swMATH ID: 41555
Software Authors: Cullan Howlett, Marc Manera, Will J. Percival
Description: L-PICOLA: A parallel code for fast dark matter simulation. Robust measurements based on current large-scale structure surveys require precise knowledge of statistical and systematic errors. This can be obtained from large numbers of realistic mock galaxy catalogues that mimic the observed distribution of galaxies within the survey volume. To this end we present a fast, distributed-memory, planar-parallel code, L-PICOLA, which can be used to generate and evolve a set of initial conditions into a dark matter field much faster than a full non-linear N-Body simulation. Additionally, L-PICOLA has the ability to include primordial non-Gaussianity in the simulation and simulate the past lightcone at run-time, with optional replication of the simulation volume. Through comparisons to fully non-linear N-Body simulations we find that our code can reproduce the z=0 power spectrum and reduced bispectrum of dark matter to within 2
Homepage: https://cullanhowlett.github.io/l-picola/
Source Code:  https://github.com/CullanHowlett/l-picola
Related Software: Python; ECOSMOG; 2HOT; GreeM; TreePM; GADGET; SciPy; FAST-PT; CAMB; GetDist; emcee; Matplotlib; NumPy; nbodykit; RAMSES
Cited in: 3 Publications

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