Computer Physics Communications

We present the Plan for Robust and Accurate Potentials (PRAPs), a software package for training and using moment tensor potentials (MTPs) in concert with the Machine Learned Interatomic Potentials (MLIP) software package. PRAPs provides an automated workflow to train MTPs using active learning procedures, and a variety of utilities to ease and improve workflows when utilizing the MLIP software. PRAPs was originally developed in the context of crystal structure prediction, in which one calculates convex hulls and predicts low energy metastable and thermodynamically stable structures, but the potentials PRAPs develops are not limited to such applications. PRAPs produces two potentials, one capable of rough estimates of the energies, forces and stresses of almost any chemical structure in the specified compositional space – the Robust Potential – and a second potential intended to provide more accurate descriptions of ground state and metastable structures – the Accurate Potential. We also present a Python library, mliputils, designed to assist users in working with the chemical structural files used by the MLIP package.

Fantômas is a C++ toolkit for exploring the parametrization dependence of parton distribution functions (PDFs) and other correlator functions in quantum chromodynamics (QCD). Fantômas facilitates the generation of adaptable polynomial parametrizations for PDFs, called metamorphs, to find best-fit PDF solutions and quantify the epistemic uncertainty associated with the parametrizations during their fitting. The method employs Bézier curves as universal approximators for a variety of PDF shapes. Integrated into the xFitter framework for the global QCD analysis, Fantômas provides a foundation for general models of PDFs, while reducing the computational time compared to the approaches utilizing traditional polynomial parametrizations as well as providing an interpretable alternative to neural-network-based models. This paper outlines the structure and practical usage of the Fantômas toolkit, including its inputs, outputs, and implementation within xFitter. It also provides a practical example of using Fantômas for uncertainty quantification as well as the combination of PDF fits into a single ensemble.

We present an extended version of MHIT36 [1], a GPU-tailored solver for interface-resolved simulations of multiphase turbulence. The framework couples direct numerical simulation (DNS) of the Navier–Stokes equations, which describe the flow field, with a phase-field method to capture interfacial phenomena. In addition, the transport equation for a scalar can also be solved. The governing equations are discretized using a second-order finite difference scheme. The Navier–Stokes equations are time advanced with an explicit fractional-step method, and the resulting pressure Poisson equation is solved using a FFT-based method. The accurate conservative diffuse interface (ACDI) formulation is used to describe the transport of the phase-field variable. Simulations can be performed in two configurations: a triply-periodic cubic domain or a rectangular domain of arbitrary dimensions bounded by two walls. From a computational standpoint, MHIT36 employs a two-dimensional domain decomposition to distribute the workload across MPI tasks. The cuDecomp library [2] is used to perform pencil transpositions and halo updates, while the cuFFT library and OpenACC directives are leveraged to offload the remaining computational kernels to the GPU. MHIT36 is developed using the managed memory feature and it provides a baseline code that is easy to further extend and modify. MHIT36 is released open source under the MIT license.

OpenSn is an open-source, massively parallel deterministic radiation transport code for solving the discrete-ordinates (SN) form of the Boltzmann transport equation on unstructured, arbitrary polyhedral meshes. It supports high-fidelity simulations involving steady-state, eigenvalue, and adjoint problems for neutral particles (e.g., neutrons, photons, multi-particles), using the multigroup approximation in energy. OpenSn combines angular discretization via discrete ordinates with a discontinuous Galerkin finite element method (DGFEM) in space, enabling accurate resolution of transport physics on arbitrary polyhedral cells, included locally refined spatial grids. It includes multiple angular quadrature types, including locally refined angular quadratures. Written in modern C++ with a Python API, OpenSn runs efficiently on platforms ranging from laptops to supercomputers. The transport sweep algorithm is implemented using a task-based, directed-acyclic-graph (DAG) approach for each angle and supports asynchronous parallelism across thousands of MPI ranks. Group-set aggregation improves compute intensity, and synthetic acceleration techniques (e.g., diffusion synthetic acceleration, second-moment method) enhance solver convergence. OpenSn has been verified on reactor physics problems and demonstrated excellent weak and strong scaling performance on more than 32,768 processes, making it a versatile and robust platform for large-scale transport simulations in complex geometries.

HepLib is a C++ Library for computations in High Energy Physics, it builds on top of other well-established libraries or programs, including GiNaC, Fermat, Form, Fire, etc., its first version has been released in Comput. Phys. Commun. 265 (2021) 107982. Here we provide a minor upgraded version with parts of obligated aspects removed and many new features added, the main feature in this new version is to use Flint for the simplification on multi-variate polynomial, so one can replace the process-based parallelism by the thread-based parallelism for the related polynomial evaluations to achieve a higher performance.

