# Emulating Simulations of Cosmic Dawn for 21cm Power Spectrum Constraints on Cosmology, Reionization, and X-ray Heating

**Authors:** Nicholas S. Kern, Adrian Liu, Aaron R. Parsons, Andrei Mesinger, Bradley Greig  
**arXiv:** [1705.04688](https://arxiv.org/abs/1705.04688)  
**Date:** 2017-05-12  
**Summary page:** https://www.summarizepaper.com/en/paper/1705.04688v1/

## Key points

- Authors address challenges in connecting 21cm statistics to physical parameters in high-redshift radio interferometric experiments
- Highlight theoretical challenge of modeling relevant physics quickly for exploring high-dimensional parameter space effectively
- Employ machine learning algorithms to develop a fast emulator replicating expensive simulations of 21cm signal
- Embed emulator within Markov-Chain Monte Carlo framework to explore posterior distribution over various model parameters
- Use emulator to present updated parameter constraint forecast for Hydrogen Epoch of Reionization Array experiment, narrowing down allowed parameter space and potentially strengthening constraints on cosmological parameters such as $\sigma_8$
- Make generalized emulator code and its implementation publicly available as software

## Summary

In their paper titled "Emulating Simulations of Cosmic Dawn for 21cm Power Spectrum Constraints on Cosmology, Reionization, and X-ray Heating," authors Nicholas S. Kern, Adrian Liu, Aaron R. Parsons, Andrei Mesinger, and Bradley Greig address the challenges associated with connecting 21cm statistics to underlying physical parameters in high-redshift radio interferometric experiments. These experiments aim to characterize the 21cm fluctuation signal during the hydrogen reionization and X-ray heating epochs of the universe. The authors highlight the theoretical challenge of modeling relevant physics at computational speeds quick enough to explore the high-dimensional and weakly constrained parameter space effectively. To overcome this challenge, they employ machine learning algorithms to develop a fast emulator that accurately replicates expensive simulations of the 21cm signal across a wide parameter space. By embedding their emulator within a Markov-Chain Monte Carlo framework, the authors are able to explore the posterior distribution over a large number of model parameters, including those governing the Epoch of Reionization, the Epoch of X-ray Heating, and cosmology. As a practical demonstration, they use their emulator to present an updated parameter constraint forecast for the Hydrogen Epoch of Reionization Array experiment. Their analysis shows that characterizing a fiducial 21cm power spectrum can significantly narrow down the allowed parameter space for reionization and heating parameters. Furthermore, it has the potential to strengthen existing constraints on cosmological parameters such as $\sigma_8$ from Planck's observations. The authors also make their generalized emulator code and its implementation specifically for 21cm parameter constraints publicly available as software. This work not only contributes to advancing our understanding of cosmic dawn phenomena but also provides valuable tools for future research in this field.