Computer Physics Communications最新文献

{"title":"A Python code for simulations of RHEED intensity oscillations within the one-dimensional dynamical approximation","authors":"Andrzej Daniluk,&nbsp;Bartłomiej Daniluk,&nbsp;Grzegorz M. Wójcik","doi":"10.1016/j.cpc.2024.109467","DOIUrl":"10.1016/j.cpc.2024.109467","url":null,"abstract":"<div><div>We present a Python-based implementation of a practical procedure of construction of simulation program, which facilitates the calculation of changes to the intensity of RHEED oscillations in the function of the glancing angle of incidence of the electron beam, employing various models of crystal potential for heteroepitaxial structures including the possible existence of various diffuse scattering models through the layer parallel to the surface. The calculations are based on the use of a one-dimensional dynamical diffraction theory. Although this theory has some limitations, in practice it is useful under so-called one-beam condition. Computation performance has been improved by using <em>Numba</em> as an open source, <em>NumPy</em>-aware optimising compiler for Python.</div></div><div><h3>Program Summary</h3><div><em>Program Title:</em> PY_RHEED_DIFF</div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/j6jxt9yr3b.1</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> GNU General Public License 3</div><div><em>Programming language:</em> Python 3.12.7</div><div><em>Journal reference of previous version:</em> Computer Physics Communications 185 (2014) 3001–3009</div><div><em>Does the new version supersede the previous version?:</em> Yes.</div><div><em>Reasons for the new version:</em> Python, as a powerful, accessible and general-purpose programming language, has gained tremendous popularity in recent years. Python is characterised by a remarkable simplicity that makes it an ideal choice for users for whom knowledge of high-level programming techniques is not the most important in research work. According to users’ suggestions we have developed a Python-based implementation of generic computational model for simulations of changes to the intensity of RHEED oscillations in the function of the glancing angle of incidence of the electron beam, employing various models of crystal potential for heteroepitaxial structures including the possible existence of various diffuse scattering models through the layer parallel to the surface. This version implements improvements for ergonomics, computational performances, readability, and code functionality by adding new capabilities which make the output data generation and visualisation process much more efficient compared to the previous version.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"308 ","pages":"Article 109467"},"PeriodicalIF":7.2,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143162807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Crystal synthesizability prediction using contrastive positive unlabeled learning","authors":"Tao Sun ,&nbsp;Jianmei Yuan","doi":"10.1016/j.cpc.2024.109465","DOIUrl":"10.1016/j.cpc.2024.109465","url":null,"abstract":"<div><div>High-throughput screening or generative models rapidly identify crystal structures with the desired properties, but the synthesizable ratio is generally low. Experimentally verifying the synthesizability of individual virtual crystals would entail significant time and resources. Therefore, a method for automatically assessing the synthesizability of virtual crystals is urgently needed. This paper describes an approach that combines contrastive learning and positive unlabeled learning. The resulting contrastive positive unlabeled learning (CPUL) model predicts the crystal-likeness score (CLscore) of virtual materials. The model achieves a true positive (CLscore &gt; 0.5) prediction accuracy of 93.95% on a test set containing 10,000 materials taken from the Materials Project (MP) database. We further validate the model by using all Fe-containing materials from the MP database as the test set, obtaining a true positive rate of 88.89%. This indicates that the CPUL model performs well, even with limited knowledge of the interactions between Fe and the atoms in the crystals. The CPUL model is then used to assess the CLscore of virtual crystals in the MP database and analyze their synthesizability by combining the energy above the hull. Finally, the synthesizability of perovskite materials is predicted using the proposed CPUL model, resulting in seven candidate halide perovskite materials for photovoltaic applications.