Computer Physics Communications最新文献

{"title":"M2C: An open-source software for multiphysics simulation of compressible multi-material flows and fluid-structure interactions","authors":"Xuning Zhao , Wentao Ma , Shafquat Islam , Aditya Narkhede , Kevin Wang","doi":"10.1016/j.cpc.2026.110023","DOIUrl":"10.1016/j.cpc.2026.110023","url":null,"abstract":"<div><div>M2C (Multiphysics Modeling and Computation) is an open-source software for simulating multi-material fluid flows and fluid-structure interactions under extreme conditions, such as high pressures, high temperatures, shock waves, and large interface deformations. It employs a finite volume method to solve the compressible Navier-Stokes equations and supports a wide range of thermodynamic equations of state. M2C incorporates models of laser radiation and absorption, phase transition, and ionization, coupled with continuum dynamics. Multi-material interfaces are evolved using a level set method, while fluid-structure interfaces are tracked using an embedded boundary method. Advective fluxes across interfaces are computed using FIVER (FInite Volume method based on Exact multi-material Riemann problems). For two-way fluid-structure interaction, M2C is coupled with the open-source structural dynamics solver Aero-S using a partitioned procedure. The M2C code is written in C++ and parallelized with MPI for high-performance computing. The source package includes a set of example problems for demonstration and user training. Accuracy is verified through benchmark cases such as Riemann problems, interface evolution, single-bubble dynamics, and ionization response. Several multiphysics applications are also presented, including laser-induced thermal cavitation, explosion and blast mitigation, and hypervelocity impact.</div><div><strong>PROGRAM SUMMARY</strong> <em>Program Title:</em> M2C (Multiphysics Modeling and Computation)</div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/gdjrrjwgf4.1</span><svg><path></path></svg></span></div><div><em>Developer’s repository link:</em> <span><span>https://github.com/kevinwgy/m2c</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> GNU General Public License 3</div><div><em>Programming language:</em> C++</div><div><em>Supplementary material:</em> The M2C package includes a suite of test cases that illustrate the software’s capabilities. These examples can also serve as templates for setting up new simulations.</div><div><em>Nature of problem:</em> This work addresses the analysis of multi-material fluid flow and fluid-structure interaction problems under conditions involving high pressure, high velocity, high temperature, or a combination of them. In such problems, material compressibility and thermodynamics play a significant role, and the system may exhibit shock waves, large structural deformations, and large deformation of fluid material subdomains. Unlike conventional fluid dynamics problems, the boundaries of the fluid domain and material subdomains are time-dependent, unknown in advance, and must be determined as part of the analysis. Across material interfaces, some state variables (e.g., density) may exhibit jumps of several orders of magnitude, while others (e.g., normal velocity) remain continuous. Some problems may also involve strong ","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"321 ","pages":"Article 110023"},"PeriodicalIF":3.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145973838","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 quantum Monte Carlo algorithm for arbitrary high-spin Hamiltonians","authors":"Arman Babakhani ,&nbsp;Lev Barash ,&nbsp;Itay Hen","doi":"10.1016/j.cpc.2026.110037","DOIUrl":"10.1016/j.cpc.2026.110037","url":null,"abstract":"<div><div>We present a universal quantum Monte Carlo algorithm for simulating arbitrary high-spin (spin greater than 1/2) Hamiltonians, based on the recently developed permutation matrix representation (PMR) framework. Our approach extends a previously developed PMR-QMC method for spin-1/2 Hamiltonians [Phys. Rev. Research 6, 013281 (2024)]. Because it does not rely on a local bond decomposition, the method applies equally well to models with arbitrary connectivities, long-range and multi-spin interactions, and its closed-walk formulation allows a natural analysis of sign-problem conditions in terms of cycle weights. To demonstrate its applicability and versatility, we apply our method to spin-1 and spin-3/2 quantum Heisenberg models on the square lattice, as well as to randomly generated high-spin Hamiltonians. Additionally, we show how the approach naturally extends to general Hamiltonians involving mixtures of particle species, including bosons and fermions. We have made our program code freely accessible on GitHub.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"321 ","pages":"Article 110037"},"PeriodicalIF":3.