2011

Multi-scale initial conditions for cosmological simulations

Hahn, Oliver, Abel, Tom

Understand

We discuss a new algorithm to generate multi-scale initial conditions with multiple levels of refinements for cosmological "zoom-in" simulations.

The method uses an adaptive convolution of Gaussian white noise with a real space transfer function kernel together with an adaptive multi-grid Poisson solver to generate displacements and velocities following first (1LPT) or second order Lagrangian perturbation theory (2LPT).
The new algorithm achieves RMS relative errors of order 10^(-4) for displacements and velocities in the refinement region and thus improves in terms of errors by about two orders of magnitude over previous approaches.
In addition, errors are localized at coarse-fine boundaries and do not suffer from Fourier-space induced interference ringing.

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