Computer Physics Communications最新文献

{"title":"Gamma ray spectrum inversion based on master-secondary encoder-decoder network","authors":"Hu Rundu ,&nbsp;Liu Jian ,&nbsp;Zhou Ruijie ,&nbsp;Hu Liqun","doi":"10.1016/j.cpc.2025.109688","DOIUrl":"10.1016/j.cpc.2025.109688","url":null,"abstract":"<div><div>Gamma-ray diagnosis can detect the energy and spatial distribution of fast ions, as well as identify disruption signs. The detector's response to the gamma-ray spectrum involves complex mappings, requiring a fast and accurate spectrum reconstruction method. The challenge lies in the ill-conditioned nature of spectrum inversion, where errors in measurement can significantly amplify the uncertainties of the inversion results. To solve this, additional information is needed, introducing non-linearity into the problem. Traditional approaches typically rely on iterative algorithms, such as linear regularization, maximum likelihood estimation method (ML-EM), and Gold deconvolution (Gold). Recently, neural networks have gained traction due to their strong capability in handling non-linear and highly ill-posed problems. In this paper, we present a method leveraging a master-secondary network structure that splits the spectrum inversion into two simpler sub-problems, improving outcomes beyond those of a single network. This network structure is verified suitable for solving highly ill-posed inversion problems and applying to gamma-ray spectrum reconstruction. Our method's accuracy is compared to ML-EM and Gold, demonstrating superior stability and effectiveness, particularly under high noise conditions, achieving a level suitable for practical applications. This method has been successfully applied to gamma-ray spectrum detection in the EAST tokamak facility.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"315 ","pages":"Article 109688"},"PeriodicalIF":7.2,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195533","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":"PHOENIX – Paderborn highly optimized and energy efficient solver for two-dimensional nonlinear Schrödinger equations with integrated extensions","authors":"Jan Wingenbach ,&nbsp;David Bauch ,&nbsp;Xuekai Ma ,&nbsp;Robert Schade ,&nbsp;Christian Plessl ,&nbsp;Stefan Schumacher","doi":"10.1016/j.cpc.2025.109689","DOIUrl":"10.1016/j.cpc.2025.109689","url":null,"abstract":"&lt;div&gt;&lt;div&gt;In this work, we introduce PHOENIX, a highly optimized explicit open-source solver for two-dimensional nonlinear Schrödinger equations with extensions. The nonlinear Schrödinger equation and its extensions (Gross-Pitaevskii equation) are widely studied to model and analyze complex phenomena in fields such as optics, condensed matter physics, fluid dynamics, and plasma physics. It serves as a powerful tool for understanding nonlinear wave dynamics, soliton formation, and the interplay between nonlinearity, dispersion, and diffraction. By extending the nonlinear Schrödinger equation, various physical effects such as non-Hermiticity, spin-orbit interaction, and quantum optical aspects can be incorporated. PHOENIX is designed to accommodate a wide range of applications by a straightforward extendability without the need for user knowledge of computing architectures or performance optimization. The high performance and power efficiency of PHOENIX are demonstrated on a wide range of entry-class to high-end consumer and high-performance computing GPUs and CPUs. Compared to a more conventional MATLAB implementation, a speedup of up to three orders of magnitude and energy savings of up to 99.8% are achieved. The performance is compared to a performance model showing that PHOENIX performs close to the relevant performance bounds in many situations. The possibilities of PHOENIX are demonstrated with a range of practical examples from the realm of nonlinear (quantum) photonics in planar microresonators with active media including exciton-polariton condensates. Examples range from solutions on very large grids, the use of local optimization algorithms, to Monte Carlo ensemble evolutions with quantum noise enabling the tomography of the system's quantum state.&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; PHOENIX&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/kthy8wj3n5.1&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/Schumacher-Group-UPB/PHOENIX/&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 provision:&lt;/em&gt; MIT&lt;/div&gt;&lt;div&gt;&lt;em&gt;Programming language:&lt;/em&gt; C++, CUDA&lt;/div&gt;&lt;div&gt;&lt;em&gt;Nature of problem:&lt;/em&gt; Time evolution of two-dimensional nonlinear systems such as Bose-Einstein condensates, nonlinear optical systems or hybrid light-matter systems (e.g., exciton-polariton condensates).