Computer Physics Communications最新文献

{"title":"A non-periodic particle mesh Ewald method for radially symmetric kernels in free space","authors":"Dennis M. Elking","doi":"10.1016/j.cpc.2025.109739","DOIUrl":"10.1016/j.cpc.2025.109739","url":null,"abstract":"<div><div>The FFT-based smooth particle mesh Ewald (PME) method is extended to non-periodic charge systems interacting via a radially symmetric kernel <span><math><mi>f</mi><mo>(</mo><mi>r</mi><mo>)</mo></math></span>. The proposed non-periodic PME (NPME) method begins by splitting the kernel <span><math><mi>f</mi><mo>(</mo><mi>r</mi><mo>)</mo></math></span> into a short-range component <span><math><msub><mrow><mi>f</mi></mrow><mrow><mi>s</mi></mrow></msub><mo>(</mo><mi>r</mi><mo>)</mo></math></span> and a smooth long-range component <span><math><msub><mrow><mi>f</mi></mrow><mrow><mi>l</mi></mrow></msub><mo>(</mo><mi>r</mi><mo>)</mo></math></span>. A Fourier extension for <span><math><msub><mrow><mi>f</mi></mrow><mrow><mi>l</mi></mrow></msub><mo>(</mo><mi>r</mi><mo>)</mo></math></span> is computed numerically using discrete Fourier transform interpolation, enabling efficient treatment of anisotropic rectangular charge volume and offering additional flexibility in the choice of kernel splitting. A derivative-matched (DM) splitting is introduced for general radially symmetric kernels <span><math><mi>f</mi><mo>(</mo><mi>r</mi><mo>)</mo></math></span>, improving computational performance over traditional Ewald splitting methods. An optimized grid storage algorithm for NPME is proposed, reducing total grid memory by a factor of four. The NPME algorithm is implemented in a C++ library, <span>npme</span>, which supports both pre-defined kernels (e.g. <span><math><mn>1</mn><mo>/</mo><mi>r</mi><mo>,</mo><msup><mrow><mi>r</mi></mrow><mrow><mi>α</mi></mrow></msup><mo>,</mo><mi>exp</mi><mo>⁡</mo><mo>(</mo><mi>i</mi><msub><mrow><mi>k</mi></mrow><mrow><mn>0</mn></mrow></msub><mi>r</mi><mo>)</mo><mo>/</mo><mi>r</mi></math></span>) and user-defined kernels via C++ classes. <span>npme</span> is benchmarked and compared to <span>fmm3D</span> on test systems in computational chemistry and computational electromagnetics. As a practical application, NPME is combined with Method of Moments (MoM) to form a hybrid MoM-NPME algorithm for calculating the radar cross section (RCS) of a perfect electric conductor (PEC). The MoM–NPME method is used to compute the bistatic RCS of a 1-meter PEC sphere at 37.8 GHz and the monostatic RCS of the NASA almond at 75 GHz.</div></div><div><h3>Program summary</h3><div><em>Program Title:</em> <span>npme</span></div><div><em>CPC Library link to program files:</em> <span><span><span>https://doi.org/10.17632/vs86pk3dpt.1</span></span><svg><path></path></svg></span></div><div><em>Developer's repository link:</em> <span><span><span>https://github.com/ElkingD/npme</span></span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> Apache 2.0</div><div><em>Programming language:</em> C++</div><div><em>Supplementary material:</em> A supplementary material containing additional technical details and results is provided.</div><div><em>Nature of problem:</em> <span>npme</span> computes the potential and its gradient of <em>N</em> ","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"315 ","pages":"Article 109739"},"PeriodicalIF":7.2,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144597089","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":"Evaluation and sensitivity analysis of the FitzHugh–Nagumo model parameters for studying electrical signals generated by different biological tissues","authors":"Fabian Andres Castaño Usuga","doi":"10.1016/j.cpc.2025.109738","DOIUrl":"10.1016/j.cpc.2025.109738","url":null,"abstract":"<div><div>Accurate modeling of cardiac electrical activity is essential for developing diagnostic and therapeutic technologies. This study presents a parameter evaluation of a modified FitzHugh–Nagumo (FHN) model to reproduce the specific waveforms generated by different cardiac tissues, such as the sinoatrial node, atria, atrioventricular node, Purkinje fibers, and ventricles. Through a systematic sensitivity analysis, the influence of key parameters on waveform features such as amplitude, duration, and frequency is identified, allowing precise calibration for each tissue type. These parameter sets were then integrated into a multi-compartment model and implemented in a two-dimensional (2D) spatial domain using COMSOL Multiphysics, following the framework of Sovilj et al. The simulations successfully replicated electrocardiographic components—including the P wave, QRS complex, and T wave—by combining spatially distributed signals with physiologically representative dynamics. Rather than proposing a new model, this work validates a methodology for tuning and applying simplified excitable models to simulate realistic cardiac behavior efficiently. The approach offers potential applications in the design of low-power wearable devices and supports the development of personalized monitoring systems. Future work will extend this methodology to other excitable tissues and explore its use in modeling pathological conditions or structural constraints, providing a flexible platform for evaluating requirements in next-generation bioelectronic devices.