support ensure that TRANSP remains a major code for the analysis of experimental data for controlled thermonuclear fusion, maintaining its critical role in supporting the optimization of tokamak operations and advancing fusion research.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"312 ","pages":"Article 109611"},"PeriodicalIF":7.2,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143820669","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 : 2025-04-08DOI: 10.1016/j.cpc.2025.109613
Aitor Calvo-Fernández , María Blanco-Rey , Asier Eiguren
<div><div>Exploiting symmetries in the numerical renormalization group (NRG) method significantly enhances performance by improving the accuracy, increasing the computational speed, and optimizing the memory efficiency. Published codes focus on continuous rotations and unitary groups, which generally are not applicable to systems with strong crystal-field effects. The <span>PointGroupNRG</span> code implements symmetries related to discrete rotation groups, which are defined by the user in terms of Clebsch-Gordan coefficients, together with particle conservation and spin rotation symmetries. In this paper we present a new version of the code that extends the available finite groups, previously limited to simply reducible point groups, in a way that all point and double groups become accessible. It also includes the full spin-orbital rotation group. Moreover, to improve the code's flexibility for impurities with complex interactions, this new version allows to choose between a standard Anderson Hamiltonian for the impurity or, as another novel feature, an ionic model that requires only the spectrum and the impurity Lehmann amplitudes.</div></div><div><h3>Program summary</h3><div><em>Program Title:</em> PointGroupNRG</div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/hjwmt6cc55.1</span><svg><path></path></svg></span></div><div><em>Developer's repository link:</em> <span><span>https://github.com/aitorcf/PointGroupNRG</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> GPLv3</div><div><em>Programming language:</em> Julia</div><div><em>Journal reference of previous version:</em> Comput. Phys. Commun. 296 (2024), 109032, <span><span>https://doi.org/10.1016/j.cpc.2023.109032</span><svg><path></path></svg></span></div><div><em>Does the new version supersede the previous version?:</em> Yes.</div><div><em>Reasons for the new version:</em> Extension.</div><div><em>Nature of problem:</em> Numerical renormalization group (NRG) calculations for realistic models are computationally expensive, mainly due to their hard scaling with the number of orbital and spin configurations available for the electrons. Symmetry considerations reduce the computational cost of the calculations by exploiting the block structure of the operator matrix elements and by removing the redundancy in the symmetry-related matrix elements. Existing codes implement continuous symmetries, which are not generally and/or straightforwardly applicable to systems where spin-orbit and crystal-field effects need to be taken into account.</div><div><em>Solution method:</em> The first version of the code <span><span>[1]</span></span> introduced finite point group symmetries together with particle conservation and spin isotropy, useful for systems with strong crystal-field effects but negligible spin-orbit coupling. This new version also includes total angular momentum conservation and double group symmetries, together with particle co
{"title":"Numerical renormalization group calculations for magnetic impurity systems with spin-orbit coupling and crystal-field effects","authors":"Aitor Calvo-Fernández , María Blanco-Rey , Asier Eiguren","doi":"10.1016/j.cpc.2025.109613","DOIUrl":"10.1016/j.cpc.2025.109613","url":null,"abstract":"<div><div>Exploiting symmetries in the numerical renormalization group (NRG) method significantly enhances performance by improving the accuracy, increasing the computational speed, and optimizing the memory efficiency. Published codes focus on continuous rotations and unitary groups, which generally are not applicable to systems with strong crystal-field effects. The <span>PointGroupNRG</span> code implements symmetries related to discrete rotation groups, which are defined by the user in terms of Clebsch-Gordan coefficients, together with particle conservation and spin rotation symmetries. In this paper we present a new version of the code that extends the available finite groups, previously limited to simply reducible point groups, in a way that all point and double groups become accessible. It also includes the full spin-orbital rotation group. Moreover, to improve the code's flexibility for impurities with complex interactions, this new version allows to choose between a standard Anderson Hamiltonian for the impurity or, as another novel feature, an ionic model that requires only the spectrum and the impurity Lehmann amplitudes.</div></div><div><h3>Program summary</h3><div><em>Program Title:</em> PointGroupNRG</div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/hjwmt6cc55.1</span><svg><path></path></svg></span></div><div><em>Developer's repository link:</em> <span><span>https://github.com/aitorcf/PointGroupNRG</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> GPLv3</div><div><em>Programming language:</em> Julia</div><div><em>Journal reference of previous version:</em> Comput. Phys. Commun. 296 (2024), 109032, <span><span>https://doi.org/10.1016/j.cpc.2023.109032</span><svg><path></path></svg></span></div><div><em>Does the new version supersede the previous version?:</em> Yes.</div><div><em>Reasons for the new version:</em> Extension.</div><div><em>Nature of problem:</em> Numerical renormalization group (NRG) calculations for realistic models are computationally expensive, mainly due to their hard scaling with the number of orbital and spin configurations available for the electrons. Symmetry considerations reduce the computational cost of the calculations by exploiting the block structure of the operator matrix elements and by removing the redundancy in the symmetry-related matrix elements. Existing codes implement continuous symmetries, which are not generally and/or straightforwardly applicable to systems where spin-orbit and crystal-field effects need to be taken into account.