Computer Physics Communications

The study of DNA charge dynamics is a highly interdisciplinary field that bridges physics, chemistry, biology, and medicine, and plays a critical role in processes such as DNA damage detection, protein-DNA interactions, and DNA-based nanotechnology. However, despite significant progress in each of these areas, knowledge often remains inaccessible to researchers in other scientific communities, limiting the broader impact of advances across disciplines. To bridge this gap, we present QuantumDNA, an open-source Python package for simulating DNA charge transfer and excited state dynamics using quantum physical methods. QuantumDNA combines an efficient Linear Combination of Atomic Orbitals (LCAO) approach combined with tight-binding models and incorporates open quantum systems techniques to account for environmental effects. This approach allows for a rapid yet sufficiently accurate analysis of large DNA ensembles, enabling statistical studies of genetic and epigenetic phenomena. To ensure accessibility, the package features a graphical user interface, making it suitable for researchers across disciplines.

We present FLOW36, a GPU-ready solver for interface-resolved simulations of multiphase turbulence. The simulation framework relies on the coupling of direct numerical simulation of turbulence, used to describe the flow field, with a phase-field method, used to describe the shape and deformation of a deformable interface and the presence of surfactants. An additional transport equation for a passive scalar can be solved to describe heat transfer in multiphase turbulence. The governing equations are solved in a cuboid domain bounded by two walls along the wall-normal direction where no-slip, free-slip or fixed/moving wall boundary conditions can be applied, while periodicity is applied along the streamwise and spanwise directions. The numerical method relies on a pseudo-spectral approach where Fourier series (periodic directions) and Chebyshev polynomials (wall-normal direction) are used to discretize the governing equations in space. Equations are advanced in time using an implicit-explicit scheme. From a computational perspective, FLOW36 relies on a multilevel parallelism. The first level of parallelism relies on the message-passing interface (MPI). A second level of parallelism uses OpenACC directives and cuFFT libraries; this second level is used to accelerate the code execution when heterogeneous computing infrastructures are targeted. In this work, we present the numerical method and we discuss the main implementation strategies, with particular reference to the MPI and OpenACC directives and code portability, performance and maintenance strategies. FLOW36 is released open source under the GPLv3 license.

We present Hotspice, a Monte Carlo simulation software designed to capture the dynamics and equilibrium states of Artificial Spin Ice (ASI) systems with both in-plane (IP) and out-of-plane (OOP) geometries. An Ising-like model is used where each nanomagnet is represented as a macrospin, with switching events driven by thermal fluctuations, magnetostatic interactions, and external fields. To improve simulation accuracy, we explore the impact of several corrections to this model, concerning for example the calculation of the dipole interaction in IP and OOP ASI, as well as the impact of allowing asymmetric rather than symmetric energy barriers between stable states. We validate these enhancements by comparing simulation results with experimental data for pinwheel and kagome ASI lattices, demonstrating how these corrections enable a more accurate simulation of the behavior of these systems. We finish with a demonstration of ‘clocking’ in pinwheel and OOP square ASI as an example of reservoir computing.

POLARIS is a 3D Monte-Carlo radiative transfer code written in C++ for simulating the Mie scattering of laser light in optically thick nanodusty plasmas. Originally developed for astrophysical applications, POLARIS has been adapted to address the specific needs of the plasma physics community. To achieve this, a given number of photon packages characterized by their traveling direction d→, wavelength λ, intensity, and polarization state in terms of the Stokes vector S→ is generated to mimic the emission of a laser source with a Gaussian intensity distribution. These photon packages are then tracked along their probabilistic paths through the particle cloud, with scattering processes determined stochastically based on probability density distributions derived from the optical properties of the dust particles. POLARIS allows simulations for arbitrary wavelengths and grain sizes, as long as the far-field approximation holds. This paper introduces this adapted version of POLARIS to the plasma physics community, highlighting its capabilities for modeling light scattering in dusty plasmas and serving as a comprehensive reference for its application. In doing so, POLARIS provides a powerful tool for the in-situ analysis of optically thick dusty plasmas.

A new version of the code system pengeom, which provides a complete set of tools to handle different geometries in Monte Carlo simulations of radiation transport, is presented. The distribution package consists of a set of Fortran subroutines and a Java graphical user interface that allows building and debugging the geometry-definition file, and producing images of the geometry in two- and three dimensions. A detailed description of these tools is given in the original paper [Comput. Phys. Commun. 199 (2016) 102–113] and in the code manual included in the distribution package. The present new version differs from the previous one in that 1) it implements a more systematic handling of round-off errors, 2) the set of examples has been updated, and 3) it allows including a single voxelized box as a geometry module. With the last optional feature, a Monte Carlo code can readily be used for describing irradiation processes with complex material structures, such as medical treatments.

