Computer Physics Communications

The concept of representative volume (REV, or RVE in material sciences) is the cornerstone of continuum scale models – one needs to get the volume big enough so that it could be represented with an averaged value (scalar, vector or tensorial, etc.). While REV should be established in all larger scale simulations, this is rarely done in practice despite widespread adoption of 3D imaging devices in all research areas starting from petroleum engineering, material sciences and spanning to biology. Sometimes REV analysis is performed in the form of very simple procedures, such as a check for convergence of porosity or surface area, which is technically identical to omitting it entirely. The main reason for this to happen is the poor understanding of REV concept in general (mainly its connection to spatial stationarity and necessity for vector metrics with high information content) and unavailability of open-source robust solutions. In this work we present PARSE library that solves exactly this problem – we developed an easy to use and well-documented code based on rigorous research carried out recently in explaining the “dark sides” of representativity. In addition to REV, our code allows spatial stationarity analysis and comparison of samples (with subsequent clusterization into different groups) based on vector metrics – correlation functions, persistence diagrams and pore-network statistics, that altogether possess high information content which is critical in establishing stationarity and REV. We test our library on images produced by known statistical processes, such as Poisson spheres. After verification, we show how to compare different samples and group them depending on their “structural DNA”. All solutions explained in the paper are represented by Jupiter notebooks that can be used to perform similar analysis, moreover, the class structure of PARSE library allows painless modifications to be implemented. We believe that such an open-source library will be useful in numerous fields and will become an invaluable tool for 3D image analysis.

Integrated computational materials engineering (ICME) has become a cornerstone for modern intelligent approaches, accelerating the discovery and design of new materials by providing extensive datasets. To support this, we have developed a straightforward and efficient command-line program named AAVDP (Atomistic Analyzer of Virtual Diffraction Patterns) for high-throughput (HT) virtual diffraction, structural analysis, and in situ visualization of various atomic configurations. AAVDP has integrated a comprehensive suite of virtual diffraction methods, spanning from X-ray diffraction (XRD), neutron diffraction (NED), kinematic electron diffraction (KED), and dynamical electron diffraction (DED), to both kinematic and dynamical Kikuchi diffractions (KKD and DKD), making it a versatile tool for researching crystalline and defective structures at atomic scale. Furthermore, AAVDP provides statistical tools, including the radial distribution function (RDF) and the static structure factor (SSF), which are crucial for understanding amorphous and liquid systems. As a command-line program, AAVDP allows for the customization of complex workflows and the extraction of high-volume statistical results with minimal scripting efforts. The program’s functionality and efficiency have been rigorously validated through a series of critical evaluations and tests, which empower users to delve deeper into the intricate diffraction behaviors and diverse material structures.

The version 2.0 of the Boundary Element Software for 3D Linear Elasticity (BESLE) is presented. BESLE is an open-source Fortran 90 code for the simulation of isotropic and anisotropic solids under quasi-static, dynamic, and high-rate boundary conditions using elastostatic and elastodynamic boundary element formulations. Compared to the initial release, this new version introduces a substantially simplified installation procedure. BESLE v1.0 required users to manually download, configure, and integrate external libraries such as MUMPS, SCOTCH, and ScaLAPACK, which often represented a barrier for new users. In contrast, version 2.0 provides an online installer, which automatically downloads, prepares, and installs the required libraries from public repositories. This new approach makes the deployment of BESLE straightforward, reducing installation time and minimising potential user errors. No changes have been made to the core numerical methods, input structure, or supported physics. BESLE v2.0 therefore retains full compatibility with existing simulations and examples, while significantly improving ease of installation, accessibility, and reproducibility.

We introduce a new open-source Python x-ray tracing code for modelling Bragg diffracting mosaic crystal spectrometers: High Energy Applications Ray Tracer (HEART). HEART'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 HEART in parallel leading to excellent performance. HEART 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.

