The global impurity transport code (GITR - pronounced “guitar”) has been developed as a high-performance Monte Carlo particle (neutral atom and ion) tracking code to simulate the erosion, ionization, migration, and redistribution of plasma-facing components in magnetically confined fusion devices. The trace impurity assumption allows for a highly parallel computational model that enables increased scaling in the number of particles simulated as well as the domain size and geometric fidelity. Novel custom algorithms that query the 3D surface geometry has alleviated the need for traditional meshing needs. Presented here is the physics model, numerical schemes, algorithmic implementation, and example simulations.
The Discrete Space Quantum Systems Solver (DSQSS) is a program package for solving quantum many-body problems defined on lattices. The DSQSS is based on the quantum Monte Carlo method in Feynman’s path integral representation and covers a broad range of problems using flexible input files that define arbitrary unit cells in arbitrary dimensions and arbitrary matrix elements representing the interactions among an arbitrary number of degrees of freedom. Finite temperature calculations of quantum spin and the Bose–Hubbard models can be performed by specifying parameters such as the number of dimensions, the lattice size, coupling constants, and temperature. The present paper details the use of DSQSS and presents a number of applications thereof.
Bloch wavefunctions in solids form a representation of crystalline symmetries. Recent studies revealed that symmetry representations in band structure can be used to diagnose the topological properties of weakly interacting materials. In this work, we introduce an open-source program qeirreps that computes the representation characters in a band structure based on the output file of Quantum ESPRESSO. Our program also calculates the Z_4 index, i.e., the sum of inversion parities at all time-reversal invariant momenta, for materials with inversion symmetry. When combined with the symmetry indicator method, this program can be used to explore new topological materials.
Gradients in free energies are the driving forces of physical and biochemical systems. To predict free energy differences with high accuracy, Molecular Dynamics (MD) and other methods based on atomistic Hamiltonians conduct sampling simulations in intermediate thermodynamic states that bridge the configuration space densities between two states of interest (’alchemical transformations’). For uncorrelated sampling, the recent Variationally derived Intermediates (VI) method yields optimal accuracy. The form of the VI intermediates differs fundamentally from conventional ones in that they are non-pairwise, i.e., the total force on a particle in an intermediate states cannot be split into additive contributions from the surrounding particles. In this work, we describe the implementation of VI into the widely used GROMACS MD software package (2020, version 1). Furthermore, a variant of VI is developed that avoids numerical instabilities for vanishing particles. The implementation allows the use of previous non-pairwise potential forms in the literature, which have so far not been available in GROMACS. Example cases on the calculation of solvation free energies, and accuracy assessments thereof, are provided.
Contributors:Magnus Fürst, Andrea Bertolino, Alberto Cuoci, Tiziano Faravelli, Alessio Frassoldati et al
As detailed chemical mechanisms are becoming viable for large scale simulations, knowledge and control of the uncertainty correlated to the kinetic parameters are becoming crucial to ensure accurate numerical predictions. A flexible toolbox for the optimization of chemical kinetics has therefore been developed in this work. The toolbox is able to use different optimization methodologies, as well as it can handle a large amount of uncertain parameters simultaneously. It can also handle experimental targets from different sources: Batch reactors, Plug Flow Reactors, Perfectly Stirred Reactors, Rapid Compression Machines and Laminar Flame Speeds. This work presents the different features of this toolbox together with five different test cases which exemplifies these features.
Studies Beyond the Standard Model (BSM) will become more and more important in the near future with the rapidly increasing amount of data from different experiments around the world. The full study of BSM models is in general an extremely time-consuming task involving long and difficult calculations. It is in practice not possible to do exhaustive predictions in these models by hand. Here we present MARTY, a new C++ framework that fully automates calculations from the Lagrangian to physical quantities such as amplitudes or cross-sections. It can fully simplify, automatically and symbolically, physical quantities in a very large variety of models and compute Wilson coefficients in effective theories. This will considerably facilitate BSM studies in flavour physics. Contrary to the existing public codes in this field MARTY aims at providing a unique, free, open-source, powerful and user-friendly tool for high-energy physicists studying predictive BSM models, in effective or full theories up to the one-loop level, which does not rely on any external package. With a few lines of code one can gather final expressions that may be evaluated numerically for statistical analysis.
