2015/03/31 by Aurel Schneider, Romain Teyssier, Doug Potter +7 · 3 citations
Physics and Astronomy · #Accuracy and precision #Astronomy and Astrophysical Research #Bispectrum #Discretization #Galaxies: Formation, Evolution, Phenomena #Matter power spectrum #Nonlinear system #Observational error #Perturbation theory (quantum mechanics) #Radio Astronomy Observations and Technology #Range (aeronautics) #Spectral density #astro-ph.CO
paper · pdf · doi:10.1088/1475-7516/2016/04/047
matches published version
arxiv created 2016/04/25 · openalex publication_date 2016/04/26 · arxiv updated 2016/05/04 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05
Future galaxy surveys require one percent precision in the theoretical knowledge of the power spectrum over a large range including very nonlinear scales. While this level of accuracy is easily obtained in the linear regime with perturbation theory, it represents a serious challenge for small scales where numerical simulations are required. In this paper we quantify the precision of present-day N -body methods, identifying main potential error sources from the set-up of initial conditions to the measurement of the final power spectrum. We directly compare three widely used N -body codes, Ramses , Pkdgrav3 , and Gadget3 which represent three main discretisation techniques: the particle-mesh method, the tree method, and a hybrid combination of the two. For standard run parameters, the codes agree to within one percent at k ⩽1 h Mpc −1 and to within three percent at k ⩽10 h Mpc −1 . We also consider the bispectrum and show that the reduced bispectra agree at the sub-percent level for k ⩽ 2 h Mpc −1 . In a second step, we quantify potential errors due to initial conditions, box size, and resolution using an extended suite of simulations performed with our fastest code Pkdgrav3 . We demonstrate that the simulation box size should not be smaller than L =0.5 h −1 Gpc to avoid systematic finite-volume effects (while much larger boxes are required to beat down the statistical sample variance). Furthermore, a maximum particle mass of M p =10 9 h −1 M ⊙ is required to conservatively obtain one percent precision of the matter power spectrum. As a consequence, numerical simulations covering large survey volumes of upcoming missions such as DES , LSST , and Euclid will need more than a trillion particles to reproduce clustering properties at the targeted accuracy.