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146073662","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":"HepLib: a C++ library for high energy physics (version 1.2)","authors":"Jia-Chen Dai,&nbsp;Feng Feng,&nbsp;Ming-Ming Liu","doi":"10.1016/j.cpc.2026.110026","DOIUrl":"10.1016/j.cpc.2026.110026","url":null,"abstract":"<div><div>The version <span>1.2</span> of the <span>HepLib</span> (a <span>C++</span> <span>Lib</span>rary for computations in <span>H</span>igh <span>E</span>nergy <span>P</span>hysics) is presented. <span>HepLib</span> builds on top of other well-established libraries or programs, including <span>GINAC</span>, <span>FLINT</span>, <span>FORM</span>, <span>FIRE</span>, <em>etc.</em>, its first version has been released in Comput. Phys. Commun. <strong>265</strong>, 107,982 (2021). Here we provide another minor upgraded version <span>1.2</span>, in which the internal depended libraries or programs are updated to their latest versions, several bugs are fixed, many functional performances are improved, and lots of new features are also introduced. We also carry out experimental tests on the program <span>FIRE</span>, employing <span>FLINT</span> to enhance its performance with multivariate polynomials in the integrate-by-parts (IBP) reduction.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"321 ","pages":"Article 110026"},"PeriodicalIF":3.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034927","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":"SUperman: Efficient permanent computation on GPUs","authors":"Deniz Elbek ,&nbsp;Fatih Taşyaran ,&nbsp;Bora Uçar ,&nbsp;Kamer Kaya","doi":"10.1016/j.cpc.2026.110027","DOIUrl":"10.1016/j.cpc.2026.110027","url":null,"abstract":"&lt;div&gt;&lt;div&gt;The &lt;em&gt;permanent&lt;/em&gt; is a function, defined for a square matrix, with applications in various domains including quantum computing, statistical physics, complexity theory, combinatorics, and graph theory. Its formula is similar to that of the determinant; however, unlike the determinant, its exact computation is #P-complete, i.e., there is no algorithm to compute the permanent in polynomial time unless P=NP. For an &lt;em&gt;n&lt;/em&gt; × &lt;em&gt;n&lt;/em&gt; matrix, the fastest algorithm has a time complexity of &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;O&lt;/mi&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;msup&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;mrow&gt;&lt;mi&gt;n&lt;/mi&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/mrow&gt;&lt;/msup&gt;&lt;mi&gt;n&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;. Although supercomputers have been employed for permanent computation before, there is no work and, more importantly, no publicly available software that leverages cutting-edge High-Performance Computing accelerators such as GPUs. In this work, we design, develop, and investigate the performance of &lt;span&gt;SUperman&lt;/span&gt;, a complete software suite that can compute matrix permanents on multiple nodes/GPUs on a cluster while handling various matrix types, e.g., real/complex/binary and sparse/dense, etc., with a unique treatment for each type. &lt;span&gt;SUperman&lt;/span&gt; run on a single Nvidia A100 GPU is up to 86 ×  faster than a state-of-the-art parallel algorithm on 44 Intel Xeon cores running at 2.10GHz. Leveraging 192 GPUs, &lt;span&gt;SUperman&lt;/span&gt; computes the permanent of a 62 × 62 matrix in 1.63 days, marking the largest reported permanent computation to date.&lt;/div&gt;&lt;div&gt;PROGRAM SUMMARY&lt;/div&gt;&lt;div&gt;&lt;em&gt;Program Title:&lt;/em&gt; &lt;span&gt;SUperman&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/10.17632/5fhxcvfmrw.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/SU-HPC/superman&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(please choose one):&lt;/em&gt; MIT&lt;/div&gt;&lt;div&gt;&lt;em&gt;Programming language:&lt;/em&gt; &lt;span&gt;C++&lt;/span&gt;, &lt;span&gt;CUDA&lt;/span&gt;&lt;/div&gt;&lt;div&gt;&lt;em&gt;Nature of problem:&lt;/em&gt;&lt;/div&gt;&lt;div&gt;The permanent plays a crucial role in various fields such as quantum computing, statistical physics, combinatorics, and graph theory. Unlike the determinant, computing the permanent is #P-complete [1] and its exact computation has exponential complexity. Even the fastest known algorithms require time that grows exponentially with matrix dimensions, making the problem computationally intractable for large matrices. The state-of-the-art tools leverage supercomputers [2, 3], but there remains a notable gap in publicly available software that exploits modern High-Performance Computing accelerators, such as GPUs. This limitation makes the researchers who require efficient and scalable methods for permanent computation suffer, particularly when dealing with various matrix types (real, complex, binary, sparse, dense) in practical applications.&lt;/div&gt;&lt;div&gt;&lt;em&gt;Solution method:&lt;/em&gt; &lt;span&gt;SUperman&lt;/span&gt; is a complete open-sourc","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"321 ","pages":"Article 110027"},"PeriodicalIF":3.