Computer Physics Communications最新文献

{"title":"Fire: An open-source adaptive mesh refinement solver for supersonic reacting flows","authors":"E. Fan ,&nbsp;Tianhan Zhang ,&nbsp;Jiaao Hao ,&nbsp;Chih-Yung Wen ,&nbsp;Lisong Shi","doi":"10.1016/j.cpc.2025.109881","DOIUrl":"10.1016/j.cpc.2025.109881","url":null,"abstract":"<div><div>In this study, we introduce Fire, an open-source adaptive mesh refinement (AMR) solver for supersonic reacting flows, and conduct theoretical analyses on the efficiency of AMR methods. Fire is developed within the AMR framework of ECOGEN (Schmidmayer et al., 2020). To accurately model compressible multi-component reacting flows, the Fire solver employs the thermally perfect gas model for multi-species gaseous mixtures, mixture-averaged transport models for viscous fluxes, and detailed finite-rate chemistry for combustion processes. The solver utilizes the Harten-Lax-van Leer Contact approximate Riemann solver with low-Mach number correction to evaluate inviscid fluxes, demonstrating its superiority over the traditional Harten-Lax-van Leer Contact solver on detonation simulations. Moreover, we deduce the theoretical speedup ratio (denoted as <span><math><msub><mrow><mi>η</mi></mrow><mrow><mtext>the</mtext></mrow></msub></math></span>) of AMR methods over uniform-grid methods by analyzing the advancing procedures. This theoretical analysis is well-supported by the numerical speedup ratio (denoted as <span><math><msub><mrow><mi>η</mi></mrow><mrow><mtext>num</mtext></mrow></msub></math></span>) given by numerical tests. To further enhance computational efficiency, we propose a three-stage AMR strategy specifically tailored to the characteristics of inert flows, flame fronts, and shock-flame interactions. Comprehensive validation tests, encompassing unsteady convection and diffusion, planar deflagration, inert and reacting shock-bubble interactions, planar detonations, and detonation cellular structures, confirm the accuracy and efficiency of Fire in simulating supersonic combustions. We anticipate that this work will not only serve as a valuable numerical tool for supersonic reacting flows research but also contribute to a deeper understanding and improvement of AMR methodologies.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"318 ","pages":"Article 109881"},"PeriodicalIF":3.4,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145263438","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":"Neural combinatorial wavelet neural operator for catastrophic forgetting free in-context operator learning of multiple partial differential equations","authors":"Tapas Tripura ,&nbsp;Souvik Chakraborty","doi":"10.1016/j.cpc.2025.109882","DOIUrl":"10.1016/j.cpc.2025.109882","url":null,"abstract":"<div><div>Machine learning has witnessed substantial growth in recent years, leading to the development of advanced deep learning models crafted to address a wide range of real-world challenges spanning various domains, including the acceleration of scientific computing. Contemporary deep learning approaches to solving partial differential equations (PDEs) involve approximating either the function mapping of a specific problem or the solution operators of a pre-defined physical system. Consequently, solving multiple PDEs representing a variety of physical systems requires training of multiple deep learning models. The creation of physics-specific models from scratch for each new physical system remains a resource-intensive undertaking, demanding considerable (i) computational time, (ii) memory resources, (iii) energy, (iv) intensive physics-specific manual tuning, and (v) large problem-specific training datasets. A more generalized machine learning-enhanced computational approach would be to learn a single unified deep learning model (commonly defined as the foundation model) instead of training multiple solvers from scratch. Besides accelerating computational simulations, such unified models will address all the above challenges. In this study, we introduce the Neural Combinatorial Wavelet Neural Operator (NCWNO) as a foundational model for scientific computing. The NCWNO leverages a gated structure that employs local wavelet integral blocks to acquire shared features across multiple physical systems, complemented by a memory-based ensembling approach among these local wavelet experts. The proposed NCWNO offers two key advantages: (i) it can simultaneously learn solution operators for multiple parametric PDEs, and (ii) with pre-training, it can be fine-tuned to new parametric PDEs with reduced training datasets and time. The proposed NCWNO is the first kernel-based foundational operator learning algorithm distinguished by its (i) integral-kernel-based learning structure, (ii) robustness against catastrophic forgetting of old PDEs, and (iii) the facilitation of knowledge transfer across dissimilar physical systems. Through an extensive set of benchmark examples, we demonstrate that the NCWNO can outperform existing multiphysics and task-specific baseline operator learning frameworks.