&lt;/div&gt;&lt;div&gt;&lt;em&gt;Solution method:&lt;/em&gt; Solving the extended two-dimensional nonlinear Schrödinger equation (Gross-Pitaevskii equation) on uniformly discretized grids in real-space with a wide range of Runge-Kutta schemes. The use of CPU and GPU and the precision used (fp32/fp64) can be set when compiling the code. Sub-grid decomposition is possible for optimal cache efficiency. The solver provides a framework that allows users unfamiliar with the details of GPU and CPU parallelization to extend the set of equations with addition","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"315 ","pages":"Article 109689"},"PeriodicalIF":7.2,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144204341","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 coupled finite volume-lattice Boltzmann method for incompressible internal flows","authors":"Yang Zhou ,&nbsp;Marta Camps Santasmasas ,&nbsp;Alessandro De Rosis ,&nbsp;Ian Hinder ,&nbsp;Charles Moulinec ,&nbsp;Alistair Revell","doi":"10.1016/j.cpc.2025.109686","DOIUrl":"10.1016/j.cpc.2025.109686","url":null,"abstract":"<div><div>We present, test and validate a two-way framework that couples macroscopic and mesoscopic methods to simulate incompressible internal flows spanning a range of spatial and temporal scales. Specifically, the unstructured finite volume method (FVM) is coupled to the structured lattice Boltzmann method (LBM). The multi-resolution domain is resolved through two strategies, <em>i.e.</em>, non-Cartesian FVM meshes and multi-level refinement LBM using octree-like Cartesian grid points. The coupled approach divides the entire computational domain into sub-regions, each solved independently. Information exchange between these sub-regions is facilitated by a coupling library that introduces spatial interpolation and temporal iteration schemes for different scales. The effectiveness of the proposed coupled strategy is assessed against well-documented benchmark tests and further examined in scenarios involving flow over artificial porous media. The results obtained by the new coupled framework show excellent agreement with reference data and exhibit strong parallel performance for tests on up to 32768 CPU cores, demonstrating the potential of the approach for large-scale investigations.</div></div><div><h3>Program summary</h3><div><em>Program Title:</em> code_saturne-LUMA-coupling</div><div><em>CPC Library link to program file:</em> <span><span>https://github.com/yangzhou-10/code_saturne-LUMA-coupling</span><svg><path></path></svg></span></div><div><em>LUMA licensing provisions:</em> Apache License 2.0</div><div><em>LUMA programming language:</em> C++</div><div><em>code_saturne licensing provisions:</em> GNU General Public License v2.0</div><div><em>code_saturne programming language:</em> C, C++</div><div><em>Nature of problem:</em> Traditional single CFD numerical methods face significant challenges in multiscale flow simulations. Numerical methods, relying on the continuum medium hypothesis, often overlook or approximate microscale effects using empirical schemes. Conversely, micro/mesoscopic methods are constrained by the computational resources required to simulate the entire domain comprehensively.</div><div><em>Solution method:</em> A coupled FVM-LBM scheme is developed wherein the computational domain is partitioned into macroscopic and microscopic sub-regions, solved independently using the FVM and LBM, respectively. Communication between these sub-regions is facilitated via a coupling interface implemented using the PLE coupling library. The LBM code is developed within the LUMA package, while the FVM code is integrated into the framework of <em>code_saturne</em>. The PLE coupling library is embedded within the <em>code_saturne</em> package.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"314 ","pages":"Article 109686"},"PeriodicalIF":7.2,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144134491","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":"FVM realization in Eulerian SPH: A comparative study within unified codebase","authors":"Zhentong Wang,&nbsp;Chi Zhang,&nbsp;Oskar J. Haidn,&nbsp;Nikolaus A. Adams,&nbsp;Xiangyu Hu","doi":"10.1016/j.cpc.2025.109683","DOIUrl":"10.1016/j.cpc.2025.109683","url":null,"abstract":"<div><div>Eulerian smoothed particle hydrodynamics (Eulerian SPH) is considered a potential meshless alternative to a traditional Eulerian mesh-based finite volume method (FVM) in computational fluid dynamics (CFD). While researchers have analyzed the differences between these two methods, a rigorous comparison of their performance and computational efficiency is hindered by the following two challenges: Firstly, the Eulerian SPH framework faces a constraint related to the normal direction of interfaces in pairwise particle interactions, which prevents achieving