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034925","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":"SPUMA: A minimally invasive approach to the GPU porting of OPENFOAM®","authors":"Simone Bnà ,&nbsp;Giuseppe Giaquinto ,&nbsp;Ettore Fadiga ,&nbsp;Tommaso Zanelli ,&nbsp;Francesco Bottau","doi":"10.1016/j.cpc.2025.110009","DOIUrl":"10.1016/j.cpc.2025.110009","url":null,"abstract":"<div><div>High Performance Computing (HPC) on hybrid clusters represents a significant opportunity for Computational Fluid Dynamics (CFD), especially when modern accelerators are utilized effectively. However, despite the widespread adoption of GPUs, programmability remains a challenge, particularly in open-source contexts. In this paper, we present SPUMA, a full GPU porting of OPENFOAM® targeting NVIDIA and AMD GPUs. The implementation strategy is based on a portable programming model and the adoption of a memory pool manager that leverages the unified memory feature of modern GPUs. This approach is discussed alongside several numerical tests conducted on two pre-exascale clusters in Europe, LUMI and Leonardo, which host AMD MI250X and NVIDIA A100 GPUs, respectively. In the performance analysis section, we present results related to memory usage profiling and kernel wall-time, the impact of the memory pool, and energy consumption obtained by simulating the well-known DrivAer industrial test case. GPU utilization strongly affects strong scalability results, reaching 65% efficiency on both LUMI and Leonardo when approaching a load of 8 million cells per GPU. Weak scalability results, obtained on 20 GPUs with the OpenFOAM native multigrid solver, range from 75% on Leonardo to 85% on LUMI. Notably, efficiency is no lower than 90% when switching to the NVIDIA AmgX linear algebra solver. Our tests also reveal that one A100 GPU on Leonardo is equivalent 200–300 Intel Sapphire Rapids cores, provided the GPUs are sufficiently oversubscribed (more than 10 million of cells per GPU). Finally, energy consumption is reduced by up to 82% compared to analogous simulations executed on CPUs.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"321 ","pages":"Article 110009"},"PeriodicalIF":3.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034991","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":"GPU-parallelized MATLAB software for atom-ion dynamics","authors":"Saajid Chowdhury,&nbsp;Jesús Pérez-Ríos","doi":"10.1016/j.cpc.2026.110041","DOIUrl":"10.1016/j.cpc.2026.110041","url":null,"abstract":"<div><div>We present a MATLAB script, <span>atomiongpu.m</span>, which can use GPU parallelization to run several million independent simulations per day of a trapped ion interacting with a low-density cloud of atoms, calculating classical trajectories of a trapped ion and an atom starting far away. The script uses <span>ode45gpu</span>, which is our optimized and specialized implementation of the Runge-Kutta algorithm used in MATLAB’s ODE solver <span>ode45</span>. We first discuss the physical system and show how <span>ode45gpu</span> can, on a CPU, solve it about 7x faster than MATLAB’s <span>ode45</span>, leading to a 600x-3500x speedup when running a million trajectories using <span>ode45gpu</span> in parallel on a GPU compared to <span>ode45</span> on a CPU. Then, we show how to easily modify the inputs to <span>atomiongpu.m</span> to account for different kinds of atoms, ions, atom-ion interactions, trap potentials, simulation parameters, initial conditions, and computational hardware, so that <span>atomiongpu.m</span> automatically finds the probability of complex formation, the distribution of observables such as the scattering angle and complex lifetime, and plots of specific trajectories.</div></div><div><h3>PROGRAM SUMMARY</h3><div><em>Program Title:</em> <span>atomiongpu.m</span></div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/sjw4hzw9jx.1</span><svg><path></path></svg></span></div><div><em>Developer’s repository link:</em> <span><span>https://github.com/saajidchowdhury/supplementGPU</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> CC0 1.0</div><div><em>Programming language:</em> MATLAB R2023a, with Parallel Computing Toolbox installed</div><div><em>Supplementary material:</em> <span><span>https://github.com/saajidchowdhury/supplementGPU</span><svg><path></path></svg></span></div><div><em>Nature of problem:</em> Simulate classical dynamics (Newton’s laws) of an ion and atom, with up to several million different sets of initial conditions, store the final conditions and a few other scalar observables and their distributions, and plot specific trajectories.</div><div><em>Solution method:</em> Implementing the algorithm behind <span>ode45</span>, MATLAB’s fourth/fifth-order adaptive-timestep Runge-Kutta method for propagating ordinary differential equations, we write a single, self-contained function, <span>ode45gpu</span>. Then, we use MATLAB’s <span>arrayfun</span> to parallelize it on multiple CPUs or GPUs. Finally, we wrote the wrapper script <span>atomiongpu.m</span> for quickly and conveniently using <span>ode45gpu</span>.</div><div><em>Additional comments:</em> The source code for <span>atomiongpu.m</span>, <span>ode45gpu</span>, and figures can be found on the repository.