Computer Physics Communications最新文献

{"title":"An algorithm for automated extraction of resonance parameters from the stabilization method","authors":"Johanna Langner , Anjan Sadhukhan , Jayanta K. Saha , Henryk A. Witek","doi":"10.1016/j.cpc.2025.109815","DOIUrl":"10.1016/j.cpc.2025.109815","url":null,"abstract":"<div><div>The application of the stabilization method (Hazi and Taylor, 1970 [1]) to extract accurate energy and lifetimes of resonance states is challenging: The process requires labor-intensive numerical manipulation of a large number of eigenvalues of a parameter-dependent Hamiltonian matrix, followed by a fitting procedure. In this article, we present <span>ReSMax</span>, an efficient algorithm implemented as an open-access <span>Python</span> code, which offers full automation of the stabilization diagram analysis in a user-friendly environment while maintaining high numerical precision of the computed resonance characteristics. As a test case, we use <span>ReSMax</span> to analyze the natural parity doubly-excited resonance states (<span><math><mmultiscripts><mrow><mtext>S</mtext></mrow><none></none><mrow><mtext>e</mtext></mrow><mprescripts></mprescripts><none></none><mrow><mn>1</mn></mrow></mmultiscripts></math></span>, <span><math><mmultiscripts><mrow><mtext>S</mtext></mrow><none></none><mrow><mtext>e</mtext></mrow><mprescripts></mprescripts><none></none><mrow><mn>3</mn></mrow></mmultiscripts></math></span>, <span><math><mmultiscripts><mrow><mtext>P</mtext></mrow><none></none><mrow><mtext>o</mtext></mrow><mprescripts></mprescripts><none></none><mrow><mn>1</mn></mrow></mmultiscripts></math></span>, and <span><math><mmultiscripts><mrow><mtext>P</mtext></mrow><none></none><mrow><mtext>o</mtext></mrow><mprescripts></mprescripts><none></none><mrow><mn>3</mn></mrow></mmultiscripts></math></span>) of helium, demonstrating the accuracy and efficiency of the developed methodology. The presented algorithm is applicable to a wide range of resonances in atomic, molecular, and nuclear systems.</div></div><div><h3>Program summary</h3><div><em>Program Title:</em> <span>ReSMax</span></div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/8yny7jycgz.1</span><svg><path></path></svg></span></div><div><em>Developer's repository link:</em> <span><span>https://github.com/giogina/ReSMax</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> MIT</div><div><em>Programming language:</em> Python</div><div><em>Nature of problem:</em> The stabilization method is a widely used indirect approach for identifying resonance states (RSs) in atomic and molecular systems. It analyzes the behavior of energy eigenvalues of the system's Hamiltonian as a function of a basis set parameter, as visualized in stabilization diagrams (SDs) [1]. Resonance states manifest as plateaus in these SDs and are characterized by the position and width of the associated Lorentzian peaks in the density of states (DOS) [2]. However, applying this method in practice remains labor-intensive and error-prone: analyzing large eigenvalue datasets, identifying plateau regions, and fitting DOS peaks manually requires significant effort and expert judgment. These difficulties limit the method's scalability and reproducibility, especially for syste","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109815"},"PeriodicalIF":3.4,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144879305","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":"Faster and objective level set-DEM mechanical simulations of discrete systems with convex particles from contact history and particle surface considerations","authors":"Jérôme Duriez ,&nbsp;Cédric Galusinski","doi":"10.1016/j.cpc.2025.109803","DOIUrl":"10.1016/j.cpc.2025.109803","url":null,"abstract":"<div><div>Aiming for versatile simulations of the mechanics of discrete systems with arbitrary convex particles, an extended Level Set (LS) description of particle shape is proposed in the framework of the Discrete Element Method (DEM). The LS shape description as a discrete field of the signed distance function is first obtained with a faster initial generation and then proposed to directly output particle surface in a validated workflow. It mostly includes an innovative optimization for the surface nodes discretization which combines with the LS distance field for DEM contact treatment. In their optimized definition, surface nodes locate in a nearly uniform fashion over a particle and are handled in a sparse manner during contact treatment, thanks to an original consideration of contact history. As such, computation speed gains are reported with a factor of more than 3 during simulations of quasi-static mechanical loading. The proposed nodes definition is also shown to be instrumental to insure objectivity of the LS contact model and DEM simulations. The present LS approach is finally applied to a preliminary study of the residual shear strength of various packings made of superquadrics all sharing the same shape. After a justification of the chosen particle number to form a Representative Elementary Volume, the shear strength is shown to lack a clear relationship with Wadell's true sphericity as a shape index, while being possibly 73% higher than the one obtained with spherical particles.