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Emulating Simulations of Cosmic Dawn for 21cm Power Spectrum Constraints on Cosmology, Reionization, and X-ray Heating
Nicholas S. Kern, Adrian Liu, Aaron R. Parsons, Andrei Mesinger, Bradley Greig
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Current and upcoming radio interferometric experiments are aiming to make a statistical characterization of the high-redshift 21cm fluctuation signal spanning the hydrogen reionization and X-ray heating epochs of the universe. However, connecting 21cm statistics to underlying physical parameters is complicated by the theoretical challenge of modeling the relevant physics at computational speeds quick enough to enable exploration of the high dimensional and weakly constrained parameter space. In this work, we use machine learning algorithms to build a fast emulator that mimics expensive simulations of the 21cm signal across a wide parameter space to high precision. We embed our emulator within a Markov-Chain Monte Carlo framework, enabling it to explore the posterior distribution over a large number of model parameters, including those that govern the Epoch of Reionization, the Epoch of X-ray Heating, and cosmology. As a worked example, we use our emulator to present an updated parameter constraint forecast for the Hydrogen Epoch of Reionization Array experiment, showing that its characterization of a fiducial 21cm power spectrum will considerably narrow the allowed parameter space of reionization and heating parameters, and could help strengthen Planck's constraints on σ₈. We provide both our generalized emulator code and its implementation specifically for 21cm parameter constraints as publicly available software.
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