An efficient hybrid method to produce high resolution large volume dark matter simulations for semi-analytic models of reionisation
Yisheng Qiu, Simon J. Mutch, Pascal J. Elahi, Rhys J. J. Poulton,, Chris Power, J. Stuart B. Wyithe

TL;DR
This paper introduces a hybrid Monte Carlo method to extend the mass resolution of large volume N-body simulations, enabling more accurate semi-analytic models of cosmic reionisation by resolving faint galaxies.
Contribution
The authors develop a novel Monte Carlo algorithm to enhance mass resolution and evolve halo positions, producing large-volume halo catalogues that improve reionisation modeling accuracy.
Findings
Halo mass function matches high-resolution simulations
Consistent two-point correlation functions with analytic predictions
Improved predictions of stellar mass functions and neutral fractions
Abstract
Resolving faint galaxies in large volumes is critical for accurate cosmic reionisation simulations. While less demanding than hydrodynamical simulations, semi-analytic reionisation models still require very large N-body simulations in order to resolve the atomic cooling limit across the whole reionisation history within box sizes . To facilitate this, we extend the mass resolution of N-body simulations using a Monte Carlo algorithm. We also propose a method to evolve positions of Monte Carlo halos, which can be an input for semi-analytic reionisation models. To illustrate, we present an extended halo catalogue that reaches a mass resolution of in a box, equivalent to an N-body simulation with particles. The resulting halo mass function agrees with smaller…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