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109803"},"PeriodicalIF":3.4,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144867334","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":"HTEM: High-throughput toolkit for elasticity modeling","authors":"Zhen Yang ,&nbsp;Jiawei Xian ,&nbsp;Yuanji Xu ,&nbsp;De-Ye Lin ,&nbsp;Qingchun Wang ,&nbsp;Xingyu Gao ,&nbsp;Fuyang Tian ,&nbsp;Haifeng Song","doi":"10.1016/j.cpc.2025.109814","DOIUrl":"10.1016/j.cpc.2025.109814","url":null,"abstract":"<div><div>Elasticity under varying temperatures and pressures is particularly significant for understanding mechanical properties and structural phase transitions. Consequently, there is an increasing demand for tools capable of determining elasticity across wide temperature and pressure ranges, either numerically or analytically. In this work, we propose HTEM, a comprehensive toolkit that automates input generation workflow, elastic calculations, modeling, and visualization within an integrated framework to solve the demand for elasticity across wide temperature and pressure ranges. HTEM performs simulations with four computational modes, allowing users to balance accuracy and efficiency. It incorporates a semi-analytic model for robust, high-precision elastic modeling with finite data combinations, even using sparse elasticity at high temperatures. To validate the algorithm and workflows for calculation and modeling, we performed HTEM to study the elasticity of Si across wide temperature and pressure ranges. The results show the high precision and high efficiency of HTEM. And modeling mitigates noise from constant pressure ensemble simulations. Furthermore, HTEM provides detailed visualizations of the elasticity and anisotropy as functions of temperature and pressure, providing a comprehensive insight into how the intrinsic properties of materials evolve under varying conditions.</div></div><div><h3>Program summary</h3><div><em>Program title:</em> HTEM</div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/8sfnsdvxyn.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.X (version &gt; 3.7)</div><div><em>External routines/libraries:</em> Numpy, Scipy, Matplotlib, Ase, Spglib, Imageio</div><div><em>Nature of problem:</em> Through the coupling of toolkit with the first-principle approaches, the temperature and pressure dependent second-order elastic stiffness coefficients (SOESC) and elastic moduli of solid materials can be calculated and modeled with less cost, and the change of elastic and mechanical properties can be dynamically visualized with temperature and pressure.</div><div><em>Solution method:</em> HTEM contains four simulation modes to obtain elasticity with high-throughput. The cold and QSA modes are based on VASP's <em>ab</em> <span><math><mi>i</mi><mi>n</mi><mi>i</mi><mi>t</mi><mi>i</mi><mi>o</mi></math></span> calculations. NVT and NPT modes correspond to VASP's <em>ab</em> <span><math><mi>i</mi><mi>n</mi><mi>i</mi><mi>t</mi><mi>i</mi><mi>o</mi></math></span> molecular dynamics (AIMD) simulations. Here, the cold mode is for zero-temperature calculations, while the QSA, NVT, and NPT modes are used to calculate the finite-temperature elasticity. This program is versatile for calculating SOESCs at various temperatures and pressures. In addition to the calculated SOESCs and elastic moduli based o","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109814"},"PeriodicalIF":3.4,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144867335","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":"DiPolMol-Py: A Python package for calculations for 2Σ ground-state molecules","authors":"Bethan Humphreys,&nbsp;Alex J. Matthies,&nbsp;Hannah J. Williams","doi":"10.1016/j.cpc.2025.109813","DOIUrl":"10.1016/j.cpc.2025.109813","url":null,"abstract":"<div><div>We present the python package DiPolMol-Py, which can be used to calculate the rotational and hyperfine structure of <span><math><mmultiscripts><mrow><mi>Σ</mi></mrow><mprescripts></mprescripts><none></none><mrow><mn>2</mn></mrow></mmultiscripts></math></span> molecules. The calculations can be performed in the presence of dc magnetic fields, dc electric fields and far off-resonant optical fields. We additionally include functions to calculate the polarisability of the molecule and the transition dipole moment between different energy eigenstates. The package is applicable to many of the molecules which can be laser cooled, specifically the alkaline earth fluorides. We provide a constants file which includes many of the required literature values for ⁴⁰CaF, ⁸⁸SrF and ¹³⁸BaF. Additional species can easily be added by updating this file.