Hybrid multi-fluid-particle simulations of the cosmic neutrino background
Joe Zhiyu Chen, Markus R. Mosbech, Amol Upadhye, Yvonne Y. Y. Wong

TL;DR
This paper introduces a multi-fluid hybrid simulation method for modeling cosmic neutrino clustering, improving accuracy and efficiency while preserving detailed momentum information, and demonstrating convergence with existing models.
Contribution
The paper presents a novel multi-fluid hybrid approach for simulating cosmic neutrinos, combining fluid and particle methods to enhance accuracy and computational efficiency.
Findings
Achieves <3% convergence in neutrino power spectrum at z=19.
Retains detailed neutrino momentum distribution information.
Compatible with existing simulations for neutrino fractions up to Ω_ν h^2=0.005.
Abstract
Simulation of the cosmic clustering of massive neutrinos is a daunting task, due both to their large velocity dispersion and to their weak clustering power becoming swamped by Poisson shot noise. We present a new approach, the multi-fluid hybrid-neutrino simulation, which partitions the neutrino population into multiple flows, each of which is characterised by its initial momentum and treated as a separate fluid. These fluid flows respond initially linearly to nonlinear perturbations in the cold matter, but slowest flows are later converted to a particle realisation should their clustering power exceed some threshold. After outlining the multi-fluid description of neutrinos, we study the conversion of the individual flows into particles, in order to quantify transient errors, as well as to determine a set of criteria for particle conversion. Assembling our results into a total neutrino…
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Taxonomy
TopicsAstrophysics and Cosmic Phenomena