The Discrete Element Method (DEM) is widely used to simulate the mechanical behavior of granular materials across a broad range of applications and industrial domains. Particle shape is a key feature playing a crucial role for physics-fidelity of DEM simulations. However, accurately representing complex particle shapes within DEM frameworks presents significant challenges such as defining unambiguous contact normals or managing geometric singularities. Rigid particles are often modeled as convex polyhedra, which inherently suffer from ill-defined outward normal vectors at sharp edges and vertices. To represent non-convex geometries, these polyhedra must typically be combined, further increasing the computational and geometric complexity. In this work, we adopt an efficient and robust strategy to overcome these limitations by using R-shapes, defined as rounded-edge shapes, also known as sphero-polyhedra, obtained by sweeping a sphere of radius R along the edges and faces of a base polyhedral shape. This construction results in smooth surface transitions and circumvents common issues associated with traditional polygonal representations. This paper provides a detailed presentation of the implementation, structure, and advantages of R-shapes in DEM simulations. The proposed solutions are implemented in a fully open-source software package called Rockable, developed in C++, which integrates state-of-the-art numerical techniques and shared-memory parallelization for enhanced performance. Beyond the geometric modeling aspects, we also address several methodological challenges, including the treatment of contact elasticity and the numerical integration scheme. The combined contributions of this work offer a practical and efficient framework for simulating complex particle shapes in DEM with high physics fidelity and computational efficiency.

The Combustion Toolbox (CT) is a newly developed open-source thermochemical code designed to solve problems involving chemical equilibrium for both gas- and condensed-phase species. The kernel of the code is based on the theoretical framework set forth by NASA’s computer program CEA (Chemical Equilibrium with Applications) while incorporating new algorithms that significantly improve both convergence rate and robustness. The thermochemical properties are computed under the ideal gas approximation using an up-to-date version of NASA’s 9-coefficient polynomial fits. These fits use the Third Millennium database, which includes the available values from Active Thermochemical Tables. Combustion Toolbox is programmed in MATLAB with an object-oriented architecture composed of three main modules: CT-EQUIL, CT-SD, and CT-ROCKET. The kernel module, CT-EQUIL, minimizes the Gibbs/Helmholtz free energy of the system using the technique of Lagrange multipliers combined with a multidimensional Newton-Raphson method, upon the condition that two state functions are used to define the mixture properties (e.g., enthalpy and pressure). CT-SD solves processes involving strong changes in dynamic pressure, such as steady shock and detonation waves under normal and oblique incidence angles. Finally, CT-ROCKET estimates rocket engine performance under highly idealized conditions. The new tool is equipped with a versatile Graphical User Interface and has been successfully used for teaching and research activities over the last six years. Results are in excellent agreement with CEA, Cantera within Caltech’s Shock and Detonation Toolbox (SD-Toolbox), and the Thermochemical Equilibrium Abundances (TEA) code. CT is available under an open-source GPLv3 license via GitHub https://github.com/CombustionToolbox/combustion_toolbox, and its documentation can be found in https://combustion-toolbox-website.readthedocs.io.

Multiscale modeling, which integrates material properties from ab initio calculations into continuum-scale simulations, is a promising strategy for optimizing semiconductor devices. However, a key challenge remains: while ab initio methods provide diffusion parameters specific to individual migration paths, continuum equations require a single effective set of parameters that captures the overall diffusion behavior. To address this issue, we present VacHopPy, an open-source Python package for vacancy hopping analysis based on molecular dynamics (MD). VacHopPy extracts an effective set of hopping parameters, including hopping distance, hopping barrier, number of effective paths, correlation factor, and attempt frequency, by statistically integrating energetic, kinetic, and geometric contributions across all paths. It also includes tools for tracking vacancy trajectories and for detecting phase transitions during MD simulations. The applicability of VacHopPy is demonstrated in three representative materials: face-centered cubic Al, rutile TiO2, and monoclinic HfO2. The extracted effective parameters reproduce temperature-dependent diffusion behavior and are in good agreement with previous experimental data. Provided in a simplified form, these parameters are well suited for continuum-scale models and remain valid over a wide temperature range spanning several hundred kelvins. Furthermore, VacHopPy inherently accounts for anisotropy in thermal vibrations, a factor often overlooked, making it suitable for simulating diffusion in complex crystals. Overall, VacHopPy establishes a robust bridge between atomic- and continuum-scale models, enabling more reliable multiscale simulations.

We present an open-source program QR2-code that computes double-resonance Raman (DRR) spectra using first-principles calculations. QR2-code can calculate not only two-phonon DRR spectra but also single-resonance Raman spectra and defect-induced DRR spectra. For defect-induced DRR spectra, we simply assume that the electron-defect matrix element of elastic scattering is a constant. Hands-on tutorials for graphene are given to show how to run QR2-code for single-resonance, double-resonance, and defect-induced Raman spectra. We also compare the single-resonance Raman spectra by QR2-code with that by QERaman code. In QR2-code, the Raman spectrum is calculated by the time-dependent perturbation theory, in which the energy dispersions of electron and phonon are taken from Quantum ESPRESSO (QE) code and the electron-phonon matrix element is obtained from the modified Electron-Phonon-Wannier (EPW) code. All codes, examples, and scripts are available on the GitHub repository.

We present INTW, a modular software environment designed for advanced electronic structure calculations. Developed in Fortran95, INTW is capable of reading self-consistent field (SCF) results, such as electron energies, wave functions, and potentials, generated by the Quantum ESPRESSO and SIESTA codes. Using these SCF results as input, INTW provides a suite of specialized subroutines and functions for the computation of various electron- and phonon-related physical properties, facilitating detailed analysis of material properties at the quantum level. INTW particularly stands out in its treatment of symmetry, fully exploiting it even when dealing with electron spinor wave functions. Furthermore, it can efficiently work with both localized basis set codes, such as SIESTA, and plane-wave codes like Quantum ESPRESSO. These capabilities make INTW unique, offering a versatile approach that effectively combines the use of symmetry with both localized basis sets and plane-wave methods.