Computer Physics Communications

Here we report the update of the pICNIK package. The update consists in the following implementations: i) smoothing filters for the numerical differentiation steps involved in the isoconversional analysis, ii) separation of the temperature range of analysis for each experimental run, iii) compensation effect to compute pre-exponential factor conversion dependent, iv) numerical reconstruction of the integral expression of the reaction model and v) model-based and model-free predictions. We also present two Graphical User Interfaces, one web and one for desktop. May this tools widen the use of the library.

This paper presents a numerical method for calculating anisotropic radiative intensities on a spherical capsule within a cylindrical hohlraum. The combination of capsule and hohlraum is the typical configuration in the indirectly driven inertial confinement fusion (ICF). The hohlraum is irradiated by lasers and thus generates an anisotropic radiative field around the capsule. The radiative energy flux along the hohlraum inner surface is firstly computed by utilizing the conventional view factor formulation. Anisotropic radiative intensities on the capsule are then obtained from the Lambertian approximation. A numerical example calibrated by experimental radiation temperature is further provided to demonstrate the anisotropy of radiative intensities in ICF.

We introduce AFiD-2phaseDarcy, an efficient, open-source and massively parallelized finite-difference solver tailored for large-scale simulations of buoyancy-driven incompressible multiphase convection in porous media. Built within the well-established AFiD framework, the solver extends the original wall-bounded buoyancy-driven convection code to handle fully coupled multiphase Darcy momentum transport, saturation and scalar transport equations. Spatial operators are discretized using finite-difference schemes, while temporal integration is performed using a low-storage third-order Runge–Kutta scheme combined with a Crank–Nicolson formulation for implicit terms. To alleviate the computational bottleneck associated with pressure–velocity coupling, a fractional-step projection method is employed. The resulting global variable-coefficient Poisson equation is decomposed using a pressure-splitting approach and solved using a Fast Fourier Transform (FFT)-based algorithm, substantially reducing parallel communication overhead. The numerical accuracy of AFiD-2phaseDarcy is rigorously verified against a series of benchmark cases, including canonical single-phase porous-media convection, isothermal two-phase flow and multiphase thermal convection. Performance benchmarks demonstrate that the proposed FFT-based pressure-splitting solver achieves an approximately fivefold computational speedup over the conventional monolithic direct solver implemented using the parallel PETSc framework, while maintaining comparable computational accuracy. Furthermore, distributed strong-scaling tests on the SCNet platform demonstrate near-linear speedup and high parallel efficiency on up to 2000 CPU cores. This open-source framework provides an efficient numerical tool for large-scale simulations of subsurface transport processes, with potential applications including geological carbon sequestration and geothermal energy exploitation.

We present a modular user-oriented simulation toolbox for studying high-harmonic generation in gases [1]. The first release consists of the computational pipeline to 1) compute the unidirectional IR-pulse propagation in cylindrical symmetry, 2) solve the microscopic responses in the whole macroscopic volume using a 1D-TDSE solver, 3) obtain the far-field harmonic field using a diffraction-integral approach. The code comes with interfaces and tutorials, based on practical laboratory conditions, to facilitate the usage and deployment of the code both locally and in HPC-clusters. The interfaces also provide extendability of the code. Additionally, the modules are designed to work as stand-alone applications as well, e.g., 1D-TDSE is available through a Pythonic interface.

Recent years have seen a reawakened interest in simplified solution schemes for nanophotonic scatterers, as they allow for significantly faster and more efficient simulations of nanoparticle clusters and arrays when compared to full Maxwell solvers. Examples are the transition or T-matrices, which expand the incoming and scattered electromagnetic fields in terms of spherical multipoles, or numerical dipoles, which describe the scatterers’ response through a collection of electric and magnetic dipoles coupled together through a generalized polarizability matrix, or P-matrix in short. In order to obtain the T- and P-matrices, one has to employ a computational Maxwell solver. Here we suggest a hybrid Maxwell solver scheme that combines computational Maxwell solvers with T- and P-matrices under a common roof. For each scatterer the simulation scheme can be chosen in an interchangeable manner, and the different solvers interact with each other through solver-independent electromagnetic fields. Our approach is expected to be beneficial for fast simulations and prototyping, where in the testing stage a fast solver is used and in the production stage one can switch to any other Maxwell solver by simply changing a few lines of code. We have implemented a hybrid Maxwell solver into our nanobem toolbox, which is based on a Galerkin implementation of the boundary element method.