We present pyBoLaNO, a Python symbolic package based on SymPy to quickly normal-order any polynomial in bosonic ladder operators regarding the canonical commutation relations, using Blasiak's formulae. By extension, this package offers the normal ordering of commutators of any two polynomials in bosonic ladder operators and the evaluation of the normal-ordered expectation value evolution in the Lindblad master equation framework for open quantum systems. The package supports multipartite descriptions and multiprocessing. We describe the package's workflow, show examples of use, and discuss its computational performance. All codes and examples are available on our GitHub repository.

Exploiting symmetries in the numerical renormalization group (NRG) method significantly enhances performance by improving the accuracy, increasing the computational speed, and optimizing the memory efficiency. Published codes focus on continuous rotations and unitary groups, which generally are not applicable to systems with strong crystal-field effects. The PointGroupNRG code implements symmetries related to discrete rotation groups, which are defined by the user in terms of Clebsch-Gordan coefficients, together with particle conservation and spin rotation symmetries. In this paper we present a new version of the code that extends the available finite groups, previously limited to simply reducible point groups, in a way that all point and double groups become accessible. It also includes the full spin-orbital rotation group. Moreover, to improve the code's flexibility for impurities with complex interactions, this new version allows to choose between a standard Anderson Hamiltonian for the impurity or, as another novel feature, an ionic model that requires only the spectrum and the impurity Lehmann amplitudes.

The Graspg program package is an extension to Grasp2018 (Froese Fischer et al. (2019) [1]) based on configuration state function generators (CSFGs). The generators keep spin-angular integrations at a minimum and reduce substantially the execution time and the memory requirement for large-scale multiconfiguration Dirac-Hartree-Fock (MCDHF) and relativistic configuration interaction (CI) atomic structure calculations. The package includes the improvements reported in Li (2023) [8] in terms of redesigned and efficient constructions of direct and exchange potentials and Lagrange multipliers. In addition, further parallelization of the diagonalization procedure has been implemented. Tools have been developed for predicting configuration state functions (CSFs) that are unimportant and can be discarded for large MCDHF or CI calculations based on results from smaller calculations, thus providing efficient methods for a priori condensation. The package provides a seamless interoperability with Grasp2018. From extensive test runs and benchmarking, we have demonstrated reductions in the execution time and disk file sizes with factors of 37 and 98, respectively, for MCDHF calculations based on large orbital sets compared to corresponding Grasp2018 calculations. For CI calculations, reductions of the execution time with factors over 200 have been attained. With a sensible use of the new possibilities for a priori condensation, CI calculations with nominally hundreds of millions of CSFs can be handled.

We introduce a program named KPROJ that unfolds the electronic and phononic band structure of materials modeled by supercells. The program is based on the k-projection method, which projects the wavefunction of the supercell onto the k-points in the Brillouin zone of the artificial primitive cell. It allows for obtaining an effective “local” band structure by performing partial integration over the k-projected wavefunctions, e.g., the unfolded band structure with layer-projection for interfaces and the weighted band structure in the vacuum for slabs. The layer k-projection is accelerated by a scheme that combines the Fast Fourier Transform (FFT) and the inverse FFT algorithms. It is now interfaced with several first-principles codes based on plane waves such as VASP, Quantum Espresso, and ABINIT. In addition, it also has interfaces with ABACUS, a first-principles simulation package based on numerical atomic basis sets, and PHONOPY, a program for phonon calculations.

Two-dimensional (2D) van der Waals (vdWs) structures are the subject of extensive research in materials science, celebrated for their unique physical properties and potential technological applications. However, the diversity of stacking modes in 2D vdWs structures poses a challenge for research. In response to the complexity of the stacking process for these layered structures, we have developed a Python package, PyHTStack2D, specifically designed to support High-Throughput Stacking of 2D materials research. The package provides two primary functionalities: Firstly, it facilitates the batch stacking of homo- and heterostructures, with careful consideration of specific sequences and patterns, such as those observed in the 1T/2H phase transitions of transition metal dichalcogenides; Secondly, it aids in the efficient creation of computational directories and the generation of requisite shell scripts for the batch computation submissions of the stacked structures. By employing this package, we performed high-throughput computational simulations of properties such as electronic energy band structures and magnetic ground states of bilayers composed of 2H-TMDHs. These results have enabled us to identify the types of electronic band structures within these systems, providing critical insights into their potential applications in optoelectronics and photocatalysis. Furthermore, preliminary findings indicate the potential feasibility of generating bipolar magnetic semiconductors via the stacking of magnetic monolayers. The PyHTStack2D package provides an opportunity to perform efficient high-throughput calculations of 2D vdWs homo/heterostructures.