Computer Physics Communications

A computational model is presented to calculate the ground state energy of neutral and charged excitons confined in semiconductor quantum dots. The model is based on the variational Quantum Monte Carlo method and effective mass Hamiltonians. Through an iterative Newton–Raphson process, minimizing the local energy, and (optional) parallelization of random walkers, fast and accurate estimates of both confinement and Coulomb binding energies can be obtained in standard desktop computers. To illustrate the reach of the model, we provide Fortran programs and illustrative calculations for colloidal CdSe nanoplatelets with large lateral dimensions and dielectric confinement, where electronic correlations are strong. The results compare well with exact variational calculations and largely outperform configuration interaction calculations in computational efficiency.

RESPACK is a first-principles calculation software for evaluating the interaction parameters of materials and is able to calculate maximally localized Wannier functions, response functions based on the random phase approximation and related optical properties, and frequency-dependent electronic interaction parameters. RESPACK receives its input data from a band-calculation code using norm-conserving pseudopotentials with plane-wave basis sets. Automatic generation scripts that convert the band-structure results to the RESPACK inputs are prepared for xTAPP and Quantum ESPRESSO. An input file for specifying the RESPACK calculation conditions is designed pursuing simplicity and is given in the Fortran namelist format. RESPACK supports hybrid parallelization using OpenMP and MPI and can treat large systems including a few hundred atoms in the calculation cell.

Dynamical Mean Field Theory (DMFT) is a successful method to compute the electronic structure of strongly correlated materials, especially when it is combined with density functional theory (DFT). Here, we present an open-source computational package (and a library) combining DMFT with various DFT codes interfaced through the Wannier90 package. The correlated subspace is expanded as a linear combination of Wannier functions introduced in the DMFT approach as local orbitals. In particular, we provide a library mode for computing the DMFT density matrix. This library can be linked and then internally called from any DFT package, assuming that a set of localized orbitals can be generated in the correlated subspace. The existence of this library allows developers of other DFT codes to interface with our package and achieve the charge-self-consistency within DFT+DMFT loops. To test and check our implementation, we computed the density of states and the band structure of well-known solid-state correlated materials, namely LaNiO_3, SrVO_3, and NiO. The obtained results are compared to those obtained from other DFT+DMFT implementations.

Understanding formation, growth and transport of aerosols is critical to processes ranging from cloud formation to disease transmission. In this work, a numerical algorithm of aerosol dynamics including nucleation, coagulation, and surface growth was coupled with flow and heat transfer equations enabling the solution of three-dimensional multi-physics aerosol processes in an open-source platform. The general dynamic equation was solved by a nodal method where the particle size distribution was represented by a finite number of nodes. The models were verified by comparing four test cases, (1) pure coagulation, (2) nucleation and coagulation, (3) pure surface growth, and (4) a general dynamic equation that includes the three mechanisms provided in literature. A high temperature aerosol flow in a cooled pipe is chosen as a tutorial case of coupled computational aerosol and fluid dynamics. The aerosolGDEFoam code is available at https://openaerosol.sourceforge.io and can be further modified under GNU general public licence.

Computer modeling and simulations are increasingly being used to predict the clinical performance of x-ray imaging devices in silico, and to generate synthetic patient images for training and testing of machine learning algorithms. We present a detailed description of the computational models implemented in the open source GPU-accelerated Monte Carlo x-ray imaging simulation code MC-GPU. This code, originally developed to simulate radiography and computed tomography, has been extended to replicate a commercial full-field digital mammography and digital breast tomosynthesis (DBT) device. The code was recently used to image 3000 virtual breast models with the aim of reproducing in silico a clinical trial used in support of the regulatory approval of DBT as a replacement of mammography for breast cancer screening. The updated code implements a more realistic x-ray source model (extended 3D focal spot, tomosynthesis acquisition trajectory, tube motion blurring) and an improved detector model (direct-conversion Selenium detector with depth-of-interaction effects, fluorescence tracking, electronic noise and anti-scatter grid). The software uses a high resolution voxelized geometry model to represent the breast anatomy. To reduce the GPU memory requirements, the code stores the voxels in memory within a binary tree structure. The binary tree is an efficient compression mechanism because many voxels with the same composition are combined in common tree branches while preserving random access to the phantom composition at any location. A delta scattering ray-tracing algorithm which does not require computing ray-voxel interfaces is used to minimize memory access. Multiple software verification and validation steps intended to establish the credibility of the implemented computational models are reported. The software verification was done using a digital quality control phantom and an ideal pinhole camera. The validation was performed reproducing standard bench testing experiments used in clinical practice and comparing with experimental measurements. A sensitivity study intended to assess the robustness of the simulated results to variations in some of the input parameters was performed using an in silico clinical trial pipeline with simulated lesions and mathematical observers. We show that MC-GPU is able to simulate x-ray projections that incorporate many of the sources of variability found in clinical images, and that the simulated results are robust to some uncertainty in the input parameters. Limitations of the implemented computational models are discussed.

