Skip to main content

Computer Physics Communications

ISSN: 0010-4655

Visit Journal website

Datasets associated with articles published in Computer Physics Communications

Filter Results
3924 results
  • FabSim3: An automation toolkit for verified simulations using high performance computing
    A common feature of computational modelling and simulation research is the need to perform many tasks in complex sequences to achieve a usable result. This will typically involve tasks such as preparing input data, pre-processing, running simulations on a local or remote machine, post-processing, and performing coupling communications, validations and/or optimisations. Tasks like these can involve manual steps which are time and effort intensive, especially when it involves the management of large ensemble runs. Additionally, human errors become more likely and numerous as the research work becomes more complex, increasing the risk of damaging the credibility of simulation results. Automation tools can help ensure the credibility of simulation results by reducing the manual time and effort required to perform these research tasks, by making more rigorous procedures tractable, and by reducing the probability of human error due to a reduced number of manual actions. In addition, efficiency gained through automation can help researchers to perform more research within the budget and effort constraints imposed by their projects. This paper presents the main software release of FabSim3, and explains how our automation toolkit can improve and simplify a range of tasks for researchers and application developers. FabSim3 helps to prepare, submit, execute, retrieve, and analyze simulation workflows. By providing a suitable level of abstraction, FabSim3 reduces the complexity of setting up and managing a large-scale simulation scenario, while still providing transparent access to the underlying layers for effective debugging. The tool also facilitates job submission and management (including staging and curation of files and environments) for a range of different supercomputing environments. Although FabSim3 itself is application-agnostic, it supports a provably extensible plugin system where users automate simulation and analysis workflows for their own application domains. To highlight this, we briefly describe a selection of these plugins and we demonstrate the efficiency of the toolkit in handling large ensemble workflows.
    • Dataset
    • File Set
  • Fortnet, a software package for training Behler-Parrinello neural networks
    A new, open source, parallel, stand-alone software package (Fortnet) has been developed, which implements Behler-Parrinello neural networks. It covers the entire workflow from feature generation to the evaluation of generated potentials, coupled with higher-level analysis such as the analytic calculation of atomic forces. The functionality of the software package is demonstrated by driving the training for the fitted correction functions of the density functional tight binding (DFTB) method, which are commonly used to compensate the inaccuracies resulting from the DFTB approximations to the Kohn-Sham Hamiltonian. The usual two-body form of those correction functions limits the transferability of the parametrizations between very different structural environments. The recently introduced DFTB+ANN approach strives to lift these limitations by combining DFTB with a near-sighted artificial neural network (ANN). After investigating various approaches, we have found the combination of DFTB with an ANN acting on-top of some baseline correction functions (delta learning) the most accurate one. It allowed to introduce many-body corrections on top of two-body parametrizations, while excellent transferability to chemical environments with deviating energetics could be demonstrated.
    • Dataset
    • File Set
  • AIMSim: An accessible cheminformatics platform for similarity operations on chemicals datasets
    The recent advances in deep learning, generative modeling, and statistical learning have ushered in a renewed interest in traditional cheminformatics tools and methods. Quantifying molecular similarity is essential in molecular generative modeling, exploratory molecular synthesis campaigns, and drug-discovery applications to assess how new molecules differ from existing ones. Most tools target advanced users and lack general implementations accessible to the larger community. In this work, we introduce Artificial Intelligence Molecular Similarity (AIMSim), an accessible cheminformatics platform for performing similarity operations on collections of molecules called molecular datasets. AIMSim provides a unified platform to perform similarity-based tasks on molecular datasets, such as diversity quantification, outlier and novelty analysis, clustering, dimensionality reduction, and inter-molecular comparisons. AIMSim implements all major binary similarity metrics and molecular fingerprints and is provided as a Python package that includes support for command-line use as well as a Graphical User Interface for code-free utilization with fully interactive plots.
    • Dataset
    • File Set
  • TAUOLA update for decay channels with e+e− pairs in the final state
    With the arrival of high luminosity B-factories like the Belle II experiment, τ decay measurements have become more precise than ever, allowing rarer processes to be explored, and finer details of τ decays to be studied. These are important to understand the spectrum of intermediate particles produced in τ decays. Therefore Monte Carlo generators, like the TAUOLA program, have to facilitate precision analysis as well as confront new models that constantly emerge with the availability of high statistics experimental data. New decay channels and models may lead to large variation of matrix elements size within the available phase space, as in the case when e+e- pairs are present in final state. It requires appropriate presampler of the phase space generator and a proper documentation to help users introduce their own models. While releasing a new update, it is important for the TAUOLA Monte Carlo library to maintain the general structure of the previous versions to preserve backward compatibility. The aim is to minimize changes from the user perspective. This paper presents a demonstration of new models implementation facilitated by the current update.
    • Dataset
    • File Set
  • Drawing Feynman diagrams with GLE
    A package for drawing publication-quality Feynman diagrams written in GLE is described.
    • Other