We introduce cuSkyrmion, a 3-dimensional Skyrme model computation and visualization software, that is written in CUDA C for rapid computation and visualization of especially the arrested Newton flow algorithm. The programme is interactive and lets the user construct Skyrmions either with configuration files, specifying coordinates, or simply at run-time using the keyboard and mouse. Rational map ansatz constituent Skyrmions can be inserted at any time and a random generator can produce a stochastic initial configuration. The software is composed into three main modules being a computational module, a rendering module and a main programme. The rendering/visualization module can readily be used by other computational modules and a Python-fork, skyrmion_solver, has been developed demonstrating the re-usability of the code.

Gaussian Type Functions (GTFs) are widely used as basis sets in electronic-structure calculations. Under many conditions, it is advantageous to express them in their Real Solid Harmonic (RSH) version, which reduce basis-set redundancy and facilitate the interpretation of results. A variation of the McMurchie–Davidson method directly utilizes RSH GTFs; however, evaluating the corresponding Hermite expansion coefficients involves intricate recurrence relations that complicate their implementation and maintenance in electronic-structure codes. To manage this, closed-source programs have used symbolic algebra tools, while public solutions are not available. We present AxolotE, an open-source framework for the automated generation of these coefficients and the corresponding C++ source code. We propose a general algorithm that focuses on the requirements imposed on indices at each recursion step rather than a fixed sequential ordering, simplifying its implementation and analysis. This tool, developed using Mathematica and Python modern symbolic algebra engines, enables reproducible derivation, validation, and code generation for arbitrary angular momentum, being tested up to ℓ=h. Benchmarks expose that the choice of symbolic algebra engine influences the compactness of the generated code and its computational performance, while preserving numerical accuracy. The resulting software will facilitate systematic comparison of Real Solid Harmonic integral implementations, providing ready-to-integrate routines for electronic-structure applications.

Melting temperature calculation is one of the important topics in computational materials science. In high-throughput in silico screening and artificial intelligence assisted design of materials, it usually requires a rapid and autonomous assessment of the melting temperature of the target. Unfortunately, molecular dynamics (MD) simulations of the melting point require many cumbersome and manual operations, making large-scale calculation of the melting point challenging. In this work, we introduce MyTm, a toolkit that employs MD to automatically determine the melting point. The method is fully modularized, and by combining these modules, the program enables fully automated melting calculations by using commonly adopted approaches, including the direct-heating method, the void method, the modified void method, the solid–liquid coexistence method, and the Z method. Moreover, a machine learning (ML) method is proposed employed to recognize and classify the solid-like and liquid-like atoms, which effectively resolve the low accuracy issue in conventional classification approaches, thus making the automated high-throughput pipeline of melting-point calculation possible. The robustness and efficacy of MyTm have been demonstrated by several well-studied systems.

We present Mumax3-cQED, a code for modeling magnon–polaritons in realistic experimental settings. It is an extension of the widely used micromagnetic simulation package Mumax3, building on its GPU-accelerated implementation. To our knowledge, Mumax3-cQED is the first numerical framework that enables the self-consistent simulation of hybrid cavity–ferromagnet dynamics at the micromagnetic level within a single model, without treating the cavity and magnetic subsystems separately. We validate the implementation by benchmarking against numerical and analytical results from the Dicke model in both the paramagnetic and superradiant phases. Mumax3-cQED accurately captures non-equilibrium dynamics and relaxation toward equilibrium. The code also enables the straightforward calculation of hybrid magnon–photon polaritons, as demonstrated by quantitative agreement with experimental observations. Finally, we highlight the potential of Mumax3-cQED for designing magnon–cavity experiments, particularly in scenarios involving strongly inhomogeneous cavity fields or complex magnetization configurations. The software is open-source and provides a versatile tool for studying microscopic saturated ferromagnets as well as spin textures, including domain walls, vortices, and skyrmions.

The electrostatic potential of a point charge inside a grounded conducting sphere is a canonical boundary-value problem with an exact image-charge Green-function solution and an equivalent separated representation in Legendre polynomials. This article presents a reproducible computational framework that evaluates both representations, generates machine-readable data, regenerates publication-quality figures, and validates primary and post-processed electrostatic quantities. In response to the need for validation beyond exact-solution benchmarking, the revised framework also contains an independent cell-centred finite-volume solution of the singularity-subtracted reaction potential. It evaluates field and boundary errors, induced surface charge, image energy, physical radial force, multipole decay, computational cost, spatial error distributions, algebraic and boundary residuals, charge conservation, and inter-grid differences. The Legendre calculations improve monotonically with multipole order over the tested cases, while the independent finite-volume results display approximately second-order refinement and agree with the analytical and Legendre reaction fields. Residual and inter-grid indicators provide practical diagnostics when an exact solution is unavailable. The package is designed for computational electrostatics, spectral approximation, and verification of numerical Poisson and Laplace solvers.