minimal-lagrangians is a Python program which allows one to specify the field content of an extension of the Standard Model of particle physics and, using this information, to generate the most general renormalizable Lagrangian that describes such a model. As the program was originally created for the study of minimal dark matter models with radiative neutrino masses, it can handle additional scalar or Weyl fermion fields which are SU (3)_C singlets, SU (2)_L singlets, doublets or triplets, and can have arbitrary U (1)_Y hypercharge. It is also possible to enforce an arbitrary number of global U (1) symmetries (with Z_2 as a special case) so that the new fields can additionally carry such global charges. In addition to human-readable and LaTeX output, the program can generate SARAH model files containing the computed Lagrangian, as well as information about the fields after electroweak symmetry breaking (EWSB), such as vacuum expectation values (VEVs) and mixing matrices. This capability allows further detailed investigation of the model in question, with minimal-lagrangians as the first component in a tool chain for rapid phenomenological studies of “minimal” dark matter models requiring little effort and no unnecessary input from the user.

ComBethAns is a Maple module developed to enable calculations concerning spin systems using combinatorial Bethe Ansatz approach. This method of spin system analysis is based on representation theory and combinatorics. It allows to consider one-dimensional spin systems with periodic boundary conditions. The module ComBethAns offers tools to define the different bases for such quantum system, to carry out transformation between these bases and to reveal some important aspects of the quantum system. Particularly powerful features are the possibility to generate the Schur–Weyl transform and to quasi-diagonalize the Hamiltonian using projection method.

The latest version of the Grasp2018 package [Froese Fischer et al. (2019)], based on the multiconfigurational Dirac–Hartree–Fock method, is extended to account for effects of crystal fields in complex systems. Instead of using the simplified treatment of the crystal field effects based on the Stevens’ operator-equivalent method the program uses the fully ab-initio method in which the external ions are treated as point charges at fixed positions. In addition, examples of how to use the CF_Hamiltonian program are given in source directory grasp2018/src/appl/CF_Hamiltonian/Sample_Runs.

The third-order elastic constants (TOECs) are fundamental to describe crystal’s nonlinear response to stress, and can be applied to explore anharmonic properties of crystals such as Grüneisen parameters, thermal expansion coefficient, and the effect of pressure on second-order elastic constants (SOECs). Here, we report an open-source python package, Elastic3rd, which is able to calculate the SOECs and TOECs using the strain–energy method for crystals with any symmetry from first-principles calculations. An algorithm to generate necessary strain modes and the corresponding coefficients for a given symmetry is proposed. These strain modes are then applied to the fully relaxed structure to generate the deformed structures. The total energies of the strained structures are calculated by a chosen first-principles code, and the SOECs and TOECs are determined by fitting the resulted strain–energy data. The present code has been validated by several case studies of C, Si and Mg, and the case of MnP4 shows the ability for low-symmetry crystals.

We implement the Multi-Rate Mass Transfer (MRMT) model for mobile–immobile transport in porous media (Haggerty and Gorelick, 1995; Municchi and Icardi, 2019 [1]) within the open-source finite volume library OpenFOAM® (Foundation, 2014). Unlike other codes available in the literature (Geiger et al., 2011 [2]; Silva et al., 2009), we propose an implementation that can be applied to complex three-dimensional geometries and highly heterogeneous fields, where the parameters of the MRMT can arbitrarily vary in space. Furthermore, being built over the widely diffused OpenFOAM® library, it can be easily extended and included in other models, and run in parallel. We briefly describe the structure of the multiContinuumModels library that includes the formulation of the MRMT based on the works of Haggerty and Gorelick (1995) and Municchi and Icardi (2020a). The implementation is verified against benchmark solutions and tested on two- and three-dimensional random permeability fields. The role of various physical and numerical parameters, including the transfer rates, the heterogeneities, and the number of terms in the MRMT expansions, is investigated. Finally, we illustrate the significant role played by heterogeneity in the mass transfer when permeability and porosity are represented using Gaussian random fields.