Ants3 is a toolkit that serves as a front-end for particle simulations in Geant4 and offers a custom simulator for optical photons. It features a fully interactive Graphical User Interface and an extensive scripting system based on general-purpose scripting languages (Python and JavaScript). Ants3 covers the entire detector simulation/optimization cycle, providing an intuitive approach for configuration of the geometry and simulation conditions, the possibility to automatically distribute workload over local and network resources, and giving a suite of versatile tools based on CERN ROOT for the analysis of the results. The intended application area is the development of new detectors and readout methods. The toolkit has been designed to be user-friendly for those with little experience in simulations and programming.

In this work we present a covariant implementation of force for Chaos Many-Body Engine (CMBE - Grossu et al., 2021) .Net application. Thus, supposing the expression of bi-particle force is known in the center-of-mass frame, we applied specific relativistic transformations for obtaining the corresponding value in laboratory frame. As an example of use, we discuss a toy-model for relativistic nuclear collisions at Facility for Antiproton and Ion Research (FAIR) energies.

DiracBilinears.jl is a Julia package for computing Dirac bilinears, which are fundamental physical quantities of electrons in relativistic quantum theory, using first-principles calculations for solids. In relativistic quantum theory, 16 independent bilinears can be defined using the four-component Dirac field. To focus on the low-energy physics typically considered in condensed matter physics, we consider the bilinears represented by the non-relativistic two-component Schrödinger field, obtained from the 1/m expansion to leading order. This package can evaluate the spatial distributions and Wannier matrix elements of the Dirac bilinears in solids quantitatively by connecting to the external first-principles calculation packages, including Quantum ESPRESSO, Wannier90, and wan2respack.

We present a general-purpose, open-source software suite, SQUIRREL (Streamlined Quantum Unified Interface for Researching Real-time Excitations with Light), for propagating the time-dependent Schrödinger equation on complex geometries in the presence of time-dependent electric and/or magnetic fields. To handle large systems that can be executed on a conventional desktop computer, the SQUIRREL software suite uses a suite of efficient propagation methods for various quantum dynamics applications, including a new perturbation-based element-dropping algorithm that improves computational performance with minimal loss of accuracy. We analyze the efficacy of these optimizations for Crank-Nicolson, scaled Taylor series approximation, and split-operator propagation methods and discuss the range of their applicability to a variety of quantum dynamics problems. In addition, we provide several examples of time-dependent dynamics calculations and extensive documentation for generating custom geometries, potentials, and time-propagation approaches. Our numerical benchmarks and results demonstrate the versatility of the SQUIRREL software suite for efficiently calculating quantum dynamics in complex nanoscale geometries, particularly in the presence of time-dependent magnetic fields, which have received less attention in previous quantum dynamics studies.

Accurate quantification of local packing density and mixing in simulations of particulate systems is essential for many industrial applications. Traditional methods which simply count the number of particle centres within a given volume of space (cell) introduce discontinuities at cell boundaries, leading to unreliable measurements of packing density. We introduce Packing3D.jl, an open-source Julia package providing analytic partial-volume calculations for spheres intersecting Cartesian and cylindrical meshes. We derive closed-form solutions for single, double and triple spherical-cap intersections, plus sphere-cylinder overlaps. We implement efficient mesh-generation routines, principal-cell indexing, and data-splitting functions for time-series analyses. Performance and accuracy were validated against simple cubic and face-centred cubic lattices and via boundary-shift continuity tests. Packing3D.jl converges exactly to theoretical lattice densities, eliminates discontinuities at sub-particle resolution, and scales linearly with particle count. Memory usage remains modest (40 B per particle, 48 B per cell). Packing3D.jl provides researchers with continuous, reproducible volume-fraction fields and robust mixing indices at high performance, facilitating sensitivity analyses and optimisation in granular process engineering.

Various methods are commonly applied for data acquisition in the melting process of substances under high pressure. However, throughout the application of these methods, challenges persist, including significant time and computational requirements, as well as issues related to hysteresis effects. We introduce the GTS package, a Python toolkit based on the work of J. W. Gibbs to obtain melting data at high pressures in a geometrical manner. We outline the theory behind constructing the Gibbs thermodynamic surface, which includes regions representing the solid and liquid phases. Several examples are presented to demonstrate program execution and validate accuracy by comparing results with prior studies. GTS is openly accessible on GitHub: https://github.com/computation-mineral-physics-group/GTS.