an equivalent algorithm of FVM; Secondly, there is no unified solver available that can be applied to both Eulerian SPH and FVM methods. To address the former constraint, this paper implements a certain form of Eulerian SPH method, where a kernel gradient correction is introduced to release the constraint. To address the latter constraint, the paper realizes the mesh-based FVM within an open-source SPH library using a shared solver, i.e. single algorithm for two methods, through developing a parser that extracts necessary information from the “.msh” format file exported from a commercial pre-processing tool, ICEM (Integrated Computer Engineering and Manufacturing). Several 2D and 3D numerical simulations using both methods within a unified codebase demonstrate that compared to the mesh-based FVM, the Eulerian SPH achieves smoother results and, when using a high-order kernel, a faster convergence rate, but at the cost of lower computational efficiency.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"314 ","pages":"Article 109683"},"PeriodicalIF":7.2,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144134404","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":"An efficiency and memory-saving programming paradigm for the unified gas-kinetic scheme","authors":"Yue Zhang ,&nbsp;Yufeng Wei ,&nbsp;Wenpei Long ,&nbsp;Kun Xu","doi":"10.1016/j.cpc.2025.109684","DOIUrl":"10.1016/j.cpc.2025.109684","url":null,"abstract":"<div><div>In recent years, non-equilibrium flows have gained significant attention in aerospace engineering and micro-electro-mechanical systems. The unified gas-kinetic scheme (UGKS) follows the methodology of direct modeling to couple particle collisions and free transport during gas evolution. However, like other discrete-velocity-based methods, the UGKS faces challenges related to high memory requirements and computational costs, such as the possible consumption of 1.32 TB of memory when using 512 cores for the simulations of the hypersonic flow around an X38-like space vehicle. This paper introduces a new UGKS programming paradigm for unstructured grids, focusing on reducing memory usage and improving parallel efficiency. By optimizing the computational sequence, the current method enables each cell in physical space to store only the distribution function for the discretized velocity space, eliminating the need to retain the entire velocity space for slopes and residuals. Additionally, the parallel communication is enhanced through the use of non-blocking MPI. Numerical experiments demonstrate that the new strategy in the programming effectively simulates non-equilibrium problems while achieving high computational efficiency and low memory consumption. For the hypersonic flow around an X38-like space vehicle, the simulation, which utilizes <span><math><mn>1</mn><mo>,</mo><mn>058</mn><mo>,</mo><mn>685</mn></math></span> physical mesh cells and <span><math><mn>4</mn><mo>,</mo><mn>548</mn></math></span> discrete velocity space mesh cells, requires only 99.30 GB for 32 cores and 168.12 GB for 512 cores of memory when executed on 512 CPU cores. This indicates that memory consumption in the UGKS is much reduced. This new programming paradigm can serve as a reference for discrete velocity methods for solving kinetic equations.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"314 ","pages":"Article 109684"},"PeriodicalIF":7.2,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144146922","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":"An immersed boundary lattice Boltzmann method on block-structured adaptive grids for the simulation of particle-laden flows on CPUs/GPUs","authors":"Yaning Wang ,&nbsp;Yuchen Wu ,&nbsp;Yadong Zeng ,&nbsp;Maoqiang Jiang ,&nbsp;Zhaohui Liu","doi":"10.1016/j.cpc.2025.109674","DOIUrl":"10.1016/j.cpc.2025.109674","url":null,"abstract":"<div><div>We developed a highly efficient CPUs/GPUs solver for the fully resolved simulation of particle-laden flows by combining the lattice Boltzmann method (LBM) for fluid and the immersed boundary method (IBM) for fluid-structure interaction into the framework of adaptive mesh refinement (AMR). The cell-centered finite volume LBM method is adopted to guarantee the mass conservation. The boundary thickening direct force-immersed boundary method is used to capture the surface of solids to satisfy the no-slip and no-permeability boundary conditions while retaining computational simplicity. The AMR algorithm is implemented on the open-source framework <em>AMReX</em>, where the solids are placed only on the finest level, and different levels advance the solutions with varying steps of time, greatly reducing the computational cost and improving stability. The developed solver achieves 97.95% weak scaling efficiency on up to 128 GPUs by optimization and specific selection of BoxSize. An 18.2-fold speedup is obtained in the case of 3-level AMR meshes, compared to that on a uniform mesh, while reducing memory usage by 97.4%. Several classic cases also validated the solver, including flow past a two-dimensional fixed/oscillating circle cylinder, flow past a three-dimensional fixed sphere, and particles freely settling with stable and unstable patterns. The qualitative and quantitative results show that this highly efficient solver has good accuracy, robustness, scalability and extensibility for the complex particle-laden flows conventionally with heavy computing cost.