    • Dataset
    • Text
  • FlexibleDecay: An automated calculator of scalar decay widths
    We present FlexibleDecay, a tool to calculate decays of scalars in a broad class of BSM models. The tool aims for high precision particularly in the case of Higgs boson decays. In the case of scalar and pseudoscalar Higgs boson decays the known higher order SM QED, QCD and EW effects are taken into account where possible. The program works in a modified scheme MS that exhibits a decoupling property with respect to heavy BSM physics, with BSM parameters themselves treated in the MS/DR-scheme allowing for an easy connection to high scale tests for, e.g., perturbativity and vacuum stability, and the many observable calculations readily available in MS/DR programs. Pure BSM effects are taken into account at the leading order, including all one-loop contributions to loop-induced processes. The program is implemented as an extension to FlexibleSUSY, which determines the mass spectrum for arbitrary BSM models, and does not require any extra configuration from the user. We compare our predictions for Higgs decays in the SM, singlet extended SM, type II THDM, CMSSM and MRSSM, as well as for squark decays in the CMSSM against a selection of publicly available tools. The numerical differences between our and other programs are explained. The release of FlexibleDecay officially deprecates the old effective couplings routines in FlexibleSUSY.
    • Dataset
    • File Set
  • COSEν: A collective oscillation simulation engine for neutrinos
    We introduce the implementation details of the simulation code COSEν, which numerically solves a set of non-linear partial differential equations that govern the dynamics of neutrino collective flavor conversions. We systematically provide the details of both finite difference method supported by Kreiss-Oliger dissipation and finite volume method with seventh order weighted essentially non-oscillatory scheme. To ensure the reliability of the code, we perform comparison of the simulation results with theoretically obtainable solutions. In order to understand and characterize the error accumulation behavior of the implementations when neutrino self-interactions are switched on, we also analyze the evolution of the deviation of the conserved quantities for different values of simulation parameters. We report the performance of our code with both CPUs and GPUs. The public version of the COSEν package is available at https://github.com/COSEnu/COSEnu.
    • Dataset
    • File Set
  • - CosmoLattice - A modern code for lattice simulations of scalar and gauge field dynamics in an expanding universe
    This paper describes CosmoLattice, a modern package for lattice simulations of the dynamics of interacting scalar and gauge fields in an expanding universe. CosmoLattice incorporates a series of features that makes it very versatile and powerful: i) it is written in C++ fully exploiting the object oriented programming paradigm, with a modular structure and a clear separation between the physics and the technical details, ii) it is MPI-based and uses a discrete Fourier transform parallelized in multiple spatial dimensions, which makes it specially appropriate for probing scenarios with well-separated scales, running very high resolution simulations, or simply very long ones, iii) it introduces its own symbolic language, defining field variables and operations over them, so that one can introduce differential equations and operators in a manner as close as possible to the continuum, iv) it includes a library of numerical algorithms, ranging from O(δt^2) to O(δt^10) methods, suitable for simulating global and gauge theories in an expanding grid, including the case of ‘self-consistent’ expansion sourced by the fields themselves. Relevant observables are provided for each algorithm (e.g. energy densities, field spectra, lattice snapshots) and we note that, remarkably, all our algorithms for gauge theories (Abelian or non-Abelian) always respect the Gauss constraint to machine precision.
    • Dataset
    • File Set
  • Automag: An automatic workflow software for calculating the ground magnetic state of a given structure and estimating its critical temperature
    We developed a Python package capable of finding the lowest-energy magnetic state of a given structure and to estimate its critical temperature from a Monte Carlo simulation of its effective Hamiltonian. In this paper, we introduce the code and present the results of tests performed on known materials: α-Fe2O3 (hematite), Ca3MnCoO6 and Ni3TeO6. After checking the calculation parameters for convergence, we computed the linear response value of U for DFT+U and then the single-point energies of a number of collinear magnetic configurations. The magnetic ground state has been correctly predicted for α-Fe2O3 and Ni3TeO6, while for Ca3MnCoO6 the DFT calculations did not reproduce the experimental low-spin states on Co atoms. For α-Fe2O3 and Ni3TeO6 we were able to estimate the Néel temperature and the computed values of 911 K and 31 K are both in good agreement with experiment (955 K and 52 K).
    • Dataset
    • Text
    • File Set
  • Coupling of an SPH-based solver with a multiphysics library
    A two-way coupling between the Smoothed Particle Hydrodynamics-based (SPH) code with a multiphysics library to solve complex fluid-solid interaction problems is proposed. This work provides full access to the package for the use of this coupling by releasing the source code, completed with guidelines for its compilation and utilization, and self-contained template setups for practical uses of the novel implemented features, is provided here. The presented coupling expands the applicability of two different solvers allowing to simulate fluids, multibody systems, collisions with frictional contacts using either non-smooth contact (NSC) or smooth contact (SMC) methods, all integrated under the same framework. The fluid solver is the open-source code DualSPHysics, highly optimised for simulating free-surface phenomena and structure interactions, uniquely positioned as a general-purpose Computational Fluid Dynamics (CFD) software with a GPU-accelerated solver. Mechanical systems that comprise collision detection and/or multibody dynamics are solved by the multiphysics library Project Chrono, which uses a Discrete Element Method (DEM). Therefore, this SPH-DEM coupling approach can manage interactions between fluid and complex multibody systems with relative constraints, springs, or mechanical joints.
    • Dataset
    • File Set
1