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"315 ","pages":"Article 109738"},"PeriodicalIF":7.2,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144580443","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":"Conformal approach to physics simulations for thin curved 3D membranes","authors":"Igor Bogush ,&nbsp;Vladimir M. Fomin ,&nbsp;Oleksandr V. Dobrovolskiy","doi":"10.1016/j.cpc.2025.109736","DOIUrl":"10.1016/j.cpc.2025.109736","url":null,"abstract":"<div><div>Three-dimensional nanoarchitectures are widely used across various areas of physics, including spintronics, photonics, and superconductivity. In this regard, thin curved 3D membranes are especially interesting for applications in nano- and optoelectronics, sensorics, and information processing, making physics simulations in complex 3D geometries indispensable for unveiling new physical phenomena and the development of devices. Here, we present a general-purpose approach to physics simulations for thin curved 3D membranes, that allows for performing simulations using finite difference methods instead of meshless methods or methods with irregular meshes. The approach utilizes a numerical conformal mapping of the initial surface to a flat domain and is based on the uniformization theorem stating that any simply-connected Riemann surface is conformally equivalent to an open unit disk, a complex plane, or a Riemann sphere. We reveal that for many physical problems involving the Laplace operator and divergence, a flat-domain formulation of the initial problem only requires a modification of the equations of motion and the boundary conditions by including a conformal factor and the mean/Gaussian curvatures. We demonstrate the method's capabilities for case studies of the Schrödinger equation for a charged particle in static electric and magnetic fields for 3D geometries, including C-shaped and ring-shaped structures, as well as for the time-dependent Ginzburg-Landau equation.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"315 ","pages":"Article 109736"},"PeriodicalIF":7.2,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144580548","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":"Record acceleration of the two-dimensional Ising model using a high-performance wafer-scale engine","authors":"Dirk Van Essendelft ,&nbsp;Hayl Almolyki ,&nbsp;Wei Shi ,&nbsp;Terry Jordan ,&nbsp;Mei-Yu Wang ,&nbsp;Wissam A. Saidi","doi":"10.1016/j.cpc.2025.109734","DOIUrl":"10.1016/j.cpc.2025.109734","url":null,"abstract":"<div><div>The versatility and wide-ranging applicability of the Ising model, originally introduced to study phase transitions in magnetic materials, have made it a cornerstone in statistical physics and a valuable tool for evaluating the performance of emerging computer hardware. Here, we present a novel implementation of the two-dimensional Ising model on Cerebras Wafer-Scale Engine (WSE) – a revolutionary processor that is opening new frontiers in computing. In our implementation of the checkerboard algorithm, we optimized the Ising model to take advantage of the unique WSE architecture. Specifically, we employed a compressed bit representation that stores 16 spins on each <span>int16</span> word, and efficiently distributed the spins over the processing units, enabling seamless weak scaling and limiting communication to only immediate neighboring units. Our implementation can handle up to 754 simulations in parallel, achieving an aggregate of over 61.8 trillion flip attempts per second for Ising models with up to 200 million spins. This represents a gain of up to 148 times over previously reported single-devices with a highly optimized implementation on NVIDIA V100 and up to 88 times in productivity compared to NVIDIA H100. Our findings highlight the significant potential of the WSE in scientific computing, particularly in the field of materials modeling.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"315 ","pages":"Article 109734"},"PeriodicalIF":7.2,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144597088","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 for transmission spectra prediction on gradient seismic metastructure","authors":"Yilin Rao ,&nbsp;Liangshu He ,&nbsp;Yabin Jin ,&nbsp;Hehua Zhu ,&nbsp;Timon Rabczuk ,&nbsp;Xiaoying Zhuang","doi":"10.1016/j.cpc.2025.109750","DOIUrl":"10.1016/j.cpc.2025.109750","url":null,"abstract":"<div><div>Seismic metastructure based on phononic crystal theory provides a possible solution to accurately manipulating surface acoustic waves. However, the prediction of gradient seismic metastructure for transmission spectra in clay remains a significant challenge due to the damping characteristics of actual soils and practical engineering factors, which become a research hotspot in recent years. Based on finite element analyses and machine learning techniques, this work proposed a data-driven method for building a general prediction model of embedded pillar seismic metastructure with different multi-resonator gradients in the clayed soil. We employed a multilayer perceptron (MLP) model, with the multi-resonator gradients of the metastructure as the input, to predict the transmission spectra. To achieve input standardization, we applied an Autoencoder (AE) to construct a unified representation of the inputs. Due to the inherent non-linearity and variability in soil-structure interactions, the attenuation zones prediction results can only offer approximate engineering applications under specific conditions. By utilizing machine learning, our method achieves better generalization and can be adapted to a wider range of metastructure configurations. This research not only advances the gradient seismic metastructure design framework but also opens new avenues for practical applications in surface acoustic wave management.