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"318 ","pages":"Article 109882"},"PeriodicalIF":3.4,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145227754","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":"Physics informed neural networks with variable Eddington factor iteration for linear radiative transfer equations","authors":"Yuhang Wu ,&nbsp;Jianhua Huang ,&nbsp;Xu Qian ,&nbsp;Wenjun Sun","doi":"10.1016/j.cpc.2025.109879","DOIUrl":"10.1016/j.cpc.2025.109879","url":null,"abstract":"<div><div>In this paper, a Physics Informed Neural Networks (PINNs) method based on Variable Eddington Factor (VEF) acceleration iteration is proposed to address the time-dependent linear radiative transfer equations (LRTEs), which exhibit the characteristics of multi-scale and high dimensionality. Firstly, the factors relating to the failure of the vanilla PINNs in solving LRTEs within the diffusion regime are analyzed by the Neural Tangent Kernel (NTK) theory. Subsequently, the VEF-PINNs method is established, where PINNs are employed to handle the radiative transfer equations and the analytic VEF equations that are used to accelerate the iteration process. It is demonstrated that as the Knudsen number <em>ε</em> approaches 0, the VEF-PINNs method converges to the iteration of diffusion limit equations, thereby ensuring the proposed method maintains the asymptotic preserving property. A theoretical analysis about the approximation errors of the iterative solution of the VEF-PINNs method is given. To evaluate the performance of the method, comparisons are made with the vanilla PINNs and Asymptotic Preserving Neural Networks (APNNs) based on micro-macro decomposition. The results reveal that the proposed VEF-PINNs can effectively solve LRTEs in various opacity regimes and can enhance the solving efficiency to a certain extent.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"318 ","pages":"Article 109879"},"PeriodicalIF":3.4,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145263524","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":"Lethe 1.0: An open-source parallel high-order computational fluid dynamics software framework for single and multiphase flows","authors":"Amishga Alphonius ,&nbsp;Lucka Barbeau ,&nbsp;Bruno Blais ,&nbsp;Olivier Gaboriault ,&nbsp;Olivier Guévremont ,&nbsp;Justin Lamouche ,&nbsp;Pierre Laurentin ,&nbsp;Oreste Marquis ,&nbsp;Peter Munch ,&nbsp;Victor Oliveira Ferreira ,&nbsp;Hélène Papillon-Laroche ,&nbsp;Paul Alexander Patience ,&nbsp;Laura Prieto Saavedra ,&nbsp;Mikael Vaillant","doi":"10.1016/j.cpc.2025.109880","DOIUrl":"10.1016/j.cpc.2025.109880","url":null,"abstract":"&lt;div&gt;&lt;div&gt;&lt;span&gt;Lethe&lt;/span&gt; is an open-source Computational Fluid Dynamics (CFD) software framework with extensive multiphase and multiphysics capabilities. By leveraging the &lt;span&gt;deal.II&lt;/span&gt; open-source framework, &lt;span&gt;Lethe&lt;/span&gt; finite element solvers scale well on modern high-performance computers while possessing advanced features such as dynamic mesh adaptation, load-balancing, isoparametric high-order capabilities, and a fully-fledged Discrete Element Method (DEM) module. To facilitate contributions from the community, &lt;span&gt;Lethe&lt;/span&gt; is extensively tested with continuous integration using over 450 unit and functional tests. Furthermore, &lt;span&gt;Lethe&lt;/span&gt; contains 74 fully documented examples with pre-processing and post-processing steps to allow users to learn how to rapidly use and modify the framework. In this article, we give an overview of the simulation models available within &lt;span&gt;Lethe&lt;/span&gt; and illustrate these capabilities with a selected list of examples including turbulent and multiphase flows.&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;Lethe&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/mc5trb4kd3.1&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;Developer's repository link:&lt;/em&gt; &lt;span&gt;&lt;span&gt;https://github.com/chaos-polymtl/lethe&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; Apache-2.0&lt;/div&gt;&lt;div&gt;&lt;em&gt;Programming language:&lt;/em&gt; C++&lt;/div&gt;&lt;div&gt;&lt;em&gt;Nature of problem:&lt;/em&gt; Single-phase incompressible flows of Newtonian and generalized Newtonian fluids. Granular flows of cohesive or non-cohesive spherical particles. Multiphase flows, including particle-laden (solid-liquid and solid-gas) flows and fluid-fluid (gas-liquid and liquid-liquid) flows. Multiphysics coupling with heat transfer.&lt;/div&gt;&lt;div&gt;&lt;em&gt;Solution method:&lt;/em&gt; &lt;span&gt;Lethe&lt;/span&gt; uses stabilized continuous Galerkin finite element formulations to solve the incompressible Navier-Stokes equations and other partial differential equations. &lt;span&gt;Lethe&lt;/span&gt; utilizes the DEM to simulate granular flows. For particle-laden flow simulations, &lt;span&gt;Lethe&lt;/span&gt; uses an unresolved CFD-DEM approach for flows containing numerous spherical particles (&lt;span&gt;&lt;math&gt;&lt;mo&gt;&gt;&lt;/mo&gt;&lt;msup&gt;&lt;mrow&gt;&lt;mn&gt;10&lt;/mn&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;3&lt;/mn&gt;&lt;/mrow&gt;&lt;/msup&gt;&lt;/math&gt;&lt;/span&gt;), while a resolved CFD-DEM approach is used for flows with few spherical or non-spherical particles (&lt;100). For gas-liquid and liquid-liquid flows, Volume of Fluid (VOF) or Cahn–Hilliard (CH) models are used.