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"308 ","pages":"Article 109465"},"PeriodicalIF":7.2,"publicationDate":"2024-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143161786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"pCI: A parallel configuration interaction software package for high-precision atomic structure calculations","authors":"Charles Cheung ,&nbsp;Mikhail G. Kozlov ,&nbsp;Sergey G. Porsev ,&nbsp;Marianna S. Safronova ,&nbsp;Ilya I. Tupitsyn ,&nbsp;Andrey I. Bondarev","doi":"10.1016/j.cpc.2024.109463","DOIUrl":"10.1016/j.cpc.2024.109463","url":null,"abstract":"&lt;div&gt;&lt;div&gt;We introduce the pCI software package for high-precision atomic structure calculations. The standard method of calculation is based on the configuration interaction (CI) method to describe valence correlations, but can be extended to attain better accuracy by including core correlations via many-body perturbation theory (CI+MBPT) or the all-order (CI+all-order) method. The software package enables calculations of atomic properties, including energy levels, &lt;em&gt;g&lt;/em&gt;-factors, hyperfine structure constants, multipole transition matrix elements, polarizabilities, and isotope shifts. It also features modern high-performance computing paradigms, including dynamic memory allocations and large-scale parallelization via the message-passing interface, to optimize and accelerate computations. To improve accuracy of the calculations, we include a supplementary program package to calculate QED corrections via a variant of QEDMOD, as well as a package to include core correlations.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Program summary&lt;/h3&gt;&lt;div&gt;&lt;em&gt;Program Title:&lt;/em&gt; pCI&lt;/div&gt;&lt;div&gt;&lt;em&gt;CPC Library link to program files:&lt;/em&gt; &lt;span&gt;&lt;span&gt;https://doi.org/10.17632/2kn5npnxj7.1&lt;/span&gt;&lt;svg&gt;&lt;path&gt;&lt;/path&gt;&lt;/svg&gt;&lt;/span&gt;&lt;/div&gt;&lt;div&gt;&lt;em&gt;Developer's repository link:&lt;/em&gt; &lt;span&gt;&lt;span&gt;https://github.com/ud-pci/pCI&lt;/span&gt;&lt;svg&gt;&lt;path&gt;&lt;/path&gt;&lt;/svg&gt;&lt;/span&gt;&lt;/div&gt;&lt;div&gt;&lt;em&gt;Licensing provisions:&lt;/em&gt; GPLv3&lt;/div&gt;&lt;div&gt;&lt;em&gt;Programming language:&lt;/em&gt; Fortran&lt;/div&gt;&lt;div&gt;&lt;em&gt;Supplementary material:&lt;/em&gt; Documentation available at &lt;span&gt;&lt;span&gt;https://pci.readthedocs.io&lt;/span&gt;&lt;svg&gt;&lt;path&gt;&lt;/path&gt;&lt;/svg&gt;&lt;/span&gt;&lt;/div&gt;&lt;div&gt;&lt;em&gt;Nature of problem:&lt;/em&gt; Calculation of atomic and ionic properties, including energy levels, hyperfine structure constants, multipole transition matrix elements, and polarizabilities.&lt;/div&gt;&lt;div&gt;&lt;em&gt;Solution method:&lt;/em&gt; The software package calculates energies and associated wave functions for the desired atomic states using the configuration interaction method. Using calculated wave functions, different atomic properties can be obtained, including &lt;em&gt;g&lt;/em&gt;-factors, hyperfine structure constants, multipole transition amplitudes, polarizabilities, and others.&lt;/div&gt;&lt;div&gt;&lt;em&gt;Additional comments including restrictions and unusual features:&lt;/em&gt; All serial programs have been compiled and tested with the freely available Intel Fortran compilers “ifx” and “ifort”, and all parallel programs with the OpenMPI wrapper “mpifort” for Intel Fortran compilers.&lt;/div&gt;&lt;div&gt;One-electron orbitals outside the nucleus are defined on the radial grid points. Inside the nucleus, they are described in a Taylor expansion over &lt;span&gt;&lt;math&gt;&lt;mi&gt;r&lt;/mi&gt;&lt;mo&gt;/&lt;/mo&gt;&lt;mi&gt;R&lt;/mi&gt;&lt;/math&gt;&lt;/span&gt;, where &lt;em&gt;R&lt;/em&gt; is the nuclear radius.&lt;/div&gt;&lt;div&gt;This software package is not designed for calculations of high Rydberg states and continuous spectrum. The parallel programs are intended to be run on large computing clusters.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;References&lt;/h3&gt;&lt;div&gt;&lt;ul&gt;&lt;li&gt;&lt;span&gt;[1]&lt;/span&gt;&lt;span&gt;&lt;div&gt;M.G. Kozlov et al., Comput. P","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"308 ","pages":"Article 109463"},"PeriodicalIF":7.2,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143162804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combining physics-informed graph neural network and finite difference for solving forward and inverse spatiotemporal PDEs","authors":"Hao Zhang,&nbsp;Longxiang Jiang,&nbsp;Xinkun Chu,&nbsp;Yong Wen,&nbsp;Luxiong Li,&nbsp;Jianbo Liu,&nbsp;Yonghao Xiao,&nbsp;Liyuan Wang","doi":"10.1016/j.cpc.2024.109462","DOIUrl":"10.1016/j.cpc.2024.109462","url":null,"abstract":"<div><div>The great success of Physics-Informed Neural Network (PINN) in