![]() This flurry of development going back to gadget-3, combined with the lack of a comprehensive description of this particular version in the literature, now makes it actually hard to precisely define what one means when referring to gadget-3. 2018), ax-gadget (Nori & Baldi 2018), mp-gadget (Huang et al. 2012), mg-gadget (Puchwein, Baldi & Springel 2013), gizmo (Hopkins 2015), ketju (Rantala et al. 2008a), has been used for a large amount of simulation work, and has also been the basis for the development of numerous modified codes spawned from it, such as arepo (Springel 2010a Weinberger, Springel & Pakmor 2020), l-gadget-3 (Angulo et al. The last extensive description of the code in the literature has been given for gadget-2 (Springel 2005), even though the newer version, gadget-3, first written for the Aquarius project (Springel et al. ![]() In this spirit, we here discuss a major update of the gadget code (Springel, Yoshida & White 2001), which has seen wide-spread use in structure formation and galaxy formation over the past two decades. Modern astrophysical codes have also grown in complexity to a point where single person efforts, which traditionally have often been the mode of creation of new codes, become increasingly more difficult, and thus are best replaced by more open, team-driven development models. In fact, it can well be argued that efforts in this direction need to be stepped up further, otherwise the rapidly growing power of modern high performance computing facilities cannot be used in full for future astrophysical research. At the same time, it is clear that code development needs to continue to improve the accuracy and physical fidelity of the modelling techniques. Sharing such codes publicly within the community has accelerated the widespread adoption of numerical techniques and lowered the entry barrier for new researchers or research groups entering the field. Consequently, substantial work has been invested in developing efficient numerical methods and appropriate codes to model cosmic structure formation. This powerful technique has become an important pillar in astrophysical research, decisively shaping our understanding of the coupled dynamics of dark matter and baryonic physics (see Naab & Ostriker 2017 Vogelsberger et al. 1985 Navarro, Frenk & White 1997 Jenkins et al. Numerical simulations allow detailed studies of non-linear structure formation and connect the simple high-redshift Universe with the complex structure we see around us today (Efstathiou et al. Methods: numerical, galaxies: interactions, dark matter 1 INTRODUCTION The gadget-4 code is publicly released to the community and contains infrastructure for on-the-fly group and substructure finding and tracking, as well as merger tree building, a simple model for radiative cooling and star formation, a high dynamic range power spectrum estimator, and an initial condition generator based on second-order Lagrangian perturbation theory. The code is able to cope with very large problem sizes, thus allowing accurate predictions for cosmic structure formation in support of future precision tests of cosmology, and at the same time is well adapted to high dynamic range zoom-calculations with extreme variability of the particle number density in the simulated volume. Two different flavours of smoothed particle hydrodynamics, a classic entropy-conserving formulation and a pressure-based approach, are supported for dealing with gaseous flows. A manifestly momentum conserving fast multipole method (FMM) can be employed as an alternative to the one-sided TreePM gravity solver introduced in earlier versions. ![]() The new version offers improvements in force accuracy, in time-stepping, in adaptivity to a large dynamic range in time-scales, in computational efficiency, and in parallel scalability through a special MPI/shared-memory parallelization and communication strategy, and a more-sophisticated domain decomposition algorithm. Here, we discuss recent methodological progress in the gadget code, which has been widely applied in cosmic structure formation over the past two decades. This calls for continuous efforts in code development, which is necessitated also by the rapidly evolving technology underlying today’s computing hardware. Numerical methods have become a powerful tool for research in astrophysics, but their utility depends critically on the availability of suitable simulation codes.
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