Computer Physics Communications最新文献

{"title":"An improved argument principle root-search method for modes of slab waveguides, optical fibers, and spheres","authors":"Sravya Rao ,&nbsp;Parry Y. Chen ,&nbsp;T. Grossinger,&nbsp;Yonatan Sivan","doi":"10.1016/j.cpc.2025.109772","DOIUrl":"10.1016/j.cpc.2025.109772","url":null,"abstract":"<div><div>We update our root-search method for transcendental equations. Our method is globally convergent and is guaranteed to locate all complex roots within a specified search domain, since it is based on Cauchy's residue theorem. We extend the implementation to treat the dispersion relations of slab waveguides and the resonances of a sphere, in addition to step-index fibers. We also implement other improvements, such as to the contour selection procedure and using non-dimensional search variables, to ensure the method remains reliable even in challenging parameter regimes. We also extend the algorithm to identify leaky modes in terms of propagation constant eigenvalue modes, revealing, to the first time to our knowledge, a discontinuity across the light line in the dispersion plot.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109772"},"PeriodicalIF":3.4,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722607","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}

{"title":"Development and validation of generalized Monte Carlo track-structure simulation model applicable to arbitrary ions in arbitrary materials","authors":"Tatsuhiko Ogawa ,&nbsp;Yuho Hirata ,&nbsp;Yusuke Matsuya ,&nbsp;Takeshi Kai","doi":"10.1016/j.cpc.2025.109758","DOIUrl":"10.1016/j.cpc.2025.109758","url":null,"abstract":"<div><div>Ion Track-Structure model for Arbitrary Radiation and Target (ITSART) Ver.2, has been developed to simulate the transport of arbitrary ions in arbitrary materials, accounting for atomic interactions on an event-by-event basis. Unlike conventional track-structure models, which were dedicated to therapeutic particles in bio-materials such as water and DNA, ITSART Ver.2 uniquely enables track-structure calculations for any ion-material combination across an energy range from 10 eV/n to 1 TeV/n. This is a significant upgrade from Ver.1, which was capable of transporting only protons in the energy range from 1 keV to some 100 MeV.</div><div>To validate ITSART Ver.2, the energy-angular distributions of secondary electrons, ion stopping ranges, radial dose distributions, and microdosimetric distributions calculated by ITSART Ver.2 were benchmarked against literature data. The unique features of ITSART Ver.2, including kinetic modeling of secondary electrons above 1 keV, modeling of secondary electron angular distribution, momentum transfer to target atoms, and interface with an atomic de-excitation model, resulted in calculations consistent with the benchmarking data. Furthermore, this benchmarking calculation demonstrated that ITSART Ver.2 can reproduce target-specific quantities such as Auger electron production and penumbra radial dose, which cannot be simulated with conventional codes that approximate the target as water.</div><div>The capability of ITSART Ver.2 to perform track-structure calculations of protons and ions in arbitrary materials paves the way for simulating various irradiation effects, such as reactor material irradiation damage, semiconductor device degradation, and other complex interactions.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109758"},"PeriodicalIF":7.2,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144713656","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}

{"title":"Study of simplified conservation flux scheme for gas kinetics based on OpenFOAM framework II: Rykov model","authors":"Mengbo Zhu ,&nbsp;Qingdian Zhang ,&nbsp;Rui Zhang ,&nbsp;Congshan Zhuo ,&nbsp;Sha Liu ,&nbsp;Chengwen Zhong","doi":"10.1016/j.cpc.2025.109763","DOIUrl":"10.1016/j.cpc.2025.109763","url":null,"abstract":"<div><div>We present a computational fluid dynamics solver for diatomic gases, meticulously developed within the dugksFOAM framework. This solver is built upon a conservative gas kinetic scheme with simplified interface flux evaluations, enabling efficient and accurate solutions of the Rykov model equation. An unstructured discrete velocity space is introduced, in which the velocity points are strategically distributed to balance computational efficiency and numerical accuracy. A sophisticated hybrid parallelization strategy, referred to as X-space parallelization, has also been introduced. It integrates domain decomposition in both physical and velocity spaces, significantly enhancing computational efficiency in large-scale simulations. We further compare the computational efficiency between the structured and unstructured velocity space approaches, demonstrating that the unstructured configuration achieves notable reductions in computational cost without compromising accuracy. Moreover, the parallel performance of the solver is systematically evaluated under both small- and large-scale settings, showcasing excellent scalability and robustness. The accuracy and reliability of the solver are validated against a comprehensive set of benchmark cases, including shock structure problems, lid-driven cavity flow, supersonic flows past a flat plate, cylindrical blunt body, and sphere. These results convincingly confirm the solver's capability to capture a wide range of rarefied flow phenomena in diatomic gases, from one-dimensional to three-dimensional flows.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109763"},"PeriodicalIF":7.2,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144695040","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}