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"314 ","pages":"Article 109674"},"PeriodicalIF":7.2,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144139683","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":"QuForge: A library for qudits simulation","authors":"Tiago de Souza Farias ,&nbsp;Lucas Friedrich ,&nbsp;Jonas Maziero","doi":"10.1016/j.cpc.2025.109687","DOIUrl":"10.1016/j.cpc.2025.109687","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Quantum computing with qudits, an extension of qubits to multiple levels, offers promising advantages in information representation and computational density. Despite its potential, tools for qudit-based quantum computation remain underdeveloped. This article presents QuForge, a Python-based library that introduces a novel computational framework for simulating quantum circuits with arbitrary qudit dimensions. QuForge distinguishes itself by providing scalable and extensible features, such as a complete set of customizable quantum gates, support for sparse matrix representations, and compatibility with GPU and TPU accelerators to optimize performance. By leveraging differentiable frameworks, QuForge accelerates simulations and facilitates quantum machine learning and algorithm development research. Through empirical demonstrations and benchmarks, we highlight the capabilities of the library to address scalability challenges and enable advances in quantum information science, establishing it as a potential tool for advancing research and applications in high-dimensional quantum computing.&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; QuForge&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/10.17632/8yxx46xgxm.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/tiago939/QuForge&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; Python&lt;/div&gt;&lt;div&gt;&lt;em&gt;Nature of problem:&lt;/em&gt; Quantum computing with qudits, a multi-level extension of qubits, provides advantages in computational density and error correction potential. However, the field faces significant challenges due to a lack of accessible, efficient, and scalable simulation tools tailored for qudits. Existing quantum simulation libraries either primarily focus on qubits or offer limited support for higher-dimensional systems, requiring significant manual effort from users to define gates and circuits. This complexity limits the exploration of high-dimensional quantum systems and the development of algorithms that leverage the unique properties of qudits, such as their expanded state spaces and denser information encoding. Additionally, the high computational and memory overhead associated with simulating large qudit systems further hinders progress, especially in machine learning and hybrid classical-quantum algorithm research.&lt;/div&gt;&lt;div&gt;&lt;em&gt;Solution method:&lt;/em&gt; The library QuForge addresses these challenges by providing a Python-based library specifically designed for simulating qudit quantum circuits. Leveraging differentiable programming frameworks such as PyTorch, QuForge enables seamless integration with GPUs and TPUs for efficient computation. The library incorporates a comprehensive set of pre-implemented qudit gates, including generalized Hadamard, rotation, and controlled gates, al","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"314 ","pages":"Article 109687"},"PeriodicalIF":7.2,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144139586","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 new method for finding more symmetry relations of Feynman integrals","authors":"Zihao Wu ,&nbsp;Yang Zhang","doi":"10.1016/j.cpc.2025.109681","DOIUrl":"10.1016/j.cpc.2025.109681","url":null,"abstract":"<div><div>We introduce a new method for deriving Feynman integral symmetry relations. By solving the ansatz of momentum transformation in the field of rational functions rather than constants, this method can sometimes find more symmetry relations, compared to some state-of-the-art software. The new method may help to further decrease the number of unique sectors in an integral family. Well-chosen gauge conditions are implemented in this method for the efficient symmetry searching.