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"321 ","pages":"Article 110041"},"PeriodicalIF":3.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034924","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":"Linked cell traversal algorithms for three-Body interactions in molecular dynamics","authors":"José Alfonso Pinzón Escobar ,&nbsp;Markus Mühlhäußer ,&nbsp;Hans-Joachim Bungartz ,&nbsp;Philipp Neumann","doi":"10.1016/j.cpc.2026.110028","DOIUrl":"10.1016/j.cpc.2026.110028","url":null,"abstract":"<div><div>In this work, algorithms for the parallel computation of three-body interactions in molecular dynamics are developed. While traversals for the computation of pair interactions are readily available in the literature, here, such traversals are extended to allow for the computation between molecules stored across three cells. A general framework for the computation of three-body interactions in linked cells is described, and then used to implement the corresponding traversals. In addition, our analysis is combined with the commonly used cutoff conditions, because they influence the total workload of the computation of interactions. The combinations between traversals and truncation conditions are validated using the well-known Lennard-Jones fluid. Validation case studies are taken from the literature and configured into homogeneous and inhomogeneous scenarios. Finally, strong scalability and performance in terms of molecule updates are measured at node-level.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"321 ","pages":"Article 110028"},"PeriodicalIF":3.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145974177","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":"Object-oriented programming as a tool for constructing high-order quantum-kinetic BBGKY equations","authors":"Ekaterina A. Tarasevich ,&nbsp;Maxim G. Gladush","doi":"10.1016/j.cpc.2026.110020","DOIUrl":"10.1016/j.cpc.2026.110020","url":null,"abstract":"<div><div>Theoretical methods based on the density matrix provide powerful tools for describing open quantum systems. However, such methods are complicated and intricate to be used analytically. Here we present an object-oriented framework for constructing the equation of motion of the correlation matrix at a given order within the quantum BBGKY hierarchy, which is widely used to describe the interaction of many-particle systems. The algorithm of machine derivation of equations includes the implementation of the principles of quantum mechanics and operator algebra. It is based on the description and use of classes in the Python programming environment. Class objects correspond to the elements of the equations that are derived: density matrix, correlation matrix, energy operators, commutator and several operators indexing systems. The program contains a special class that allows one to define a statistical ensemble with an infinite number of subsystems. For all classes, methods implementing the actions of the operator algebra are specified. The number of subsystems of the statistical ensemble for the physical problem and the types of subsystems between which pairwise interactions are possible are specified as an input parameters. It is shown that this framework allows one to derive the equations of motion of the fourth-order correlation matrix in less than one minute.</div><div><strong>Program summary</strong></div><div><em>Program title</em>: Program for symbolic generation of kinetic equations in quantum Bogolyubov hierarchies (BBGKY).</div><div><em>CPC Library link to program files</em>: <span><span>https://doi.org/10.17632/f97bwbypfd.1</span><svg><path></path></svg></span></div><div><em>Licensing provisions</em>: GNU General Public License 3</div><div><em>Programming language</em>: Python 3.10</div><div><em>Nature of problem</em>: Construction of Bogolyubov hierarchies for reduced many-particle density matrices and correlation matrices is a powerful tool for solving problems in Physics. However, the analytical derivation of equations requires considerable time and effort to avoid multiple errors. Bogolyubov hierarchies for problems in quantum optics is a novel approach and requires special attention.</div><div><em>Solution method</em>: In order to solve this problem, we used object-oriented programming. Each element of quantum-mechanical object (operator, density matrix, correlation matrix, etc.) is assigned to a class with specified attributes and methods. The attributes and methods of each class represent operations of quantum-mechanical algebra. This allows one to perform all the necessary operations on a computer and significantly reduce the time to obtain error-free output.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"321 ","pages":"Article 110020"},"PeriodicalIF":3.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146073663","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":"Accurate calculation of the gradients of the equilibrium poloidal flux in tokamaks","authors":"M. Woo,&nbsp;G. Jo,&nbsp;B.H. Park,&nbsp;A.Y. Aydemir,&nbsp;J.