Computer Physics Communications最新文献

Astrophysical turbulent flows display an intrinsically multi-scale nature, making their numerical simulation and the subsequent analyses of simulated data a complex problem. In particular, two fundamental steps in the study of turbulent velocity fields are the Helmholtz-Hodge decomposition (compressive+solenoidal; HHD) and the Reynolds decomposition (bulk+turbulent; RD). These problems are relatively simple to perform numerically for uniformly-sampled data, such as the one emerging from Eulerian, fix-grid simulations; but their computation is remarkably more complex in the case of non-uniformly sampled data, such as the one stemming from particle-based or meshless simulations. In this paper, we describe, implement and test vortex-p, a publicly available tool evolved from the vortex code, to perform both these decompositions upon the velocity fields of particle-based simulations, either from smoothed particle hydrodynamics (SPH), moving-mesh or meshless codes. The algorithm relies on the creation of an ad-hoc adaptive mesh refinement (AMR) set of grids, on which the input velocity field is represented. HHD is then addressed by means of elliptic solvers, while for the RD we adapt an iterative, multi-scale filter. We perform a series of idealised tests to assess the accuracy, convergence and scaling of the code. Finally, we present some applications of the code to various SPH and meshless finite-mass (MFM) simulations of galaxy clusters performed with OpenGadget3, with different resolutions and physics, to showcase the capabilities of the code.

In this article, we propose a modified Allen–Cahn (AC) equation with a space-dependent interfacial parameter. When numerically solving the AC equation with a constant interfacial parameter over large domains, a substantial number of grid points are essential, which leads to significant computational costs. To effectively resolve this problem, numerous adaptive mesh techniques have been developed and implemented. These methods use locally refined meshes that adaptively track the interfacial positions of the phase field throughout the simulation. However, the data structures for adaptive algorithms are generally complex, and the problems to be solved may involve challenges at multiple scales. In this article, we present a modified AC equation with a mesh size-dependent interfacial parameter on a triangular mesh to efficiently solve multi-scale problems. In the proposed method, a triangular mesh is used, and the interfacial parameter value at a node point is defined as a function of the average length of the edges connected to the node point. The proposed algorithm effectively uses large and small values of the interfacial parameter on coarse and fine meshes, respectively. To demonstrate the efficiency and superior performance of the proposed method, we conduct several representative numerical experiments. The computational results indicate that the proposed interfacial function can adequately evolve the multi-scale phase interfaces without excessive relaxation or freezing of the interfaces. Finally, we provide the main source code for the methodology, including mesh generation as described in this paper, so that interested readers can use it.

The web-based application NEBOAS was developed to calculate the neutron yield of the accelerator-based neutron source MONNET (MONo-energetic NEutron Tower) at JRC-Geel. Neutrons are produced with p and d-induced reactions on particular targets. NEBOAS provides double differential neutron yields, as a function of the angle of neutron emission and energy. It provides also integrated neutron yields, and neutron energy spectra. Any projectile energy may be utilized, as long as it is covered by the nuclear data available on thin targets (that just degrade the projectiles' energy) or thick targets (that stop the projectiles). The calculation employs reaction cross-section evaluations from Evaluated Nuclear Data File (ENDF) or compilations of experimental measurements from the Experimental Nuclear Reaction Data (EXFOR), and stopping powers as recommended in the National Institute of Standards and Technology (NIST) or the Stopping and Range of Ions in Matter (SRIM-2013) databases.

Neutrino telescopes are gigaton-scale neutrino detectors comprised of individual light-detection units. Though constructed from simple building blocks, they have opened a new window to the Universe and are able to probe center-of-mass energies that are comparable to those of collider experiments. Prometheus is a new, open-source simulation tailored for this kind of detector. Our package, which is written in a combination of C++ and Python provides a balance of ease of use and performance and allows the user to simulate a neutrino telescope with arbitrary geometry deployed in ice or water. Prometheus simulates the neutrino interactions in the volume surrounding the detector, computes the light yield of the hadronic shower and the out-going lepton, propagates the photons in the medium, and records their arrival times and position in user-defined regions. Finally, Prometheus events are serialized into a parquet file, which is a compact and interoperational file format that allows prompt access to the events for further analysis.

Program summary

Program title: Prometheus

CPC Library link to program files: https://doi.org/10.17632/svwyd4rd83.1

Developer's repository link: https://github.com/Harvard-Neutrino/prometheus

Licensing provisions: GNU Lesser General Public License 2.1

Programming language: Python

Nature of problem: Simulation of neutrino telescopes in ice and water.

Solution method: Monte Carlo methods.

The generalized stacking fault energy (GSFE) stands as a fundamental yet pivotal parameter for the plastic deformation of materials. In our investigation, we conduct first-principles calculations using the full-potential linearized augmented planewave (FLAPW) method to assess the GSFE, employing both single-shift and triple-shift supercell models. Different defects in these models result in different impacts on the self-consistent field (SCF) iterations and atomic relaxation. We propose an adaptive preconditioning scheme that can identify the long-wavelength divergence behavior of the Jacobian during the SCF iteration and automatically switch on the Kerker preconditioning to accelerate the convergence without any prior information. We implement this algorithm based on Elk-7.2.42 package and calculate the GSFE curves for the (111) plane along $〈\overline{1}\overline{1}2〉$ direction of Al, Cu, and Si. The results indicate that defects induced by the vacuum layer in the single-shift supercell model negatively impact the convergence of SCF iterations and atomic relaxation, therefore the triple-shift supercell model is more recommended.