&lt;/div&gt;&lt;div&gt;&lt;em&gt;Additional comments including restrictions and unusual features:&lt;/em&gt; &lt;span&gt;Lethe&lt;/span&gt; possesses both matrix-based and matrix-free CFD solvers for incompressible flows. The matrix-free solver efficiently simulates larger problem sizes with more than 1B unknowns, but only supports hexahedral (structured or unstructured) meshes, whereas the matrix-based solver supports both tetrahedral an","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"318 ","pages":"Article 109880"},"PeriodicalIF":3.4,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145263439","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":"HEART: A new X-ray tracing code for mosaic crystal spectrometers","authors":"Thomas Gawne ,&nbsp;Sebastian Schwalbe ,&nbsp;Thomas Chuna ,&nbsp;Uwe Hernandez Acosta ,&nbsp;Thomas R. Preston ,&nbsp;Tobias Dornheim","doi":"10.1016/j.cpc.2025.109878","DOIUrl":"10.1016/j.cpc.2025.109878","url":null,"abstract":"<div><div>We introduce a new open-source Python x-ray tracing code for modelling Bragg diffracting mosaic crystal spectrometers: <em>High Energy Applications Ray Tracer (HEART)</em>. <em>HEART</em>'s high modularity enables customizable workflows as well as efficient development of novel features. Utilizing Numba's just-in-time (JIT) compiler and the message-passing interface (MPI) allows running <em>HEART</em> in parallel leading to excellent performance. <em>HEART</em> is intended to be used for modelling x-ray spectra as they would be seen in experiments that measure x-ray spectroscopy with a mosaic crystal spectrometer. This enables the user to make predictions about what will be seen on a detector in experiment, perform optimizations on the design of the spectrometer setup, or to study the effect of the spectrometer on measured spectra. However, the code certainly has further uses beyond these example use cases. Here, we discuss the physical model used in the code, and explore a number of different mosaic distribution functions, intrinsic rocking curves, and sampling approaches which are available to the user. Finally, we demonstrate its strong predictive capability in comparison to spectroscopic data collected at the European XFEL in Germany.</div></div><div><h3>Program summary</h3><div><em>Program Title:</em> High Energy Applications Ray Tracer (HEART)</div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/d3wc5jxdgj.1</span><svg><path></path></svg></span></div><div><em>Developer's repository link:</em> <span><span>https://gitlab.com/heart-ray-tracing/HEART</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> GPLv3</div><div><em>Programming language:</em> Python ≥3.10</div><div><em>Nature of problem:</em> Mosaic crystal spectrometers are widely-used at high energy density (HED) facilities owing to their very high integrated reflectivities. However, the mosaic nature of the crystal introduces a lot of complexity into the instrument functions of these spectrometers. Understanding how the mosaic crystal will impact the measured spectrum is vital for reliably inferring conditions measured via x-ray spectroscopy and for planning experiments.</div><div><em>Solution method:</em> We have developed a ray tracing code with specific support for mosaic crystals. With the implemented precise dynamical theory models, our ray tracing code simulates accurate detector images enabling realistic comparisons with experiments. It takes advantage of the inherent randomness of mosaic crystals to run Monte Carlo simulations of rays passing through the crystal. This also means the detector images produced contain similar photon counting noise that would appear in experiments. A number of options for crystal materials, geometries, mosaic distribution functions, and rocking curves are supported. Effects such as absorption and multiple ray reflections are also treated explicitly.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"318 ","pages":"Article 109878"},"PeriodicalIF":3.4,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145227728","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":"Fourier pseudospectral methods for the variable-order space fractional wave equations","authors":"Yanzhi Zhang ,&nbsp;Xiaofei Zhao ,&nbsp;Shiping Zhou","doi":"10.1016/j.cpc.2025.109876","DOIUrl":"10.1016/j.cpc.2025.109876","url":null,"abstract":"<div><div>In this paper, we propose Fourier pseudospectral methods to solve the variable-order space fractional wave equation and develop an accelerated matrix-free approach for its effective implementation. In constant-order cases, fast algorithms can be designed via the fast Fourier transforms (FFTs), and the computational cost at each time step is <span><math><mi>O</mi><mo>(</mo><mi>N</mi><mi>log</mi><mo>⁡</mo><mi>N</mi><mo>)</mo></math></span> with <em>N</em> the total number of spatial points. In variable-order cases, however, the spatial dependence in the power <span><math><mi>s</mi><mo>(</mo><mi>x</mi><mo>)</mo></math></span> leads to the failure of inverse FFTs. While the direct matrix-vector multiplication approach becomes impractical due to excessive memory requirements. Hence, we propose an accelerated matrix-free approach for effective implementation in variable-order cases. The computational and storage costs are <span><math><mi>O</mi><mo>(</mo><mi>M</mi><mi>N</mi><mi>log</mi><mo>⁡</mo><mi>N</mi><mo>)</mo></math></span> and <span><math><mi>O</mi><mo>(</mo><mi>M</mi><mi>N</mi><mo>)</mo></math></span>, respectively, with <span><math><mi>M</mi><mo>≪</mo><mi>N</mi></math></span>. Moreover, our method can be easily parallelized to further enhance efficiency. Numerical studies show that our methods are effective in solving the variable-order space fractional wave equations, especially in high-dimensional cases. Wave propagation in heterogeneous media is studied in comparison to homogeneous counterparts. We find that wave dynamics in fractional cases become more intricate due to nonlocal interactions. Particularly, dynamics in heterogeneous media are more complex than those in homogeneous media.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"318 ","pages":"Article 109876"},"PeriodicalIF":3.4,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145227755","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 of a high-order MPI-Kokkos accelerated fluid solver","authors":"Filipp Sporykhin ,&nbsp;Holger Homann","doi":"10.1016/j.cpc.2025.109873","DOIUrl":"10.1016/j.cpc.2025.109873","url":null,"abstract":"<div><div>This work discusses the performance of a modern numerical scheme for fluid dynamical problems on modern high-performance computing (HPC) architectures. Our code implements a spatial nodal discontinuous Galerkin (NDG) scheme that we test up to an order of convergence of eight. It is temporally coupled to a set of Runge-Kutta (RK) methods of orders up to six. The code integrates the linear advection equations as well as the isothermal Euler equations in one, two, and three dimensions. In order to target modern hardware involving many-core Central Processing Units (CPUs) and accelerators such as Graphic Processing Units (GPUs) we use the Kokkos library in conjunction with the Message Passing Interface (MPI) to run our single source code on various NVidia and AMD GPU systems.</div><div>By means of one- and two-dimensional simulations of simple test equations we find that the higher the order the faster is the code. Eighth-order simulations attain a given global error with much less computing time than third- or fourth-order simulations. The RK scheme has a smaller impact on the code performance and a classical fourth-order scheme seems to generally be a good choice.</div><div>The code performs very well on all considered HPC GPUs. We observe very good scaling properties up to 64 AMD MI250x GPUs and we show that the scaling properties are the same in two and three dimensions. The many-CPU performance is also very good and perfect weak scaling is observed up to many hundreds of CPU cores using MPI. We note that small grid-size simulations are faster on CPUs than on GPUs while GPUs win significantly over CPUs for simulations involving more than 10⁷ degrees of freedom (<span><math><mo>≈</mo><msup><mrow><mn>3100</mn></mrow><mrow><mn>2</mn></mrow></msup></math></span> grid points). When it comes to the environmental impact of numerical simulations we estimate that GPUs consume less energy than CPUs for large grid-size simulations but more energy on small grids. Further, we observe a tendency that the more modern is the GPU the larger needs to be the grid in order to use it efficiently. This yields a rebound effect because larger simulations need longer computing times and in turn more energy that is not compensated by the energy efficiency gain of the newer GPUs.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"318 ","pages":"Article 109873"},"PeriodicalIF":3.4,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145227727","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":"First-principles calculation of higher-order elastic constants from divided differences","authors":"Ruvini Attanayake ,&nbsp;Umesh C. Roy ,&nbsp;Abhiyan Pandit ,&nbsp;Angelo Bongiorno","doi":"10.1016/j.cpc.2025.109877","DOIUrl":"10.1016/j.cpc.2025.109877","url":null,"abstract":"<div><div>A method is presented to calculate from first principles the higher-order elastic constants of a solid material. The method relies on finite strain deformations, a density functional theory approach to calculate the Cauchy stress tensor, and a recursive numerical differentiation technique homologous to the divided differences polynomial interpolation algorithm. The method is applicable as is to any