</div><div><em>Solution method:</em> The first version of the code <span><span>[1]</span></span> introduced finite point group symmetries together with particle conservation and spin isotropy, useful for systems with strong crystal-field effects but negligible spin-orbit coupling. This new version also includes total angular momentum conservation and double group symmetries, together with particle co","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"312 ","pages":"Article 109613"},"PeriodicalIF":7.2,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816721","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 : 2025-04-07DOI: 10.1016/j.cpc.2025.109614
Jiaxin Chen , M. Weinert , Mingxing Chen
We introduce a program named KPROJ that unfolds the electronic and phononic band structure of materials modeled by supercells. The program is based on the k-projection method, which projects the wavefunction of the supercell onto the k-points in the Brillouin zone of the artificial primitive cell. It allows for obtaining an effective “local” band structure by performing partial integration over the k-projected wavefunctions, e.g., the unfolded band structure with layer-projection for interfaces and the weighted band structure in the vacuum for slabs. The layer k-projection is accelerated by a scheme that combines the Fast Fourier Transform (FFT) and the inverse FFT algorithms. It is now interfaced with several first-principles codes based on plane waves such as VASP, Quantum Espresso, and ABINIT. In addition, it also has interfaces with ABACUS, a first-principles simulation package based on numerical atomic basis sets, and PHONOPY, a program for phonon calculations.
Program summary
Program Title: KPROJ
CPC Library link to program files:https://doi.org/10.17632/f6n5phpy8f.1
Nature of problem: Supercells are widely used to model doped systems and interfaces within the framework of first-principles methods. However, the use of supercells causes band folding, which is unfavorable for understanding the effects of doping and interfacing on the band structure of materials. Moreover, the folding also brings difficulties in explaining the results of angle-resolved photoemission spectroscopy experiments.
Solution method: This program is designed to calculate the unfolded band structure for systems modeled by supercells. The unfolding is performed by projecting the wave functions of the supercell onto the k-points in the BZ of the primitive cell. The projector operator is built by the translation operator and its irreducible representation. The layer k-projected band structure is obtained by integrating the projected wave function in a selected spatial window, for which the FFT and inverse FFT algorithms are used to accelerate the calculation.
{"title":"KPROJ: A program for unfolding electronic and phononic bands","authors":"Jiaxin Chen , M. Weinert , Mingxing Chen","doi":"10.1016/j.cpc.2025.109614","DOIUrl":"10.1016/j.cpc.2025.109614","url":null,"abstract":"<div><div>We introduce a program named KPROJ that unfolds the electronic and phononic band structure of materials modeled by supercells. The program is based on the <em>k</em>-projection method, which projects the wavefunction of the supercell onto the <em>k</em>-points in the Brillouin zone of the artificial primitive cell. It allows for obtaining an effective “local” band structure by performing partial integration over the <em>k</em>-projected wavefunctions, e.g., the unfolded band structure with layer-projection for interfaces and the weighted band structure in the vacuum for slabs. The layer <em>k</em>-projection is accelerated by a scheme that combines the Fast Fourier Transform (FFT) and the inverse FFT algorithms. It is now interfaced with several first-principles codes based on plane waves such as VASP, Quantum Espresso, and ABINIT. In addition, it also has interfaces with ABACUS, a first-principles simulation package based on numerical atomic basis sets, and PHONOPY, a program for phonon calculations.</div></div><div><h3>Program summary</h3><div><em>Program Title:</em> KPROJ</div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/f6n5phpy8f.1</span><svg><path></path></svg></span></div><div><em>Developer's repository link:</em> <span><span>https://github.com/mxchen-2020/kproj</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> GPLv3.0</div><div><em>Programming language:</em> Fortran 90</div><div><em>Nature of problem:</em> Supercells are widely used to model doped systems and interfaces within the framework of first-principles methods. However, the use of supercells causes band folding, which is unfavorable for understanding the effects of doping and interfacing on the band structure of materials. Moreover, the folding also brings difficulties in explaining the results of angle-resolved photoemission spectroscopy experiments.</div><div><em>Solution method:</em> This program is designed to calculate the unfolded band structure for systems modeled by supercells. The unfolding is performed by projecting the wave functions of the supercell onto the <em>k</em>-points in the BZ of the primitive cell. The projector operator is built by the translation operator and its irreducible representation. The layer <em>k</em>-projected band structure is obtained by integrating the projected wave function in a selected spatial window, for which the FFT and inverse FFT algorithms are used to accelerate the calculation.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"312 ","pages":"Article 109614"},"PeriodicalIF":7.2,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143808326","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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