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"315 ","pages":"Article 109750"},"PeriodicalIF":7.2,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144597090","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":"Data-driven reduced modeling of streamer discharges in air","authors":"Jannis Teunissen ,&nbsp;Alejandro Malagón-Romero","doi":"10.1016/j.cpc.2025.109733","DOIUrl":"10.1016/j.cpc.2025.109733","url":null,"abstract":"<div><div>We present a computational framework for simulating filamentary electric discharges, in which channels are represented as conducting cylindrical segments. The framework requires a model that predicts the position, radius, and line conductivity of channels at a next time step. Using this information, the electric conductivity on a numerical mesh is updated, and the new electric potential is computed by solving a variable-coefficient Poisson equation. A parallel field solver with support for adaptive mesh refinement is used, and the framework provides a Python interface for easy experimentation. We demonstrate how the framework can be used to simulate positive streamer discharges in air. First, a dataset of 1000 axisymmetric positive streamer simulations is generated, in which the applied voltage and the electrode geometry are varied. Fit expressions for the streamer radius, velocity, and line conductivity are derived from this dataset, taking as input the size of the high-field region ahead of the streamers. We then construct a reduced model for positive streamers in air, which includes a stochastic branching model. The reduced model compares well with the axisymmetric simulations from the dataset, while allowing spatial and temporal step sizes that are several orders of magnitude larger. 3D simulations with the reduced model resemble experimentally observed discharge morphologies. The model runs efficiently, with 3D simulations with 20+ streamers taking 4–8 minutes on a desktop computer.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"315 ","pages":"Article 109733"},"PeriodicalIF":7.2,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144572495","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":"AutoEncoders latent space interpretability in the light of proper orthogonal decomposition: Machine learning of periodically forced fluid flows","authors":"Rémi Bousquet,&nbsp;Caroline Nore,&nbsp;Didier Lucor","doi":"10.1016/j.cpc.2025.109728","DOIUrl":"10.1016/j.cpc.2025.109728","url":null,"abstract":"<div><div>This work explores the learning and interpretability challenges of Autoencoders (AEs) and Variational Autoencoders (VAEs) when applied to the reconstruction of dynamic velocity fields governed by the Navier-Stokes equations. Throughout model training, the emphasis is on understanding how flow features are encoded into the latent space and how this impacts the interpretability and usability of the models. Based on a parametric study of forced flows, i.e. flows around an oscillating cylinder, as well as a von Kármán swirling flow, we first investigate the trade-offs between reconstruction accuracy and regularization in VAEs. We confirm that increasing the regularization parameter degrades reconstruction quality, which underscores a significant limitation of the Gaussian prior from this point of vue. A comparative analysis reveals that standard AEs exhibit quite robust training behaviour, while VAEs show a sharper transition between non-learning and learning regimes, depending on the amount of regularization. By leveraging Proper Orthogonal Decomposition (POD) to identify characteristic flow structures and frequencies, we establish connections between latent space organisations and POD modes. To address the interpretability challenge, we then perform a symmetry analysis of latent spaces, stating equivariance relations between latent and physical variables. Despite reduced reconstruction precision, VAEs show greater fidelity in preserving these relationships. Building on this, we propose a clustering-inspired method to interpret latent representations, identifying characteristic states from temporal POD time coefficients to provide deeper insights into latent space structure and untangling. This work highlights pathways for autoencoder's analysis methodological advancements, emphasizing the critical need to align latent space representations with physical interpretation for broader applicability in fluid dynamics.