</div></div><div><h3>Program summary</h3><div><em>Program Title:</em> DiPolMol-Py</div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/36gp2kd4jj.1</span><svg><path></path></svg></span></div><div><em>Developer's repository link:</em> <span><span>https://github.com/durham-qlm/DiPolMol</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> BSD 3-clause</div><div><em>Programming language:</em> Python ≥3.11</div><div><em>Nature of problem:</em> Calculating the rotational and hyperfine structure for <span><math><mmultiscripts><mrow><mi>Σ</mi></mrow><mprescripts></mprescripts><none></none><mrow><mn>2</mn></mrow></mmultiscripts></math></span> ground state molecules both field free and in the presence of dc magnetic, electric and off-resonant light fields.</div><div><em>Solution method:</em> A Python package which calculates the eigenenergies and eigenvalues via diagonalization of the Hamiltonian.</div><div><em>Additional comments including restrictions and unusual features:</em> This package is based on previous work for <span><math><mmultiscripts><mrow><mi>Σ</mi></mrow><mprescripts></mprescripts><none></none><mrow><mn>1</mn></mrow></mmultiscripts></math></span> molecules [1]. External magnetic and electric fields must be coaxial.</div></div><div><h3>References</h3><div><ul><li><span>[1]</span><span><div>J.A. Blackmore, P.D. Gregory, J.M. Hutson, S.L. Cornish, Comput. Phys. Commun. 282 (2023) 108512, <span><span>https://doi.org/10.1016/j.cpc.2022.108512</span><svg><path></path></svg></span>.</div></span></li></ul></div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109813"},"PeriodicalIF":3.4,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144867184","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":"Efficient cosmic ray generator for particle detector simulations","authors":"David Díez-Ibáñez,&nbsp;Luis Obis","doi":"10.1016/j.cpc.2025.109805","DOIUrl":"10.1016/j.cpc.2025.109805","url":null,"abstract":"<div><div>Traditional cosmic ray simulations commonly employ the Monte Carlo method to randomize the energy and direction of each simulated particle, often employing simplified or uncorrelated distributions. The flux of cosmic rays is modelled as incident particles originating from a plane above the object of interest (e.g., detectors in particle physics or surfaces in dosimetry studies) with experimentally determined angular and energy distributions. This strategy is highly inefficient because a significant number of particles never intersect the detector. This paper proposes a refined Monte Carlo method to generate a sample of events that intersect the target volume, ensuring their angular distribution matches that of the conventional approach. It is based on the projection of a sphere containing the target volume onto a plane tangent to it at a fixed angle; this is termed the <em>Probability Distribution Projection</em> (PDP) method. This configuration allows computation of the probability that a cosmic particle hits the sphere at this incoming angle, with this probability being proportional to the area of the corresponding section of a cylinder. The performance of this method demonstrates enhanced computational speed while yielding identical physical results. It has been implemented within the REST-for-Physics framework and tested using the geometry of a real detector, the IAXO-D0 Micromegas X-ray detector for the future axion helioscope BabyIAXO. The proposed method achieves a 37-fold improvement in efficiency compared to the traditional Monte Carlo scheme for the same accuracy, and is particularly advantageous when the target volume deviates from a spherical shape.