{"title":"Performance optimization of GJK collision detection in discrete element simulations","authors":"Alireza Yazdani ,&nbsp;Anthony Wachs","doi":"10.1016/j.cpc.2025.109768","DOIUrl":"10.1016/j.cpc.2025.109768","url":null,"abstract":"<div><div>This paper presents a comprehensive performance analysis of the Gilbert-Johnson-Keerthi (GJK) algorithm and its variants in the context of Discrete Element Method (DEM) simulations. Various optimization techniques, including bounding volumes, different distance sub-algorithms, Nesterov acceleration, and temporal coherence are investigated to evaluate their impact on computational efficiency for different particle shapes and aspect ratios. The study considers both static packing and rotating drum benchmarks, covering a wide range of particle geometries such as cubes, icosahedrons, cylinders, and superquadrics. Our findings indicate that the choice of bounding volume technique significantly affects performance, with oriented bounding cylinder outperforming oriented bounding boxes for elongated particles. Nesterov acceleration, although theoretically promising, generally shows limited performance improvements except for highly spherical particles. Temporal coherence, while beneficial for certain particle shapes and moderate aspect ratios, is less effective when particles are highly elongated or distant from each other. These results offer valuable insights for optimizing DEM simulations involving complex particle shapes and varying elongation levels.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109768"},"PeriodicalIF":7.2,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144695025","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}

{"title":"Dynasor 2: From simulation to experiment through correlation functions","authors":"Esmée Berger ,&nbsp;Erik Fransson ,&nbsp;Fredrik Eriksson ,&nbsp;Eric Lindgren ,&nbsp;Göran Wahnström ,&nbsp;Thomas Holm Rod ,&nbsp;Paul Erhart","doi":"10.1016/j.cpc.2025.109759","DOIUrl":"10.1016/j.cpc.2025.109759","url":null,"abstract":"<div><div>Correlation functions, such as static and dynamic structure factors, offer a versatile approach to analyzing atomic-scale structure and dynamics. By having access to the full dynamics from atomistic simulations, they serve as valuable tools for understanding material behavior. Experimentally, material properties are commonly probed through scattering measurements, which also provide access to static and dynamic structure factors. However, it is not trivial to decode these due to complex interactions between atomic motion and the probe. Atomistic simulations can help bridge this gap, allowing for detailed understanding of the underlying dynamics. In this paper, we illustrate how correlation functions provide structural and dynamical insights from simulation and showcase the strong agreement with experiment. To compute the correlation functions, we have updated the Python package <span>dynasor</span> with a new interface and, importantly, added support for weighting the computed quantities with form factors or cross sections, facilitating direct comparison with probe-specific structure factors. Additionally, we have incorporated the spectral energy density method, which offers an alternative view of the dispersion for crystalline systems, as well as functionality to project atomic dynamics onto phonon modes, enabling detailed analysis of specific phonon modes from atomistic simulation. We illustrate the capabilities of <span>dynasor</span> with diverse examples, ranging from liquid <figure><img></figure> to perovskites, and compare computed results with X-ray, electron and neutron scattering experiments. This highlights how computed correlation functions can not only agree well with experimental observations, but also provide deeper insight into the atomic-scale structure and dynamics of a material.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109759"},"PeriodicalIF":7.2,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144695041","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}

{"title":"CLT-fx: Non-axisymmetric flexible mesh finite difference scheme for stellarator MHD simulations","authors":"J. Wang ,&nbsp;Y. Zhou ,&nbsp;J.M. Duan ,&nbsp;Z.W. Ma ,&nbsp;W. Zhang","doi":"10.1016/j.cpc.2025.109776","DOIUrl":"10.1016/j.cpc.2025.109776","url":null,"abstract":"<div><div>The adaptive moving mesh CLT code is extended to be applicable for the stellarator magneto-hydrodynamic (MHD) simulations. Compared with the tokamak version, the mesh can not only be non-uniform, but can also be non-axisymmetric and strongly shaped with a concave boundary. The extra toroidal transformation from the physical domain to the computational domain has to be taken into consideration. In the computational domain, the fourth-order finite difference scheme is constructed on a Cartesian computational mesh. To verify the code, we simulate the internal kink mode in a W7-X configuration, and benchmark the linear and non-linear results with the M3D-C¹ code. The method can also be used for different 3D equilibria, and a calculation of the resistive ballooning mode in a NCSX equilibrium is given.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109776"},"PeriodicalIF":7.2,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144714091","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}

