BibTeX

@article{2311.18017v1,
Author        = {Nicolas Payot and Pablo Lemos and Laurence Perreault-Levasseur and Carolina Cuesta-Lazaro and Chirag Modi and Yashar Hezaveh},
Title         = {Learning an Effective Evolution Equation for Particle-Mesh Simulations
  Across Cosmologies},
Eprint        = {2311.18017v1},
ArchivePrefix = {arXiv},
PrimaryClass  = {astro-ph.CO},
Abstract      = {Particle-mesh simulations trade small-scale accuracy for speed compared to
traditional, computationally expensive N-body codes in cosmological
simulations. In this work, we show how a data-driven model could be used to
learn an effective evolution equation for the particles, by correcting the
errors of the particle-mesh potential incurred on small scales during
simulations. We find that our learnt correction yields evolution equations that
generalize well to new, unseen initial conditions and cosmologies. We further
demonstrate that the resulting corrected maps can be used in a simulation-based
inference framework to yield an unbiased inference of cosmological parameters.
The model, a network implemented in Fourier space, is exclusively trained on
the particle positions and velocities.},
Year          = {2023},
Month         = {Nov},
Url           = {http://arxiv.org/abs/2311.18017v1},
File          = {2311.18017v1.pdf}
}