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"317 ","pages":"Article 109805"},"PeriodicalIF":3.4,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144895991","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":"PrecisionLauricella: Package for numerical computation of Lauricella functions depending on a parameter","authors":"M.A. Bezuglov ,&nbsp;B.A. Kniehl ,&nbsp;A.I. Onishchenko ,&nbsp;O.L. Veretin","doi":"10.1016/j.cpc.2025.109812","DOIUrl":"10.1016/j.cpc.2025.109812","url":null,"abstract":"&lt;div&gt;&lt;div&gt;We introduce the &lt;span&gt;PrecisionLauricella&lt;/span&gt; package, a computational tool developed in Wolfram Mathematica for high-precision numerical evaluations of the Laurent expansion coefficients of Lauricella functions whose parameters depend linearly on a small regulator, &lt;em&gt;ε&lt;/em&gt;. In practical multi-loop calculations, Lauricella functions are required only as series around &lt;span&gt;&lt;math&gt;&lt;mi&gt;ε&lt;/mi&gt;&lt;mo&gt;=&lt;/mo&gt;&lt;mn&gt;0&lt;/mn&gt;&lt;/math&gt;&lt;/span&gt;, and &lt;span&gt;PrecisionLauricella&lt;/span&gt; is designed specifically to deliver such coefficients with arbitrary precision. The package leverages a method based on analytic continuation via Frobenius generalized power series, providing an efficient and accurate alternative to conventional approaches relying on multi-dimensional series expansions or Mellin–Barnes representations. This one-dimensional approach is particularly advantageous for high-precision calculations and facilitates further optimization through &lt;em&gt;ε&lt;/em&gt;-dependent reconstruction from evaluations at specific numerical values, enabling efficient parallelization. The underlying mathematical framework for this method has been detailed in our previous work, while the current paper focuses on the design, implementation, and practical applications of the &lt;span&gt;PrecisionLauricella&lt;/span&gt; package.&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; PrecisionLauricella&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/10.17632/6f958yz2dr.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://bitbucket.org/BezuglovMaxim/precisionlauricella-package/src/main/&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; Wolfram Mathematica&lt;/div&gt;&lt;div&gt;&lt;em&gt;Supplementary material:&lt;/em&gt; PrecisionLauricella_Examples.nb&lt;/div&gt;&lt;div&gt;&lt;em&gt;Nature of problem:&lt;/em&gt; Lauricella functions, generalizations of hypergeometric functions, appearing in physics and mathematics, including Feynman integrals and string theory. When their indices depend linearly on a small parameter &lt;em&gt;ε&lt;/em&gt;, their numerical evaluation becomes challenging due to the complexity of high-dimensional series and singularities. Traditional methods, like hypergeometric re-expansion or Mellin–Barnes integrals, often lack efficiency and precision.&lt;/div&gt;&lt;div&gt;Managing multi-dimensional sums exacerbates computational costs, especially for high-precision requirements, making these approaches unsuitable for many practical applications. Thus, there is a pressing need for efficient, scalable methods capable of maintaining numerical accuracy and effectively handling parameter dependencies.&lt;/div&gt;&lt;div&gt;&lt;em&gt;Solution method:&lt;/em&gt; Our method uses the Frobenius approach to achieve analytic continuations of Lauricella functions through generalized power series. Representing the functions as one-dimensional series simplifies high-precision numerical evaluations compa","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109812"},"PeriodicalIF":3.4,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144830691","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":"Classical bounds on two-outcome bipartite Bell expressions and linear prepare-and-measure witnesses: Efficient computation in parallel environments such as graphics processing units","authors":"István Márton ,&nbsp;Erika Bene ,&nbsp;Péter Diviánszky ,&nbsp;Gábor Drótos","doi":"10.1016/j.cpc.2025.109809","DOIUrl":"10.1016/j.cpc.2025.109809","url":null,"abstract":"<div><div>The presented program aims at speeding up the brute force computation of the so-called <span><math><msub><mrow><mi>L</mi></mrow><mrow><mi>d</mi></mrow></msub></math></span> norm of a matrix <em>M</em> using graphics processing units (GPUs). Alternatives for CPUs have also been implemented, and the algorithm is applicable to any parallel environment. The <span><math><mi>n</mi><mo>×</mo><mi>m</mi></math></span> matrix <em>M</em> has real elements which may represent coefficients of a bipartite Bell expression or those of a linear prepare-and-measure (PM) witness. In this interpretation, the <span><math><msub><mrow><mi>L</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span> norm is the local bound of the given correlation-type Bell expression, and the <span><math><msub><mrow><mi>L</mi></mrow><mrow><mi>d</mi></mrow></msub></math></span> norm for <span><math><mi>d</mi><mo>≥</mo><mn>2</mn></math></span> is the classical <em>d</em>-dimensional bound of the given PM witness, which is associated with the communication of <em>d</em>-level classical messages in the PM scenario. The program is also capable of calculating the local bound of Bell expressions including marginals. In all scenarios, the output is assumed to be binary.