{"title":"Intelligent cross-linking in polymer simulations: SuSi’s approach to complex 3D networks","authors":"David Naranjo ,&nbsp;Didac Martí ,&nbsp;Carlos Alemán ,&nbsp;José García-Torres ,&nbsp;Juan Torras","doi":"10.1016/j.cpc.2025.109767","DOIUrl":"10.1016/j.cpc.2025.109767","url":null,"abstract":"<div><div>Cross-linked polymers play a vital role in the materials science due to their mechanical strength, chemical resistance, and thermal stability, making them invaluable in biomedical devices, coatings, and electronics. However, constructing realistic molecular models of these systems remains a challenge due to their complex cross-linked networks. This study introduces SuSi, a Python-based program designed to generate both linear and cross-linked polymer systems for molecular simulations. SuSi uses artificial intelligence tree search algorithms to optimize the cross-linking process, ensuring efficient and collision-free network formation. The program is compatible with the AMBER force field and supports a wide variety of polymer architectures, including homopolymers, block copolymers, and complex 3D-network structures. To demonstrate its capabilities, SuSi was employed to generate three distinct cross-linked systems: silane-cross-linked polyethylene (Si-XLPE), thermosensitive poly(NIPAAm-co-MBA), and the complex unsaturated polyesteramide hydrogel made of phenylalanine, butenediol, and fumarate, cross-linked with polyethylene glycol (UPEA-PEG). The generated structures were successfully parametrized for molecular dynamics simulations and validated through experimental observables, showing that SuSi is a versatile tool for accurately modeling complex polymeric systems and advancing polymer simulations.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109767"},"PeriodicalIF":7.2,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144695042","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}

{"title":"Integrating physics and data-driven approaches: An explainable and uncertainty-aware hybrid model for wind turbine power prediction","authors":"Alfonso Gijón ,&nbsp;Simone Eiraudo ,&nbsp;Antonio Manjavacas ,&nbsp;Daniele Salvatore Schiera ,&nbsp;Miguel Molina-Solana ,&nbsp;Juan Gómez-Romero","doi":"10.1016/j.cpc.2025.109761","DOIUrl":"10.1016/j.cpc.2025.109761","url":null,"abstract":"<div><div>The rapid growth of the wind energy sector underscores the urgent need to optimize turbine operations and ensure effective maintenance through early fault detection systems. While traditional empirical and physics-based models offer approximate predictions of power generation based on wind speed, they often fail to capture the complex, non-linear relationships between other input variables and the resulting power output. Data-driven machine learning methods present a promising avenue for improving wind turbine modeling by leveraging large datasets, enhancing prediction accuracy but often at the cost of interpretability. In this study, we propose a hybrid semi-parametric model that combines the strengths of both approaches, applied to a dataset from a wind farm with four turbines. The model integrates a physics-inspired submodel, providing a reasonable approximation of power generation, with a non-parametric submodel that predicts the residuals. This non-parametric submodel is trained on a broader range of variables to account for phenomena not captured by the physics-based component. The hybrid model achieves a 37% improvement in prediction accuracy over the physics-based model and performs comparably to a purely data-driven reference model, while offering additional advantages in terms of explainability and robustness. To further enhance interpretability, SHAP values are used to analyze the influence of input features on the residual submodel's output. Additionally, prediction uncertainties are quantified using a conformalized quantile regression method. The combination of these techniques, alongside the physics grounding of the parametric submodel, provides a flexible, accurate, and reliable framework. Ultimately, this study opens the door for evaluating the impact of unmodeled phenomena on wind turbine power generation, offering a basis for potential optimization.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109761"},"PeriodicalIF":7.2,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144672337","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}

{"title":"CWebGen A tool to study colour structure of scattering amplitudes in IR limit","authors":"Neelima Agarwal ,&nbsp;Sourav Pal ,&nbsp;Aditya Srivastav ,&nbsp;Anurag Tripathi","doi":"10.1016/j.cpc.2025.109765","DOIUrl":"10.1016/j.cpc.2025.109765","url":null,"abstract":"<div><div>Infrared singularities in perturbative Quantum Chromodynamics (QCD) are captured by the Soft function, which can be calculated efficiently in terms of multiparton webs. Web is a closed set of diagrams whose colour and kinematics mix through a web mixing matrix. The web mixing matrices are computed using a well known replica trick algorithm. We present a package implemented in Mathematica to calculate these mixing matrices. Along with the package, we provide benchmark points for several state-of-the art computations.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109765"},"PeriodicalIF":7.2,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679110","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}