-H Kim","doi":"10.1016/j.cpc.2026.110022","DOIUrl":"10.1016/j.cpc.2026.110022","url":null,"abstract":"<div><div>This paper presents a novel method for calculating the first, second, and third derivatives of the equilibrium poloidal flux in different directions in tokamaks. The method is implemented in a new code called Equilibrium Derivative in Arbitrary Mesh (EDAM) which is designed for practical fusion applications. The spectral method is adopted along the boundary with evenly spaced angles, while unstructured triangular meshes are used inside the computational domain. A new boundary integral equation (BIE) is derived and solved numerically to obtain the first and higher-order derivatives at the boundary. Using GS equation, linear partial differential equations for the first and higher-order flux derivatives are then constructed and solved. Validation is performed using an analytical equilibrium constructed by Cicogna, which describes D-shaped plasmas with steep profiles near the boundary. The code demonstrates similar convergence rates for the first and higher-order derivatives, achieving second order accuracy. This new method has significant potential for practical fusion simulations, providing derivatives up to the third order with the required accuracy and precisely given values at any nodal points of the unstructured mesh.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"321 ","pages":"Article 110022"},"PeriodicalIF":3.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145974174","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":"DynHeMat: A program for zero-point averaged dynamics of pure and doped helium nanodroplets","authors":"David A. Bonhommeau","doi":"10.1016/j.cpc.2025.110014","DOIUrl":"10.1016/j.cpc.2025.110014","url":null,"abstract":"&lt;div&gt;&lt;div&gt;DynHeMat is a parallel program aimed at modeling the dynamics of pure and doped helium nanodroplets (HNDs) by means of zero-point averaged dynamics (ZPAD), a method where the quantum nature of helium atoms is taken into account through the use of a He-He pseudopotential which includes zero-point effects of helium clusters on an average manner. Three He-He pseudopotentials, defined for applications in different contexts, are implemented. Large HNDs can be formed by successive coalescences of smaller HNDs keeping in mind that, depending on the HND size and He-He pseudopotential in use, the liquid character of the HND is more or less pronounced. Files containing the positions and velocities of HNDs formed with the three aforementioned He-He pseudopotentials are collected in a local databank, called ZPAD_DB. ZPAD simulations can be carried out at constant energy or temperature, then enabling the user to investigate collision, coagulation or submersion processes in pure or doped HNDs. Impurities can be rare-gas atoms (Ne, Ar, Kr, Xe and Rn), alkali atoms (Li, Na, K, Rb, Cs), or homogeneous clusters composed of such atoms. The program provides information on trajectories, namely positions, velocities, energies, radial distribution functions, and the initial distribution of HND surface atoms. Extension to other impurities or He-He pseudopotentials is made possible by the current structure of the program and keyword system.&lt;/div&gt;&lt;div&gt;PROGRAM SUMMARY&lt;/div&gt;&lt;div&gt;&lt;em&gt;Program title&lt;/em&gt;: DynHeMat&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/10.17632/3hrfykstvr.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 3 (GPL)&lt;/div&gt;&lt;div&gt;&lt;em&gt;Programming language&lt;/em&gt;: Fortran 90&lt;/div&gt;&lt;div&gt;&lt;em&gt;Nature of problem&lt;/em&gt;:&lt;/div&gt;&lt;div&gt;Helium nanodroplets (HNDs) are large quantum systems containing from a few thousands to billion atoms. The more quantum approaches, like quantum Monte Carlo, time-dependent density functional theory and path integral molecular dynamics, are often limited to the treatment of a few hundreds or thousands atoms or to small statistics in terms of projectile velocities or impact parameters, for instance. On the contrary, a classical approach would enable simulations on larger systems provided that the quantum nature of helium atoms is included on an average manner in the calculation in order to ensure that the expected heliophilic or heliophobic nature of impurities can be maintained.&lt;/div&gt;&lt;div&gt;&lt;em&gt;Solution method&lt;/em&gt;:&lt;/div&gt;&lt;div&gt;The zero-point averaged dynamics (ZPAD) includes zero-point effects on an average manner in classical simulations through the use of an effective He-He potential, and possibly effective He-impurity potentials, which makes the HND liquid and drastically improves the agreement with quantum calculations compared to standard classical simulations. Initially used to tackle the fragmentation of rare-gas clusters embedded in HNDs io","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"321 ","pages":"Article 110014"},"PeriodicalIF":3.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034923","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}