The Green’s function method was applied to solve the one-dimensional positron diffusion equation for a system consisting of up to four layers that contain defects with different trapping rates. These allow us to obtain the analytical relationships valid for the evaluation of data obtained from variable energy positron measurements. They have been implemented in user-friendly free computer code available to users. Fitting strategies are presented to extract the relevant physical parameters. The code was used to determine positron diffusion length in samples of polycrystalline pure, well-annealed iron, depleted uranium, and titanium.
We present the public python package munuSSM that can be used for phenomenological studies in the context of the μ-from-ν Supersymmetric Standard Model (μνSSM). The code incorporates the radiative corrections to the neutral scalar potential at full one-loop level. Sizable higher-order corrections, required for an accurate prediction of the SM-like Higgs-boson mass, can be consistently included via an automated link to the public code FeynHiggs. In addition, a calculation of effective couplings and branching ratios of the neutral and charged Higgs bosons is implemented. This provides the required ingredients to check a benchmark point against collider constraints from searches for additional Higgs bosons via an interface to the public code HiggsBounds. At the same time, the signal rates of the SM-like Higgs boson can be tested applying the experimental results implemented in the public code HiggsSignals. The python package is constructed in a flexible and modular way, such that it provides a simple framework that can be extended by the user with further calculations of observables and constraints on the model parameters.
Contributors:Xu He, Nicole Helbig, Matthieu J. Verstraete, Eric Bousquet
We present TB2J, a Python package for the automatic computation of magnetic interactions, including exchange and Dzyaloshinskii-Moriya, between atoms of magnetic crystals from the results of density functional calculations. The program is based on the Green’s function method with the local rigid spin rotation treated as a perturbation. As input, the package uses the output of either Wannier90, which is interfaced with many density functional theory packages, or of codes based on localized orbitals. One of the main interest of the code is that it requires only one first-principles electronic structure calculation in the non-relativistic case (or three in the relativistic case) and from the primitive cell only to obtain the magnetic interactions up to long distances, instead of first-principles calculations of many different magnetic configurations and large supercells. The output of TB2J can be used directly for the adiabatic magnon band structure and spin dynamics calculations. A minimal user input is needed, which allows for easy integration into high-throughput workflows.
Contributors:Katharina Boguslawski, Aleksandra Leszczyk, Artur Nowak, Filip Brzęk, Piotr Szymon Żuchowski et al
Pythonic Black-box Electronic Structure Tool (PyBEST) represents a fully-fledged modern electronic structure software package developed at Nicolaus Copernicus University in Toruń. The package provides an efficient and reliable platform for electronic structure calculations at the interface between chemistry and physics using unique electronic structure methods, analysis tools, and visualization. Examples are the (orbital-optimized) pCCD-based models for ground- and excited-states electronic structure calculations as well as the quantum entanglement analysis framework based on the single-orbital entropy and orbital-pair mutual information. PyBEST is written primarily in the Python programming language with additional parts written in C＋＋, which are interfaced using Pybind11, a lightweight header-only library. By construction, PyBEST is easy to use, to code, and to interface with other software packages. Moreover, its modularity allows us to conveniently host additional Python packages and software libraries in future releases to enhance its performance. The electronic structure methods available in PyBEST are tested for the half-filled 1-D model Hamiltonian. The capability of PyBEST to perform large-scale electronic structure calculations is demonstrated for the model vitamin B_12 compound. The investigated molecule is composed of 190 electrons and 777 orbitals for which an orbital optimization within pCCD and an orbital entanglement and correlation analysis are performed for the first time.