</div><div>The code for GPUs is written in CUDA C and can utilize one NVIDIA GPU in a computer. To illustrate the performance of our implementation, we refer to Brierley et al. <span><span>[1]</span></span> who needed approximately three weeks to compute the local bound on a Bell expression defined by a <span><math><mn>42</mn><mo>×</mo><mn>42</mn></math></span> matrix on a standard desktop using a single CPU core. In contrast, our efficient implementation of the brute force algorithm allows us to reduce this to three minutes using a single NVIDIA RTX 6000 Ada graphics card on a workstation. For CPUs, the algorithm was implemented with OpenMP and MPI according to the shared and distributed memory models, respectively, and achieves a comparable speedup at a number of CPU cores around 100.</div></div><div><h3>Program summary</h3><div><em>Program Title:</em> L_CUDA.cu, L_MPI.c, L_OpenMP.c</div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/scfjjt9svm.1</span><svg><path></path></svg></span></div><div><em>Developer's repository link:</em> <span><span>https://github.com/istvanmarton/L-norms_BruteForce</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> GPLv3</div><div><em>Programming language:</em> C, CUDA, OpenMP, MPI</div><div><em>Nature of problem:</em> The computational demand of determining the <span><math><msub><mrow><mi>L</mi></mrow><mrow><mi>d</mi></mrow></msub></math></span> norm of a matrix of real coefficients is high; exact <span><math><msub><mrow><mi>L</mi></mrow><mrow><mi>d</mi></mrow></msub></math></span> norms have been computed so far for relatively small matrices only. Besides that any exact algorithm appears to scale exponentially with the numbe","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109809"},"PeriodicalIF":3.4,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144830769","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":"Adaptive mesh refinement in semi-implicit particle-in-cell method","authors":"Talha Arshad,&nbsp;Yuxi Chen,&nbsp;Gábor Tóth","doi":"10.1016/j.cpc.2025.109806","DOIUrl":"10.1016/j.cpc.2025.109806","url":null,"abstract":"<div><div>The particle-in-cell (PIC) method is powerful for simulating plasma kinetic processes. However, PIC simulations are usually computationally expensive, and improving the computational efficiency is essential for expanding their capabilities. Adaptive mesh refinement (AMR) is an important technique that can be applied to accelerate PIC simulations. In this paper, we introduce a novel adaptive mesh refinement (AMR) algorithm that is implemented for a semi-implicit electromagnetic particle-in-cell (PIC) code. Our approach supports different refinement ratios as well as multiple refinement levels. The electric field solver is carefully designed to minimize artifacts at interfaces of different levels, and we introduce an algorithm to reduce errors in Gauss's law across all levels. To maintain a uniform particle distribution, which is crucial for achieving high computational efficiency, particle splitting and merging techniques are integrated into the code. We validate our algorithm with several tests, including a two-dimensional double current sheet reconnection test, that show accurate solutions on the AMR grid with considerable speed-up relative to a uniform high-resolution grid.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109806"},"PeriodicalIF":3.4,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144830689","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":"A pencil-distributed finite-difference solver for extreme-scale calculations of turbulent wall flows at high Reynolds number","authors":"Rafael Diez Sanhueza,&nbsp;Jurriaan Peeters,&nbsp;Pedro Costa","doi":"10.1016/j.cpc.2025.109811","DOIUrl":"10.1016/j.cpc.2025.109811","url":null,"abstract":"<div><div>We present a computational method for extreme-scale simulations of incompressible turbulent wall flows at high Reynolds numbers. The numerical algorithm extends a popular method for solving second-order finite differences Poisson/Helmholtz equations using a pencil-distributed parallel tridiagonal solver to improve computational performance at scale. The benefits of this approach were investigated for high-Reynolds-number turbulent channel flow simulations, with up to about 80 billion grid points and 1024 GPUs on the European flagship supercomputers Leonardo and LUMI. An additional GPU porting effort of the entire solver had to be