addressing partial differential equations (PDEs) has enhanced our ability to simulate and understand complex physical systems across various science and engineering disciplines. Despite their achievements, existing PINN-like methods often face limitations in scalability and are primarily effective within in-sample scenarios. To overcome these challenges, this work proposes a novel discrete approach termed Physics-Informed Graph Neural Network (PIGNN) to solve both forward and inverse problems associated with nonlinear PDEs. Our approach seamlessly integrates the strength of graph neural network (GNN), physical laws and finite difference method to approximate the solutions of physical systems. Through a series of comprehensive numerical experiments, we compare the performance of our PIGNN against the established PINN baseline using three well-known nonlinear PDEs: the heat equation, the Burgers equation, and the FitzHugh-Nagumo equation. Experimental outcomes highlight the superior performance of our PIGNN in handling irregular meshes, long time steps, flexible spatial resolutions, and diverse initial and boundary conditions. These results also demonstrate the superiority of our approach in terms of accuracy, time extrapolability, generalizability and scalability. A key advantage of our approach lies in its exceptional adaptability: models initially trained on small, simplified domains exhibit robust fitting capabilities that can be seamlessly transferred to more complex, larger-scale scenarios.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"308 ","pages":"Article 109462"},"PeriodicalIF":7.2,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143162803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GRANDlib: A simulation pipeline for the Giant Radio Array for Neutrino Detection (GRAND)","authors":"","doi":"10.1016/j.cpc.2024.109461","DOIUrl":"10.1016/j.cpc.2024.109461","url":null,"abstract":"<div><div>The operation of upcoming ultra-high-energy cosmic-ray, gamma-ray, and neutrino radio-detection experiments, like the Giant Radio Array for Neutrino Detection (GRAND), poses significant computational challenges involving the production of numerous simulations of particle showers and their detection, and a high data throughput. <span>GRANDlib</span> is an open-source software tool designed to meet these challenges. Its primary goal is to perform end-to-end simulations of the detector operation, from the interaction of ultra-high-energy particles, through—by interfacing with external air-shower simulations—the ensuing particle shower development and its radio emission, to its detection by antenna arrays and its processing by data-acquisition systems. Additionally, <span>GRANDlib</span> manages the visualization, storage, and retrieval of experimental and simulated data. We present an overview of <span>GRANDlib</span> to serve as the basis of future GRAND analyses.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"308 ","pages":"Article 109461"},"PeriodicalIF":7.2,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143162062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PyLOM: A HPC open source reduced order model suite for fluid dynamics applications","authors":"Benet Eiximeno ,&nbsp;Arnau Miró ,&nbsp;Beka Begiashvili ,&nbsp;Eusebio Valero ,&nbsp;Ivette Rodriguez ,&nbsp;Oriol Lehmkhul","doi":"10.1016/j.cpc.2024.109459","DOIUrl":"10.1016/j.cpc.2024.109459","url":null,"abstract":"<div><div>This paper describes the numerical implementation in a high-performance computing environment of an open-source library for model order reduction in fluid dynamics. This library, called pyLOM, contains the algorithms of proper orthogonal decomposition (POD), dynamic mode decomposition (DMD) and spectral proper orthogonal decomposition (SPOD), as well as, efficient SVD and matrix-matrix multiplication, all of them tailored for supercomputers. The library is profiled in detail under the MareNostrum IV supercomputer. The bottleneck is found to be in the QR factorization, which has been solved by an efficient binary tree communications pattern. Strong and weak scalability benchmarks reveal that the serial part (i.e., the part of the code that cannot be parallelized) of these algorithms is under 10% for the strong scaling and under 0.7% for the weak scaling. Using pyLOM, a POD of a dataset containing <span><math><mn>1.14</mn><mo>×</mo><msup><mrow><mn>10</mn></mrow><mrow><mn>8</mn></mrow></msup></math></span> gridpoints and 1808 snapshots that takes 6.3Tb of memory can be computed in 81.08 seconds using 10368 CPUs. Additionally, the algorithms are validated using the datasets of a flow around a circular cylinder at <span><math><mi>R</mi><msub><mrow><mi>e</mi></mrow><mrow><mi>D</mi></mrow></msub><mo>=</mo><mn>100</mn></math></span> and <span><math><mi>R</mi><msub><mrow><mi>e</mi></mrow><mrow><mi>D</mi></mrow></msub><mo>=</mo><mn>1</mn><mo>×</mo><msup><mrow><mn>10</mn></mrow><mrow><mn>4</mn></mrow></msup></math></span>, as well as the flow in the Stanford diffuser at <span><math><mi>R</mi><msub><mrow><mi>e</mi></mrow><mrow><mi>h</mi></mrow></msub><mo>=</mo><mn>1</mn><mo>×</mo><msup><mrow><mn>10</mn></mrow><mrow><mn>4</mn></mrow></msup></math></span>.