Computer Physics Communications

Nonequilibrium Green’s functions provide a powerful framework for studying quantum many-body dynamics including the laser-induced dynamics in solids. The Non-Equilibrium Systems Simulation package (NESSi) offers an efficient platform for such simulations, ranging from perturbative approaches like nonequilibrium GW to nonequilibrium dynamical mean-field theory. However, simulations based on nonequilibrium Green’s functions become computationally demanding when the dynamics span a large temporal range, such as from sub-femtosecond electron dynamics to the picosecond dynamics of collective modes. Due to the memory integral in the Kadanoff-Baym equations, which serve as equations of motion for nonequilibrium Green’s functions, the computational cost scales as O(N_t^3) with the number of timesteps N_t, and the memory requirement scales as O(N_t^2). In this work, we extend NESSi by incorporating techniques that aim to overcome this bottleneck: (i) By truncating the memory integrals in the KBE to a maximum of N_c timesteps, the computational complexity is reduced to O(N_t N_c^2), and the memory requirement to O(N_c^2). Provided that the results converge with respect to the cutoff Nc, memory truncation allows to extend the simulations to significantly longer times. (ii) We introduce functionalities to describe nonequilibrium steady states, i.e. time-translationally invariant nonequilibrium states. Such states are relevant for transport settings, and they provide an approximate description of slowly evolving (prethermal) nonequilibrium states.

Linear systems with finite-group symmetry, from geometric invariances to repetitive structural patterns, are ubiquitous in science and engineering, and standard computational software rarely exploits that structure. This paper introduces PySymmetry, an open-source Sage/Python framework that applies the constructive algorithms of classical representation theory to the symmetry reduction of G-equivariant linear systems. Projection operators built from the characters of the irreducible representations of a finite group generate a symmetry-adapted basis, which carries an equivariant operator into block-diagonal form and decouples one large problem into several small independent ones. A single character-theoretic construction serves two paths inside one open environment: an exact symbolic path over an exact ring, and a numerical path interoperable with NumPy, SciPy, and sparse matrix formats. Three case studies exercise both. The GF method of molecular vibrations illustrates the workflow. A non-Hermitian Schrödinger eigenvalue benchmark shows the reduced path to be nearly 17 times faster than a general-purpose dense eigensolver on the largest grid tested. A symbolic investigation produced the first complete analytical classification of the nested cube central configuration in celestial mechanics. Source code, documentation, and the notebooks that reproduce the results are publicly available.

This paper introduces a software suite whose purpose is simulating the linear momentum transfer to charged particles caused by interactions with an arbitrary superposition of Gaussian beams or plane wave beams. The program can automatically compare the results of the momentum transfer between the relativistic Lorentz force model and the relativistic ponderomotive approximation method, then create 2D momentum transfer maps for parameter sweeps such as increasing the laser intensity, together with 2D error maps, for quantitatively finding the validity domain of the ponderomotive method. The implementation is a hybrid C and OpenMP for the simulation segments, and Python scripts for easily configuring the simulation scenarios and creating parameter sweeps. The core particle pusher algorithm for the electromagnetic mode is the Higuera-Cary push, alongside a fourth-order Runge-Kutta integrator for the ponderomotive method.

CN-Waves’ objective is to simplify and automate the generation and modeling of realistic water wave fields in numerical wave tanks and open domains. Wave modeling uses the High-Order Spectral codes HOS-Ocean and HOS-NWT, which are based on fully nonlinear potential flow theory. CN-Waves packages the HOS command-line executable files, and provides a Python package to execute HOS simulations. The Python methods have default numerical parameters that allow a user with only a basic knowledge of wave theory to model and generate water waves, while allowing a more advanced user to control the different parameters. Various visualization features have been implemented. The package is designed to facilitate the launch and analysis of a substantial number of simulations. Furthermore, the Python package implements several wave generation methodologies for the wave tank configuration. These include well-established approaches such as second-order wave generation or accounting for the side-walls reflection during the generation of oblique waves. Other recently developed methods, including the time reversal method, an iterative approach to calibrate a sea state, and the generation of response-conditioned waves, are also made available in CN-Waves.

We present a finite element (FE) software library, IRENE, which allows for numerically solving the dynamics of a viscous fluid layer embedded in three-dimensional space. IRENE describes two-dimensional, dynamical open surfaces, and it is restricted to manifolds described with the Monge gauge. IRENE supports a wide range of boundary conditions and shapes of inter-surface obstacles, and is built upon the user-friendly and versatile finite element computational software (FEniCS). Also, the library can describe a wide range of physical regimes—both low-Reynolds-number and inertia-dominated ones—capturing the complex coupling between in-plane flows, out-of-plane deformations, surface tension, and elastic response. We validate IRENE against known analytical and numerical results, and demonstrate its capabilities through physical examples. Overall, IRENE provides a versatile and efficient tool for understanding fluid-layer dynamics on multiple physical scales, from flows of lipidic membranes on a microscopic level, to fluid flows on a macroscopic scale, to atmospheric air flows on a planetary level.

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.