undertaken for the latter. Our results confirm that, while 1D domain decompositions are favorable for smaller systems, they become inefficient or even impossible at large scales. This restriction is relaxed by adopting a pencil-distributed approach. The results show that, at scale, the revised Poisson solver is about twice as fast as the baseline approach with the full-transpose algorithm for 2D domain decompositions. Strong and weak scalability tests show that the performance gains are due to the lower communication footprint. Additionally, to secure high performance when solving for wall-normal implicit diffusion, we propose a reworked flavor of parallel cyclic reduction (PCR) that is split into pre-processing and runtime steps. During pre-processing, small sub-arrays with independent 1D coefficients are computed by parallel GPU threads, without any global GPU communication. Then, at runtime, the reworked PCR enables a fast solution of implicit 1D diffusion without computational overhead. Our results show that the entire numerical solver, coupled with the PCR algorithm, enables extreme-scale simulations with 2D pencil decompositions, which do not suffer performance losses even when compared to the best 1D slab configurations available for smaller systems.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109811"},"PeriodicalIF":3.4,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144830688","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":"SIREN: An open-source neutrino injection toolkit","authors":"Austin Schneider ,&nbsp;Nicholas W. Kamp ,&nbsp;Alex Y. Wen","doi":"10.1016/j.cpc.2025.109799","DOIUrl":"10.1016/j.cpc.2025.109799","url":null,"abstract":"<div><div>Modeling of rare neutrino processes often relies on either simple approximations or expensive detector simulations. The former is often not sufficient for interactions with complex morphologies, while the latter is too time-intensive for phenomenological studies. We present <span>SIREN</span> (Sampling and Injection for Rare EveNts), a new tool for neutrino phenomenology and experimental searches alike that enables accurate interaction and detector geometry modeling without the overhead of detailed detector response simulations. <span>SIREN</span> handles the injection of rare process final states and the associated weighting calculations with the speed needed for phenomenological investigations and the detail necessary for dedicated experimental searches. The extensible design of <span>SIREN</span> allows it to support a wide range of experimental designs and Beyond Standard Model neutrino interactions. Users need only specify the physical process, detector geometry, and initial neutrino flux under consideration before they can accurately simulate a model in their detector of choice. We demonstrate the capability of <span>SIREN</span> through two examples: (1) Standard Model <span><math><msub><mrow><mi>ν</mi></mrow><mrow><mi>μ</mi></mrow></msub></math></span> deep inelastic scattering in IceCube, DUNE, and ATLAS; and (2) heavy neutral lepton interactions in MiniBooNE, MINER<em>ν</em>A, and CCM. A variety of detector geometry descriptions, interaction cross sections, and neutrino fluxes are also provided for users to get started with immediately.</div></div><div><h3>Program summary</h3><div><em>Program Title:</em> <span>SIREN</span></div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/j8mftngm5m.1</span><svg><path></path></svg></span></div><div><em>Developer's repository link:</em> <span><span>https://github.com/Harvard-Neutrino/SIREN</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> GNU Lesser General Public License, v3</div><div><em>Programming Language:</em> <span>C++</span>17, <span>Python</span></div><div><em>External Routines:</em> <span><span>Boost</span><svg><path></path></svg></span>, <span><span>HDF5</span><svg><path></path></svg></span>, <span><span>pybind11</span><svg><path></path></svg></span>, <span><span>Photospline</span><svg><path></path></svg></span>, <span><span>SuiteSparse</span><svg><path></path></svg></span>, <span><span>DarkNews</span><svg><path></path></svg></span></div><div><em>Nature of problem:</em> Injection and reweighting of neutrinos and rare-processes across diverse experiments and models.</div><div><em>Solution method:</em> An extensible framework for injection and weighting of rare processes with detailed material and geometry modeling and built-in support for a variety of experiments and models.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109799"},"PeriodicalIF":3.4,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144867185","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}