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"308 ","pages":"Article 109459"},"PeriodicalIF":7.2,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143162060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fourier transforms of time correlation functions using Hermite functions","authors":"Hui Li ,&nbsp;Shaojie Wang ,&nbsp;Youjun Zhang ,&nbsp;Martin T. Dove","doi":"10.1016/j.cpc.2024.109456","DOIUrl":"10.1016/j.cpc.2024.109456","url":null,"abstract":"<div><div>We present an alternative to standard Fourier transform methods in order to obtain the power spectrum from a time correlation function. Our approach involves fitting the correlation function with a sum of Hermite functions, and recombining these to obtain the power spectrum directly. Although Fourier transform methods have been used for many decades, our approach avoids some ambiguities and uncertainties that face the user, and also allow for a more flexible form of the power spectrum to be obtained. We present a few examples to show the quality of the method.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"308 ","pages":"Article 109456"},"PeriodicalIF":7.2,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143162061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"twoPhaseInterTrackFoam: An OpenFOAM module for arbitrary Lagrangian/Eulerian interface tracking with surfactants and subgrid-scale modeling","authors":"Moritz Schwarzmeier ,&nbsp;Suraj Raju ,&nbsp;Željko Tuković ,&nbsp;Mathis Fricke ,&nbsp;Dieter Bothe ,&nbsp;Tomislav Marić","doi":"10.1016/j.cpc.2024.109460","DOIUrl":"10.1016/j.cpc.2024.109460","url":null,"abstract":"<div><div>We provide an implementation of the unstructured Finite-Volume Arbitrary Lagrangian / Eulerian (ALE) Interface-Tracking method for simulating incompressible, immiscible two-phase flows as an OpenFOAM module. In addition to interface-tracking capabilities that include tracking of two fluid phases, an implementation of a Subgrid-Scale (SGS) modeling framework for increased accuracy when simulating sharp boundary layers is enclosed. The SGS modeling framework simplifies embedding subgrid-scale profiles into the unstructured Finite Volume discretization. Our design of the SGS model library significantly simplifies adding new SGS models and applying SGS modeling to Partial Differential Equations (PDEs) in OpenFOAM.</div></div><div><h3>Program summary</h3><div><em>Program title:</em> twoPhaseInterTrackFoam</div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/6b49wb7fvd.1</span><svg><path></path></svg></span></div><div><em>Developer's repository link:</em> <span><span>https://gitlab.com/interface-tracking/twophaseintertrackfoamrelease</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> GPLv3</div><div><em>Programming language:</em> C++</div><div><em>Nature of problem:</em> Two-phase flow problems involving surface-active agents (surfactants), variable surface tension force and very sharp boundary layers.</div><div><em>Solution method:</em> An OpenFOAM implementation of the Arbitrary Lagrangian / Eulerian Interface Tracking method.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"308 ","pages":"Article 109460"},"PeriodicalIF":7.2,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143162067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PolyPal: A parallel microscale virtual specimen generator","authors":"Younggak Shin ,&nbsp;Vichhika Moul ,&nbsp;Keonwook Kang ,&nbsp;Byeongchan Lee","doi":"10.1016/j.cpc.2024.109458","DOIUrl":"10.1016/j.cpc.2024.109458","url":null,"abstract":"&lt;div&gt;&lt;div&gt;We present an open source program, PolyPal, that can generate a polycrystalline virtual specimen in the micrometer scale for atomistic calculations and visualization. Unlike regular meshes or perfect lattices, atomic positions in polycrystalline materials need to be defined before calculations, and the capability of an atom-generation code is evaluated by the maximum size of the virtual specimen it can generate as well as by the efficiency of the necessary input-output process. Present atom-generation codes are implemented in a serial fashion, and the maximum size of the virtual specimen is limited