A fundamental task in particle-in-cell (PIC) simulations of plasma physics is solving for charged particle motion in electromagnetic fields. This problem is especially challenging when the plasma is strongly magnetized due to numerical stiffness arising from the wide separation in time scales between highly oscillatory gyromotion and overall macroscopic behavior of the system. In contrast to conventional finite difference schemes, we investigated exponential integration techniques to numerically simulate strongly magnetized charged particle motion. Numerical experiments with a uniform magnetic field show that exponential integrators yield superior performance for linear problems (i.e. configurations with an electric field given by a quadratic electric scalar potential) and are competitive with conventional methods for nonlinear problems with cubic and quartic electric scalar potentials.

We present the TRIQS/Nevanlinna analytic continuation package, an efficient implementation of the methods proposed by J. Fei et al. (2021) [53] and (2021) [55]. TRIQS/Nevanlinna strives to provide a high quality open source (distributed under the GNU General Public License version 3) alternative to the more widely adopted Maximum Entropy based analytic continuation programs. With the additional Hardy functions optimization procedure, it allows for an accurate resolution of wide band and sharp features in the spectral function. Those problems can be formulated in terms of imaginary time or Matsubara frequency response functions. The application is based on the TRIQS C++/Python framework, which allows for easy interoperability with other TRIQS-based applications, electronic band structure codes and visualization tools. Similar to other TRIQS packages, it comes with a convenient Python interface.

Program summary

Program Title: TRIQS/Nevanlinna

CPC Library link to program files: https://doi.org/10.17632/4cbzfy5rds.1

Developer's repository link: https://github.com/TRIQS/Nevanlinna

Licensing provisions: GPLv3

Programming language: C++/Python

External routines/libraries: TRIQS 3.2 [1], Boost >= 1.76.0, Eigen >= 3.4.0, cmake >= 3.20.

Nature of problem: Finite-temperature field theories are widely used to study quantum many-body effects and electronic structure of correlated materials. Obtaining physically relevant spectral functions from results in the imaginary time/Matsubara frequency domains requires solution of an ill-posed analytic continuation problem as a post-processing step.

Solution method: We present an efficient C++/Python open-source implementation of the Nevanlinna/Caratheodory analytic continuation.

In reservoir simulation, the non-isothermal multiphase flow problem introduces the temperature variable to account for thermal effects, simultaneously posing challenges in efficiently solving the nonlinear systems for large-scale simulations. In this paper, we introduce and investigate a family of Schur-complement-based field-split algorithms designed for addressing non-isothermal multiphase flow problems, particularly those characterized by high heterogeneity. This algorithm involves decomposing a large system into smaller, more manageable sub-systems for solving non-isothermal multiphase flow problems with multiple physical fields, which enables parallel computation and makes it suitable for high-performance computing environments. Furthermore, a multilevel Schur-complement preconditioner, which involves applying the Schur-complement technique at each level of the hierarchy by capturing the coupling between different fields and physics, is proposed to enhance the efficiency and robustness of the parallel simulator. Large-scale simulations for both benchmark and realistic problems are conducted on a supercomputer, showcasing the method's efficacy in managing heat diffusion, significantly reducing linear iterations, and demonstrating a good parallel scalability.

Laser plasma instabilities (LPIs) have significant influences on the laser energy deposition efficiency and therefore are important processes in inertial confined fusion (ICF). Numerical simulations play important roles in revealing the complex physics of LPIs. Since LPIs are typically a three wave coupling process, the precise simulations of LPIs with kinetic effects require to resolve the laser period (around one femtosecond) and laser wavelength (less than one micron). In the typical ICF experiments, however, LPIs are involved in a spatial scale of several millimeters and a temporal scale of several nanoseconds. Therefore, the precise kinetic simulations of LPIs in such scales require huge computational resources and are hard to be carried out by present kinetic codes like particle-in-cell (PIC) codes. In this paper, a full wave fluid model of LPIs is constructed and numerically solved by the particle-mesh method, where the plasma is described by macro particles that can move across the mesh grids freely. Based upon this model, a two-dimensional (2D) GPU code named PM2D is developed. The PM2D code can simulate the kinetic effects of LPIs self-consistently as normal PIC codes. Moreover, as the physical model adopted in the PM2D code is specifically constructed for LPIs, the required macro particles per grid in the simulations can be largely reduced and thus overall simulation cost is considerably reduced comparing with PIC codes. More importantly, the numerical noise in the PM2D code is much lower, which makes it more robust than PIC codes in the simulation of LPIs for the long-time scale above 10 picoseconds. After the distributed computing is realized, our PM2D code is able to run on GPU clusters with a total mesh grids up to several billions, which meets the requirements for the simulations of LPIs at ICF experimental scale with reasonable cost.

Program summary

Program Title: PM2D

CPC Library link to program files: https://doi.org/10.17632/xscj6vnkkw.1

Licensing provisions: GNU General Public License v3.0.

Programming language: C++, CUDA.

Nature of problem: Although the large scale simulations of laser plasma instabilities (LPIs) is of great significance for the inertial confinement fusion (ICF), there is still no suitable code to simulate these problems. PM2D code based on a GPU platform provides an effective method to simulate these large scale problems in ICF.

Solution method: A fluid model for LPIs is established firstly, which contains wave equations that describe the laser propagating process, electron and ion fluid equations that describe the plasma motions, and a Poisson's equation that describes the electrostatic field induced by charge separation. The wave equation is solved on a rectangular region using absorption boundary conditions on all of four boundaries. The absorption boun