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Title: Multi-Fidelity Emulation for the Matter Power Spectrum using Gaussian Processes
Abstract We present methods for emulating the matter power spectrum by combining information from cosmological N-body simulations at different resolutions. An emulator allows estimation of simulation output by interpolating across the parameter space of a limited number of simulations. We present the first implementation in cosmology of multi-fidelity emulation, where many low-resolution simulations are combined with a few high-resolution simulations to achieve an increased emulation accuracy. The power spectrum’s dependence on cosmology is learned from the low-resolution simulations, which are in turn calibrated using high-resolution simulations. We show that our multi-fidelity emulator predicts high-fidelity counterparts to percent-level relative accuracy when using only 3 high-fidelity simulations and outperforms a single-fidelity emulator that uses 11 simulations, although we do not attempt to produce a converged emulator with high absolute accuracy. With a fixed number of high-fidelity training simulations, we show that our multi-fidelity emulator is ≃ 100 times better than a single-fidelity emulator at k ≤ 2 hMpc−1, and ≃ 20 times better at 3 ≤ k < 6.4 hMpc−1. Multi-fidelity emulation is fast to train, using only a simple modification to standard Gaussian processes. Our proposed emulator shows a new way to predict non-linear scales by fusing simulations from different fidelities.  more » « less
Award ID(s):
1817256
PAR ID:
10356099
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Monthly Notices of the Royal Astronomical Society
ISSN:
0035-8711
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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