by the on-board memory. Furthermore, it is difficult to handle a single position file with billions of atoms not only because it takes a long time to read in a row but also full domain decomposition takes hours. PolyPal addresses these challenges with a fully parallelized MPI input-output scheme that supports multiple export options on a Linux cluster. It has no limit in the system size with virtually perfect scalability. Additionally by controlling the size distribution and homogeneity of grains, the program can simulate different microstructures, as typically found in the bulk system or in thin-film samples, prepared with different fabrication processes. PolyPal will harness molecular dynamics codes in the coming age of the exascale computing.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Program summary&lt;/h3&gt;&lt;div&gt;&lt;em&gt;Program Title:&lt;/em&gt; PolyPal&lt;/div&gt;&lt;div&gt;&lt;em&gt;CPC Library link to program files:&lt;/em&gt; &lt;span&gt;&lt;span&gt;https://doi.org/10.17632/5cpbmrtzbr.1&lt;/span&gt;&lt;svg&gt;&lt;path&gt;&lt;/path&gt;&lt;/svg&gt;&lt;/span&gt;&lt;/div&gt;&lt;div&gt;&lt;em&gt;Developer's repository link:&lt;/em&gt; &lt;span&gt;&lt;span&gt;https://gitlab.com/GeonbuShin/polypal.git&lt;/span&gt;&lt;svg&gt;&lt;path&gt;&lt;/path&gt;&lt;/svg&gt;&lt;/span&gt;&lt;/div&gt;&lt;div&gt;&lt;em&gt;Licensing provisions:&lt;/em&gt; GPLv3&lt;/div&gt;&lt;div&gt;&lt;em&gt;Programming language:&lt;/em&gt; C++&lt;/div&gt;&lt;div&gt;&lt;em&gt;Nature of problem:&lt;/em&gt; There is no open source code capable of generating massive polycyrstalline microstructures that contain billions of atoms. Existing codes run in a single thread, and hence, have a system size limited by the memory resources. Also, a single input/output filestream is not appropriate for a system with a large amount of atoms as file reading and writing would take a prohibitively long time, working as a bottleneck.&lt;/div&gt;&lt;div&gt;&lt;em&gt;Solution method:&lt;/em&gt; PolyPal not only creates atomic structures in parallel but also writes positions to multiple files in parallel within the Message Passing Interface (MPI). The parallel computing feature not only enables access to micrometer-scale atomic systems but also accelerates the entire process from atomic generation to file generation. In this code, each subdomain is filled with atoms simultaneously according to the prescribed domain topology with inherent load balancing. The atomic structure is written out to multiple files in parallel; one structure file is generated for each domain assigned to the corresponding node of a computing cluster via MPI-IO, which drastically reduces the input","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"308 ","pages":"Article 109458"},"PeriodicalIF":7.2,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143162066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"HepLean: Digitalising high energy physics","authors":"Joseph Tooby-Smith","doi":"10.1016/j.cpc.2024.109457","DOIUrl":"10.1016/j.cpc.2024.109457","url":null,"abstract":"<div><div>We introduce HepLean, an open-source project to digitalise definitions, theorems, proofs, and calculations in high energy physics using the interactive theorem prover Lean 4. HepLean has the potential to benefit the high energy physics community in four ways: making it easier to find existing results, allowing the creation of new results using artificial intelligence and automated methods, allowing easy review of papers for mathematical correctness, and providing new ways to teach high energy physics. We will discuss these in detail. We will also demonstrate the digitalisation of three areas of high energy physics in HepLean: Cabibbo-Kobayashi-Maskawa matrices in flavour physics, local anomaly cancellation, and Higgs physics.</div></div><div><h3>Program summary</h3><div><em>Program title:</em> HepLean</div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/9m7rd69bjs.1</span><svg><path></path></svg></span></div><div><em>Developer's repository link:</em> <span><span>https://github.com/HEPLean/HepLean</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> Apache License, 2.0</div><div><em>Programming language:</em> Lean 4</div><div><em>Nature of problem:</em> Digitalising results from high energy physics in a way that a computer can read and understand.</div><div><em>Solution method:</em> Use the interactive theorem prover Lean 4 to create a repository of results from high energy physics.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"308 ","pages":"Article 109457"},"PeriodicalIF":7.2,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143162065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}