GADGET

GADGET: a code for collisionless and gasdynamical cosmological simulations. We describe the newly written code GADGET which is suitable both for cosmological simulations of structure formation and for the simulation of interacting galaxies. GADGET evolves self-gravitating collisionless fluids with the traditional N-body approach, and a collisional gas by smoothed particle hydrodynamics. Along with the serial version of the code, we discuss a parallel version that has been designed to run on massively parallel supercomputers with distributed memory. While both versions use a tree algorithm to compute gravitational forces, the serial version of GADGET can optionally employ the special-purpose hardware GRAPE instead of the tree. Periodic boundary conditions are supported by means of an Ewald summation technique. The code uses individual and adaptive timesteps for all particles, and it combines this with a scheme for dynamic tree updates. Due to its Lagrangian nature, GADGET thus allows a very large dynamic range to be bridged, both in space and time. So far, GADGET has been successfully used to run simulations with up to 7.5×107 particles, including cosmological studies of large-scale structure formation, high-resolution simulations of the formation of clusters of galaxies, as well as workstation-sized problems of interacting galaxies. In this study, we detail the numerical algorithms employed, and show various tests of the code. We publicly release both the serial and the massively parallel version of the code.


References in zbMATH (referenced in 72 articles )

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  1. Hernández-Aguayo, César; Ruan, Cheng-Zong; Li, Baojiu; Arnold, Christian; Baugh, Carlton M.; Klypin, Anatoly; Prada, Francisco: Fast full (N)-body simulations of generic modified gravity: derivative coupling models (2022)
  2. Long, Sifan; Fan, Xiaokang; Li, Chao; Liu, Yi; Fan, Sijiang; Guo, Xiao-Wei; Yang, Canqun: VecDualSPHysics: a vectorized implementation of smoothed particle hydrodynamics method for simulating fluid flows on multi-core processors (2022)
  3. Zhang, Chi; Zhu, Yujie; Lyu, Xiuxiu; Hu, Xiangyu: An efficient and generalized solid boundary condition for SPH: applications to multi-phase flow and fluid-structure interaction (2022)
  4. Chen, Joe Zhiyu; Upadhye, Amol; Wong, Yvonne Y. Y.: The cosmic neutrino background as a collection of fluids in large-scale structure simulations (2021)
  5. Moradinezhad Dizgah, Azadeh; Biagetti, Matteo; Sefusatti, Emiliano; Desjacques, Vincent; Noreña, Jorge: Primordial non-Gaussianity from biased tracers: likelihood analysis of real-space power spectrum and bispectrum (2021)
  6. Ramachandran, Prabhu; Bhosale, Aditya; Puri, Kunal; Negi, Pawan; Muta, Abhinav; Dinesh, A.; Menon, Dileep; Govind, Rahul; Sanka, Suraj; Sebastian, Amal S.; Sen, Ananyo; Kaushik, Rohan; Kumar, Anshuman; Kurapati, Vikas; Patil, Mrinalgouda; Tavker, Deep; Pandey, Pankaj; Kaushik, Chandrashekhar; Dutt, Arkopal; Agarwal, Arpit: PySPH: a Python-based framework for smoothed particle hydrodynamics (2021)
  7. Schlottke-Lakemper, Michael; Winters, Andrew R.; Ranocha, Hendrik; Gassner, Gregor J.: A purely hyperbolic discontinuous Galerkin approach for self-gravitating gas dynamics (2021)
  8. Schmidt, Fabian: Sigma-eight at the percent level: the EFT likelihood in real space (2021)
  9. Schmidt, Fabian: An (n)-th order Lagrangian forward model for large-scale structure (2021)
  10. Eckmann, Jean-Pierre; Hassani, Farbod: The detection of relativistic corrections in cosmological (N)-body simulations (2020)
  11. Schmidt, Fabian; Cabass, Giovanni; Jasche, Jens; Lavaux, Guilhem: \textitUnbiasedcosmology inference from biased tracers using the EFT likelihood (2020)
  12. Zhang, Chi; Rezavand, Massoud; Hu, Xiangyu: Dual-criteria time stepping for weakly compressible smoothed particle hydrodynamics (2020)
  13. Dakin, Jeppe; Brandbyge, Jacob; Hannestad, Steen; Haugbølle, Troels; Tram, Thomas: (\nu)CO(N)CEPT: cosmological neutrino simulations from the non-linear Boltzmann hierarchy (2019)
  14. Dakin, Jeppe; Hannestad, Steen; Tram, Thomas; Knabenhans, Mischa; Stadel, Joachim: Dark energy perturbations in (N)-body simulations (2019)
  15. de Mattia, Arnaud; Ruhlmann-Kleider, Vanina: Integral constraints in spectroscopic surveys (2019)
  16. Fair, Rebecca; Guo, Xiaohu; Cui, Tao: Particle sorting for the projection based particle method (2019)
  17. Huang, C.; Long, T.; Li, S. M.; Liu, M. B.: A kernel gradient-free SPH method with iterative particle shifting technology for modeling low-Reynolds flows around airfoils (2019)
  18. Ji, Zhe; Fu, Lin; Hu, Xiangyu Y.; Adams, Nikolaus A.: A new multi-resolution parallel framework for SPH (2019)
  19. Moutsanidis, Georgios; Kamensky, David; Zhang, Duan Z.; Bazilevs, Yuri; Long, Christopher C.: Modeling strong discontinuities in the material point method using a single velocity field (2019)
  20. Reverberi, Lorenzo; Daverio, David: \textttfRevolution-- relativistic cosmological simulations in (f(R)) gravity. I: Methodology (2019)

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