{"title":"Machine learning assisted canonical sampling (Mlacs)","authors":"Aloïs Castellano ,&nbsp;Romuald Béjaud ,&nbsp;Pauline Richard ,&nbsp;Olivier Nadeau ,&nbsp;Clément Duval ,&nbsp;Grégory Geneste ,&nbsp;Gabriel Antonius ,&nbsp;Johann Bouchet ,&nbsp;Antoine Levitt ,&nbsp;Gabriel Stoltz ,&nbsp;François Bottin","doi":"10.1016/j.cpc.2025.109730","DOIUrl":"10.1016/j.cpc.2025.109730","url":null,"abstract":"&lt;div&gt;&lt;div&gt;The acceleration of material property calculations while maintaining &lt;em&gt;ab initio&lt;/em&gt; accuracy (1 meV/atom) is one of the major challenges in computational physics. In this paper, we introduce a Python package enhancing the computation of (finite temperature) material properties at the &lt;em&gt;ab initio&lt;/em&gt; level using machine learning interatomic potentials (MLIP). The Machine Learning Assisted Canonical Sampling (&lt;span&gt;Mlacs&lt;/span&gt;) method, grounded in a self-consistent variational approach, iteratively trains a MLIP using an active learning strategy in order to significantly reduce the computational cost of &lt;em&gt;ab initio&lt;/em&gt; simulations.&lt;/div&gt;&lt;div&gt;&lt;span&gt;Mlacs&lt;/span&gt; offers a modular and user-friendly interface that seamlessly integrates Density Functional Theory (DFT) codes, MLIP potentials, and molecular dynamics packages, enabling a wide range of applications, while maintaining a near-DFT accuracy. These include sampling the canonical ensemble of a system, performing free energy calculations, transition path sampling, and geometry optimization, all by utilizing surrogate MLIP potentials, in place of &lt;em&gt;ab initio&lt;/em&gt; calculations.&lt;/div&gt;&lt;div&gt;This paper provides a comprehensive overview of the theoretical foundations and implementation of the &lt;span&gt;Mlacs&lt;/span&gt; method. We also demonstrate its accuracy and efficiency through various examples, showcasing the capabilities of the &lt;span&gt;Mlacs&lt;/span&gt; package.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Program summary&lt;/h3&gt;&lt;div&gt;&lt;em&gt;Program title:&lt;/em&gt; &lt;span&gt;Mlacs&lt;/span&gt;&lt;/div&gt;&lt;div&gt;&lt;em&gt;CPC Library link to program files:&lt;/em&gt; &lt;span&gt;&lt;span&gt;https://doi.org/10.17632/vtfzjnc6cr.1&lt;/span&gt;&lt;svg&gt;&lt;path&gt;&lt;/path&gt;&lt;/svg&gt;&lt;/span&gt;&lt;/div&gt;&lt;div&gt;&lt;em&gt;Licensing provisions:&lt;/em&gt; GNU General Public License, version 3&lt;/div&gt;&lt;div&gt;&lt;em&gt;Programming language:&lt;/em&gt; Python&lt;/div&gt;&lt;div&gt;&lt;em&gt;Nature of problem:&lt;/em&gt; Numerous material properties, whether related to the ground state or finite temperature thermodynamic quantities, cannot be deduced from classical simulations and require accurate but highly demanding &lt;em&gt;ab initio&lt;/em&gt; calculations. Enhancing the efficiency of these simulations while preserving a near-&lt;em&gt;ab initio&lt;/em&gt; accuracy is one of the biggest challenges in modern computational physics.&lt;/div&gt;&lt;div&gt;&lt;em&gt;Solution method:&lt;/em&gt; The emergence of MLIP potentials enables us to tackle this issue. The method implemented in &lt;span&gt;Mlacs&lt;/span&gt; allows for the acceleration of &lt;em&gt;ab initio&lt;/em&gt; calculations by training a MLIP potential on the fly. At the end of the simulation, &lt;span&gt;Mlacs&lt;/span&gt; produces an optimal local surrogate potential, a database that includes a sample of representative atomic configurations with their statistical weights, as well as information on convergence control and thermodynamic quantities.&lt;/div&gt;&lt;div&gt;&lt;em&gt;Additional comments:&lt;/em&gt; The seminal version is defined in [1]. The new version [2], &lt;span&gt;Mlacs&lt;/span&gt; v1.0.2, works on various architectures and includes several new features.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;References&lt;/h3&gt;&lt;div&gt;&lt;ul&gt;","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109730"},"PeriodicalIF":7.2,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679111","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}