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"314 ","pages":"Article 109681"},"PeriodicalIF":7.2,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144146921","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":"QWAK: Quantum walk analysis kit","authors":"Jaime Santos ,&nbsp;Bruno Chagas ,&nbsp;Rodrigo Chaves ,&nbsp;Lorenzo Buffoni","doi":"10.1016/j.cpc.2025.109676","DOIUrl":"10.1016/j.cpc.2025.109676","url":null,"abstract":"<div><div>In this paper, we describe a continuous-time quantum walk (CTQW) simulation package for <span>Python 3</span>, covering their theoretical foundations and practical applications. The software provides both unitary and open system evolution of over general graphs, alongside tools for visualization and exploration of several different aspects of the quantum walk. We go over installation, design and performance of the package, concluding with several examples on how <span>QWAK</span> can be used to explore problems such as search, perfect state transfer, among others. Additionally, we demonstrate how <span>CuPy</span> is utilized to leverage GPU acceleration.</div></div><div><h3>Program Summary/New Version Program Summary</h3><div><em>Program Title:</em> QWAK</div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/wyrm54zc3f.1</span><svg><path></path></svg></span></div><div><em>Developer's repository link:</em> <span><span>https://github.com/JaimePSantos/QWAK</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> CC By 4.0</div><div><em>Programming language:</em> Python, Javascript, HTML and CSS.</div><div><em>Nature of problem:</em> <span>QWAK</span> simulates unitary and stochastic continuous-time quantum walks, focusing on transport property analysis, applications, visualization and ease of use.</div><div><em>Solution method:</em> We leverage <span>Python</span>'s vast package resources such as <span>NumPy</span> and <span>NetworkX</span> to implement the desired structures, and then generate the Hamiltonians via spectral decomposition. For the stochastic case, the Lindblad master equations are solved with <span>Qutip</span>.</div><div><em>Additional comments including restrictions and unusual features:</em> The GUI provided uses <span>MongoDB</span> to store <span>QWAK</span> objects, which currently limits the size of the graphs since the adjacency matrices are also stored.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"314 ","pages":"Article 109676"},"PeriodicalIF":7.2,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144115069","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":"Self-consistent charging of complex objects in flowing plasma: Implementation and analysis in WarpX","authors":"Ashwyn Sam,&nbsp;Sigrid Elschot","doi":"10.1016/j.cpc.2025.109680","DOIUrl":"10.1016/j.cpc.2025.109680","url":null,"abstract":"<div><div>The charging of conducting bodies in plasma environments is a fundamental process with implications spanning astrophysical, space, and laboratory plasmas. Accurate modeling of this charging process is essential for understanding and predicting the behavior of objects interacting with plasmas. In this study, we present the implementation of a charging algorithm in the open-source particle-in-cell code WarpX, which enables the simulation of charging for arbitrary 3D geometries in a plasma. The algorithm is verified against analytical solutions from orbital motion limited (OML) theory for a sphere in a static plasma and against published numerical results for a CubeSat in a flowing plasma. We investigate the charging of debris in Low Earth Orbit (LEO) conditions, considering both spherical and realistic debris geometries generated using a custom tool. The simulations reveal that the debris surface potential oscillates at the plasma frequency Doppler-shifted into the lab frame, a phenomenon not previously reported. The oscillations are robust to numerical convergence tests and persist for irregular debris geometries. Reduced density simulations suggest a critical threshold below which the oscillations disappear. Contrary to some earlier studies, precursor solitons do not form in our realistic LEO simulations, even with self-consistent charging of irregular debris. This study demonstrates WarpX's new capabilities for high-fidelity simulations of object charging in plasmas and highlights the complex nature of plasma-object interactions. The insights gained can inform the development of debris detection and mitigation strategies, while the WarpX code provides a valuable tool for future research in this field.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"314 ","pages":"Article 109680"},"PeriodicalIF":7.2,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144115067","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}