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相关论文: GRAPESPH: Cosmological SPH simulations with the sp…

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We present the multi-GPU realization of the StePS (Stereographically Projected Cosmological Simulations) algorithm with MPI-OpenMP-CUDA hybrid parallelization and nearly ideal scale-out to multiple compute nodes. Our new zoom-in…

宇宙学与河外天体物理 · 物理学 2019-03-22 Gábor Rácz , István Szapudi , László Dobos , István Csabai , Alexander S. Szalay

We describe a new algorithm for the integration of self-gravitating fluid systems using SPH method. We split the Hamiltonian of a self-gravitating fluid system to the gravitational potential and others (kinetic and internal energies) and…

天体物理仪器与方法 · 物理学 2015-05-13 Takayuki R. Saitoh , Junichiro Makino

Cosmological simulations of structures and galaxies formations have played a fundamental role in the study of the origin, formation and evolution of the Universe. These studies improved enormously with the use of supercomputers and parallel…

天体物理学 · 物理学 2010-11-11 U. Becciani , V. Antonuccio , M. Comparato

We have invented a new algorithm to use with self-gravitating SPH Star Formation codes. The new method is designed to enable SPH simulations to self-regulate their numerical resolution, i.e. the number of SPH particles; the latter is…

天体物理学 · 物理学 2007-05-23 Spyridon Kitsionas

The complex structure of interplanetary magnetic fields and their variability, due to solar activity, make it necessary to compute the Cosmic Ray (CR) modulation with numerical simulations. COde for a Speedy Monte Carlo (MC) Involving Cuda…

计算物理 · 物理学 2025-02-11 Giovanni Cavallotto , Stefano Della Torre , Giuseppe La Vacca , Massimo Gervasi

We present pkdgrav3, a high-performance, fully parallel tree-SPH code designed for large-scale hydrodynamic simulations including self-gravity. Building upon the long development history of pkdgrav, the code combines an efficient…

地球与行星天体物理 · 物理学 2026-05-14 Thomas Meier , Douglas Potter , Christian Reinhardt , Joachim Stadel

We provide a description of the SNSPH code--a parallel 3-dimensional radiation hydrodynamics code implementing treecode gravity, smooth particle hydrodynamics, and flux-limited diffusion transport schemes. We provide descriptions of the…

天体物理学 · 物理学 2009-11-13 C. L. Fryer , G. Rockefeller , M. S. Warren

Starting from the single graphics processing unit (GPU) version of the Smoothed Particle Hydrodynamics (SPH) code DualSPHysics, a multi-GPU SPH program is developed for free-surface flows. The approach is based on a spatial decomposition…

We present a practical guide to Smoothed Particle Hydrodynamics (\SPH) and its application to astrophysical problems. Although remarkably robust, \SPH\ must be used with care if the results are to be meaningful since the accuracy of \SPH\…

天体物理学 · 物理学 2007-05-23 T. J. Martin , F. R. Pearce , P. A. Thomas

Cosmological N-Body simulations are used for a variety of applications. Indeed progress in the study of large scale structures and galaxy formation would have been very limited without this tool. For nearly twenty years the limitations…

天体物理学 · 物理学 2010-05-07 J. S. Bagla , Nishikanta Khandai

I review the Marseille GRAPE systems and the N-body simulations done with them. I first describe briefly the available hardware and software, their possibilities and their limitations. I then describe work done on interacting galaxies and…

天体物理学 · 物理学 2009-10-30 E. Athanassoula

The formation of galaxies in hierarchical cosmogonies is studied using high resolution N-body plus SPH hydrodynamics simulations. The collapse of structure is followed self-consistently from Mpc scale filamentary structures to kpc scale…

天体物理学 · 物理学 2007-05-23 F J Summers

The Smoothed Particles Hydrodynamics (SPH) is a particle-based, meshfree, Lagrangian method used to simulate multidimensional fluids with arbitrary geometries, most commonly employed in astrophysics, cosmology, and computational…

计算工程、金融与科学 · 计算机科学 2022-12-21 Aurélien Cavelan , Rubén M. Cabezón , Michal Grabarczyk , Florina M. Ciorba

We test and improve the numerical schemes in our smoothed particle hydrodynamics (SPH) code for cosmological simulations, including the pressure-entropy formulation (PESPH), a time-dependent artificial viscosity, a refined timestep…

The spherical harmonic transform is a powerful tool in the analysis of spherical data sets, such as the cosmic microwave background data. In this work, we present a new scheme for the spherical harmonic transforms that supports both CPU and…

天体物理仪器与方法 · 物理学 2022-11-18 Chi Tian , Siyu Li , Hao Liu

Period estimation is an important task in the classification of many variable astrophysical objects. Here we present GRAPE: Genetic Routine for Astronomical Period Estimation, a genetic algorithm optimised for the processing of survey data…

天体物理仪器与方法 · 物理学 2018-07-19 Paul R. McWhirter , Iain A. Steele , Abir Hussain , Dhiya Al-Jumeily , Marley M. B. R. Vellasco

Numerical methods have become a powerful tool for research in astrophysics, but their utility depends critically on the availability of suitable simulation codes. This calls for continuous efforts in code development, which is necessitated…

天体物理仪器与方法 · 物理学 2021-08-19 Volker Springel , Rüdiger Pakmor , Oliver Zier , Martin Reinecke

We present and test a general-purpose code, called PPASPH, for evolving self-gravitating fluids in astrophysics, both with and without a collisionless component. In PPASPH, hydrodynamical properties are computed by using the SPH (Smoothed…

天体物理学 · 物理学 2009-10-28 Arturo Serna , Jean-Michel Alimi , Jean-Pierre Chieze

Cosmological field-level inference requires differentiable forward models that solve the challenging dynamics of gas and dark matter under hydrodynamics and gravity. We propose a hybrid approach where gravitational forces are computed using…

宇宙学与河外天体物理 · 物理学 2025-10-31 Arne Thomsen , Tilman Tröster , François Lanusse

We present results from a series of cosmological SPH (smoothed particle hydrodynamics) simulations coupled with the P3M (Particle-Particle-Particle-Mesh) solver for the gravitational force. The simulations are designed to predict the…

天体物理学 · 物理学 2009-10-31 Kohji Yoshikawa , Y. P. Jing , Yasushi Suto