material, regardless its symmetry, to calculate elastic constants of, in principle, any order. Here, we introduce conceptual framework and technical details of our method, we discuss sources of errors, we assess convergence trends, and we present selected applications. In particular, our method is used to calculate elastic constants up to the 6<span><math><msup><mrow></mrow><mrow><mi>t</mi><mi>h</mi></mrow></msup></math></span> order of two crystalline materials with the cubic symmetry, silicon and gold. To demonstrate general applicability, our method is also used to calculate the elastic constants up to the 5<span><math><msup><mrow></mrow><mrow><mi>t</mi><mi>h</mi></mrow></msup></math></span> order of <em>α</em>-quartz, a crystalline material belonging to the trigonal crystal system, and the second- and third-order elastic constants of kevlar, a material with an anisotropic bonding network. Higher order elastic constants computed with our method are validated against density functional theory calculations by comparing stress responses to large deformations derived within the continuum approximation.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"318 ","pages":"Article 109877"},"PeriodicalIF":3.4,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145156860","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":"Modeling and verification of dynamic field ionization for laser-target interactions","authors":"Brandon M. Medina,&nbsp;Scott V. Luedtke,&nbsp;Lin Yin,&nbsp;Brian J. Albright","doi":"10.1016/j.cpc.2025.109875","DOIUrl":"10.1016/j.cpc.2025.109875","url":null,"abstract":"<div><div>Integrating field ionization models into kinetic plasma simulations is required for a variety of applications, especially when field strengths vary from low to high regimes, such as in laser-target interactions. The introduction of new physics models into kinetic codes requires a rigorous verification of their accuracy through well-defined verification problems. In this work, the field ionization model that has been included in the kinetic plasma code VPIC is presented, along with the detailed approach adopted for its integration. This model includes a comprehensive range of field ionization mechanisms: multiphoton ionization, tunneling ionization, and barrier suppression ionization. New verification problems employed to evaluate the ionization model's fidelity are outlined, and the simulation parameters that affect the accuracy of simulation results are explored. Additionally, this work addresses the impact of field ionization on computational performance.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"318 ","pages":"Article 109875"},"PeriodicalIF":3.4,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145156859","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":"GRILLIX as unified fluid turbulence code for tokamaks and stellarators","authors":"Andreas Stegmeir ,&nbsp;Marion E. Finkbeiner ,&nbsp;Christoph Pitzal ,&nbsp;Joachim Geiger ,&nbsp;Frank Jenko","doi":"10.1016/j.cpc.2025.109874","DOIUrl":"10.1016/j.cpc.2025.109874","url":null,"abstract":"<div><div>The Flux-Coordinate Independent (FCI) approach in the edge fluid turbulence code <span>GRILLIX</span> has proven very successful for tokamaks in handling anisotropic turbulent structures in complex diverted geometries. We extend GRILLIX to non-axisymmetric geometries, maintaining a single, unified codebase for both tokamaks and stellarators. For this proof of principle, the 3D magnetic configurations are based on analytical expressions, that can be adjusted to experimental scenarios, and we demonstrate the code's ability to resolve stellarator geometries correctly via various numerical tests and verifications. We apply the global electromagnetic drift-reduced Braginskii fluid model with trans-collisional extensions and a three-moment fluid neutrals model to two distinct cases. In the first case, we simulate a configuration with imposed magnetic islands and observe profile flattening across the island on time scales consistent with analytic theory. In the second case, we perform a comprehensive turbulence simulation of the Wendelstein 7-AS (W7-AS) stellarator at realistic parameters, including segmented target plates modeled via the immersed boundary approach. Following an initial transient phase, the plasma settles into a self-consistent equilibrium state with Shafranov shift. We then observe small-scale turbulence, characterized by strong elongation along magnetic field lines, which drives turbulent cross-field transport of particles and heat, ultimately directed to target plates in the open field line region. Notably, a parallel mode reflecting the discrete toroidal symmetry of W7-AS is also present. Furthermore, we introduce a novel approach for visualizing data from locally aligned numerical frameworks.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"318 ","pages":"Article 109874"},"PeriodicalIF":3.4,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145156857","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}