Cosmic Inference: Constraining Parameters with Observations and a Highly Limited Number of Simulations

Journal Article · Mon Jan 11 00:00:00 EST 2021 · The Astrophysical Journal (Online)

DOI:https://doi.org/10.3847/1538-4357/abc8ed· OSTI ID:1844518

Takhtaganov, Timur ^[1]; Lukić, Zarija ^[1]; Müller, Juliane ^[1]; Morozov, Dmitriy ^[1]

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1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

We look at cosmological probes that pose an inverse problem where the measurement result is obtained through observations, and the objective is to infer values of model parameters that characterize the underlying physical system-our universe, from these observations and theoretical forward-modeling. The only way to accurately forward-model physical behavior on small scales is via expensive numerical simulations, which are further “emulated” due to their high cost. Emulators are commonly built with a set of simulations covering the parameter space with Latin hypercube sampling and an interpolation procedure; the aim is to establish an approximately constant prediction error across the hypercube. In this paper, we provide a description of a novel statistical framework for obtaining accurate parameter constraints. The proposed framework uses multi-output Gaussian process emulators that are adaptively constructed using Bayesian optimization methods with the goal of maintaining a low emulation error in the region of the hypercube preferred by the observational data. In this paper, we compare several approaches for constructing multi-output emulators that enable us to take possible inter-output correlations into account while maintaining the efficiency needed for inference. Using a Lyα forest flux power spectrum, we demonstrate that our adaptive approach requires considerably fewer-by a factor of a few in the Lyα P(k) case considered here-simulations compared to the emulation based on Latin hypercube sampling, and that the method is more robust in reconstructing parameters and their Bayesian credible intervals.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE Office of Science (SC), High Energy Physics (HEP)
• Grant/Contract Number: AC02-05CH11231
• OSTI ID: 1844518
• Alternate ID(s): OSTI ID: 23162691
• Journal Information: The Astrophysical Journal (Online), Journal Name: The Astrophysical Journal (Online) Journal Issue: 2 Vol. 906; ISSN 1538-4357
• Publisher: IOP Publishing
• Country of Publication: United States
• Language: English

Related Subjects

79 ASTRONOMY AND ASTROPHYSICS
computational
cosmological parameters
cosmology
galaxies
intergalactic medium