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"315 ","pages":"Article 109728"},"PeriodicalIF":7.2,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549650","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":"High-performance data format for scientific data storage and analysis","authors":"Gagik Gavalian","doi":"10.1016/j.cpc.2025.109732","DOIUrl":"10.1016/j.cpc.2025.109732","url":null,"abstract":"<div><div>In this article, we present the High-Performance Output (HiPO) data format developed at Jefferson Laboratory for storing and analyzing data from Nuclear Physics experiments. The format was designed to efficiently store large amounts of experimental data, utilizing modern fast compression algorithms. The purpose of this development was to provide organized data in the output, facilitating access to relevant information within the large data files. The HiPO data format has features that are suited for storing raw detector data, reconstruction data, and the final physics analysis data efficiently, eliminating the need to do data conversions through the lifecycle of experimental data. The HiPO data format is implemented in C++ and JAVA, and provides bindings to FORTRAN, Python, and Julia, providing users with the choice of data analysis frameworks to use. In this paper, we will present the general design and functionalities of the HiPO library and compare the performance of the library with more established data formats used in data analysis in High Energy and Nuclear Physics (such as ROOT <span><span>[3]</span></span> and Parquete).</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"315 ","pages":"Article 109732"},"PeriodicalIF":7.2,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144518928","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":"A numerical study of the symplectic FDTD(p,q) method combined with matrix exponential technique for anisotropic magnetized plasma","authors":"Guilin Hou ,&nbsp;Guoda Xie ,&nbsp;Wenjie Ding ,&nbsp;Yingsong Li ,&nbsp;Yang Hong ,&nbsp;Zhixiang Huang","doi":"10.1016/j.cpc.2025.109735","DOIUrl":"10.1016/j.cpc.2025.109735","url":null,"abstract":"<div><div>A novel algorithm has been developed to simulate the electromagnetic properties of anisotropic magnetized plasma media, integrating the matrix exponential (ME) approach with the symplectic finite-difference time-domain (ME-SFDTD⁽<em>^p</em>^,<em>^q</em>⁾) method. The SFDTD⁽<em>^p</em>^,<em>^q</em>⁾ method achieves <em>p</em>-th order accuracy in the temporal domain and <em>q</em>-th order accuracy in the spatial domain, providing a foundational numerical discretization of Maxwell's equations and the current density equation. Subsequently, the ME method is employed to accurately solve the matrix exponential coefficient terms that arise from the multi-stage symplectic integration of the governing equations. This leads to the successful establishment of a unified numerical framework for the ME-SFDTD⁽<em>^p</em>^,<em>^q</em>⁾ method, capable of computing the field components in anisotropic magnetized plasma regions. In parallel, an efficient sub-grid technique is introduced to manage the air-plasma interface when employing a high-order spatial difference approximation. Following this, a thorough analysis of the numerical characteristics of the proposed method, including dispersion, stability, and computational complexity, is conducted. Additionally, two numerical examples are utilized to examine the computational characteristics of the ME-SFDTD⁽<em>^p</em>^,<em>^q</em>⁾ method under different differential strategies. Finally, a comprehensive assessment of computational accuracy, efficiency, and memory usage observes that the ME-SFDTD^(4,4) method effectively reconciles the trade-off between these factors, establishing itself as a viable numerical solver for the accurate simulation of anisotropic magnetized plasmas.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"315 ","pages":"Article 109735"},"PeriodicalIF":7.2,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549649","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":"Hybrid EPIC–GOD: An energy–conserving hybrid particle–in–cell code for GPU acceleration using OpenACC","authors":"Sunjung Kim ,&nbsp;Dongsu Ryu ,&nbsp;G.S. Choe ,&nbsp;Sibaek Yi","doi":"10.1016/j.cpc.2025.109726","DOIUrl":"10.1016/j.cpc.2025.109726","url":null,"abstract":"<div><div>Hybrid simulations, which combine ion particles with an inertialess, charge-neutralizing electron fluid, offer a valuable bridge between fully kinetic particle–in–cell (PIC) and magnetohydrodynamic (MHD) approaches. In this paper, we present Hybrid EPIC–GOD, a new hybrid particle–in–cell code designed to ensure strict conservation of both local charge and total energy—two critical properties often neglected in conventional hybrid codes.</div><div>Hybrid EPIC–GOD solves the coupled equations governing ion particle dynamics and electromagnetic fields using an iterative scheme. The code exactly satisfies the charge continuity equation, while total energy conservation is guaranteed through the iterative convergence process. We describe the implementation in detail and validate the code's performance across a broad spectrum of plasma processes, including waves, instabilities, collisionless shocks, and magnetic reconnection.</div><div>The results show that Hybrid EPIC–GOD accurately reproduces analytical solutions and benchmark results, while maintaining rigorous charge and energy conservation. Moreover, the code is optimized for GPU acceleration using OpenACC, delivering significant performance gains when running on multiple GPUs compared to its CPU–based counterpart. With its combination of accuracy, conservation properties, and computational efficiency, Hybrid EPIC–GOD provides a powerful tool for studying collisionless plasma dynamics in both space and astrophysical environments.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"315 ","pages":"Article 109726"},"PeriodicalIF":7.2,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144518927","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}